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Socio-economic Impact of an Air Transport
Liberalisation Agreement in the Southern
African Development Community
Graham Muller Associates
30 August 2010
Final Report
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
Table of Contents
Executive Summary ....................................................................................................................................... v
Introduction .............................................................................................................................................. v
Literature Review ...................................................................................................................................... v
The nine freedoms of the air ................................................................................................................ v
The Yamoussoukro Decision ............................................................................................................... vii
Assessing and forecasting the impact of air transportation liberalisation agreements ....................... x
Economic Impact of an air transport liberalisation agreement in SADC ................................................xiii
Overview of current status of the SADC Aviation Industry .................................................................xiii
Cost-Benefit Analysis Methodology .................................................................................................... xvi
Cost Benefit Analysis Results ............................................................................................................. xvii
Impact of an air transport liberalisation agreement in the Southern African Development Community
................................................................................................................................................................. xx
Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure
in airport and navigational infrastructure .............................................................................................. xxi
Introduction .................................................................................................................................................. 1
1 Literature Review .................................................................................................................................. 2
1.1 Introduction .................................................................................................................................. 2
1.2 The nine freedoms of the air ........................................................................................................ 3
1.3 History of aviation agreements ..................................................................................................... 5
1.3.1 Chicago Convention 1944 ..................................................................................................... 5
1.3.2 Formation of state owned or sponsored airlines.................................................................. 6
1.3.3 Liberalisation of aviation agreements................................................................................... 7
1.4 Assessing and forecasting the impact of air transportation liberalisation agreements ............. 15
1.4.1 The case study approach .................................................................................................... 15
1.4.2 The trends model ................................................................................................................ 16
1.4.3 The gravity model ............................................................................................................... 16
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
1.4.4 The stimulation model ........................................................................................................ 17
1.4.5 Air transport cost analysis ................................................................................................... 17
1.5 Case Studies ................................................................................................................................ 18
1.5.1 United States – United Kingdom ......................................................................................... 18
1.5.2 The European Union ........................................................................................................... 20
1.5.3 India – United Kingdom....................................................................................................... 22
1.5.4 Impact of an international air transportation liberalisation agreement ............................ 26
1.6 Forecasted effects of air transportation liberalisation agreements ........................................... 26
1.6.1 Infrastructure, regulatory body, skills and market size limitations .................................... 27
1.6.2 Spread of development from hubs to outlying areas ......................................................... 31
1.7 Concluding Comments ................................................................................................................ 32
2 Impact of air transport liberalisation agreement in Southern African development Community ..... 34
2.1 Introduction ................................................................................................................................ 34
2.2 Overview of the Current Status of the SADC Aviation Industry .................................................. 35
2.2.1 Angola ................................................................................................................................. 35
2.2.2 Botswana ............................................................................................................................. 36
2.2.3 Democratic Republic of the Congo (DRC) ........................................................................... 39
2.2.4 Lesotho ................................................................................................................................ 40
2.2.5 Madagascar ......................................................................................................................... 41
2.2.6 Malawi ................................................................................................................................. 43
2.2.7 Mauritius ............................................................................................................................. 45
2.2.8 Mozambique ....................................................................................................................... 47
2.2.9 Namibia ............................................................................................................................... 49
2.2.10 Seychelles ............................................................................................................................ 51
2.2.11 South Africa ......................................................................................................................... 52
2.2.12 Tanzania .............................................................................................................................. 57
2.2.13 Zambia ................................................................................................................................. 60
2.2.14 Airports in SADC .................................................................................................................. 63
2.2.15 Fleet size of all SADC airlines .............................................................................................. 68
2.3 Analysis of Questionnaire Results ............................................................................................... 70
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2.3.1 Airlines ................................................................................................................................ 70
2.3.2 Airports ............................................................................................................................... 74
2.3.3 Other Stakeholders in the aviation industry ....................................................................... 76
2.4 Cost-Benefit Analysis Methodology ............................................................................................ 82
2.4.1 Model .................................................................................................................................. 82
2.4.2 Direct Impacts ..................................................................................................................... 92
2.4.3 Indirect Impacts .................................................................................................................. 99
2.4.4 Airport and Navigational Infrastructure ........................................................................... 102
2.5 Cost-Benefit Analysis Results .................................................................................................... 107
2.5.1 Direct Impacts ................................................................................................................... 107
2.5.2 Benefit to airlines .............................................................................................................. 107
2.5.3 Benefits to passengers ...................................................................................................... 111
2.5.4 Indirect Impacts ................................................................................................................ 121
2.5.5 Airport and navigational infrastructure ............................................................................ 131
2.6 Impact of an air transport liberalisation agreement in the Southern African Development
Community (SADC) ................................................................................................................................ 137
2.6.1 Total Computable Benefits ............................................................................................... 137
2.6.2 Total Costs ......................................................................................................................... 139
2.6.3 Impact of an air transport liberalisation agreement in the Southern African Development
Community ........................................................................................................................................ 140
2.7 Impact of an air transport liberalisation agreement reflecting the investment and capital
expenditure in airport and navigational infrastructure ........................................................................ 142
Conclusion ................................................................................................................................................. 145
References ................................................................................................................................................ 146
List of References .............................................................................................................................. 146
Conversions are based on the following websites............................................................................ 146
List of Tables ............................................................................................................................................. 148
List of Figures ............................................................................................................................................ 151
List of Boxes .............................................................................................................................................. 156
Appendix A – Signing States of the Chicago Convention 1944 ................................................................. 157
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Appendix B – United States Air transportation liberalisation Partners and status of the agreement ..... 158
Appendix C – State ownership for international flag carriers................................................................... 161
Appendix D – Spider Diagram ................................................................................................................... 166
Appendix E – Questionnaires .................................................................................................................... 167
Air transportation liberalisation Questionnaire for Southern African Airlines ..................................... 167
Air transportation liberalisation Questionnaire for Southern African Airlines ..................................... 187
Air transportation liberalisation Questionnaire for other Southern Africa Aviation Industry
Stakeholders ......................................................................................................................................... 205
Appendix F – Destinations within SADC .................................................................................................... 212
Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure
costs (R Millions) ....................................................................................................................................... 233
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
Executive Summary
Introduction
This report has been compiled in conjunction with the South African Department of Transport. The
project measures the economic impact of implementing an air transportation liberalisation agreement
within the Southern African Development Community (SADC) region. The report is divided between a
review of literature analysing the impact of air transportation liberalisation agreements around the
world, and the forecasted impact of implementing the air transportation liberalisation agreement in the
SADC region.
Literature Review
Air transportation liberalisation is the liberalisation of aviation regulations between countries or within
geographic regions. Air transportation liberalisation agreements have largely been adopted and pursued
by developed countries. The United States has actively been involved in negotiating Air transportation
liberalisation agreements between various countries since 1972, while the European Union initiated its
internal common market or cabotage area by means of air transportation liberalisation between
member states in 1988. The Yamoussoukro Decision (YD) is the inter-African version of air transport
liberalisation Agreements and this was signed into operation by member states in 1999, however limited
progress has been made on this agreement.
The literature review has been structured in such a way that it looks at:
Analysing the various components that can be utilised when entering air transportation liberalisation agreement;
The short comings of Yamoussoukro Decision and the requirement for the establishment of a competition body to monitor airline behaviour in Africa (or SADC);
The various methods of measuring the impact of air transportation liberalisation agreements; and
The impact of air transportation liberalisation as measured by existing reports and studies.
The nine freedoms of the air
Table 1.1-1 displays the various freedoms of the air that make up aviation agreements between
countries and regions. Air freedoms 1 to 4 make up traditional aviation agreements between countries
with very restrictive aviation laws, whereas air freedoms 5 to 9 would represent a relaxing in aviation
agreements between countries. Freedoms 5 to 9 have been allowed by certain countries since 1944, but
this has largely been the case in a limited number of aviation agreements.
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Table 1.1-1 Definition of air freedom rights
1st Freedom
To overfly one country en-route to another
2nd Freedom
To make a technical stop in another country
3rd Freedom
To carry freight and passengers from the home country to another country
4th Freedom
To carry freight and passengers to the home country from another country
5th Freedom
To carry freight and passengers between two countries on route (by an airline of a third (home) country) with origin / destination in its home country
6th Freedom
To carry freight and passengers between two countries by an airline of a third country on two routes connecting in its home country
7th Freedom
To carry freight and passengers between two countries by an airline of a third country on a route with no connection with its home country
8th Freedom or Cabotage
To carry freight and passengers within a country by an airline of another country on a route with origin / destination in its home country
9th Freedom or True Domestic
To carry freight and passengers within a foreign country with no connection with the home country
More recent air
transportation
liberalisation
regulations
Traditional bilateral
aviation regulations
3rd Freedom 5th Freedom
Source: ICAO Manual of Regulation (2004) and
WTO Secretariat
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The Yamoussoukro Decision
Over the last three decades the African aviation market has been dominated by national flag carriers
that have benefited from government protection and free market economic logic has played little to no
role in this industry. Therefore there has been little improvement and innovation in the quality and
quantity of air services around the continent. The African tax payer is predominantly the biggest loser as
governments subsidise, recapitalise or protect national flag carriers that typically operate under dismal
financial conditions.
Table 1.1-2 below shows the international growth in the aviation market over a 17 year period. It can be
seen that while the African aviation market has grown, while this is the fastest growing market after
Latin America and Caribbean, the African market is still small when compared with the market size of
the Worlds other regions.
Table 1.1-2 Total number of domestic and international airline passengers, by region
Source: ICAO, 2007
The YD encourages co-operation between African states through aviation. YD advocates the following:
That only African owned airlines would benefit from the implementation of YD
The granting of 1st to 5th air freedom rights (as well as cabotage, the 8th air freedom rights);
Encouraging the development of new routes;
40
.8
31
8.9 5
46
.2
47
.8
74
1.8
83
.5
60
.9
66
5.5
74
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79
.1
11
04
.9
13
4.5
11
4
98
0
13
67
11
1
15
29
27
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0
200
400
600
800
1000
1200
1400
1600
1800
Afr
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ific
Euro
pe
Mid
dle
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t
No
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A
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ica
Lati
n A
mer
ica
and
C
arib
bea
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Passengers (millions)
1989
1999
2006
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Removal of capacity restrictions on passenger seats, freight and flights on certain routes;
The removal of expensive and complex tariff regulations;
The elimination of all protective policies that protect national flag carriers;
The termination of regulations on carriers’ alliance;
Doing away with restriction on the conversion of revenues to hard currency and repatriation;
Agree on code sharing; and
Allow carriers to have own-ground-service abroad
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History and failure to implement
The implementation of the YD was expected to be concluded by 2002, with the complete removal of
regulations and all the air freedoms being permitted. Capacity constraints would be removed and a
monitoring body would be established to enforce and monitor that countries and airlines do not partake
in anti-competitive behaviour.
The YD agreement between African states in 1999 was over flowing with optimism and good intention,
but has faced a number of obstacles which have brought implementation to a complete standstill. The
reasons for this failure were highlighted by the African Union Report (2005):
confusion in the monitoring body of the Yamoussoukro Decision;
conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These conditions allow any airline which has “its headquarters, central administration and principal place of business physically located in the state concerned” to be eligible to benefit from the advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most part controlled by foreign capital or interests. The European Union has put in place very restrictive conditions in terms of eligibility so as to protect the airlines of its community
YD makes no mention of economic control of eligible airlines - there should be a provision in YD requiring airlines to avail to audit boards all accounting and financial documents to ascertain their economic status. These audit boards do not exist.
competition rules as contained in the Yamoussoukro Decision are inadequate. Competition rules need to be defined further.
YD has remained mostly stagnant since its inception, except in the Western African region.
African Aviation Competition Authority
Instrumental in the success of the YD is the establishment of a competition authority to oversee the
implementation of the agreement, while also monitoring that governments, airlines and airports don’t
partake in uncompetitive behaviour. This authority must be comprised of the various member states
and not favour any member state.
The completion rules have already been stated, but are worth repeating:
Only African owned airlines should benefit from the implementation of YD
The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights);
Encourage the development of new routes;
Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes;
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
Ensure the removal of expensive and complex tariff regulations;
Ensure the elimination of all protective policies that protect national flag carriers;
Ensure the termination of regulations on carriers’ alliance;
Remove restriction on the conversion of revenues to hard currency and repatriation;
Agree on code sharing;
Allow carriers to have own-ground-service abroad;
Not allow any direct or indirect state or parastatal subsidies;
Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing;
Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages);
Ban on airlines who abuse a dominant positions;
Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.
Assessing and forecasting the impact of air transportation liberalisation agreements
The literature reviewed displayed various methods of estimating the impact of air transportation
liberalisation regulations. The most common methods used to estimate the impacts are: the trends
model; the gravity model; air transport costs analysis; and the case study approach.
The trends approach uses statistical regression analysis to predict future growth in the aviation market;
this method is only applicable where air transportation liberalisation agreements have been in place
over period and data is available.
The gravity model estimates total unconstrained demand between origins and destinations, by taking
into account data such as GDP per capita or population levels, while also considering the distance flown.
Equation 1 indicates the mathematical equation utilised in calculating the gravity model for each routes
flown. This method calculates weights for each specific route, the higher the weight, the higher demand
for those flights.
Equation (1) Demand = (GDP Origin * GDP Destination)/Distance
The simulation method uses historical data and shows how demand in flights changes as air fares
increase and decrease, while this is possibly the most thorough way of calculating the impact of an air
transportation liberalisation agreement it is mostly inapplicable as reliable data is unavailable, limited or
compromised.
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Lastly the case study approach is the most common method of estimating the impact of air
transportation liberalisation agreements; this approach looks at the impact experienced in other
countries or regions that have already implemented air transportation liberalisation policies and
legislation. Unsurprisingly the case study approach is completely qualitative, speculative, and imprecise;
it is also the easiest form of measuring air transportation liberalisation impacts.
Case studies
Case studies showing the impact of implemented air transportation liberalisation agreements have been
conducted between the United States and the European Union, the European Union, and India and the
United Kingdom. All case studies indicating the impact of air transportation liberalisation agreements
involve developed countries, or at least one developed country, as well as countries with established
and large aviation markets. This is partly due to the developed countries being among the first states to
open their skies and liberalise their aviation legislation. The other observation is that all the case studies
are enthusiastically positive with regards to air transportation liberalisation agreements; there is no
mention of any negative side effects and impacts.
It is estimated that the air transportation liberalisation agreement between the U.S. and U.K. is
responsible for stimulating 9,197 full-time equivalent jobs in the United States and over 16,700 full-time
equivalent positions in the United Kingdom. It is also estimated that the gross domestic product of the
United States also expanded by $747 million due to the agreement and the United Kingdom by roughly
$970 million.
Liberalisation of the E.U. aviation market between 1988 and 1993 has led to an additional 44 million
passengers being carried annually, which equals a 33% increase in passenger seats. This traffic
expansion has encouraged development of both the tourism sector and other industries. Some 1.4
million full-time jobs resulted from the liberalisation, and European GDP grew by $US 85 billion. Most
importantly noted is the dramatic market growth in low cost carrier airlines and the market share
decline of national flag carriers.
Between summer 2004 and summer 2006, the number of direct flights between India and the UK rose
from 34 to 112 per week. The increase in capacity and more intense competition has resulted in a
reduction in air fares, from £882 to £736 for one-way fare paid by passengers travelling for business
class and £251 to £231 for one-way fare paid by passengers travelling economy class.
Forecasted effects of air transportation liberalisation agreements
While the case studies were overwhelmingly positive with regards to air transportation liberalisation
agreements, there were two studies that raised legitimate concerns as they forecasted and analysed the
effects of air transportation liberalisation agreements. These reports were conducted by Micco and
Serebrisky (2006) and Swan (2008).
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There are two essential issues that these reports raised as they analysed their data’s results:
Firstly, does the country have adequate infrastructure, a regulatory body, available skills and sufficient market size?
And secondly, can a country afford to shift aviation activity away from a central hub airport
Answering these questions has particular relevance for Africa and more specifically for the Southern
African Development Community.
Micco et al. (2006) discovered while running a regression on all countries and airports that operate
under air transportation liberalisation legislation, that airport with insufficient infrastructure, skills and
limited market sizes could not benefit fully from the effects of air transportation liberalisation
agreements.
Swan (2008) while analysing aviation data in the Far East discovered that air transportation liberalisation
agreements over time will move flights away from major hub airports to smaller airports as flights are
added to airline routes.
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Economic Impact of an air transport liberalisation agreement in SADC
The purpose of the study is to go further than just assessing the international experience of
implementing air transportation liberalisation agreements and determine the impact of implementing
the air transportation liberalisation agreement in the SADC region. The impact has been measured on
two levels, firstly the impacts experienced within the aviation market (direct impacts); and secondly the
impacts felt by supporting industries to the aviation market (indirect impacts).
The study identified the following direct and indirect impacts:
Direct impacts:
On Airlines
On Airports
Passengers
Freight
Customs
Indirect impacts:
On Tourism
On Airport services
Aircraft manufacturers
Environment
Intermodal services
Government
Overview of current status of the SADC Aviation Industry
SADC flight departure and passenger data indicates that certain airlines in SADC service mainly domestic
routes and service very few international routes, while other airlines are largely reliant on international
business. The general trend for most airlines indicates that there has been a gradual increase in the total
number of departures over the years; however a decrease in total departures is noted during the 2007
to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in the global economy
over this period. Although the September 11 2001 attacks reduced worldwide air travel significantly,
most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine flu also had
little impact on most SADC based airlines. SADC airlines more commonly encountered periodic problems
due to internal issues such as financial losses, inefficiency and safety of aircraft or due to localised
external problems such as political instability in countries where the airlines operate. It is noted that
national carriers generally split departures between international and domestic while low cost carriers
mainly undertake domestic flights.
A country by country analysis reveals that most national airlines struggle financially whilst some are
greatly affected by the political situation in the country such as Air Madagascar and Air Zimbabwe. All
airlines from the Democratic Republic of Congo (DRC) and Zambezi Airlines have been banned in
European airspace as a result of substandard safety management practices. Airlines within the SADC
that have shut down over the years due to the inability to cope with operations include Air Lesotho, Air
Tanzania and Zambia airways. Airlines with a greater number of international passengers compared to
domestic include Air Mauritius and Air Namibia. The most popular airlines within SADC with total
passenger numbers greater than 500,000 annually are Air Mauritius, South African Airways (SAA), SA
Airlink and Comair.
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International airports with greater than 1,000,000 passengers annually include O R Tambo Airport, Cape
Town International, Durban International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur
Ramgoolam International in Mauritius. O R Tambo Airport recorded over 10 million passengers annually.
International airports with less than 1,000,000 passengers annually include Kinshasa N’Djili, Maputo
International, Zanzibar airport, Ivato International, Windhoek International and Lusaka International.
International airports that recorded the lowest number of passengers with less than 700,000 annually
are Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and Victoria Falls.
South Africa has the largest number of airports within SADC of which 7 are domestic airports. Port
Elizabeth airport had the largest number of domestic passengers with over 800,000 annually followed by
East London and George airports with over 400,000 domestic passengers annually.
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Analysis of questionnaire results
Of 106 questionnaires sent, only 16 responses from the following were received.
Category Type of Service Offered Company / Organisation Country
Airline Airline Comair Ltd South Africa
Airline Airline Federal Airlines South Africa
Airline Airline Owenair Pty Ltd South Africa
Airline Airline Air Malawi Malawi
Airport Airport ACSA South Africa
Airport Airport NAC Zambia
Other Stakeholders Aircraft leasing and charter AirQuarius Aviation South Africa
Other Stakeholders Aircraft sales, maintenance, leasing, charter and management
National Airways Corporation South Africa
Other Stakeholders Aircraft brakes and landing gear overhauls
Mistral Aviation Services South Africa
Other Stakeholders Passenger/cargo scheduled/charter flights
Phoebus Apollo Aviation South Africa
Other Stakeholders Non-profit private association representing SADC based airlines.
Airlines Association of South Africa AASA
South Africa
Other Stakeholders Tourism and incentive charters Namibia Commercial Aviation Namibia
Other Stakeholders Passenger, freight and mail services
Precision Air Services Tanzania
Other Stakeholders Ground handling and cargo services
Swissport Tanzania Tanzania
Other Stakeholders Charter operations Proflight commuter services Zambia
An overview of the fleet size of airlines in SADC shows that South African Airways has the largest fleet
within 50 aircraft, while other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar,
Air Mauritius, Air Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying
between 4 and 12 aircraft each. Fleet sizes of airlines operating on domestic routes vary between 1 and
32 aircraft.
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Feedback from airlines, airports and other stakeholders was generally positive regarding an air
transportation liberalisation agreement, however most respondents stated that implementation was
poor. Full implementation has been hindered due to lack of government and SADC member
commitment to YD, Corruption, poor or substandard airport infrastructure in many countries and airport
security concerns among other factors. In order to successfully implement an air transportation
liberalisation agreement, governments will have to play an active role and stakeholders should be
afforded the opportunity to participate in the decision making. Major changes to infrastructure,
improved aircrafts, up to date avionics and transparent policies are some of the compulsory factors
necessary to ensure smooth operation of the air transportation liberalisation agreement.
The following changes in status quo are expected by airlines and airports.
Airlines Airports
Frequency of flights Increase Increase on certain routes
Capacity May increase or remain static Increase
Pricing Decrease Decrease
Volume of freight business Increase Likely to increase
Number of competitors on each route Increase on higher traffic route but will decrease on marginal routes
n/a
Market share on each route Reduce n/a
Overall, airlines, airports and other stakeholders are positive about the implementation of air
transportation liberalisation agreements but are sceptical about the progress made to date on YD and
likely to be made into the future. All the stakeholders involved support the idea behind YD and are
willing to open their markets to Africa but are not certain that the current infrastructure, legislation and
policies support the rapid implementation of such a decision.
Cost-Benefit Analysis Methodology
The economic impacts have been measured using the principles of the gravity model. However, actual
economic data between origins and destinations has been used. More specifically we’ve used GDP per
capita, urban population levels per country, city population levels and distance between origins and
destinations. Equation 2 and 3 show an example of how the various sources of economic data were used
to calculate the estimated demand for each potential route in the SADC region.
Equation (2) GDP demand airport A&B = ((GDP per capita index airport A) + (GDP per capita index airport B))/2
Equation (3) Route demand = (GDP demand airport A&B x A)+(City pop demand airport A&B x B)+(Urban pop demand airport A&B x C)+(Airport infra demand airport A&B x
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D)+(Bus, Pol & Dev demand airport A&B x E)+(Tourism infra demand airport A&B x F)
where: A + B + C + D + E + F = 100%
With the estimated demand known for each route and the use of South African aviation data (such as:
actual pricing; seats numbers available on flights; quantity of flights and distance between airports)
potential seat numbers, turnover, costs to airlines, benefits to passengers, indirect costs and tourism
impacts can be estimated for each route. The impacts have been estimated over a 50 year period, and
this is determined by staggering the potential routes by initially allowing only the routes with a high
estimated demand and then every 5 years allowing routes with lower estimated demand. At the 50 year
point all routes would be included in the impact analysis.
Cost Benefit Analysis Results
Total Benefits
Total benefits include the following: potential turnover to airlines; time saved by passengers and the
direct impact of the tourism industry on GDP. All of these have been reported in 2009 Rands and
exclusively look at the aviation industry in the SADC region. Table 1.3-1 and Figure 1.3-1, display the
total benefits experienced over a 50 year period post the implementation of air transportation
liberalisation agreement in SADC. It can be seen Table 1.3-1 that the most significant benefit brought by
an air transportation liberalisation agreement being implemented in SADC is the direct impact on the
tourism industry. Tourism is a very labour intensive industry and we can expect that over the 50 year
period that approximately 101 million jobs would be created in this industry alone.
Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement in SADC
Years*
BENEFITS
Potential Turnover Passenger Time Saving
(Rand per KM)
Direct Impact Of Tourism Industry On GDP (2009
Rands) TOTAL BENEFITS
5 R 395,592,569.17 R 8,070,414.24 R 7,552,340,410.36 R 7,956,003,393.77
10 R 615,030,014.60 R 14,835,378.82 R 13,205,292,139.30 R 13,835,157,532.72
15 R 631,437,961.30 R 15,242,987.56 R 13,673,144,858.21 R 14,319,825,807.06
20 R 1,055,829,325.19 R 26,510,838.22 R 28,251,360,598.84 R 29,333,700,762.24
25 R 3,194,221,298.65 R 76,673,240.19 R 50,738,372,511.99 R 54,009,267,050.82
30 R 8,886,816,358.07 R 296,141,084.61 R 105,672,816,915.10 R 114,855,774,357.77
35 R 15,354,301,000.26 R 720,722,026.57 R 165,457,639,030.49 R 181,532,662,057.32
40 R 20,306,047,606.09 R 1,242,964,240.75 R 217,448,285,885.45 R 238,997,297,732.29
45 R 21,592,032,312.26 R 1,370,343,414.87 R 228,121,055,753.45 R 251,083,431,480.59
50 R 21,804,364,460.93 R 1,395,717,456.70 R 229,837,249,446.98 R 253,037,331,364.61
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
Figure 1.1-1 below graphs the total benefits over the 50 year period. The s-curve graph is to be expected
as it indicates that initially benefits are limited as the market adjusts to the new aviation regulations,
and once this adjustment is made large benefits start accruing. Finally after 35 years benefits begin to
drop off as all major routes are saturated and lower demanded flights are added to flight schedules. It
can also be seen on this figure the sheer size of the benefit experience by the tourism industry and the
slight benefit experienced by time savings to passengers.
Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC
R -
R 50,000,000,000.00
R 100,000,000,000.00
R 150,000,000,000.00
R 200,000,000,000.00
R 250,000,000,000.00
R 300,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
Total Benefits
Direct Impact On GDP (2009 Rands)
Time Saving (Rand per KM)
Potential Turnover
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Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates
Total Costs
The total costs included: cost of flight cancellation; cost of flight diversions; cost of accident resulting in fatality; cost of minor injury during flight;
cost of major injury during flight; cost of pollution; cost of noise pollution; and cost of security. These costs have been shown in Table 1.3-2 and
Figure 1.1-2. These results are shown over a 50 year period in 2009 Rands.
Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight
cancellation Cost of flight diversions
Cost of accident resulting in fatality
Cost of minor injury during flight
Cost of major injury during flight
Cost of Pollution
Cost of noise pollution
Cost of Security Navigation Route Costs (FL 145)
TOTAL COSTS
5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719
10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421
15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847
20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835
25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979
30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721
35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177
40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812
45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596
50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042
*post implementation of an air transportation liberalisation agreement in SADC
Once again the S-curve bend can be observed in Figure 1.1-1. It can also be seen that the cost of security is by far the highest cost over the 50
year period. The cancellation costs and diversion costs could increase depending on occurrence disasters like the recent volcanic eruption in
Iceland, grounding all the aircrafts and costing airlines billions of Euros.
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Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC
Impact of an air transport liberalisation agreement in the Southern African
Development Community
Figure 1.1-3 shows the total impact of an air transport liberalisation agreement in SADC being
implemented in the Southern African Development community. This Figure graphs both the total
benefits and the total costs. It can be seen how marginal the total costs are in relation to the overall
economic benefit in the case of an air transport liberalisation agreement being implemented in the
SADC region.
R -
R 500,000,000
R 1,000,000,000
R 1,500,000,000
R 2,000,000,000
R 2,500,000,000
R 3,000,000,000
R 3,500,000,000
R 4,000,000,000
R 4,500,000,000
R 5,000,000,000
5 10 15 20 25 30 35 40 45 50
Year
Navigation Route Costs (FL 145)
Cost of Security
Cost of noise pollution
Cost of Pollution
Cost of major injury during flight
Cost of minor injury during flight
Cost of accident resulting in fatality
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Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the Southern African Development community
Impact of an air transport liberalisation agreement reflecting the investment
and capital expenditure in airport and navigational infrastructure
An air transport liberalisation is unable reach the full potential of the demand indicated in the previous
section unless there is a significant upgrade and investment to both the airport and navigational
infrastructure and equipment in the SADC region. Annual airport capacities would need to be increased
to meet the anticipated passengers expected through the various airports in the region. The information
that has contributed to infrastructural costs has been provided by Airports Company South Africa (ACSA)
and Air Traffic Navigational Systems (ATNS.)
ATNS provided a list of infrastructure required per airport based on expected demand for flights and
ACSA provided the airport capacities for each of the South African airports and indicated that for an
additional 1 million passenger capacity that the infrastructure would cost R 600 million. Table 1.1-5
below lists the various infrastructural investments in the navigational equipment and cost of creating
additional passenger capacity per airport. The column ‘benefit’s less costs’ indicates the total weekly
costs and benefits per week highlighted in previous sections over the 50 year period. Once taken into
account the infrastructural costs the column ‘Total impact after infrastructure costs’ highlights the
R -
R 50,000,000,000.00
R 100,000,000,000.00
R 150,000,000,000.00
R 200,000,000,000.00
R 250,000,000,000.00
R 300,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
TOTAL BENEFITS
TOTAL COSTS
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Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham
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impact per airport. It can be seen that only 5 airports cannot meet the infrastructural costs incurred
over the 50 year period, but in total the benefits of air transport liberalisation are overwhelming and
cross subsidisation of these airport that incur negative impacts could easily make them feasiable.
Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport
infrastructure Airport navigational systems
Total impact after infrastructure costs
Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288
Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492
Dundo R - R - R - R -
Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703
Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227
Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601
Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471
Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724
Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245
Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591
Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150
Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695
Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126
Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072
Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524
Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539
Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231
Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838
Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482
Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622
Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118
Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459
Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852
Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857
Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789
Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255
Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127
Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582
Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224
Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952
Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731
Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576
Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984
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Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392
Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962
Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001
Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493
Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915
Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904
Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469
Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466
Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448
Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776
Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105
Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016
Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071
Moçimboa da Praia
R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085
Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631
Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935
Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812
Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814
Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929
Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458
Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115
Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521
Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379
Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501
Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578
Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462
Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847
Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766
Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539
Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959
George R - R - R - R -
Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229
Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969
Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808
Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627
Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189
Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465
Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311
Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507
Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786
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Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693
Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194
Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927
Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976
Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566
Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871
Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588
Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426
Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528
Kitwe R -770,778,388 R - R - R -770,778,388
Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937
Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427
Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300
Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446
Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191
Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338
Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837
Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462
TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266
Conclusion
The literature review and impact analysis have both overwhelmingly demonstrated the positive effects
of implementing an air transportation liberalisation in the SADC region. However, there are a few issues
that need to be considered before implementing an air transportation liberalisation agreement:
The establishment of a competition authority, with the power to penalise countries and airlines acting in ways that are un-competitive.
The inevitable market share decline of national flag carriers and in some cases the closing of unprofitable nation flag carriers. This will, in all likelihood save taxes.
The emergences of privately owned low cost carriers as the dominant airlines within the region.
The shifting of connector flights away from historical hub airports.
Substantial new investment in airports within SADC and in additional infrastructure, skills and capacity (including aircraft) to take advantage of an air transportation liberalisation.
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Introduction
This report has been prepared for the South African Department of Transport.
The report summarises the methodology and findings of an investigation into the impacts of
implementing air transportation liberalisation legislation in the form of implementation of an air
transport liberalisation agreement throughout the Southern African Development Community (SADC)
region.
The report has been divided into two parts:
1) The first part (Section 1) investigates the current literature regarding air transportation
liberalisation and the effects and impacts experienced in other countries and regions around the
world;
2) The second part (Section 2) of the report takes some of the lessons learnt from the first section
and applies these in an analytical and modelling study to forecast the impact of air
transportation liberalisation legislation being introduced in the SADC region in the form of
implementation of an air transport liberalisation agreement throughout the Southern African
Development Community (SADC) region.
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1 Literature Review
1.1 Introduction
Air transportation liberalisation agreements are concerned with the liberalisation of aviation regulations
and agreements between countries. This report comprises a review of the current literature regarding
the economic impacts of air transportation liberalisation agreements and of the consequences and
potential risks of adopting air transportation liberalisation agreements. This report is primarily
concerned with setting the back drop to assessing the impact of an air transportation liberalisation
agreement on Africa in the Southern African Development Community (SADC).
Key to this study is the African air transportation liberalisation initiative known as the Yamoussoukro
Decision (YD) launched in 1999. Although this initiative is now more than a decade old, little of it has
been implemented and the aviation market within Africa remains largely closed, regulated and
dominated by national flag carriers. There has been limited political will in implementing YD in the
various African regions and the wider continent. YD relates to the liberalisation of access to the aviation
market in Africa and seeks to achieve:
Unrestricted access to all air routes;
Elimination of restriction on capacity, frequency on any route and in operation in any international markets;
Elimination of restriction on charters;
Liberalization of air cargo rules;
Doing away with restrictions on the conversion of revenues to hard currency and repatriation of revenues;
Agreement on code sharing;
Permitting carriers to have their own ground service abroad; and
Termination of regulations on carriers’ alliance.
At the time of writing this report literature available on air transportation liberalisation agreements and
the Yamoussoukro decision was limited and lacking in economic quality. Furthermore, most of the air
transportation liberalisation literature is focussed on developed countries (the United States, the
European Union and the United Kingdom) and thus the analysis is more applicable to highly developed
countries and regions. The emphasis on developed country studies is somewhat to be expected,
however aviation markets of these regions are double the size of those in the rest of the world. More
specifically, the African aviation market is only 7.45% of the size of the North American aviation market
and 8.34% of the size of the European aviation market, as seen in Figure 1.3-3. Therefore, the
anticipated impact of an air transport liberalisation agreement in SADC would be a fraction of that
experienced in developed regions where air transportation liberalisation has been adopted.
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Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham
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The report is structured as follows:
Section 1.2 examines the nine ‘freedoms of the air’ that make up a typical air transportation
liberalisation agreement.
Section 1.3 looks briefly at the history of aviation and the history of aviation agreements,
starting with the Chicago Convention of 1944 and concluding with an in depth analysis of the
Yamoussoukro Decision of 1999 (Africa’s air transportation liberalisation initiative).
Section 1.4 reviews five methods that can be used to assess or forecast the impacts of aviation
agreements.
Section 1.5 reviews three case studies that detail the impacts of implementing air transportation
liberalisation agreements. These case studies review the United States and the United Kingdom;
the European Union; and India and the United Kingdom. Included is research conducted by
InterVISTA-ga2 in 2006, which attempts to determine the global impact of every country
liberalising their aviation regulations.
Section 1.6 discusses two significant research reports which highlight some important
considerations regarding the economic impact of air transportation liberalisation agreements.
Finally section 1.7 concludes the analysis by highlighting the implications of the report for
Southern Africa.
1.2 The nine freedoms of the air
As a point of departure it is important that the nine freedoms of the air are clearly defined, as they will
be referred to throughout the remainder of this study. Aviation agreements between countries and
within regions can consist of up to nine freedoms of the air. Table 1.2-1 overleaf explains each of the
nine air freedom rights in a typical aviation agreement between two nations or a region.
Freedom Rights 1 - 4 are known as traditional bilateral aviation regulations that have been in place since
the Chicago Convention of 1944 (discussed overleaf), whereas Freedom Rights 5 - 9 are the more recent
air transportation liberalisation regulations being pursued by a number of countries and regions.
Freedoms 5 – 9 are far more liberal and give airlines and airports far more flexibility and possibilities.
For a complete list of countries with air transportation liberalisation agreements with the United States
in place please refer to Appendix B.
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Table 1.2-1 Definition of air freedom rights
1st Freedom
To overfly one country en-route to another
2nd Freedom
To make a technical stop in another country
3rd Freedom
To carry freight and passengers from the home country to another country
4th Freedom
To carry freight and passengers to the home country from another country
5th Freedom
To carry freight and passengers between two countries on route (by an airline of a third (home) country) with origin / destination in its home country
6th Freedom
To carry freight and passengers between two countries by an airline of a third country on two routes connecting in its home country
7th Freedom
To carry freight and passengers between two countries by an airline of a third country on a route with no connection with its home country
8th Freedom or Cabotage
To carry freight and passengers within a country by an airline of another country on a route with origin / destination in its home country
9th Freedom or True Domestic
To carry freight and passengers within a foreign country with no connection with the home country
More recent air
transportation
liberalisation
regulations
Traditional bilateral
aviation regulations
3rd Freedom 5th Freedom
Source: ICAO Manual of Regulation (2004) and
WTO Secretariat
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Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham
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1.3 History of aviation agreements
Aviation as a mode of transport has grown increasingly in importance over the last century, ever since
the Wright brothers took their first controlled flight on 17 December 1903. Less than a decade later
aircraft were being used in World War I for reconnaissance and attacks against both ground positions
and enemy aircraft. The first aircraft to start transporting people and cargo over long distances were
known as Zeppelin blimps or airships. This short lived technology came to an end in 1937, when the
Hindenburg Zeppelin blimp crashed killing 36 people (Bryan, L.A, Taylor, M.S, 2006).
The 1920’s and 1930’s saw great advances within the aviation industry, such as the first transatlantic
flight in 1927 and the first transpacific flight a year later. By the start of the World War II many towns
and cities had built airports, and there were many qualified pilots. World War II brought about a number
of advances in the aviation industry, such as the first jet aircraft and the first liquid fuelled aircraft.
During World War II the importance of modern aviation was recognised and a conference was convened
to agree on aviation regulations. This conference, known as the Chicago Convention of 1944, resulted in
regulations that have governed international aviation law and bilateral agreements between countries
for the second half of last century (Bryan, et al, 2006).
1.3.1 Chicago Convention 1944
The Chicago Convention of 1944 was attended by 54 states (see Appendix A for a list of countries that
attended the Chicago Convention) but ended in 52 states signing the Convention on International Civil
Aviation. The signed convention was a list of international aviation regulations, standards and
procedures decided on by participating nations.
The regulations, standards and procedures dealt with included: communications systems and air
navigation; airport characteristics; rules of the air and airport traffic control; air worthiness of aircrafts;
licensing and operation and mechanical personnel; aeronautical maps and charts; log books; and
measures to facilitate air navigation (Bryan, L.A., et al; 2006).
Most importantly, the convention affirmed that every nation has sovereignty over the airspace above its
territory and that “every civil aircraft must be registered, carry the nationality of the country of
registration, and bear appropriate identification markings” (Bryan, L.A., et al; 2006). However, the
convention also granted transit rights and permitted non-scheduled, charter, and private flights. Transit
rights refer to the right to fly over another nation’s territory and to the right to land for non-traffic
purposes, such as refuelling (1st to 4th freedoms of the air, see Section 2, above.)
The Chicago Conference agreed that a regulatory body should be established to ensure that the
contracting states implement and abide by the regulations, standards and procedures decided upon at
the convention. This was the initial formation of the ‘International Civil Aviation Organisation’ (ICAO).
The ICAO was formally established in 1947 as an agency of the United Nations linked to the Economic
and Social Council (ECOSOC). The Chicago Conference set forth the purpose of ICAO as:
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"The future development of international civil aviation can greatly help to create and preserve friendship
and understanding among the nations and peoples of the world, yet its abuse can become a threat to the
general security; and it is desirable to avoid friction and to promote that co-operation between nations
and peoples upon which the peace of the world depends; therefore, the undersigned governments having
agreed on certain principles and arrangements in order that international civil aviation may be
developed in a safe and orderly manner and that international air transport services may be established
on the basis of equality of opportunity and operated soundly and economically.”
(Preamble to the Convention on International Civil Aviation - Chicago, 7th December 1944)
The ICAO’s primary mandate was to foster development and promote co-operation in international civil
aviation. The major success of the convention was that it greatly advanced aviation safety and standards
as well as helping to foster bilateral aviation agreements between participating states.
1.3.2 Formation of state owned or sponsored airlines
The formation of state owned or sponsored flag carrier airlines (such as South African Airways)
operating out of a hub airport (such as O.R. Tambo Airport), is a result of the regulations set out by the
Chicago Convention. Traditional aviation agreements between countries help protect flag carrier airlines
by defining the landing rights allowed, restricting the number of flights on a particular route, restricting
the amount of freight or passenger seats available and restricting foreign airlines to specific airports.
Therefore, flights are directed through a specific airport, as illustrated in figure 1.3-1, below. As can be
seen in this figure an overwhelming majority of South African Airways flights are directed through O.R.
Tambo International Airport in Johannesburg.
Figure 1.3-1 South African Airways International Route Map
Source: http://www.airlineroutemaps.com/Africa/South_African_Airways.shtml, accessed October 2009
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Illustrated in Figure 1.3-1, airlines have traditionally operated out of a central hub airport to various
destinations around the world. Therefore, if a person wants to travel from Windhoek (Namibia) to
Lusaka (Zambia) on South African Airways, they would need to fly first to Johannesburg before
transferring to a flight to Lusaka. The trip to Johannesburg not only adds unnecessary time to the
journey, but adds significant cost in airport taxes and flight costs.
State sponsorship or ownership of international flag carrier airlines is still very prevalent in Africa and a
list of flag carriers and level of state ownership can be found in Appendix C. More than 50% of national
flag carriers listed in Appendix C are still owned or funded by the state.
1.3.3 Liberalisation of aviation agreements
Since the Chicago Convention of 1944, aviation technology has accelerated rapidly. Today modern
aircraft are far more efficient in terms of speed, service and safety than in the past. However, due to
aviation regulations between countries not modernizing in tandem with technology and increased levels
of globalisation, these improvements in the aviation industry have had a somewhat limited impact on
the commercial aviation market. The InterVISTA-ga2 report highlights this in the following passage:
“Commercial aviation still faces a challenge common to many of the newer and technically advanced
areas of our society. Our social and political institutions have not kept pace with the evolution of
technology or the needs of the public. Commercial aviation remains encumbered by well-meaning but
outmoded and arcane rules, principles and institutions. They often prevent fit, willing and able airlines
from fully serving passengers and shippers who are completely willing and able to pay. They also impose
protective machinery that frustrates innovation and directs the evolution of the industry into a contrived
and artificial structure. By sheltering airlines from market forces, they reduce the incentives to pass on to
passengers, shippers and investors the benefits of improved technologies.”
When aviation regulations were created in the first half of last century, aircraft technology, speed and
safety were limited and expensive. This encouraged formation of national flag carrier airlines that were
either state-owned or state-subsidised. Airlines were treated and run as pure monopolies (within nation
states) and cartels internationally, requiring state assistance and regulation to survive. However, as
technologies and efficiencies in the aviation industry have improved and become accessible, the overall
costs of operating airlines have decreased.
The airline market can best be explained by Figure 1.3-2 overleaf, which shows the demand curve for a
pure monopoly and a monopoly.
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Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly
When aircraft technology was expensive and airline efficiency was severely limited compared with
today, airlines were treated as pure monopolies or members of cartels that needed to be protected and
subsidised or owned by government. Thus Part A of Figure 1.3-2 shows that the average cost of an
airline, characterised as a pure monopoly, is higher than the price, resulting in economic losses. This is
due to inefficient technologies which were too costly for commercial viability. To ensure the survival of
an industry or company operating under conditions of pure monopoly, it is essential that it is subsidised
by the difference of P2 and P1. Therefore, in order for countries to access the global market, it was
essential for governments to meet this short fall in the operating costs of national flag carrier airlines.
In today’s world where aviation technology is more advanced and accessible, average costs have
decreased and the market can better be described as a monopoly. It can be argued that the average
costs of the airline industry have decreased to levels where average costs are now lower than price.
National flag carrier airlines operating as monopolies seek to maximise profit through offering a sub-
optimal quantity of seats. This profit can be seen in Part B of 1.3-2, namely the difference of P1 and P2. In
an open and competitive market, national flag carrier airlines would be forced to operate at competitive
equilibrium (where the marginal cost line, average cost line and average revenue/demand line
intersect). As can be seen in the figure, competitive market forces would determine equilibrium at price
PE (lower than that of the price set by a monopoly) and quantity of seats QE (higher than the quantity set
by a monopoly), directly benefiting consumers of air transport and freight.
Airlines have not only functioned as monopolies in the last 15 years, but also as oligopolies on routes
that are shared with competing airlines. Airlines collaborate with each other to reduce competition and
keep prices high on certain routes, thus increasing the profit made. In an open competitive market, both
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airlines would undercut each other prices and improve their services and capacity on those routes,
thereby making air travel more accessible.
Thus, the focus of the international aviation community over the last 15 years has been on liberalising
aviation agreements between countries and opening up the airways, to eliminate this market
inefficiency that is ultimately being paid for by the consumer.
1.3.3.1 Air Transportation Liberalisation Agreements
The United States started pursuing the first air transportation liberalisation agreement in 1972. By 1983
the country had signed 23 bilateral air service agreements. European states followed suite in the 1990s
by opening up their airspaces to other European nations (discussed in Section 1.5.2 further on). In 1992
a massive step was taken towards liberalising air regulations when the US signed an air transportation
liberalisation agreement with the Netherlands. This agreement gave each country unrestricted landing
rights.
Air transportation liberalisation has been more vigorously pursued by the international community over
the past 15 years, particularly at a regional level. Prior to 1994 there were just two regional air
transportation liberalisation agreements, namely the European Union that included 15 member states,
and the Andean Pact that comprised of five South American states (ICAO, 2005). Since 1995, eight more
regional arrangements have emerged:
The Caribbean Community (CARICOM) Air Service Agreement amongst 15 States in the
Caribbean (1996, entry into force in 1998 for nine States);
The Fortaleza Agreement amongst six states in South America (1997);
The Banjul Accord amongst six states in Western Africa (1997, a separate more liberal
multilateral agreement was signed among seven States in 2004);
The CLMV Agreement by Cambodia, Lao People’s Democratic Republic, Myanmar and Viet Nam
(1998, a formal multilateral agreement was signed in 2003);
The Intra-Arab Freedoms of the Air Programme amongst 16 States of the Arab Civil Aviation
Commission (ACAC) in the Middle East and Northern Africa (1999);
MALIAT – Multilateral Agreement on the Liberalisation of International Air Transportation
(MALIAT) between Brunei, Chile, New Zealand, Singapore and the United States
An agreement amongst the six States of the Economic and Monetary Community of Central
Africa (CEMAC) (1999);
An agreement amongst the 20 States of the Common Market for Eastern and Southern Africa
(COMESA) (1999); and
The Yamoussoukro II Ministerial Decision amongst 53 African Union States (1999, entry into
force in 2000).
Of the eleven agreements listed above, eight have been fully implemented or are in the process of a
gradual implementation. The last three in the above list require further discussion or decisions made by
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the various governments, one of these being the air transportation liberalisation initiative for Africa the
Yamoussoukro Decision. An attempt has been made to find more information on these regional air
transportation liberalisation agreements; however the literature available is either in a foreign language
or does not give the detail required for analysis. There is no literature available for the Africa air
transportation liberalisation agreements.
1.3.3.2 The Yamoussoukro Decision
The structure of the aviation market in Africa over the last three decades has been shaped by protective
bilateral agreements between states, where free market economic logic has played an limited role. The
majority of African states have moved towards bilateral aviation agreements and regulations that
ensure the protection of national flag airline carriers (Economic Commission for Africa, 2001). There has
been a limitation on the agreement of 3rd and 4th air freedoms (air freedoms are explained in Section
1.2) and reluctance to authorise technical landing for flights continuing to other destinations. The
majority of African countries designated flag carriers enjoy exclusive monopolistic rights in these
markets. The consequence of this has been a limited improvement in the quality and quantity of air
services throughout the continent. In addition, the vast majority of African airlines either have
government as a majority or full shareholder. This has been demonstrated in the table provided in
Appendix C, listing every airline in the world and whether these airlines are owned, partly owned or
subsidised by their governments.
Figure 1.3-3 overleaf shows the total number of domestic and international airline passengers, by
region. As can be seen from the figure, Africa has significantly smaller volumes of passenger seats being
purchased, at 114 million seats in 2006, than the developed regions of North America, Europe and Asia -
at 1529 million, 1367 million and 980 million passenger seats respectively. Latin America and the
Caribbean is almost double the size of Africa, at 272 million passenger seats, with only the Middle East
showing similar market size at 111 million seats in the year 2006.
African ministers took significant steps forward in liberalisation of the African airspace when they signed
the Yamoussoukro Decision (YD) in 1999. The intention was that YD would be achieved by gradual
liberalization of scheduled and non-scheduled intra African air transport services, thus leading to the
emergence of a viable and quality African air transport that meets the imperatives of the consumers of
air services (African Union, 2005).
The general aim of YD is to encourage co-operation among African states through air transportation
policies that encourage deregulation of the aviation industry, promoting competition on routes and
reduced airfares between African destinations. YD promotes fundamental changes in the nature and
operation of airlines, in national economies, in tourism and in relationships between African states
(SSamula B. & Venter C., 2005). YD gave the Economic Commission for Africa (ECA) and the ICAO the
responsibility of implementing the agreement between the various African states.
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Figure 1.3-3 Total number of domestic and international airline passengers, by region
Source: ICAO, 2007
YD advocates the following:
That only African owned airlines would benefit from the implementation of YD
The granting of 1st to 5th air freedom rights (as well as cabotage, the 8th air freedom rights);
Encouraging the development of new routes;
Removal of capacity restrictions on passenger seats, freight and flights on certain routes;
The removal of expensive and complex tariff regulations;
The elimination of all protective policies that protect national flag carriers;
The termination of regulations on carriers’ alliance;
Doing away with restriction on the conversion of revenues to hard currency and repatriation;
Agree on code sharing; and
Allow carriers to have own-ground-service abroad
The ECA and ICAO are not the only institutions that are interested in the liberalisation of the African
skies. Figure 1.3-4 overleaf highlights the relationship of the various organisations and structures that
are responsible for the implementation of YD
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Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs
Source: SSamula B. & Venter C., 2005
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Full aviation liberalisation proposed by YD was expected to be completed by 2002 with a total removal
of restrictions on traffic rights (including 5th air freedoms), as well as removal of capacity constraints
between origins and destinations, non-regulation of tariffs by government, multiple designations, and
complete liberalisation of cargo and non-scheduled air services (Economic Commission for Africa, 2001).
Also by 2002 a monitoring body would have been formed to oversee and enforce the various YD
agreements.
All in all YD had a number of very good intentions for the African continent; however it has faced
significant obstacles in realising the potential gains and implementation has largely failed. The reasons
for this failure are highlighted in an African Union Report (2005):
Confusion in the monitoring body of the Yamoussoukro Decision
o The African Union (AU) is named as chair of the monitoring body, but has been given
equal status to the other specialised African institutions such as the African Airlines
Association (AFRAA), the African Civil Aviation Commission (AFCAC) and Regional Trade
Organisations (RTOs).
o The roles of these specialised African institutions are unclear and they are cited only as
members, resulting in confusion as to responsibilities.
o Furthermore the RTOs are mentioned as back-up to the AU, which is not practical as
these bodies would primarily be responsible for ensuring the implementation of YD at a
regional level.
Conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These
conditions allow any airline which has “its headquarters, central administration and principal
place of business physically located in the state concerned” to be eligible to benefit from the
advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most
part controlled by foreign capital or interests. The European Union has put in place very
restrictive conditions in terms of eligibility so as to protect the airlines of its community.
YD makes no mention of economic control of eligible airlines - there should be a provision in YD
requiring airlines to avail to audit boards all accounting and financial documents to ascertain
their economic status. These audit boards do not exist.
Competition rules as contained in the Yamoussoukro Decision are inadequate. Competition
rules need to be defined further and the following prohibitions need to be made:
o No direct or indirect state or parastatal subsidies.
o No private financial aid that is not consistent with generally accepted rules and
regulations governing private financing.
o Equal access of all community airlines to state or parastatal markets (travels of state or
parastatal officials, tenders and pilgrimages)
o Ban on abuse of dominant positions.
o Clear and equitable rules for the allocation of time slots through the establishment of a
time slot co-ordination body comprising airport authorities, airlines and civil aviation
authorities.
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o Establishment of an African Union level body to ensure implementation and compliance.
o Authorities responsible for the implementation of the Yamoussoukro Decision lack
resources and co-ordination for the attainment of the objectives set in the short term -
The monitoring body requires adequate financial resources and political support to
enable it to fully play its role.
For the most part of the last decade the implementation of YD has moved at slower pace than expected
and is still far from being implemented in most regions of Africa and the continent itself. Progress has
been made amongst many of the West African countries and domestically within South Africa.
Furthermore, a number of countries have opened their skies to the United States; among these are
Morocco, Nigeria, Ghana, Senegal, Tanzania, Namibia, Burkina Faso, Gambia and Benin (see Appendix B)
Both Ethiopia and Kenya have entered into air transportation liberalisation negotiations with the United
States.
1.3.3.3 African Aviation Competition Authority
For a successful implementation of an air transport liberalisation agreement, a proper competition
authority is required to monitor that no airline acts in an uncompetitive, monopolistic or oligopolistic
manor. Without a monitoring body national flag carriers who have dominated the aviation market in
Africa could uncompetitive restrict the access of new low cost carriers. Dominant airlines in the region
(such as South African Airways) could also exert unnecessary pressure on smaller airlines.
It is necessary that a competition authority be setup by the regional political body such as the South
African Development Community. The competition authority should comprise of employees/members
from the various members states of the agreement, if this is not possible each state must be in full
agreement with the staff/member complement of the competition authority. It is absolutely essential
that the competition authority be given full political support of each member state and the power to
prosecute airlines that act in an uncompetitive manor. Without any of these commitments establishing
an aviation competition authority is pointless.
The completion rules have already been stated, but are worth repeating:
o Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC
o The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights);
o Encourage the development of new routes;
o Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes;
o Ensure the removal of expensive and complex tariff regulations;
o Ensure the elimination of all protective policies that protect national flag carriers;
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o Ensure the termination of regulations on carriers’ alliance;
o Remove restriction on the conversion of revenues to hard currency and repatriation;
o Agree on code sharing;
o Allow carriers to have own-ground-service abroad;
o Not allow any direct or indirect state or parastatal subsidies;
o Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing;
o Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages);
o Ban on airlines who abuse a dominant positions;
o Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.
1.4 Assessing and forecasting the impact of air transportation liberalisation
agreements
There are various methods that have been used to evaluate and forecast the impact of air
transportation liberalisation agreements on aviation markets. Methods include: the case study
approach; the trends model; gravity models; stimulation models and air transportation cost analysis
(Swan, 2008). These methods predict or analyse the growth in aviation markets if regulations were
liberalised, thereby making it possible to understand how growth is being restricted in regulated airline
markets. Each method has its limitations and takes into account different aspects predicting the effects
of air transportation liberalisation agreements. The various approaches that can be used are discussed in
detail in this section. Graham Muller Associates incorporated various aspects of these methods when
predicting the impact of air transportation liberalisation agreements in SADC region.
1.4.1 The case study approach
The case study approach is relatively simple and looks at actual data. Of all the existing methods, it is the
only method that does not forecast or predict future growth. The case study approach analyses
passenger seats, freight by tonnage and air fares before and after air transportation liberalisation
agreements have been implemented. This is a crude analysis of air transportation liberalisation
agreements as it does not fully take into account the market size, distances between countries, level of
airport infrastructure and the proportion of the urban population with access to airports. This analysis
has a limited applicability to nations considering air transportation liberalisation agreements, as country
conditions often differ drastically. This method tends to be the most common analysis used in the
literature reviewed. Various case studies are discussed in Section 1.5 further on.
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1.4.2 The trends model
The trends model uses statistical regression analysis to isolate the effects of travel against an economic
activity such as GDP. This model uses historic travel, flight and GDP data to forecast future aviation
industry growth. Therefore the model does not recognize changing conditions like air transportation
liberalisation agreements that increase the amount of passenger seats and freight tonnage as shown in
the case studies reviewed below. GDP is used to explain growth in air travel, there is no dependence on
other causal activities, such as price, service, trade, distance, regulations or airport infrastructure. Thus
results using this method are often unreliable and if a country is still operating under regulated aviation
agreements the method will not account automatically for the growth brought about by deregulation.
(Swan, 2008). This can always be catered for in a more complex model.
1.4.3 The gravity model
While the trends model constrains the forecast by not being able to account for regulation changes, the
gravity model is an unconstrained forecast that determines total demand in a deregulated air market.
The gravity model uses the size of the origin (city or country) times the size of the destination as an
indication of the demand for flights between them. This model assumes that the bigger the population
size of the origin and the population size of the destination, the bigger the attraction and demand for
flights. Sizes of the origin and destination are measured in population, GDP or number of
passengers/freight traveling by air.
The model does not account for distance and therefore ignores the impact expected when the origin
and destination are further apart and the flights demanded diminish. Therefore in some instances the
distance between the origin and destination can be used to further calculate the estimated demand of
flights on a particular route (number of flights or airline operating on routes is not taken into account.)
Equation (1) shows the most classical form of the gravity model calculation.
Equation (1) Demand = (Pop Origin * Pop Destination)/Distance
The problem with this model is that it tends to overstate or understate demand on certain routes. This
model also assumes that bigger populations consume more air travel, which is only a valid assumption
provided that the majority of the population is earning a salary that permits them to consume air travel.
Figure 1.4-1 overleaf shows the ratio between the gravity model’s forecasted amount of air travel
consumed and the actual amount of air travel consumed in the European region. For this to be an
accurate method of forecasting the majority of the points should be located around the horizontal line
at 1.0. Instead, for the majority of these routes there was far more air travel consumed than forecasted
(Swan, 2008).
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Figure 1.4-1 Gravity forecast fails to fit actual data, European Region
Source: Swan, W. 2008
1.4.4 The stimulation model
The stimulation model estimates the increase in air traffic arising from changes in fares and service
levels. This model requires good data on how the volume of air tickets purchased changes as the price of
these tickets changes. The model could have problems in forecasting air traffic levels where the base
data is taken from an airport or airline running at full capacity. Generally the type of data required for
this analysis is not available or there is inadequate historical data on how price changes have affected air
traffic (Swan, 2008).
1.4.5 Air transport cost analysis
There has only been one study to date that uses various sources of historic data to run regressions
analysing the main contributors to air transportation costs. This is not a reflection of the merit of the
approach, but is likely to be a result of the extensive data requirements of a fully comprehensive cost
analysis. This approach is discussed in detail in Section 1.6.1 further on. Cost analysis is able to take into
account distance, total volume, value per unit weight of cargo, foreign airport infrastructure, regulatory
quality, as well as whether or not an air transportation liberalisation agreements existed between the
countries involved and to what extent air freedoms were allowed in this agreement.
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1.5 Case Studies
This section examines three case studies with respect to the impact that air transportation liberalisation
agreements have had on each country. These case studies look at the United States and the United
Kingdom, the European Union, and finally India and the United Kingdom. It is important to note from the
outset of this section that all the case studies discussed below instituted 1st to 5th air freedoms, as well
as allowing cabotage the 8th air freedom, when liberalising their aviation markets.
1.5.1 United States – United Kingdom
The United States (U.S.) and United Kingdom (U.K.) aviation agreement is complex and somewhat
contentious. While this agreement is liberal in some aspects it is still restrictive by limiting access to
Heathrow and Gatwick airport. In the years leading up to the 1990’s U.K. – U.S. air traffic represented
one third of all U.S. – E.U. traffic. During the 1990’s, the U.S. and the U.K. liberalized the traditional
agreement that had been in place since 1978. As part of that agreement, the U.S. - U.K. market was
deregulated, with the exception of Heathrow and Gatwick airports. Otherwise, carriers could operate
any city pairs, and at pricing that was commercially determined. Both the U.S. and the U.K. have globally
dominant aviation markets and large economies, which tends to make aviation agreements involving
these two counties fairly problematical. Both states attempted to sway the agreement in their favour
and maintain or grow their market share.
The liberalisation of the air market between the U.K. and the U.S. led to capacity growth on then trans-
Atlantic route at a compound annual rate of 7.8%. The market share in passenger seats over the Atlantic
shifted over a ten year period from 48% U.S. flag carriers in 1990 to 58% U.S. flag carrier in 2000. At the
end of 2005, the U.S. had lost a slight portion of this gain with market share over the transatlantic falling
back to 56%. Figure 1.5-1, overleaf, demonstrates graphically the number of passenger seats for both
U.S. and U.K. carriers between the periods 1990-2005. A decrease in passenger seats between 2001 and
2002 can be attributed to the 11 September 2001 attacks in the U.S. and the outbreak of the Severe
Acute Respiratory Syndrome (SARS) virus in 2002.
It is estimated that the air transportation liberalisation agreement between the U.S. and U.K. is
responsible for stimulating 9,197 full-time equivalent jobs in the United States and over 16,700 full-time
equivalent positions in the United Kingdom. It is also estimated that the gross domestic product of the
United States also expanded by $747 million due to the agreement and the United Kingdom by roughly
$970 million. InterVISTA-ga2, 2006, estimated that a full air transportation liberalisation agreement
between the U.S. and the E.U. would result in a 29% increase in traffic, due to increased passenger
volumes between the U.S. and Heathrow and Gatwick airports. The economic benefits of a complete air
transportation liberalisation agreement would also mean that “117,000 full-time equivalent positions
would be created and the GDP of the two countries would grow by roughly $7.8 billion” in 2006
(InterVISTA-ga2, 2006.) Subsequent to the InterVISTA-ga2, 2006 report, the U.S. negotiated an air
transportation liberalisation agreement with the E.U. that has paved the way for the U.S. to enter into a
complete air transportation liberalisation agreement with the U.K.
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Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers
Source: adapted, InterVISTA-ga2, 2006
1.5.1.1 A limited air transportation liberalisation agreement with the U.S.
The E.U. air transportation liberalisation agreement with the U.S. has been criticised due to E.U.
companies being restricted such that they cannot obtain more than 25% of voting rights in US aviation
companies. On the other hand U.S. companies can acquire more than 50% of any E.U. aviation company
or airline (www.wharton.universia.net, 2009).
E.U. airlines are allowed to fly from any European Airport to any U.S. Airport, but cabotage within the
U.S. is completely restricted. On the other hand U.S. airlines are not only allowed to fly from any U.S.
Airport to any E.U. Airport, but cabotage within the E.U. is permitted.
British Airways has indicated that under an air transportation liberalisation agreement with the US it has
the most to lose, as 40% of transatlantic flights from Europe depart from Heathrow Airport which has
been deregulated. E.U. leaders (in particular the U.K. leaders) believe they can push the U.S. to review
the limitations of the agreement in 2010 when the air transportation liberalisation agreement is
revisited.
These restrictions are destroying competition and already DHL (a European based freight company)
cannot compete against U.S. freight companies. In this regard, DHL has closed down its U.S. branch,
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which means that some 8000 U.S. jobs have been lost. Furthermore it has now outsourced its aviation
services to ABX Air & ASTAR (both of these are US based freight companies) (Brown, 2008).
1.5.2 The European Union
The European Union signed an internal air transportation liberalisation agreement in 1992, called the
‘Single Aviation Market’; this was signed by the 12 member states at the time. The InterVISTA-ga2, 2006
report looked at the impact of this deregulation on the European Community market as a whole and the
impact of this deregulation on a number of selected air routes from Germany.
The process of liberalising aviation regulations was spread between 1987 and 1992, as it was resisted by
various member states and the entire aviation industry. The 1992 legislation was the third of three
packages. The first two (1987 and 1990) retained the bilateral system. Table 1.5-2 shows a summary of
the Intra-EU transport packages, the three air legislation agreements (1987, 1990 and 1992) and the
various aspects of this agreement.
The three stages of liberalisation in the E.U. aviation market and the dates that these agreements came
into force have been displayed in the three columns on Table 1.5-2, overleaf. The columns display how
over a 4 year period:
The regulations of airfares (fares) were relaxed,
More route designations could be added regardless of smaller demand,
Capacity share between states was eventually abolished, and
Air freedoms were increased
Table 1.5-3, overleaf, is a good indication of how a phased implementation of an air transportation
liberalisation agreement could be structured, thereby giving states, airports and airlines time to adjust
and improve aviation efficiencies.
Table 1.5-1, overleaf, shows the capacity and traffic growth for all of Europe, between the periods of
1990 – 2002. The results shown only take into account the change between the first and the last year in
the four year period. This removes some of the explainable short term fluctuations such as the 11
September 2001 attacks in the U.S. As can be seen, the growth in passengers carried by all European
airlines between 1998 - 2002 more than doubles that between 1990 - 1994.
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Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002
Increase in passengers carried
Market 1990-1994
1994-1998
1998-2002
Total Europe
20.40% 37.80% 40.90%
Source: InterVISTA-ga2, 2006
One of the significant findings of the liberalisation process in the E.U. has been the gain in market share
by low cost carriers. Before liberalisation low cost carriers were restricted to certain
Table 1.5-2 Summary of Intra-EU transport packages
Source: InterVISTA-ga2, 2006
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routes and booking slots. They also competed against subsidised national flag carriers. Table 1.5-3
below shows how the low cost carrier airlines have grown their market share in the aviation industry,
from 1996 to 2003. These low cost carriers have moved from a 1.4% market share to more than a fifth of
the share in the aviation market.
Table 1.5-3 : Capacity Shares of Low Cost Carriers
Year Low-Cost Operators’ Share of Capacity
1996 1.40%
1997 2.80%
1998 3.70%
1999 4.20%
2000 6.00%
2001 6.40%
2002 11.10%
2003 20.20% Source: InterVISTA-ga2, 2006
Liberalisation of the E.U. aviation market between 1988 and 1993 has led to an additional 44 million
passengers being carried annually, which equals a 33% increase in passenger seats. This traffic
expansion has encouraged development of both the tourism sector and other industries. Some 1.4
million full-time jobs resulted from the liberalisation, and European GDP grew by $US 85 billion.
1.5.3 India – United Kingdom
The aviation regulations between India and the United Kingdom (UK) were liberalised in late 2004 to mid
2005. The United Kingdom Civil Aviation Authority put together a case study of pre- and post- lair
transportation liberalisation agreements between India and the UK. The Civil Aviation Authority focuses
primarily on the effects that this agreement has had to date on aviation in the UK. They laid out the
report in four sections: impact on consumers; impact on the airlines; impact on the airports; and impact
on the wider economy.
1.5.3.1 Impact on consumers
Consumers were the biggest beneficiaries of the air transportation liberalisation agreement between
India and the UK, due to the increased number and choice of services, destinations and airlines
operating between these two countries. Between summer 2004 and summer 2006, the number of
direct flights between India and the UK rose from 34 to 112 per week. This can be seen in Figure 1.5-2
overleaf, which shows growth in U.K. – India direct services between 2000 and 2006.
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Figure 1.5-2 Growth in UK-India direct services 2000-2006
Source: United Kingdom Civil Aviation Authority, 2006
The majority of the new flights are operating between the main airports of India and the UK– London
Heathrow (an increase of 77 services per week), Delhi (an increase of 23 services per week) and Mumbai
(an increase of 38 services per week). However, new flight origins and destinations have been added in
both the UK and in India– Birmingham, Amritsar and Bangalore. This increase in services has been
provided by a combination of airlines which were already serving the market (British Airways, Virgin and
Air India) and new entrant airlines (JetAirways, bmi and Air Sahara.) Figure 1.5-3, overleaf, shows the
added airports and airlines serving the market.
Furthermore, the increase in capacity and more intense competition has resulted in a reduction in air
fares, from £882 to £736 for one-way fare paid by passengers travelling for business class and £251 to
£231 for one-way fare paid by passengers travelling economy class. Airlines have had to discount fares
to compete for customers.
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Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006
Source: United Kingdom Civil Aviation Authority, 2006
1.5.3.2 Impact on Airlines
The impact of air transportation liberalisation agreements on airlines is both positive and negative. The
increased competition reduces profits, whilst the new commercial freedoms enabled previously
excluded carriers to enter the market, offering services for the first time. The frequency market shares
for the carriers before and after liberalisation can be seen in Table 1.5-4 below. This shows that the
liberalisation of the aviation market led to more competition and reduced the oligopolistic and
uncompetitive nature of this previously regulated market.
Civil Aviation Authorities modelling shows that while UK airlines benefited from an increase in revenue
of £30 million between 2004 and 2005, reductions in fares reduced profits by £46 million.
Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons
Airline Summer
2004 Summer
2006
British Airways 56% 37% Virgin Atlantic 9% 12% bmi 0% 6% Air India 35% 22% Jet Airways 0% 20% Air Sahara 0% 3%
Total 100% 100% Source: United Kingdom Civil Aviation Authority, 2006
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1.5.3.3 Impact on Airports
The benefit to airports from air transportation liberalisation agreements is the added revenue brought
about by the increase in services from the added number of flights. Civil Aviation Authorities modelling
suggests a net benefit to UK airports of around £12 million of additional profits from increased revenues
of £65 million. The paper did not quantify the impact on Indian Airports. Airports such as Amritsar and
Bangalore, which were previously not served, now accommodate international flights to and from the
UK. Figure 1.5-4 below shows the growth of point-to-point markets from the UK to India. As can be
seen, the air transportation liberalisation agreement benefited the existing airports as well as new
airports accepting international flights.
Figure 1.5-4 Growth of direct point-to-point markets from the UK to India
Source: United Kingdom Civil Aviation Authority, 2006
1.5.3.4 Impact on the wider economy
The impact on the wider economy is mostly made up of circumstantial evidence in the report. Trade
levels between the UK and India increased by approximately 25% from 2005 to 2006. Foreign direct
investment by Indian companies into the UK grew by 110 % in the same period. While it is difficult to
demonstrate that the air transportation liberalisation agreement was responsible for this, the results
suggest that the agreement was certainly a contributor. The Civil Aviation Authority stated that “this
point is supported by survey data for the latest available years (2004 to 2005) which shows that direct
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business traffic has grown at a similar rate to leisure traffic in the year 2004 to 2005 (37 per cent
compared to 48 per cent), suggesting that aviation liberalisation is facilitating greater business activity
between the two countries.” Added to this circumstantial evidence is the fact that India’s strong
economic growth is being partly driven by a move into higher-value, more export-orientated sectors
such as IT and pharmaceuticals, which have a requirement for air transportation. The growth in the
frequency and capacity of direct UK-India flights is likely to have a further effect on the development of
these businesses. It is also important not to forget that there has been substantial growth in tourism
between these two countries.
1.5.4 Impact of an international air transportation liberalisation agreement
The InterVISTA-ga2 report attempts to measure the impact of a global liberalisation of aviation
agreements. The impacts were measured in
Passenger seats,
Air freight traffic,
Employment,
Gross domestic product,
Tourism and
Catalytic investment impacts
for any country-pair. Most of the base data used in the models came from various case studies that
analysed the various changes in the measurements when aviation regulations were liberalised. Time
series and cross sectional models were then used to assess the impact of air transportation
liberalisation.
The findings of the United Kingdom Civil Aviation Authority, 2006, report estimated that if 320 pair
country markets, currently not in an air transportation liberalisation mode, liberalise their air service
agreements air traffic would grow by 63%, significantly higher than recent world traffic growth of
around 6 - 8% per annum. This growth could potentially create 24.1 million full-time jobs and generate
an additional $490 billion in GDP, which is the equivalent of an economy the size of Brazil.
1.6 Forecasted effects of air transportation liberalisation agreements
The case study approach in Section 1.5 paints air transportation liberalisation agreements in a very
positive light and suggests that only benefits accrue to countries that open up their airspaces and
airports. However, air transportation liberalisation agreements do not always have the impact hoped by
countries entering negotiations, as shown in studies conducted by Micco and Serebrisky (2006) and
Swan (2008).
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There are two essential issues discussed by Micco, et al, (2006) and Swan (2008) that should be
considered before a country enters into an air transportation liberalisation agreement:
Firstly, does the country have adequate infrastructure, a regulatory body, available skills and sufficient market size?
And secondly, can a country afford to shift aviation activity away from a central hub airport as shown in Figure 1.3-1.
These two questions have particular relevance for Africa and more specifically for the Southern African
Development Community. In this section we will discuss and highlight the outcomes and
recommendations of Micco, et al, (2006) and Swan (2008).
1.6.1 Infrastructure, regulatory body, skills and market size limitations
The first study undertaken by Micco, et al, (2006), made use of regression analysis to estimate the effect
that air transportation liberalisation agreements had on transport costs. They primarily used data on air
transport costs from the US Imports of Merchandise Database. The data covered the period 1990 to
2003, where the US entered into a number of air transportation liberalisation agreements with various
countries. This period provides ample time to analyse these agreements and assess their effects in
totality.
Further data used in the regression included:
The distance between the freights origin and its destination in the US. This is an important consideration as distances between origins and destinations do not change when air transportation liberalisation agreements are concluded, and the price of jet fuel price is unaffected by these agreements.
GDP and GDP per capita in US dollars for both the origin of the freight and its destination in the US.
The percentage of the population which resides in urban areas, as it was assumed that the vast majority of air freight is generated from urban and peri-urban areas.
Certain data on airports and cities; these geographic coordinates, population of major urban cities, number of paved runways, as well as runway lengths and widths.
An infrastructure skills index.
The econometric model used in Micco, et al, (2006), is shown in equation (2) overleaf. The coefficients
are shown in Table 1.6-1 overleaf. The results display the cross sectional analysis of regression on
transport costs. It can be seen in Table 1.6-1 that the product unit value (which is the value per unit
weight of cargo at 4-digit SITC) and distance per port of entry (which is the distance between the origin
of the air freight and the destination in the US) have the highest positive coefficients, meaning that total
transport cost increases most significantly for each additional km travelled or value per unit weight of
freight transported. Improved foreign airport infrastructure reduces transport costs by the greatest
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amount, whilst the benefit of an air transportation liberalisation agreement has a much smaller impact
on transport costs than expected.
The figures in brackets in Table 1.6-1 show the standard error, and it can be seen that the standard error
for certain coefficients is so slight that we can assume these to be close to correct. However, the
standard error for Total Volume, Imbalance and Open Sky Agreement vary quite significantly. It is also
reported on Table 1.6-1 that Distance per port of entry, Product unit value, Foreign airport
infrastructure index and the implied effect infrastructure index are all significant at 1%, this tells us that
we are 99% confident that these variables have an effect on transportation costs. These results tell us
that the distance of an airport, the value of the product being shipped and the infrastructure of the
foreign airport have the largest significant effect on transportation costs.
Table 1.6-1 Section analysis of regression on transport costs
Distance per port of entry (ln) 0.244
S.E. (0.04) significant at 1%
Total volume (ln) 0.001
S.E. (0.02)
Product unit value (ln) 0.476
S.E. (0.011) significant at 1%
Imbalance -0.079
S.E. (0.072)
Air transportation liberalisation agreement -0.04
S.E. (0.046)
Foreign airport infrastructure index II (FAII1) -0.39
S.E. (0.119) significant at 1%
Regulatory quality -0.15
S.E. (0.04)
Implied effect infrastructure index -0.183 significant at 1%
Sample All countries
R-squared 0.335 Source: Micco, et al, (2006)
Equation (2): Transport cost origin-destination = dummy variable + distance origin-destination + total volume origin-destination + product unit value origin-destination + trade imbalance origin-destination + foreign airport infrastructure origin + regulatory quality origin + air transportation liberalisation agreements + error term
Further analysis was conducted on the air transportation liberalisation agreement coefficient in this
study but more noteworthy are the results shown in Figure 1.6-1 overleaf. As seen in Figure 1.6-1, the
coefficient on air transportation liberalisation agreements increases in size with each year, indicating
that air transportation liberalisation agreements have more of an impact on reducing transport costs the
longer the time period elapsed since implementation. This is to be expected as air markets need time to
adjust to the new regulations when significant changes take place. Micco, et al, (2006) primarily focused
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on air freight transport. They eventually estimated that over a period of five or more years, an air
transportation liberalisation agreement could potentially reduce air freight transport costs by roughly
9% and increase foreign trade by 12%.
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Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time
Source: Micco, A. et al 2006
The most important finding in this paper is that air transportation liberalisation agreements do not have
the same effects in all countries. For instance air transportation liberalisation agreements in developed
and upper-middle- income developing countries reduce air transport costs, but for low-income
developing countries air transportation liberalisation agreements are not associated with a fall in freight
rates. This is understood as an indication that low-income developing countries cannot take full
advantage of air transportation liberalisation agreements because of other barriers to competition or
because of their limited market size. Micco, et al, (2006) also find that countries with better access to
airports, well trained airport staff, adequate airport infrastructure and better regulatory quality, have
lower air transport costs.
Therefore, if air transportation liberalisation agreements are to be maximised to their full potential
these issues need to be dealt with first:
Sufficient airport infrastructure needs to be in place .i.e. Appropriate runway lengths and widths, modern air traffic control systems etc.
Staff needs to be skilled in the various areas required to run an efficient air service.
Regulatory structures need to be in place to monitor the air market.
The market size of the country needs to be assessed and increased. Cargos and manufactured products (such as certain agricultural products, as well as electronic and highly technological goods) that are transported by air freight need to be assisted and initiated.
Other barriers to competition could range from political unrest and corruption to restrictive government policies. All of these need to be addressed in order for air transportation liberalisation to be successful in a country.
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1.6.2 Spread of development from hubs to outlying areas
The second study by Swan (2008) investigates how regulated markets have constrained travel within the
region. Swan (2008) lists techniques for forecasting air transportation levels in deregulated air markets,
highlighted in Section 1.5 above (the ‘Aviation forecasting models’). The paper moves on to review
forecasts by Boeing and Airbus for regional growth in air travel and air freight, by comparing these to
recent trends in growth and forecasts conducted by the author.
Table 1.6-2 below shows the forecasted growth in air travel between North-East Asia and North America
predicted by Airbus, Boeing and Swan. As can be seen these growth levels fluctuate between 5% - 6.5%
over 10 and 20 year periods.
Table 1.6-2 Forecasts in North-East Asian travel to North America
Swan 10yr
Boeing 20yr
Boeing Airbus 20yr
China 5.1% 6.4% 6.4%
Japan 5.3% 5.1% 5.0% 4.2%
Korea 5.9% 5.1% 5.6% 5.9% Source: adapted Swan, W. 2008
Figure 1.6-2 Actual air travel between North-East Asia and North America
Source: Swan, W. 2008
The report reveals how accurate these growth levels are by comparing them to the actual trends in air
travel growth to North America for the periods of 2007 and 2008. The actual air travel between these
two regions can be seen in Figure 1.6-2 above
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. Air travel between Japan and North America decreased during this period, while air travel grew at a
much higher rate than expected in China and Korea. Swan (2006) explains such differences between the
actual figures and the forecasts by stating: “the lesson here is that useful regional forecasts need to start
with good regional data, and they need to recognize changes in routes, fares, and political constraints
specific to the markets.”
The models used to forecast air travel growth are unable to account for changes in routes and route
development, and this tended to be the main reason the forecasts differed so much from the actual
data in air travel. Swan (2008) found that actual growth levels in air travel were similar to GDP growth
levels for each of the countries concerned.
One of Swan’s (2008) major findings in this report was that air services dramatically increased travel to
cities outside the existing list of major gateways, allowing them to participate to a much greater degree
in international trade. This is an important point for the Southern African Development Community to
take into account, as air travel and services may shift away from O.R. Tambo Airport in South Africa, to
outer lying airports in the region. Hence it is these smaller airports which may stand to benefit the most
from an air transportation liberalisation agreement and this may be at the expense of larger airports.
Over time an air transportation liberalisation agreement could help small regional and airports develop
by attracting more air traffic and economic activity into these regions, but at the same time O.R. Tambo
may lose air traffic and potential revenue.
1.7 Concluding Comments
From the literature reviewed we can conclude that air transportation liberalisation initiatives that have
been pursued are mostly successful in regions where implemented, provided that there is adequate
airport and tourism infrastructure. The literature would seem to suggest strongly that the deregulation
of the air space over Africa and the Southern African Development Community would bring about
significant changes to the structure and makeup of the current air market in Africa, and add value to the
economies of Africa. The level of change would depend on the how many freedoms of the air would be
permitted.
A number of African national flag carrier airlines would be the most vulnerable to these changes, as it
was reported in European region that low cost carrier airlines were the most likely to benefit from air
transportation liberalisation legislation. National flag carrier airlines would need to cut costs and move
towards efficient practices (similar to those of low cost carriers); they would also lose out on potential
revenue and market share as low cost airlines compete for passengers around Africa and the Southern
African Development Community. African tourism and business relationships would stand to gain the
most from an air transportation liberalisation agreement.
Crucial to the success of an air transport liberalisation agreement being implemented in the SADC region
and ultimately the African continent as a whole is the establishment of a competition authority. The
primary role of this authority would to discourage anti-competitive behaviour, allow easy access for new
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African airlines wishing to enter the market and ensure that no airline abuses a position of market
dominance. Furthermore this regulator could ensure that African governments remove aviation
regulations in the time frames agreed upon. It is therefore necessary that African member states to this
agreement give this body ultimate authority and the power to enforce the terms of the agreement
among reluctant states, airlines and airports.
The literature reviewed also shows that air freedoms 1 – 5, along with air freedom 8 encompasses the
standard package for an air transportation liberalisation agreement. Furthermore the literature
forecasts that if there were a global liberalisation of aviation markets, then air traffic would grow
significantly. This growth in air traffic would be create large amounts of additional full time employment,
as well as contributing hundreds of billions of additional dollars to global GDP (this extra GDP was
estimated to be equivalent to that of total Brazilian GDP.) The impact of air transport liberalisation
agreement being implemented in SADC is discussed and forecasted in the sections to follow.
An important consideration raised by the literature is that in order to take advantage of air
transportation liberalisation agreements, appropriate aviation infrastructure and skills are required,
namely– airport infrastructure, airline and airport efficiencies, regulatory controls, market size, the
population’s ease of access to airports and aviation markets, and political and business stability. Without
these conditions, countries will not be able to take advantage of these liberalised regulations.
Furthermore, the literature recognised that air transportation liberalisation would divert flights away
from hub airports, as passengers would demand more direct flights. It is necessary to assess whether
the current hub airports in SADC could sustain themselves in the future as further use is made of
alternative airports within the region.
Whilst the following sections will only estimate the impact of an air transportation liberalisation
agreement on the SADC region, it would be advisable for the Department of Transport to further
investigate the functions and make up of a regulatory body that would be necessary to assist in
implementing the air transportation liberalisation agreement for the entire region.
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2 Impact of air transport liberalisation agreement in Southern African
development Community
2.1 Introduction
This study sets out to determine the impact of implementing an air transport liberalisation agreement in
SADC. The following measures of liberalisation have been taken into account throughout the remained
of this section:
Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC;
The granting of up to 5th air freedom rights plus cabotage, the 8th air freedom right;
Encouraging the development of new routes;
Removal of capacity restrictions on passenger seats, freight and flights on certain routes;
The removal of expensive and complex tariff regulations;
The elimination of all protective policies in favour of national flag carriers;
The termination of regulations on carriers’ alliance;
Doing away with restriction on the conversion of revenues to hard currency and repatriation;
Agree on code sharing; and
Allow carriers to have own-ground-service abroad
After considering the above agenda and the general experience with air transportation liberalisation
initiatives elsewhere in the world, the research team determined that if an air transport liberalisation
agreement were to be implemented within the SADC region, two results can be expected:
a) That there will be impacts within the aviation market; and
b) There will be impacts felt within supporting industries to the aviation market. The impacts that
will be felt within the aviation market are termed as direct impacts and the impacts experienced
within the supporting industries are termed as indirect impacts.
An assessment of both the direct and indirect impacts will be used to determine the costs and benefits
of implementing the an air transport liberalisation agreement within the SADC region. This method is
known as cost-benefit analysis (CBA).
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The study identified the following direct and indirect impacts:
Direct impacts:
On Airlines
On Airports
Passengers
Freight
Customs
Indirect impacts:
On Tourism
On Airport services
Aircraft manufacturers
Environment
Intermodal services
Government
Based on available data, direct and indirect impacts are calculated and utilised in the cost benefit
analysis. Data used includes feedback from stakeholders via the questionnaire and other sources..
A diagram that illustrates the various components of the cost benefit analysis can be viewed in the
Appendix D.
It is observed that the quantifiable benefits of implementing an air transport liberalisation agreement in
SADC far outweighs the quantifiable costs of such an implementation over the 50 year period.
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2.2 Overview of the Current Status of the SADC Aviation Industry
SADC flight departure data indicates that certain airlines in SADC service mainly domestic routes and
service very few international routes, while other airlines are largely reliant on international business.
The following analysis focuses on the number of domestic and international departures for major
airlines in the SADC region. The general trend for most airlines indicates that there has been a gradual
increase in the total number of departures over the years; however a decrease in total departures is
noted during the 2007 to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in
the global economy over this period. Although the September 11 attacks reduced worldwide air travel
significantly, most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine
flu also had little impact on most SADC based airlines. SADC airlines more commonly encountered
periodic problems due to internal issues such as financial losses, inefficiency and safety of aircraft or due
to localised external problems such as political instability in countries where the airlines operate. It is
noted that national carriers generally split departures between international and domestic while low
cost carriers mainly undertake domestic flights.
A country by country analysis follows.
2.2.1 Angola
There are currently 9 airlines operating in Angola. Non-availability of data for these airlines prevents
analysis of the current and past trend in departures and passenger numbers. Fleet sizes for the airlines
were available and are illustrated in Figure 2.2-1 overleaf.
The largest fleet belongs to SonAir with 32 aircraft. SonAir is a privately owned airline that specialises in
transporting passengers to and from offshore and onshore oil industry facilities. The airline also
provides services to other businesses, single entities, charter services within Africa, and private and
government businesses. It operates from 7 regional airports within Angola and internationally to
Houston with the aid of World Airways. SonAir also provides helicopter services to businesses.
The national operator TAAG Angola Airlines has 12 aircraft and flies to Cameroon, Cape Verde, Central
African Republic, DRC, Congo, Mozambique, Namibia, Sao Tome and Principe, South Africa, Zambia,
Zimbabwe, Cuba, Brazil, China, United Arab Emirates and Portugal internationally. It operates from 16
airports within Angola. TAAG has code share agreements with Air France, Brussels Airlines, British
Airways and Lufthansa.
Diexim Expresso operates regional flights, VIP flights and charter flights between Angola and Namibia. It
operates from 5 destinations within Angola. Air 26 also provides domestic services within Angola and
operates from 7 airports within Angola. Alada provides passenger and cargo charter services throughout
Angola and to other parts of Africa. Air Gemini is a cargo airline mainly servicing the diamond mines and
undertaking humanitarian missions. Aeronautica provides charter freight and passenger services.
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Angola Air Charter is a charter airline specialising in charters within Africa and to Europe, particularly to
Belgium and the Netherlands. Transafrik is a cargo airline.
Figure 2.2-1 Fleet size – Airlines in Angola
2.2.2 Botswana
Air Botswana is the national airline of Botswana. The airline was faced with numerous financial
problems since 1988 as can be seen on Figure 2.2-2 overleaf. In 1994, the government had to write off
losses of over 50 million Pula as the airline was unable to cope with the financial demands being made
upon it. The airline began to pick up after the losses were written off and both domestic and
international departures began to increase. The airline recorded a net profit for the years 1998 and
1999, but expenses exceeded revenues in 2000 resulting in a drop in net profit for that year. The airline
was hard hit when a pilot on a suicide mission crashed into two other planes at the airport. The airline
had to lease an aircraft after the incident in order to resume operations.
2
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Figure 2.2-2 Air Botswana Financial data
Departures increased over the years as the government attempted to privatise the airline due to
recurring losses. Negotiations to privatise failed and the airline resumed operating at a loss. Although
the airline is faced with many challenges, international and domestic departures continued to increase
over the years indicating that there is demand for travel into and out of Botswana regardless of the
financial turmoil of the airline. Departures data can be seen on Figure 2.2-3 overleaf. Air Botswana has
a greater number of international departures than domestic departures; this would indicate that
Gabarone Airport is the primary destination for businessman and tourist entering Botswana. It must
also be considered that Botswana is considered one of the stronger economies of southern Africa with
lucrative diamond exports due to the presence of the world’s largest and richest diamond mine
attracting thereby attracting flights and passengers.
-15
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Figure 2.2-3 Air Botswana Domestic and International departures
While the airline has struggled financially over the years, statistics show that passenger numbers have
not suffered. Air Botswana experienced an increase in both domestic and international passengers over
the years. Air Botswana flies to 4 airports within Botswana and internationally to South Africa and
Zimbabwe. Air Botswana has a greater number of international passengers than domestic passengers
indicating that travel within Botswana is not as popular as international travel. Both International and
domestic passenger volumes have been increasing over the years as can be seen on Figure 2.2-4 below.
Figure 2.2-4 Air Botswana Domestic and International passengers
Air Botswana has 6 aircraft in its fleet. The airline has three ATR 42-500s, two ATR 72-500s and one
Boeing 737-200 aircraft. The fleet size is illustrated in Figure 2.2-5 overleaf.
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AirBotswana Domestic AirBotswana International
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Figure 2.2-5 Air Botswana Fleet
2.2.3 Democratic Republic of the Congo (DRC)
There are 7 airlines currently operating in the DRC. Hewa Bora Airways is the largest airline in DRC and
operates regional and domestic routes. It operates from 8 airports within DRC and also flies to the
Republic of the Congo and to South Africa. Filair operates within DRC and flies to 5 airports within the
DRC. Air Tropiques provides domestic, regional and charter flight services. Air Kasai operates charter
services within Africa. Business Aviation provides domestic and international air services. It flies within
the DRC and internationally to Brazzaville and Pointe-Noire. Comapgnie Africaine d’Aviation operates
domestic routes within the DRC to 8 airports. Wimbi Dira is a charter, passenger and cargo airline flying
to the main cities in the DRC. All the airlines based in the DRC are prohibited from entering European
airspace due to sub-standard safety management practices. Fleet sizes of the above airlines can be seen
on Figure 2.2-6 overleaf.
3
2
1
ATR 42-500 ATR 72-500 Boeing 737-200
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Figure 2.2-6 Fleet size – DRC Airlines
2.2.4 Lesotho
Air Lesotho was a government owned national airline and operated on both domestic and international
routes. The airline ceased international operations in 1996 due to the inability to satisfy the minimum
requirements specified by the Department of Civil Aviation. As can be seen on Figure 2.2-7 below,
domestic and international departures decreased drastically over the years until it stopped operations in
1996. At the end of 1996, the airline was financially insolvent and ceased to operate.
Figure 2.2-7 Air Lesotho Domestic and International Departures
5 5
2
3
6
9
2
Air Kasai Air Tropiques
Business Aviation
Compagnie Africaine D
Aviation
Filair Hewa Bora Airways
Wimbi Dira Airways
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1000
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5000
1990 1991 1992 1995 1996
Domestic International
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2.2.5 Madagascar
In Madagascar an average of 15,000 departures were recorded between 1990 and 1998. Most of these
were domestic departures with a small portion of international departures. In the late 1990s the
country was recovering from years of political instability. In the 1998 elections, President Ratsiraka was
re-elected, restoring some confidence in the country. Both domestic and international departures
increased. Domestic departures rose from 14,472 to 19,771 in 1999 while international departures
increased from 1,885 to 2,260. The country enjoyed a few years of growth and stability but confidence
was quickly lost when the country held new elections in December 2001 which led to sporadic violence
due to ethnic clashes and the political crisis ensued until July 2002.
Departures recovered from the sharp drop in 2002 and returned to average departures by 2003.
Madagascar recorded its highest ever tourist numbers in 2007. This can be seen on Figure 2.2-8 below
where both domestic and international departures more than doubled from 2006. Domestic departures
increased by 145% from 11,115 to 27,238 departures, while international departures increased by 220%
from 3,168 to 10,168 departures in 2007.
In 2008, departures dropped drastically from the previous record high of 2007 due to the onset of a
global economic recession and renewed political instability in the country. The majority of tourists flying
to Madagascar are from France and, as a result, the global recession had a significant impact on tourism
to Madagascar. In 2009, a coup to overthrow the government led to political riots indicating that the
country was politically unstable. The swine flu pandemic further fuelled fears for international travellers
as many countries around the world proved vulnerable, mainly in South America and Africa, due to
perceived limited resources for curbing a potential epidemic.
Figure 2.2-8 Air Madagascar Domestic and International departures
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Passenger numbers for Air Madagascar are reflected in the figure below. As is seen in the departures
Figure 2.2-8 on the previous page, Air Madagascar experienced a sharp decline in the number of
domestic and international passengers in 2002 and again in 2009 due to political instability and a global
recession visible on Figure 2.2-9 below. The national government owned airline is directly affected by
instability in the country. The political situation in Madagascar has damaged the economy.
Figure 2.2-9 Air Madagascar Domestic and International passenger numbers
Air Madagascar recorded the largest number of domestic and international passengers in 2001 and 2007
while the lowest number of passengers was experienced in 2002 and 2009.
Although Madagascar has been plagued with years of political unrest, the airline has managed to break
even over the years barely covering expenses with revenues as seen on Figure 2.2-10 overleaf. The
decline in the economy in 2001 and 2002 affected the airline’s revenues resulting in losses in the years
2001 and 2002. The airline recovered in 2003 and managed to record a profit. By 2008 the airline once
again recorded a loss as the country was once again impacted with fresh political turmoil.
0
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AirMadagascar Domestic AirMadagascar International
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Figure 2.2-10 Air Madagascar Financial Data
There are two Madagascar based airlines operating in Madagascar, Air Madagascar and Tiko Air. Tiko
Air provides charter services within Madagascar. Figure 2.2-11 below shows the fleet size of both
airlines.
Figure 2.2-11 Fleet size – Madagascar airlines
2.2.6 Malawi
Air Malawi is the national airline of Malawi. The airline mainly services domestic routes and has a few
flights on international routes. It operates from 2 airports in Malawi and flies to South Africa, Tanzania,
Zambia and Zimbabwe, internationally. Data is only available for the years 1990 to 1993 seen on Figure
2.2-12 overleaf. Domestic departures make up a larger portion of total departures while international
departures have remained constant at about 1,100 annually. The government has since attempted to
-40
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Air Madagascar Tiko Air
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privatise the airline however all negotiations have been unsuccessful. The airline has generally operated
at a loss over the years; however, the airline posted a profit for the year 2007.
Figure 2.2-12 Air Malawi domestic and international departures
As can be seen on Figure 2.2-13 below, both domestic and international passengers patronising Air
Malawi remained fairly constant for the years 1990 and 1991 but an increase of 11% and 8% for
domestic and international passengers respectively was recorded in 1993.
Figure 2.2-13 Air Malawi Domestic and International Passengers
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Air Malawi Domestic Air Malawi International
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1990 1991 1992 1993
Domestic International
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Air Malawi has 4 aircraft in its fleet. The airline has 1 ATR 42-320 and 3 Boeing 737-200s illustrated in
Figure 2.2-14 below.
Figure 2.2-14 Air Malawi Fleet
2.2.7 Mauritius
Air Mauritius mainly services the international market as Mauritius is regarded as one of the world’s
best holiday destinations. Over the years, Mauritius has become very popular for its sandy beaches and
friendly hospitality as well as its 5 star resorts. Mauritius is also a very stable country, politically. It
boasts a rich cultural heritage, superior diving and fishing spots, great food and tropical weather
conditions. Departures to the only domestic destination, Rodrigues (Sir Gaetan Duval Airport) are very
few in number as can be seen in the figure overleaf.
Air Mauritius flies to over 30 destinations around the world. In Africa, Air Mauritius operates to South
Africa, Kenya, Madagascar and Reunion. Departures for Air Mauritius were highest in 2004 and 2005
but have since dropped to lower levels. A drop in departures in 2008 and 2009 in Figure 2.2-15 overleaf
can be attributed to the global recession as many foreign travellers opted not to travel. The country
depends heavily on tourism. A drop in departures is also attributed to a change and upgrade in the
airline’s fleet.
Air Mauritius reduced the operation of two older aircraft in 2007 while awaiting delivery of new aircraft
to permit an increase in operations to major destinations such as India, Malaysia, Singapore and Perth.
1
3
ATR 42-320 Boeing 737-200
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Figure 2.2-15 Air Mauritius Domestic and International departures
The main focus of the airline is its international clientele. Over the years the number of international
passengers has grown steadily reaching a peak in 2007. Although the global recession has resulted in a
decrease in international travel, the number of international passengers serviced in 2009 was still quite
high at over 100,000 as illustrated in Figure 2.2-16 below.
Figure 2.2-16 Air Mauritius Domestic and International passengers
Air Mauritius has 12 aircraft in its fleet. The fleet comprises of 2 Airbus A319-100s, 2 Airbus A330-200s, 6
Airbus A340-300 and 2 ATR 72-500s as seen in Figure 2.2-17 overleaf.
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Air Mauritius Domestic Air Mauritius International
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Air Mauritius Domestic Air Mauritius International
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Figure 2.2-17 Air Mauritius Fleet
2.2.8 Mozambique
Linhas Aereas de Moçambique (LAM) is the national airline of Mozambique. Between 1977 and 1992,
Mozambique suffered an intense civil war. President Chissano worked hard to reform the country and
the civil war ended in October 1992. Over 1.5 million Mozambicans fled the country to neighbouring
states but began to return by mid 1995. The country suffered severely and this is visible in Figure 2.2-18
overleaf where both international and domestic departures dropped significantly up to the 1992 to 1994
period.
By 1996, the country began to recover stability, leading to an improvement in the local economy.
Elections held in December 1999 were peaceful and thus had little impact on tourism. Both domestic
and international departures began to increase gradually over the years and have peaked for the
moment in 2009. Mozambique is popular for its beaches and diving resorts, attracting mostly tourists
from neighbouring states. The global recession in 2008 has therefore had little impact on departures as
tourists opt to choose destinations closer to their home countries to contain costs.
Since Mozambique’s main tourist market is within southern Africa, an increase in total departures
indicates that the Mozambique tourism industry has not been impacted as adversely as many
international holiday destinations.
2 2
6
2
Airbus A319-100 Airbus A330-200 Airbus A340-300 ATR 72-500
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Figure 2.2-18 LAM Domestic and International Departures
Figure 2.2-19 below shows that both domestic and international passengers on LAM have increased
over the years indicating that the country has recovered from its previously adverse political situation.
Domestic passengers are much higher as LAM flies to 10 domestic destinations within Mozambique
while international routes operated include Angola, Kenya, Portugal, South Africa and Tanzania.
Figure 2.2-19 LAM Domestic and International Passengers
LAM has 6 aircraft in its fleet as seen on Figure 2.2-20 overleaf. Its fleet consists of one Antonov An-26,
three Boeing 737-200s and two Embraer E-190 LR/ARs.
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1990 1991 1992 1993 1994 1996 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
LAM Domestic LAM International
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Figure 2.2-20 LAM Fleet
2.2.9 Namibia
Air Namibia is the national airline of Namibia. In 1994, majority of Air Namibia’s operations were
domestic; however domestic departures have decreased over the years and had halved between 1994
and 2000. International departures have increased over the years to almost double the 1994 level in
2000. Departures figures for the years 1994, 1996 and 200 are illustrated in Figure 2.2-21 below. Air
Namibia has been upgrading aircraft over the years and has 2 Airbus A340-312s which has enabled the
airline to cut costs and increase efficiency. Air Namibia currently flies to Angola, Zimbabwe, Botswana,
South Africa and Germany on its international routes and operates from 7 airports within Namibia.
Figure 2.2-21 Air Namibia Domestic and International Departures
1
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Antonov An-26 Boeing 737-200 Embraer E-190 LR/AR
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1994 1996 2000
Air Namibia Domestic Air Namibia International
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Air Namibia has a relatively large number of international passengers compared to domestic passengers
as can be seen in Figure 2.2-22 below. Both international and domestic passenger numbers have
increased over the years 1994 to 2000. The airline suspended flights to Switzerland and UK in 2009 but
still flies to Germany in Europe.
Figure 2.2-22 Air Namibia Domestic and International Passengers
The Air Namibia fleet comprises of two Airbus A340-300s, one Boeing 737-200, two Boeing 737-500s,
one Boeing 737-800 and two Raytheon Aircraft Beechcraft 1900D Airliners seen in Figure 2.2-23 below.
Figure 2.2-23 Air Namibia Fleet
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2.2.10 Seychelles
Air Seychelles is the national airline of Seychelles and is wholly owned by the Seychelles Government.
Seychelles is a popular holiday destination offering a spectacular beach holiday. The airline has been
operating successfully over the years with both domestic and international departures increasing over
the years as seen in Figure 2.2-24 below. The airline offers domestic flights as well as international
flights. It operates from 3 airports within the Seychelles and also flies to Mauritius, South Africa,
Singapore, France, Italy and the United Kingdom, internationally.
Figure 2.2-24 Air Seychelles Domestic and International Departures
Many passengers fly into the main airport in Mahe and take flights internally to the Praslin and Bird
Island airports. As can be seen on Figure 2.2-25 overleaf, domestic and international passengers have
been increasing over the years. International passengers decreased in 1998 and 1999 as many routes
previously serviced were discontinued. The airline stopped flying to Kenya, Israel, Spain and Manchester
in 1998 and discontinued operations to India, the Maldives, Thailand, United Arab Emirates, Frankfurt
and Munich in Germany, Russia and Switzerland between 2000 and 2010.
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Figure 2.2-25 Air Seychelles Domestic and International passengers
Air Seychelles has 9 aircraft in its fleet as seen in Figure 2.2-26 below. Its fleet comprises of 1 Boeing
767-200, 1 Boeing 767-200ER, 3 Boeing 767-300ERs, 3 DHC-6 Twin Otter Series 300s and 1 Shorts 360-
300.
Figure 2.2-26 Air Seychelles Fleet
2.2.11 South Africa
South Africa is served by 18 locally based airlines providing services to both the domestic and the
international markets. Some of the larger airlines are South African Airways (SAA), SA Airlink, Comair,
0
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Air Seychelles Domestic Air Seychelles International
1 1
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Boeing 767-300ER
DHC-6 Twin Otter Series 300
Shorts 360-300
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Mango Airlines and 1time Airlines. Smaller airlines provide charter and air cargo services and specialise
in providing services to private businesses and VIP customers.
South African Airways (SAA) is the national carrier for South Africa. It has been operating for more than
seventy years and is a member of the Star Alliance global network. It has code share agreements with
United Airlines, Air New Zealand, Lufthansa and other Star Alliance partners. SAA flies to 5 domestic
destinations and 32 international destinations worldwide.
SAA recorded very low international and domestic departures in 1990 and 1991 as the country was
emerging from apartheid rule and the country faced international sanctions that prohibited travel into
and out of South Africa. By 1993, the government began to prepare for democratic elections and
sanctions against South Africa were dropped allowing for freer travel to and from South Africa. A surge
in domestic and international departures followed in 1993 and 1994 as confidence in South Africa was
slowly restored as seen in Figure 2.2-27 below. Lack of data between 1995 and 2001 does not allow for
analysis of air travel into and out of South Africa, however from 2002 to 2009, there has been a
consistent increase in international departures while SAA domestic departures have decreased over
these years due to the introduction of many low cost airlines into South Africa. SAA began to lose its
majority share in the domestic market as more airlines began offering seats on competing routes at
lower prices. The global recession appears to have had a very small impact, resulting in a small decrease
in total departures in 2009.
Figure 2.2-27 South African Airways Domestic and International departures
Passengers travelling on both domestic and international routes on SAA have consistently increased
over the past 7 years as illustrated on Figure 2.2-28 overleaf. Domestic passengers have shown a slight
decline since 2007 because many passengers opted to travel on other airlines within South Africa due to
affordability and flexibility.
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1990 1991 1993 1994 2002 2003 2004 2005 2006 2007 2008 2009
Domestic International
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Figure 2.2-28 South African Airways Domestic and International passengers
SA Airlink has been an alliance partner with South African Airways and South African Express since 1997.
SA Airlink operates on domestic routes within South Africa and flies to Bulawayo, Harare, Tete, Beira,
Antananarivo, Pemba, Livingstone, Lusaka, Maseru, Manzini and Ndola. Domestic departures for SA
Airlink varied between 20,000 and 30,000 over the 6 year period as seen in Figure 2.2-29 below.
International departures have increased in 2007 and 2008 as SA Airlink changed its name and corporate
identity and began to offer flights to smaller and regional centres throughout Southern Africa.
Figure 2.2-29 SA Airlink Domestic and International departures
A change in brand image led to an increase in both domestic and international passengers on SA Airlink
in 2007. International passengers remained constant from 2002 to 2006 but an increase in the number
of routes offered within southern Africa increased the number of international passengers departing on
SA Airlink. Domestic routes are very popular and about 65,000 passengers fly on SA Airlink monthly. A
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decrease in 2005 in domestic passengers due to increased competition within the South African
domestic airline industry caused SA Airlink to modify its strategy which was implemented in early 2006.
The airline has since, once again, achieved an increase in both domestic and international passengers as
demonstrated in Figure 2.2-30 below.
Figure 2.2-30 SA Airlink Domestic and International passengers
Comair Ltd started operating its low cost airline Kulula.com in 2002. Since then, South Africa has seen
the growth of low cost airlines with the introduction of Mango, 1Time and Nationwide Airlines. Comair
successfully launched its low cost airline in 2002 allowing many travellers the option to fly economically.
Comair also operates British Airways domestic flights within South Africa and regionally within SADC.
The airline market in South Africa was previously dominated by South African Airways which was costly,
thus deterring many travellers from flying and causing potential customers to seek alternative cheaper
options for travel. Comair introduced its low cost airline with flexibility and cheaper prices and became
instantly popular.
Departures have constantly increased over the 7 years Kulula.com has been in operation. Comair mainly
services the domestic market but offers flights to the African cities of Windhoek, Harare, Lusaka, Ndola
and Mauritius. Domestic departures have almost doubled since Comair started operation in 2002 and
serviced about 31,000 domestic and 3,100 international departures in 2009 as seen in Figure 2.2-31
overleaf. The global recession hit South Africa in early 2009; however it did not affect low cost airlines
as adversely because, in unfavourable economic times, more customers choose to travel on low cost
airlines.
0
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2002 2003 2004 2005 2006 2007 2008
SA Airlink Domestic SA Airlink International
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Figure 2.2-31 Comair Domestic and International departures
Passenger numbers for Comair have increased consistently over the 7 years from 100,000 passengers to
330,000 passengers as seen in Figure 2.2-31 below. International passenger numbers have remained
constant over the same period of time. Comair currently flies to Harare, Windhoek, Lusaka daily, flies to
Ndola five times a week and once a week to Mauritius. As the international flights are not as frequent
as domestic flights, the number of passengers carried on international flights is much lower.
Figure 2.2-32 Comair Domestic and International passenger numbers
The fleet size of the various airlines within South Africa is illustrated in Figure 2.2-33 overleaf. SAA has
the largest fleet in South Africa with 50 aircraft. SA Airlink and SA express both have over 20 aircraft
0
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2002 2003 2004 2005 2006 2007 2008 2009
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0
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2002 2003 2004 2005 2006 2007 2008 2009
Comair Domestic Comair International
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while low cost carriers Comair, Kulula.com and 1time Airlines have more than 10 aircraft each. National
Airways Corporation (NAC) is a private charter company with a large fleet of 18 aircraft. While Mango
Airlines is a large player in the low cost airline market, it only has 4 aircraft. Other South African airline
companies have less than 10 aircraft each and mainly service domestic charter and cargo markets.
Figure 2.2-33 Fleet size – South African Airlines
2.2.12 Tanzania
Air Tanzania temporarily suspended operations in December 2008 and has not resumed operations as
yet. Air Tanzania was government owned until 2002 when it sold 49% stake to South African Airways.
This partnership lasted till September 2006 when the government of Tanzania bought back SAA’s stake
in the business. The partnership between SAA and Air Tanzania was regarded as unsuccessful and the
government stated that the airline was more successful before undertaking the abortive partnership.
Air Tanzania was revamped in 2007 and began using electronic ticketing, a new trademark and cleared
outstanding debt in order to start afresh. As can be seen on Figure 2.2-34 overleaf, international and
domestic departures were high in 1991 but began to fall in 1993. The airline maintained a fairly constant
level of departures until 1998 but the airline began to experience a decline in business by 1999 and the
number of departures fell. During the privatisation process, the airline experienced poor trading
conditions with the lowest level of departures noted in 2001 and 2002. The airline failed to operate
successfully after the revamp and suspended operations in 2008.
13
26
3
1512
2 3
10
4
18
6 4
22
4
11
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41
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Figure 2.2-34 Air Tanzania Domestic and International departures
While domestic passengers on Air Tanzania have been falling since 1990, international passengers have
remained constant over the years. The lowest number of passengers was recorded in 2002 and this can
be attributed to change in ownership and privatization. After SAA took over operations, domestic
passengers increased between 2002 and 2005 as more flights were introduced. However, by 2006, the
airline was struggling again and both domestic and international passengers numbers began to decrease
as can be seen on Figure 2.2-35 below.
Figure 2.2-35 Air Tanzania Domestic and International Passengers
Air Tanzania has not operated successfully over the years and maintained a net loss for the 3 years to
1993. The airline managed to operate profitably between 1993 and 1996; however by 1998 the airline
was again suffering financially and began to make losses as seen on Figure 2.2-36 overleaf. Expenses
exceeded revenues and the airline struggled to break even. Due to its unfavourable financial position,
the government decided to privatise the airline so as to cut its losses however this was also
unsuccessful, finally leading to liquidation.
0
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Domestic International
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08
Air Tanzania Domestic Air Tanzania International
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Figure 2.2-36 Air Tanzania Financial data
Besides Air Tanzania, there are 3 other airlines operating in Tanzania. Eagle Air and Regional Air Services
are domestic airlines operating flights within Tanzania and charter flights in eastern and southern Africa.
Regional Air Services is a subsidiary of Air Kenya. Precision Air is a low cost airline operating from 10
airports within Tanzania and also operated flights to Kenya and Uganda.
The fleet size of the above airlines is illustrated in Figure 2.2-37 overleaf. Precision Air has the largest
fleet and is currently the largest airline in Tanzania since Air Tanzania ceased operations. Regional Air
Services has 5 aircraft while Eagle Air only has 2 aircraft.
-30
-20
-10
0
10
20
30
40
50
60
70
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
US
$ (
Mill
ion
)
Operating Revenues Operating Expenses Net Profit
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Figure 2.2-37 Fleet size – Tanzania airlines
2.2.13 Zambia
Zambia Airways was the national airline of Zambia. The airline was liquidated in 1995 as it was unable to
cope with operations domestically and internationally. The government of Zambia could not assist the
airline and indicated that it had to cover its own debts and expenses from revenues. The airline was not
able to cover costs in a worsening economic climate and shut down operations in early 1995. Departures
data for Zambia Airways’ last few years in operation are illustrated in Figure 2.2-38 below.
Figure 2.2-38 Zambia Airways Domestic and International departures
2
8
5
Eagle Air Precisionair Regional Air Services
0
500
1000
1500
2000
2500
3000
3500
4000
1990 1991 1992 1993 1994
Domestic International
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Zambezi Airlines is a privately owned airline operating in Zambia. It operates at 2 airports within Zambia
and flies to South Africa and Tanzania internationally. It has 3 aircraft in its fleet, 2 Boeing 737-500s
which were acquired in mid 2009 seen in Figure 2.2-39 below. The airline is currently banned from
entering European Airspace due to substandard safety standards.
Figure 2.2-39 Zambezi Airlines Fleet
2.2.13.1 Zimbabwe
Air Zimbabwe is the national airline of Zimbabwe. Negative publicity, politics and the economic
situation in Zimbabwe has had an adverse effect on the national airline. The volatile political situation in
Zimbabwe has led to the general decline of the tourism industry as well as an economic crisis. As seen
in Figure 2.2-40 overleaf, the highest number of departures was recorded in 1992 but the airline
experienced a large decrease in both domestic and international departures in 1993 and 1994 attributed
to clashes between the government and trade unions, resulting in general unrest in the country. The
airline recovered in 1995 but land redistribution and the eviction of white farmers in 1999 led to a
general decline of economic conditions in the country. Zimbabwe began to attract negative publicity
and widespread international condemnation of the situation in the country followed. Departures began
to fall in 1999 and the airline began to suffer financially due to the economic and political situation. In
2003 the airline announced that it was struggling financially and ceased operations temporarily and
departures fell to less than 1,000 that year. Operations have since resumed.
2
1
Boeing 737-500 Embraer EMB-120 Brasilia
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Figure 2.2-40 Air Zimbabwe Domestic and International Departures
Air Zimbabwe has had a somewhat tumultuous history as the number of domestic passengers began to
drop between the years 1996 and 2003. International passengers also decreased over the same period.
The drop in domestic passenger numbers was, however, far greater than that of international passenger
numbers as seen in Figure 2.2-41 below.
Figure 2.2-41 Air Zimbabwe Domestic and International passengers
Air Zimbabwe has been operating at a loss for most of the past two decades. In 1992, the airline was
able to realise a profit however, by 1993 the airline was once again making losses. The decline in the
political situation and the economy of Zimbabwe has had an adverse impact on the viability of the
airline. The airline was losing customers and was unable to cover its operating costs with the revenue
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Air Zimbabwe Domestic Air Zimbabwe International
0
2000
4000
6000
8000
10000
12000
14000
1990 1992 1993 1994 1995 1996 1997 1998 1999 2000 2002 2003
Domestic International
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received from sales, excess baggage and freight. The financial situation of Air Zimbabwe is illustrated in
Figure 2.2-42 below.
Figure 2.2-42 Air Zimbabwe Financial Data
2.2.14 Airports in SADC
The table overleaf reflects the total number of passengers recorded arriving or departing at airports in
the SADC region. Airports that served more than 1,000,000 passengers in 2009 are defined as airports
with high frequency, airports with mid to high frequency serve between 200,000 to 1,000,000
passengers and airports with low frequency serve less than 200,000 passengers in 2009.
-40
-20
0
20
40
60
80
100
120
140
1990 1991 1992 1993 1994 1995 1996 1997 1998
US
$ (
Mill
ion
)
Operating Revenues Operating Expenses Net Profit
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Table 2.2-1 Airports in SADC – Total Passengers
Airport Country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Gaborone - Sir Seretse Khama
InternationalBotswana 188,925 224,488 240,526 225,392 473,794 285,708 355,727 518,284 346,411 386,313
Maun Botswana 137,056 139,571 163,307 142,737 154,092 193,067 205,078 239,368 272,010
Kinshasa N'Djili DRC 267,175 273,563 298,019 358,833 437,882 516,345 599,845 586,870 677,865 663,354
Antananarivo - Ivato International Madagascar 581,965 611,423 678,366 707,304 713,566 336,711 552,138 611,973 709,034 714,488 812,151 828,162 611,175
Majunga Madagascar 89,054 87,897 82,437 84,244 77,505 28,206 43,820 59,849 57,037 52,405 58,443 62,400 46,746
Lilongwe Malawi 208,356 207,157 198,924 202,618 193,446 173,521 176,703 196,140 186,363 173,829 282,529 303,210 296,190
Mauritius - Sir Seewoosagur
Ramgoolam InternationalMauritius 1,484,263 1,524,738 1,600,155 1,763,143 1,819,136 1,896,307 1,982,855 2,058,944 2,167,468 2,217,167 2,562,830 2,606,813 2,381,810
Maputo International Mozambique 308,500 330,969 390,882 436,849 419,327 437,832 445,383 478,115 558,979 624,540 693,618 669,372 668,706
Windhoek International Namibia 429,811 470,534 490,325 481,419 379,327 404,759 506,077 527,085 530,675 637,247 693,671 712,242 681,324
Bloemfontein South Africa 233,121 221,205 219,607 211,490 210,359 215,643 225,636 242,315 305,578 424,223 411,726 399,826
Cape Town International South Africa 3,998,316 4,306,716 4,614,931 4,654,107 4,210,792 5,019,283 5,329,534 6,018,044 6,738,020 7,224,587 8,400,569 8,150,611 7,725,223
Durban Louis Botha International South Africa 2,386,247 2,488,370 2,523,899 2,501,999 2,405,726 2,580,323 2,773,133 3,105,269 3,592,501 4,029,074 4,799,702 4,458,223 4,310,095
East London South Africa 369,445 363,262 352,012 318,793 365,069 380,771 422,672 560,419 664,292 744,455 714,427 674,680
George South Africa 111,892 132,401 227,591 245,052 285,464 335,813 438,747 579,017 589,854 651,563 630,385 527,026
Johannesburg O.R. Tambo
InternationalSouth Africa 9,722,758 10,870,104 11,339,920 11,680,598 11,789,814 12,743,545 13,506,495 15,340,670 15,769,094 17,344,669 19,439,083 18,636,251 17,607,255
Kimberley South Africa 84,444 83,903 82,703 91,100 93,193 89,676 97,442 102,841 129,136 147,277 155,507 130,644
Port Elizabeth South Africa 812,601 822,343 869,523 860,691 836,324 866,955 950,622 1,050,552 1,163,218 1,409,609 1,491,800 1,468,176 1,357,696
Upington South Africa 28,225 29,242 25,730 29,553 32,842 33,681 30,546 32,856 37,009 47,666 50,378 42,519
Kruger Mpumalanga 177,498 215,353 241,533 247,573 208,751
Dar-es-Salaam Tanzania 572,447 582,166 621,513 652,008 703,483 816,263 1,011,392 1,124,235 1,249,419 1,450,138 1,542,778 1,422,846
Kilimanjaro International Tanzania 310,469 134,407 207,256 221,108 192,204 184,652 294,750 363,512 480,053 566,579 521,915 426,600
Mwanza Tanzania 93,311 204,915 111,282 137,767 161,213 186,590 203,087 234,301 229,496 224,207
Zanzibar Tanzania 196,816 236,148 248,554 203,586 307,765 317,308 418,980 549,408 534,466 593,482 571,416 575,504
Lusaka International Zambia 328,132 339,944 341,361 466,533 433,521 392,285 390,505 432,712 447,141 603,107 734,442 837,901 663,223
Victoria Falls Zambia 178,376 168,849 194,938 181,167 210,464 185,859 137,552
Harare International Zimbabwe 629,549 554,370 592,437 629,979 610,221 731,340 674,281 612,208
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Airports in SADC – Total Passengers
Figure 2.2-43 Airports with highest frequency:
Airports with highest frequency are O R Tambo Airport Johannesburg, Cape Town International, Durban
International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur Ramgoolam International in
Mauritius. O.R Tambo Airport in South Africa has had a total of over 10 million passengers a year. Total
passengers at these airports have been increasing over the years and peaked in 2007 after which
passenger numbers began to decline. The global recession has had some effect on air travel and total
passengers declined in 2008 and 2009. All the above airports are international airports and serve both
domestic and international flights and passengers. Dar es Salaam, Harare and Mauritius airports have
recorded over 1.5 million passengers annually. These 6 airports illustrated in Figure 2.2-43 above are
the most frequented airports in the SADC region.
2.2.14.1 Airports with mid- to high frequency:
Airports with mid- to high frequency include airports in Madagascar, the DRC, Mozambique, Zanzibar,
Zambia and Namibia illustrated in Figure 2.2-44 overleaf. These airports recorded between 200,000 and
900,000 passengers annually. Most of the airports noted show an upward trend in the total number of
passengers embarking over the years. A dip in total passengers in 2002 and 2009 for Madagascar
occurred due to the political unrest experienced in the country during those years. All the airports that
recorded mid to high number of passengers are international airports except for East London airport
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Johannesburg O.R. Tambo International Cape Town International
Durban International Mauritius - Sir Seewoosagur Ramgoolam International
Dar-es-Salaam Harare International
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which only serves domestic flights. Air travel numbers were generally low in 2002 due to the aftermath
of the September 11 attacks, fuelling fears of terrorist attacks amongst passengers and deterring air
travel. The attacks did not have a large impact on African destinations; however there was global decline
in air travel during the period following the attacks in the US.
Figure 2.2-44 Airports with mid to high frequency:
2.2.14.2 Airports with low frequency:
Airports with low frequency are the airports serving the lowest number of total passengers annually –
defined as airports with fewer than 700,000 passengers annually. In general, passenger numbers at low
frequency airports gradually increase and peak in 2007. A decline is experienced in 2002 due to the
September 11 attacks and again in 2008 and 2009, which can be attributed to the global downturn in
the economy. International airports illustrated in Figure 2.2-45 overleaf that recorded low numbers of
passengers include Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and
Victoria Falls. Kilimanjaro International and Gaborone recorded the largest increase in total passengers,
while Majunga, Lilongwe, Victoria Falls, Mwanza and Maun had constant number of passengers over the
years. Kilimanjaro international recorded the largest increase in total passengers over the years.
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Kinshasa N'Djili Antananarivo - Ivato International
Maputo International Windhoek International
Zanzibar Lusaka International
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Figure 2.2-45 International Airports with low frequency:
Domestic airports illustrated in Figure 2.2-46 below with low numbers of passengers include Port
Elizabeth, East London, Bloemfontein, George, Kimberley, Upington and Kruger Mpumalanga. Upington
and Kimberley airports reflect a fairly constant level of total passengers over the years, while the rest of
the domestic airports demonstrated an increase in total passengers.
Figure 2.2-46 Domestic Airports with low frequency:
0
100,000
200,000
300,000
400,000
500,000
600,000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Gaborone - Sir Seretse Khama International Maun
Majunga Lilongwe
Kilimanjaro International Mwanza
Victoria Falls
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Bloemfontein East London George Kimberley
Port Elizabeth Upington Kruger Mpumalanga
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2.2.15 Fleet size of all SADC airlines
An overview of the fleet size of all airlines within SADC in 2007 is provided in Figure 2.2-47 overleaf.
Fleet size between airlines fluctuates enormously. The fleet size between airlines operating
internationally and domestically varies greatly compared to low cost airlines that only operate to
domestic destinations. National carrier South African Airways has the largest fleet within SADC, while
other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar, Air Mauritius, Air
Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying between 4 and 12
aircraft each..
Privately owned airlines in Angola, DRC, South Africa, Tanzania and Zambia own smaller fleets mainly
serving the domestic market. SonAir has the largest fleet of 32 aircraft while popular operators such as
Diexim Expresso, Transafrik, 1time, Mango, Comair and Precision Air have less than 10 aircraft each.
Specialized charter companies in South Africa, Angola and DRC have a variety of small aircraft. National
Airways Corporation of South Africa has a large fleet of 18 small aircraft.
The figure overleaf shows the fleet size of the larger SADC based airlines. Each country has been
differentiated by means of a colour coded system and the key appears below the figure.
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Figure 2.2-47 Fleet Size (2007)
Angola Malawi South Africa
Botswana Mauritius Tanzania DRC Mozambique Zambia
Madagascar Namibia Zimbabwe
Seychelles
27 5 3 1
8
32
128 6 5 5
2 36
9
2
11
14
12
6 8 913
26
3
1512
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4
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2.3 Analysis of Questionnaire Results
Between August 2009 and January 2010, 106 airlines, 3 airport authorities and 14 SADC transport
ministries were contacted and sent questionnaires regarding progress with the implementation of an air
transport liberalisation agreement in SADC related to the adoption of air transportation liberalisation
policies in Africa (the questionnaires can be found in Appendix E.) Of the 68 questionnaires sent out,
only 16 were returned completed. Analysis of the answers to the returned and completed
questionnaires follows.
2.3.1 Airlines
Feedback was received from five airlines within the SADC namely Federal Airlines, Owenair Pty Ltd,
South African Airways and Comair Limited of South Africa and Air Malawi of Malawi. Each airline is
unique servicing a different market or market segment. However the five airlines share similar views on
the impact of implementing an air transportation liberalisation agreement in the SADC region. The
profiles of the responding airlines are summarised in Table 2.3-1 below:
Table 2.3-1 Airlines Data Company / Organisation
Country of Operation
Type of Airline Annual Turnover
Ownership Owners
Federal Airlines South Africa High end domestic and international
Did not disclose
Private company
100% domestic private ownership
Air Malawi Malawi National flag carrier Did not disclose
Government owned
100% domestic government ownership
Comair limited South Africa Domestic low cost carrier, high end domestic and international, charter carrier, British Airways franchise, code sharing and alliance
R 3 billion Privately owned company
88% domestic private ownership,
12% foreign private ownership
Owenair (Pty) Ltd
South Africa Chartered carrier R 6 million Private company
100% domestic private ownership
South African Airways
South Africa National flag carrier Did not disclose
Government owned
100% domestic government ownership
The responding airlines stated in general, that the air transportation liberalisation aviation agreement
reached between African states, namely the Yamoussoukro Decision (YD,) was a poor and a weak
agreement as there has been no evidence of any multilateral implementation. This is due to lack of
arbitration procedures being agreed to progress deadlocked negotiations and lack of regulation by
means of competition laws. A phased in approach whereby each airline could have been engaged with
individually taking into account the differing passenger route densities on the routes that each airline
operates was recommended. There was no deadline set and the agreement was reached without prior
consultation with airlines. African states have not implemented YD due to lack of political commitment,
anti-transformation, resistance from weak state owned airlines, based on fear of the consequences of
more open commercial competition, lack of infrastructure development, limited fleet size in less
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developed countries and lack of consensus on a clear way forward. YD does not consider the strengths
and weaknesses of countries airlines, nor of the state of airport and aviation infrastructure in the various
regions of the African continent. The likely impact of implementing such an agreement on specific
countries has also not been determined.
Airlines cited the following as reasons why full implementation of the YD has been hindered:
Lack of individual government commitment to YD;
Lack of SADC member commitment to YD;
National flag carriers disapproval of YD due to perceived threats to existing privileged positions of aviation industry dominance;
Lack of effective competition law in individual countries and regionally;
Corruption;
Poor or non-existent legislation;
Political instability in certain African countries;
Poor / substandard airport infrastructure in many countries;
Airport security concerns;
Risks regarding the handling of higher flight frequencies at some airports; and
Resistance from stakeholders trying to protect monopoly or privileged positions of market dominance.
Airlines recommend that in order to successfully implement YD, governments will be required to play an
active role in ensuring that airlines are informed about intended progress (to a declared timetable)
towards implementation of YD in Africa. Bottlenecks need to be addressed; national airlines need to be
supplied with avionics so as to compete effectively; regulations need to be standardised and amended
to cover aspects such as competition law and arbitration procedures to speedily resolve disputes; and
stakeholders should be afforded the opportunity to buy into the implementation plan and be party to
discussions and planning of implementation. Lastly, African governments should focus on African
carriers which must be developed to compete globally rather than focusing on non-African airlines.
The airlines have differing views on the likely impact on countries that would implement YD. While some
airlines are sceptical and feel that most African airlines will not survive, others feel that a number of
small airlines will be sacrificed initially but the long term overall consequences will be positive.
Implementation will see an increase in tourism and business travel leading to increased traffic on dense
and lucrative routes resulting in lower fares, more competition and therefore more participants in the
airline industry. Airlines will benefit from offering reliable and efficient services at pricing levels that will
stimulate demand and therefore profitability - which will have widespread benefits for SADC economies.
Many national flag carriers and smaller, less efficient airlines will be unable to compete if they are not
recapitalised with competitive equipment and many may not survive.
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Impact of the YD on airlines will result in the following changes in the current status quo:
Frequency of flights – increase
Capacity (number of seats on offer) – may increase or remain static
Pricing – decrease due to increased competition
Volume of freight business – increase
Number of competitors on each route – increase on higher traffic routes but will decrease on more marginal routes
Market share of airline on each route – will reduce but as part of a rapidly growing industry
With the implementation of YD, airlines will be able to fly to destinations previously inaccessible. Airlines
will tend to increase the frequency of flights on the more lucrative routes so as to reap maximum
benefits. Depending on the demand for seats of the more popular routes, airlines will have to either
reduce flights on less popular routes and divert flights to the more popular routes or increase their fleet
to accommodate the demand. This will result in either an increase in overall capacity if more aircraft are
introduced or the overall capacity will remain static with airlines diverting aircraft to more popular
routes.
An increase in competition in the form of an increase in number of flights on routes within the SADC will
lead to a decrease in the average price of air tickets as airlines compete to maximise their market share.
This decrease in price will likely benefit passengers directly and may boost the number of passengers
travelling within the region, thereby greatly extending access by the general public to air travel. Not only
will this boost tourism and business travel around SADC and Africa, but will also benefit airlines, airports,
hotels, car hire companies, restaurants and other direct and indirect stakeholders in the aviation
industry. Similarly, freight business will be stimulated through cheaper tariffs leading to an increase in
the volumes of freight being imported and exported throughout SADC and the African continent.
As airlines strive to maximize market share, an increase in the number of competitors will lead to a
decrease in the market share of individual airlines. Airlines will need to emphasise aspects of service
such as reliability, safety and the level of service provided in order to mitigate against market share
losses. Although airlines will experience a fall in market share due to an increase in the number of
players in the market, the overall size of the market is expected to grow rapidly, which will result in
individual airlines, in the main continuing to grow despite falling market share.
Airlines that will benefit the most from implementing the YD are typically strong network and alliance
carriers, while small charters and weak state owned carriers may not survive. Strong network alliance
carriers will survive the intense competition which may result in a decrease in fares as these carriers
have financial muscle and easy access to capital for rapid expansion. Large airlines will feel intimidated
as new airline start serving the same routes and will feel threatened by the increase of operators, but
airlines with a large market share will be better off than small airlines which may not be able to compete
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as efficiently. Weak state owned airlines are characterised by old out-dated aircraft fleets that, together
with reluctance to embrace change, will limit expansion possibilities.
The state of airport infrastructure will have a significant influence in determining the effect of
implementing an air transportation liberalisation agreement. If YD is implemented, infrastructure
constraints will restrict transformation of the aviation industry as current infrastructure will not be
sufficient to cope with the resulting growth of air traffic volumes. Implementation of YD will result in an
increase in flight frequencies around Africa and infrastructure investment will need to be facilitated to
ensure that capacity is enhanced to cater for these demands. Currently, air traffic control, airport
runway capacity, airport runway length, baggage handling, security and even freight logistics capacity is
in the hands of government departments that will be incapable of responding to the increased demand.
There is insufficient capacity to accommodate increased number of flights in terms of limited airport
runway slots, restricted manpower and expertise in air traffic control, airport runway lengths at some
airports, not enough capacity to handle large numbers of passengers and baggage and a strained and
inadequate security at most airports. These constraints will have to be addressed before YD is
implemented and failure to do so will result in dire consequences such as flight delays, loss of baggage,
security threats and safety concerns. Airports will have to ensure that facilities comply with minimum
standard requirements. Customs facilities, information technology infrastructure and effective airport
security are some of the issues that will need to be revised and addressed in order to successfully
benefit from the YD agreement. Privatisation of many of these services is probably a necessary reform
for successful implementation of YD.
If SADC undertakes a comprehensive implementation of an air transportation liberalisation agreement,
airlines feel that it would open up the opportunity to review the mix of aircraft types, assessing the need
for both bigger and smaller types of aircraft on certain routes, existing and new. Implementing YD will
create additional job opportunities on both existing and new routes, creating the opportunity to expand
network reach and frequency leading to additional and increasing competition , lowering of prices for air
tickets and ultimately to an increase in market size, revenue and profits. Airlines will be willing to
operate on new routes as well change some of the current routes so as to avoid stopovers and hub
transfers by introducing direct flights to more destinations. In relative terms YD will disadvantage small
local airlines because they are less likely to have access to investment funding for expansion which
larger, mainly international airlines will be able to access more readily. All airlines will, nevertheless,
have the potential to benefit from YD if management embraces the business opportunities that will be
on offer.
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2.3.2 Airports
If YD is implemented in the SADC region, then an increase in the number of flights to both current and
new airport destinations can be expected. Therefore, airports that are currently being utilised (as hubs
or as international gateways) will experience an increase in inbound and outbound flights, while some
airports (with adequate infrastructure, not receiving international flights) that are underutilised will also
experience an increase in inbound and outbound flights.
Receiving only two responses from major airport companies may not clearly indicate the impact on
airports of implementing the YD but feedback does provide a basic idea about the implications that the
YD will have on airports. Feedback was received from two airport companies profiled in Table 2.3-2
below:
Table 2.3-2 Airports Data
Company / Organisation
Country of Operation
Annual Turnover
Main sources of income Ownership Owners
Airports Company of South Africa
(ACSA)
South Africa R 3.17 billion
Aeronautical revenue, landing fees, passenger service charges, aircraft parking, commercial revenue, advertising, retail, parking, car hire, property rental, premiums received
Partly owned by government
74.6% domestic government ownership,
25.4% domestic private ownership
National Airports Corporation Limited
Zambia US $ 26.7 Million
Aviation - landing, passenger service charge, parking, ground handling, air navigation charges and Non-aviation - rentals, car parks, concessions, advertisements
Fully owned by government
100% domestic government ownership
The main sources of income reported by airports include aviation business - landing, passenger service
charge, parking, ground handling, air navigation charges and non-aviation business - rentals, car parks,
concessions and advertisements. Major airports within the SADC are either fully or partly owned by the
government thus any commercial benefit to the airport will have an impact on the country’s economic
conditions, directly and indirectly.
While airports authorities agree with airline operators that the YD agreement is good in principle, they
also feel that implementation has been poor. The YD agreement will improve revenue generation as
more airlines will operate from various airports, in turn, positively impacting the profitability of airports.
Thus, an introduction of the fifth freedom will lead to a removal of restrictions, allowing more airlines to
operate freely on numerous routes previously forbidden. YD will also stimulate traffic growth and make
travel more affordable by introducing more intense market competition. Lack of progress with
implementation has resulted in constrained aviation industry conditions prevailing in the past and while
much consideration needs to be given as to how to pave the way forward, airports authorities state that
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a huge transformation in airport operation will need to occur and this will have to be done with many
parties involved, including private sector investment and management.
Bottlenecks identified by airport authorities are identical to those mentioned above and include:
Lack of government commitment to YD
Lack of SADC commitment to YD
National flag carriers resistance to YD
In order to successfully implement YD, governments will need to remove bottlenecks that hinder the
free flow of private sector investment and participation in the air transport industry. This can be done by
granting the fifth freedom and at the same time helping local air transport businesses to partner with
international or local large participants in the industry to form alliances to ensure that they will survive
under the intense competition that is characteristic of a successful implementation of an air
transportation liberalisation agreement. This will result not only in rapid growth as lower prices
stimulate economic activity, but will also encourage quality in the aviation industry through providing
consumers with choice and providing local airlines the opportunity to participate in this growth through
the introduction of innovative approaches to service provision.
The impact of YD on airports will be:
Frequency of flights – increase on certain routes
Capacity – increase
Pricing – decrease
Volume of freight business – likely to increase, dependent on demand and pricing structure (affordability)
Airports expect an increase in frequency of flights on certain more popular routes which would lead to
an overall increase in frequency of flights at many airports. Increase in flight frequencies will lead to an
increase in capacity as more flights to more varied destinations will become available. Ticket prices will
decrease due to increased competition. Although no indication of the trend of airport charges has been
mentioned, increased choice and economies of scale should drive airport charges down as well. Volume
of freight business will be dependent on demand and pricing and if pricing decreases, there will be an
increase in the volume of freight into and out of airports thus relieving other modes of transport
especially road .
Increased aviation activities will certainly have a positive effect on the commercial standing of all
airports within SADC, however airports enjoying the highest demand will benefit at a larger scale than
those enjoying less demand. Implementation of YD will create a climate characterised by an increase in
demand for aviation services in general, however the decision itself will not convert into automatic
demand for more flights at any individual airport. Airports will be afforded the opportunity to grow
their business if there is a pro-active move on the part of individual airport management teams to
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attract business in the more open and flexible environment that will accompany implementation of YD.
As more flights are introduced, revenues will rise, encouraging airports to further expand capacity in
order to facilitate continually increasing levels of aviation activities.
Potential infrastructure constraints such as airport runway capacity, airport runway length and baggage
handling facilities will need to be addressed as these will cause bottlenecks and may lead to delays and
inefficiencies in service support, which will discourage rather than encourage new business.
Infrastructure constraints are likely to significantly restrict the potential benefits associated with
implementation of YD if airspace and airport capacity is limited by inadequate infrastructure investment.
Not all airports have the facilities and infrastructure to accommodate all sizes of aircraft and large
increases in air traffic volumes. Airport planners will need to ensure that facilities are of adequate
capacity to meet increased levels of demand and are compliant with minimum standards in order to
fully benefit from the implementation of YD.
Airlines will be free to develop routes more easily and open up new markets for travellers, the overall
the impact of air transportation liberalisation on airports will be to increase potential revenues which
will, in turn, justify investments in upgraded airport infrastructure and facilities.
2.3.3 Other Stakeholders in the aviation industry
Other stakeholders in the aviation industry include small charter operators, aircraft leasing companies,
aircraft sales and maintenance businesses, cargo and freight service operators and mail services.
Currently these are typically small operations that service a niche market and offer specialised services
such as package tours, domestic charter or scheduled flights. Stakeholders in this category that
provided feedback are listed in the schedule overleaf.
Most of the above named stakeholders are small charter operators with the exception of Mistral
Aviation, which specialises in landing gear overhauls and aircraft brake maintenance, Airline Association
of South Africa (AASA), which is a non-profit organisation providing guidance to SADC airlines and
Swissport Tanzania, which is a ground handling and cargo services company.
More than half the stakeholders stated that the agreement reached at YD was positive for the industry
because it provided greater opportunity for start up airlines to compete with established airlines and
level the playing field by allowing competitive operators freer access to potentially lucrative markets.
Implementation of YD will also allow established airlines to serve a broader market without
encountering rigid barriers that have previously restricted their operations. Some stakeholders feel that
the YD agreement has been poorly received because it was adopted out of the recognition that the
restrictive and protectionist intra-African regulatory regime based primarily on bilateral air services
agreements (BASAs) has historically hampered expansion and improvement of air transportation on the
African continent. As such, existing vested interests, which often rely on old, poorly maintained aircraft
operating out of poorly managed airports, feel threatened and have consequently successfully resisted
multi-lateral implementation of YD.
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Other Stakeholders that responded are profiled in Table 2.3-3 below:
Table 2.3-3 Stakeholders Data
Company / Organisation
Country of Operation
Annual Turnover
Main sources of income Ownership Owners
AirQuarius Aviation
South Africa R 101 million
Aircraft leasing and charter Private
company
Private ownership
NAC South Africa R1,9 billion Aircraft sales, aircraft maintenance, aircraft leasing, aircraft (rotor and fixed wing) charter, aircraft management
Privately owned company
100% domestic private ownership
Airline Association of Southern Africa (AASA)
South Africa n/a Membership subscriptions and management fees
Non-profit privately owned company
Private ownership
Mistral Aviation Services
South Africa R10 - R12 million
Aircraft brakes and landing gear overhauls
Private
company
Private ownership
Namibia Commercial Aviation
Namibia $ 7 million Namibian
Tourism and incentive charters Private
company
Private ownership
Phoebus Apollo Aviation
South Africa Passenger/ cargo scheduled/ charter flights and wet-leasing of aircraft
Sole proprietorship
Private ownership
Precision Air services Ltd
Tanzania $65 million US
Provision of scheduled passenger, freight and mail services
Private
Partnership
51% domestic private, 49% foreign private
Proflight commuter services
Zambia $ 8 million US
Charter operations Private
Partnership
75% domestic private, 25% foreign private
Swissport Tanzania
Tanzania T Shs 18.528 million
Ground handling, cargo services Private
Partnership
49% domestic private, 51% foreign private
One of the vital principles of YD is market liberalisation, which is viewed as a means to stimulate the
development of air services in Africa and attract the flow of private capital into the industry. In essence
the agreement reached is solid and the theory makes sense for Africa and for airline industry
stakeholders. In practice, however, YD made assumptions regarding compliance by individual countries
that have not been realised. The heads of state came to an agreement, but at “grassroots level” many of
the stakeholders (and individual managers in stakeholder entities) have not been committed to YD and
may have actively resisted implementation of the agreement. Implementation of YD has thus been very
limited and stakeholders believe that national governments have resisted implementation with the
result that no meaningful progress has been made since the agreement was reached.
The Yamoussoukro Decision, which came into force in 2000, evolved from the Yamoussoukro
Declaration of 1988. However, throughout the intervening years, the full potential of YD to unlock
commercial opportunities for African airlines has not been realised and implementation has been
virtually non-existent. A sub-committee on air transport established by this decision and monitored by a
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body comprised of representatives from Economic Commission for Africa (ECA), African Union (AU),
African Civil Aviation Commission (AFCAC) and African Airlines Association (AFRAA) then overseen by an
executing agency has not carried out the duties set out in the declaration even though a large fund was
set aside for implementation. The explicit roles of these organisations were unclear thus no action was
taken due to the confusion. Only a few countries practise true “air transportation liberalisation”. These
are mainly countries which have implemented bilateral agreements instead of letting airline companies
get on with freely operating the routes and frequencies that they want to as envisaged by YD.
The following factors have been identified by stakeholders as hindering the full implementation of YD:
Lack of individual national government commitment to YD
Lack of SADC commitment to YD
National flag carriers resistance to implementation of YD
A lack of laws promoting free competition regionally
A lack of laws promoting free competition within individual countries
Corruption
Poor legislation
Political instability in some African countries
Poor/substandard airport infrastructure in Africa
Airport security concerns
Lack of start up capital for would be operators
European Union blacklisting of African airlines
Lack of clarity regarding the roles of the various sub-committees and monitoring bodies
Lack of commitment and action by ministry officials
Lack of incorporation of the principles of YD, as appropriate and necessary, into national legislation
Lack of infrastructure (no effective executing agency and other monitoring structures)
Government protection of airlines from competition (preserving of state monopolies)
The above have been identified as factors which hinder the successful implementation of the YD and will
need to be addressed before any progress can be made. Governments need to amend aviation policies
and legislation accordingly. Before implementation, a plan needs to be formulated to include all
stakeholders in a participative process to evaluate options and develop a well rounded policy that will
benefit all stakeholders including the governments involved. It is important that the appropriate officials
are mandated to implement the YD within a specified time frame. Existing bilateral government
agreements should be amended to remove limits on frequency and capacity.
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A possible approach would be to involve a larger authority in decision making. The African Union (AU) is
Africa’s premier institution and is the principal organization for the promotion of socio-economic
integration on the continent. The AU is also the monitoring body established to oversee
implementation of the Yamoussoukro Decision. Given the AU’s objective to promote sustainable
development and to integrate African economies, the African Union (AU) is best positioned to provide
the necessary oversight platform for steering implementation of the Yamoussoukro Decision and
liberalization of the air transport industry in Africa. Its recent moves to actively support the African Civil
Aviation Commission (AFCAC) and the various regional economic communities (RECs) demonstrated the
willingness of the organization to accept leadership. Individual national governments need therefore to
support the AU and provide the necessary funds and resources to assist the AU in this regard.
If implemented successfully, the impact of the YD would be immensely positive for countries partaking
in the decision. It would create an environment for the development of intra-African and international
air services, liberalized intra-African aviation markets and highly stimulatory developments concerning,
traffic rights, capacity, frequency and pricing. YD will lead to the rapid development of inter-African air
transport activities and improved quality of service to consumers. Sub-regional services will be
encouraged to merge and grow as well as permit air transport services to privatise. With the
implementation of YD, countries will establish safe, reliable and affordable air transport services that are
attractive to customers and that will stimulate a freer and much higher level of movement of persons,
goods and services in Africa. Implementation of YD may also protect African airlines from European and
other non-African competitors and eliminate barriers that hamper the sustainable development of air
transport services. African airlines will be able to create a strong regional base from which they can
expand and compete with international airlines by forming international alliances and strong business
partnerships that will assist in future growth and development. Although the impact is largely expected
to be positive, stakeholders do recognise that some countries may struggle to adapt mainly due to a
misguided commitment to outdated aviation practices and equipment. Countries that are reluctant to
embrace transformation and face competition will eventually suffer dire consequences in respect of
their own national airlines and other aviation industry stakeholders as continent-wide competition
overtakes those who refuse to adapt.
Stake holders agree that companies throughout Africa that embrace the changes implied by full
implementation of YD will be able to build strong partnerships with other operators around Africa and
further afield and will enjoy the chance to exploit the many opportunities available to them. Airlines will
benefit as it will be easier to obtain quicker flight clearances and all fees surrounding flights which
include landing and parking fees should be more competitive as opposed to companies not based in
Africa. Increased scheduled flight services will act as a catalyst for economic growth within the
continent. The financial benefit gained from implementing the YD will be significant for almost all
participants as there will be greater freedom, more capacity to accommodate new routes, increased
revenue for all stakeholders. Implementation of YD will create the opportunities to increase aircraft
fleets for both new and established operators as they build their capacity to serve the higher levels of
demand created from the implementation. Thus, not only will airlines benefit, but also companies that
service, lease and maintain aircraft will reap benefits.
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The view of stakeholders is that the companies most likely to benefit from the YD will be start up and
low cost operators, regional airlines, established airlines and airlines that can sustain the more intense
levels of competition. With the freedom to operate on any routes airlines will prioritise the most
lucrative ones. Small carriers will have the opportunity to expand and diversify their current flight
operations. Companies involved in maintenance and aircraft leasing will benefit from the opening of
new potential markets enabling stakeholders to widen their business horizons. Some stakeholders feel
that emerging airlines will be faced with limited growth while established airlines that already have a
strong base in the market will find it easier to attract new business. Companies least likely to benefit
from the YD are underperforming domestic carriers, inefficient national carriers and companies that are
unable to compete effectively.
Infrastructure constraints that stakeholders indentified as possibly restricting implementation of YD are:
Air traffic control
Airport runway capacity (no. of slots)
Airport runway length
Baggage handling
Security
Freight logistics capacity
The above constraints are the same as those mentioned by both the airlines and airports groups of
stakeholders. Stakeholders are mainly concerned that those factors that will affect the smooth
operation of companies due to the increased demand that will result once the YD has been
implemented. In some countries, where services have not been upgraded to meet international
standards, infrastructure may not be able to cope with the increased air traffic. In many cases airports
are not geared to accommodate large aircraft and thus they do not have sufficient capacity or the
appropriate runway length for modern aircraft. In terms of freight logistics, airports and freight
companies would have to ensure that they can handle an increase in freight and cargo volumes by
creating efficient cargo hubs. Air freight usually consists of perishable goods that have a short life span
and must be handled with speed and without delay. One of the biggest passenger concerns when
travelling around Africa is baggage handling and security. This would have to be addressed effectively
and measures need to be taken to ensure that no compromises are made.
A comprehensive air transportation liberalisation agreement would be a great benefit to all stakeholders
in the aviation industry as it gives companies the opportunity to investigate new markets and routes and
source new and modern equipment in partnership with other operators. This will inevitably lead to
structural changes to some of the companies to allow for ongoing expansion. Expansion will benefit not
only the company but the economy as whole through creating employment and generating higher levels
of revenue. The implications for ground handling companies are also positive as the increased demand
will require larger operations allowing these companies to expand; however, these trends may also
attract an increase in competition. Stakeholders are generally realistic in recognising that before any of
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the benefits are enjoyed, infrastructure investment will be required to accommodate the increase in
flights, passenger numbers and cargo volumes. Some stakeholders are concerned that they may not be
able to survive as they will get swallowed by the competition of an open market and thus are not
entirely enthusiastic about the implementation of YD.
Overall, however, airlines, airports and other stakeholders are positive about the implementation of YD
but are sceptical about the progress made to date and likely to be made into the future. Stakeholders
support the idea behind YD and are willing to open their markets to Africa but are not certain that the
current infrastructure, legislation and policies support the rapid implementation of such a decision.
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2.4 Cost-Benefit Analysis Methodology
2.4.1 Model
2.4.1.1 Introduction
The demand forecast model predicts the potential routes that airlines could operate in the South African
Development Community (SADC) under an air transportation liberalisation regime. It is principally based
on the gravity method described in the literature review. The gravity model traditionally uses the size of
the origin (city or country) times the size of the destination as an indication of the demand for flights
between them. This model assumes that the bigger the population size or GDP of the origin and the
population size or GDP of the destination, the bigger the attraction and demand for flights. Equation (1)
shows the typical mathematical equation that would be used to determine the potential demand
between an origin and destination.
Equation (1) Demand = (GDP Origin * GDP Destination)/Distance
For the purpose of this study the demand forecast model has been based on the principles of the gravity
model, by using data from origin and destination location in a similar fashion as Equation 1 above (this
will be explained in the sections that follow.) In the sections to follow it will be shown how a demand
forecast has been predicted for each potential route in the SADC region and this forecast has been
weighted between 0 and 1 (0 being very low demand and 1 being extremely high demand). The model
excludes all airports with a runway length shorter than 6500 feet (1.98 km), as airlines and aircraft
manufacturers cited this length as a minimum for commercial aircrafts and aircrafts designed to carry
freight, and runways that are unpaved. Routes that are less than 200 km were excluded, due to
ineffectiveness of flying distances this short.
2.4.1.2 Data Utilised To Calculate Demand Forecast Indicator
The demand forecast indicator takes into account various indices for each airport that fit the description
discussed above. The indices accounted for include:
Country’s gross domestic product per capita;
Population of origin and destination cities;
Country’s urban population for 2005;
The business, politics and development index indicators;
Tourism infrastructure index;
Whether the origins and destinations fall internally within one country;
Airport infrastructure; and
Distance between the various origins and destinations.
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A brief description of these various data sets and indices follows in the remainder of this section.
2.4.1.2.1 Gross domestic product per capita
The gross domestic product per capita has been sourced from the International Monetary Fund website.
The GDP per capita figures used are stated in US$ 2007 at current prices and are displayed in Table 2.4-1
below. GDP per capita was used as countries with a higher GDP per capita are more likely to demand
more flights as flying is still largely a luxury form of transport in Africa.
Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices Country GDP per capita US$
Angola 5,276.83
Botswana 8,032.88
Democratic Republic of Congo 174.068
Lesotho 706.021
Madagascar 430.419
Malawi 268.594
Mauritius 5,891.24
Mozambique 420.611
Namibia 3,502.10
Seychelles 8,482.88
South Africa 6,185.43
Swaziland 2,380.52
Tanzania 392.434
Zambia 957.335
Zimbabwe 139.754
2.4.1.2.2 Population by city
Where a city has an airport with the appropriate runway length and surface, the rough population of
that city has been taken into account. It has been assumed that the larger the city, the higher the
demand for flights to and from that city. A full list of cities in the SADC region and the population levels
for each of these cities was obtained from http://www.tageo.com/index.htm. This data was used to
create relative proportions for each of the cities, thereby determining the ranking of cities expected to
have a higher demand for flights under an air transportation liberalisation regime. A table listing the
populations used by city can be found in Appendix F.
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2.4.1.2.3 Urban population
In addition to the city population data, each country’s urban population levels were gathered from a
United Nations database (http://data.un.org/Default.aspx). Urban population data for 2005 for the
SADC countries in question was utilised. This data is shown in Table 2.4-2, below. These figures have
been taken into account to determine a ranking of origin and destination cities that could be expected
to have a higher demand for flights under an air transportation liberalisation regime based on the
overall urban population of the countries where these sites are located.
Table 2.4-2 Urban Population by Country Country Urban population
Angola 5,930,052
Botswana 926,625
Democratic Republic of Congo 18,818,523
Lesotho 326,690
Madagascar 5,023,620
Malawi 2,216,048
Mauritius 545,310
Mozambique 7,520,960
Namibia 680,385
Seychelles 46,980
South Africa 27,463,128
Swaziland 246,648
Tanzania 14,373,375
Zambia 4,258,820
Zimbabwe 4,670,590
2.4.1.2.4 Business, politics and development index indicators
The business, politics and development indicators have been drawn from various sources and have been
combined to create one weight in the demand forecast model. The business information which included
the ‘Country Risk Rating (September 2008)’ and ‘Global Competitiveness Index (2007-2008)’, is sourced
from the World Economic Forum (gcr.weforum.org). The political information is sourced from the ‘Press
Freedom Index (2008)’ and can be found in the Reporters Without Borders website
(http://www.rsf.org/). The development information utilised is the ‘Human Development Index (2006)’
from the United Nations Development Program (http://hdr.undp.org/en/statistics/). These indicators
are summarised in Table 2.4-3, overleaf. Each of these indicators has been modified to be rated
between 100 and 0 (with 100 being an excellent rating and 0 being an extremely poor rating). The
various indicators have been averaged in the last column of the table and these averages have been
used in determining the demand weighting for each qualifying airport.
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Table 2.4-3 Business, Political and Development Indicators for SADC Country Country Country Risk Rating
(Sept 2008) Global Competitiveness
Index (2007-2008) HDI
2006 Press Freedom
Index (2008) Average
Angola 36 45 48.4 70.5 50.1
Botswana 65 60.71428571 66.4 86 69.6
Democratic Republic of Congo 30 41.14285714 36.1 48.75 39.0
Lesotho 41 48.57142857 49.6 70.5 52.3
Madagascar 35 48.28571429 53.3 79 54.0
Malawi 35 48.85714286 45.7 85 53.6
Mauritius 56 60.71428571 80.2 91 72.0
Mozambique 41 45 36.6 79.5 50.5
Namibia 40 57 63.4 94.5 63.7
Seychelles 40 60.71428571 83.6 84.5 67.2
South Africa 60 63 67 92 70.6
Swaziland 38 48.57142857 54.2 49.5 47.6
Tanzania 39 49.85714286 50.3 85 56.1
Zambia 36 49.85714286 45.3 84.5 53.9
Zimbabwe 30 41.14285714 32.1 46 37.3
Source: World Economic Forum (gcr.weforum.org), Reporters Without Borders website (http://www.rsf.org/) and United Nations Development
Program (http://hdr.undp.org/en/statistics/)
2.4.1.2.5 Tourism infrastructure index
The level of tourism infrastructure is likely to influence the number of flights demanded in each country
under an air transportation liberalisation regime. Countries with modern and developing tourism
infrastructure tend to attract far more tourists; therefore the ‘Tourism Infrastructure index’ was sourced
from the World Economic Forum website (http://www.weforum.org/documents/TTCR09/index.html).
This index takes into account the following:
Air transport infrastructure in each country,
Ground transport infrastructure,
Tourism infrastructure,
Information and Communication Technologies (ICT) infrastructure and,
Price competitiveness in the transport and tourism industry.
The tourism infrastructure index is measured between 7 and 0 (with 7 representing excellent tourism
infrastructure and 0 representing extremely poor tourism infrastructure.) The tourism infrastructure
index for each SADC country is summarised in Table 2.4-4.
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Table 2.4-4 Tourism Infrastructure Index by Country Country Tourism Infrastructure Index
Angola 3.05
Botswana 4.125
Democratic Republic of Congo 3.1
Lesotho 3.05
Madagascar 3.425
Malawi 3.025
Mauritius 5.05
Mozambique 3.05
Namibia 4.075
Seychelles 5.05
South Africa 4.775
Swaziland 3.05
Tanzania 3.2
Zambia 3.325
Zimbabwe 3.1
2.4.1.2.6 Airport infrastructure
Airport infrastructure influences the demand forecast for routes. Where infrastructure is lacking, so is
the supply of flights. A detailed list of airport infrastructure has been obtained from the International
Civil Aviation Organisation. This data indicates the airports with an instrument procedure list (a landing
procedure manual for pilots), airports with runways, airports with customs facilities, and whether the
airports run privately, publicly or by the military. An example of the information utilised can be seen in
Table 2.4-5 below, where an airport which has a given infrastructure is given a value of 1.
Table 2.4-5 Airport Infrastructure Airport Country Usage Customs Runway
Paved Instrument Approach Procedure
Previously Served Airport
Luanda Angola Civil 1 1 1 1
Gaborone Botswana Civil 1 1 1 1
Maseru Lesotho Civil 1 1 1 1
Antanànarìvo Madagascar Civil 1 1 1 1
Lilongwe Malawi Civil 1 1 1 1
Port Louis Mauritius Civil 1 1 1 1
Maputo Mozambique Civil 1 1 1 1
Windhoek Namibia Civil 1 1 1 1
Johannesburg South Africa Private 0 1 1 0
Johannesburg South Africa Civil 1 1 1 1
Dar-Es-Salaam Tanzania Civil 1 1 1 1
Lusaka Zambia Civil 1 1 1 1 Source: International Civil Aviation Organisation
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2.4.1.2.7 Domestic flights
Domestic routes within one country exhibit higher flight supply than international routes. Therefore
where air routes are entirely domestic a positive weighting of one has been assigned.
2.4.1.3 Determining the Demand for Each Potential Route in SADC
2.4.1.3.1 Method of calculating the indices for each factor
As already mentioned, each of the aforementioned data sets for each of the potential pairs of airports in
the SADC region has been converted into an index between 0 and 1. The calculation of these indices
varies according to the data available; the 1 and 0 index only considers two airports. The varied data
results in a varied effect on the ultimate anticipated demand for flights to and from various destinations.
The indices have been calculated by one of two methods, the dimension index method or as a
proportion.
2.4.1.3.1.1 The dimension index method
For each indicator a minimum and maximum goalpost must be defined and then the indicator must be
normalized between 0 and 1, based on the country or the airports relative position. This concept is
displayed in Box 2.4-1 below.
Box 2.4-1
Actual value
of indicator
Minimum of indicator|------------x------------------|Maximum of indicator
Index =(Actual value of indicator) – (Minimum of indicator)
(Maximum of indicator) – (Minimum of indicator)
Where this method was utilised in determining the various indices it was observed that those indices
would tend to supply more flights if they started from a low level of operation. This was evident when
considering GDP per capita (discussed in detail below). Therefore each indicator was logged, as seen in
Box 2.4-2.
Box 2.4-2
Index = log (Actual value of indicator) – log (Minimum of indicator)
log (Maximum of indicator) – log (Minimum of indicator)
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In the case of GDP per capita this effectively means that increases in income at a lower level has a
greater impact on the GDP per capita index, as shown in Figure 2.4-1 below.
Figure 2.4-1 GDP per Capita Index
2.4.1.3.1.2 Proportion method
The proportion method was used where data had already been taken from an existing index. This was
effectively converted into an index between 0 and 1, where proportions were maintained.
2.4.1.3.2 Gross domestic product per capita index
The GDP per capita index used the dimension index method to determine the weight of the index. The
calculation of the GDP per capita index assumes that an air transport liberalisation agreement in SADC
will make flying more affordable and that those individuals with lower income levels. These individual
will switch to air transportation when cost and amount of time travelling between various cities within
the SADC region decreases. Therefore the higher an individual’s income and countries GDP per capita
the higher the amount of people utilising air transport as method of transportation. Thereby as incomes
increase within a country the transition from road and rail transport to air transport will increase at an
increasing rate due to new low cost carriers entering the market.
2.4.1.3.3 Urban population of countries
Urbanization has increased significantly around Africa; we would expect this over the next 50 years.
Governments increasingly will be required to respond to this phenomenon with appropriate social,
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
GD
P p
er
cap
ita
Ind
ex
GDP per capita, US$ (2007)
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political and economic interventions that would lead to increased job creation and economic activity
around urban centres. As shown in the literature review one of the basic assumptions of the gravity
model is that increased urban populations will lead to an increase in demand for flights.
Once again the dimension index method is utilised, since countries moving off a low base of
urbanization would, under an air transportation liberalisation regime, demand flights from low income
carriers more rapidly as the population urbanises. The bias towards countries with lower urban
populations follows the argument presented by Swan (2008) in the literature review where under an air
transportation liberalisation agreement between countries flights and aviation development shift away
from the traditional airport hubs to the more decentralised airports and cities. This has been observed in
South Africa over the last decade where low income carrier airlines have increasingly expanded their
destinations to urban centres with lower populations such as the Durban to George, Durban to Port
Elizabeth and Johannesburg to Windhoek or Gaborone flights (www.1time.aero & www.kulula.com).
This is a trend that has also been displayed in the European Union and India where routes have began to
expand to traditionally less well serviced airports and cities with lower populations.
2.4.1.3.4 Population by city
Similar to the argument above it is anticipated that cities with higher populations tend to demand more
flights, and with the implementation of air transport liberalisation agreement in SADC it is expected that
there will be a gradual shift away from the traditional airport hubs and major urban centres. Once again
the dimension index method was employed to determine an index level for each airport.
2.4.1.3.5 Business, politics and development index indicators
The countries business, politics and development index indicators were already in index form. They
were converted into proportions between 0 and 100 as shown in Table 2.4-3 above. These were then
averaged and then converted to an index between 0 and 1, maintaining the established proportions.
2.4.1.3.6 Tourism infrastructure index
Likewise the tourism infrastructure index has already been established by the World Economic Forum as
shown in Table 2.4-4. These indices fall between 0 and 7 for each country, thus we divided each of these
indices by 7 to establish proportion between 0 and 1.
2.4.1.3.7 Airport infrastructure
As seen in Table 2.4-5, above, airport infrastructure for the various airports in SADC has been rated
between 0 – 1, depending on whether an airport has the infrastructure in place for the four factors
listed. To calculate this into an index we added the factors together and divided by 4 to yield an airport
infrastructure index.
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2.4.1.3.8 Example of calculated Indices
Table 2.4-6, below, gives an example of the various indices discussed for the main airports of each SADC
country.
Table 2.4-6 Example of Calculated Indices by Airport Airport Country Airport
Infra. GDP per capita
City Pop.
Urban Pop.
Business, Politics & Development
Tourism Infra.
Luanda Angola 1 0.8991 0.9169 0.6740 0.5006 0.4357
Gaborone Botswana 1 0.9802 0.6707 0.4189 0.6958 0.5893
Kinshasa DRC 0.95 0.2407 0.9747 0.8328 0.3900 0.4429
Maseru Lesotho 1 0.5109 0.6379 0.2756 0.5232 0.4357
Antanànarìvo Madagascar 1 0.4154 0.8308 0.6512 0.5397 0.4893
Lilongwe Malawi 1 0.3244 0.7513 0.5387 0.5364 0.4321
Port Louis Mauritius 1 0.9203 0.6432 0.3460 0.7204 0.7214
Maputo Mozambique 1 0.4110 0.8562 0.7067 0.5048 0.4357
Windhoek Namibia 1 0.8200 0.6928 0.3764 0.6373 0.5821
Seychelles Seychelles 1 0.9907 0.4969 0.0025 0.6719 0.7214
Johannesburg South Africa 1 0.9297 0.9604 0.8847 0.7062 0.6821
Manzini Swaziland 0.9375 0.7455 0.6013 0.2369 0.4757 0.4357
Dar-Es-Salaam Tanzania 1 0.3976 0.8960 0.7980 0.5605 0.4571
Lusaka Zambia 1 0.5697 0.8346 0.6285 0.5392 0.4750
Harare Zimbabwe 0.875 0.1983 0.8902 0.6412 0.3731 0.4429
2.4.1.4 Utilising the Gravity Model to Establish the Route Demand
Determining the demand for each factor above between airports in SADC requires use of the gravity
model, where similar factors are averaged to determine a combined index per route. The methods
employed in the model are shown in Box 2.4-3 overleaf.
Box 2.4-3
Equation (2) Factor Demand = (Factor Index airpory A
) + (Factor Index airport B
)
2
Example: GDP demand airport A&B
= (GDP per capita index airport A
) + (GDP per capita index airport B
)
2
To determine the estimate route demand, each of the factor demands needs to be combined. The
model in question has done this by assigning weights to each factor depending on the importance that
this factor has on overall demand. See equation (3) in Box 2.4-4 below. The model allows these weights
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to be changed for the various demand factors on the tab ‘Weights & Proportions’. Table 2.4-7 below
gives an example of how the demand estimates for each potential route in SADC has been calculated
using the weights. The higher the demand estimate the higher the number of flights will be demanded.
Box 2.4-4
Equation (3) Route demand = (GDP demand airport A&B
x A)+(City pop demand airport A&B
x B)+(Urban pop demand airport A&B
x C)+(Airport infra demand
airport A&B x D)+(Bus, Pol & Dev demand
airport A&B x E)+(Tourism infra demand
airport A&B x F)
where: A + B + C + D + E + F = 100%
Table 2.4-7 Determining the Demand Estimate for Routes Airports Same
Country Airport Infra-structure
GDP per capita
City Populatn
Urban Populatn
Business, Politics & Development
Tourism Infra-structure
DEMAND ESTIMATE
Weight 15% 5% 20% 25% 5% 20% 10% 100%
Windhoek Johannesburg 0 1 0.8748 0.8266 0.6306 0.6717 0.6321 0.6607
Cape Town Johannesburg 1 1 0.9297 0.9363 0.8847 0.7062 0.6821 0.8737
Durban Johannesburg 1 1 0.9297 0.9302 0.8847 0.7062 0.6821 0.8722
Johannesburg Lusaka 0 1 0.7497 0.8975 0.7566 0.6227 0.5786 0.6445
2.4.1.5 Time Frames
There are 3916 potential routes in the SADC region. These routes are comprised of 89 airports with
paved runways that are longer than 6400 feet. Not all of these routes will be feasible or cost effective in
the short run, particularly if the current aviation market in SADC is taken into account. However, in the
long term there is no reason for these routes not to become feasible, provided infrastructure, business
and income levels continue to improve in each country. Therefore the model is structured such that it
determines demand, potential turnover and seat numbers over a 50 year period.
In the first 5 years post implementation of an air transport liberalisation agreement in SADC, it can be
expected that all the routes that are currently being operated by national flag carriers and low cost
carriers would expand and attract new airlines and lower prices. New routes are unlikely as airlines and
airports adjust to the new market regulations and demands. The first five years post the air transport
liberalisation agreement in SADC only takes into account current routes being used. After 10 years the
model predicts that routes with a demand estimate of greater than 0.75 would see new flights being
operated. After a 15 year period the model predicts that routes with a demand estimate of greater than
0.70 would see new flights being operated. The model continues in this fashion of decreasing the
demand estimate by 0.05 over 5 year intervals all the way to a 50 year time period where all routes have
been included in the model.
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2.4.2 Direct Impacts
2.4.2.1 Determining Potential Turnover and Seat Numbers per Route
This section deals only with the direct impact experienced by airlines if an air transport liberalisation
agreement was implemented in the SADC region. The red blocks highlighted in Figure 2.4-2 below
display the primary focus of this model, namely; introduction and expansion of new flights to both new
and existing destinations. Sections that follow will detail methodology used to estimate the direct and
indirect impacts.
Figure 2.4-2 Flow chart showing methodology for the section
The demand estimate for each route has been used to determine the potential turnover as well as the
seats demanded per week. The following section explains the methodology on how the figures for each
individual route have been determined.
The questionnaire sent to airlines revealed both current seat capacities and pricing per flight. We
received information on these from South African Airways (SAA), Comair (British Airways & Kulula.com)
and Airports Company South Africa (ACSA). This information combined with the now calculated demand
estimates between 0 and 1 reveals potential turnover and seat requirements on each route per week.
The model only takes into account data from South African domestic flights on very competitive routes
(namely: Durban to Johannesburg, Cape Town to Johannesburg and Cape Town to Durban.) This is
because of the vigorous competition of the established low cost carriers that operate on these routes.
An air transportation liberalisation agreement in the SADC region will encourage aviation competition
along all routes, which favours mostly low cost carriers.
Open SkiesDirect
Impacts
Airlines
Benefits New Flights
New destinations
Current Destinations
Costs
Airports
Passengers
Freight
Customs
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Table 2.4-8 shows how the supply of seats and potential turnover per route were determined. The
average seats per route, along with the minimum price per seat were obtained from Kulula, British
Airways and SAA questionnaires and online information. Multiplying these columns gives us the
estimated turnover per flight; this has then been adjusted for a 75% take up of capacity. (SAA stated in
their questionnaire that roughly 75% of capacity is taken up on flights). The distance in kilometres was
then used to determine the turnover per kilometre on the three routes, which as can be seen in Table
2.4-8 ranged from R 34.68 to R 40.64. The turnover per kilometre was then divided by the demand
estimate (these ranged between R 40.18 to R 46.60.) From these figures we determined if the demand
estimate was 1 then an average of R 43.71 per kilometre would be the potential turnover per kilometre.
The R43.71 per kilometre was then multiplied by:
Each routes distance in kilometres;
Each routes demand estimate; and
131.56 (the average number of flights per week to and from Johannesburg to each South African domestic destination, as obtained from ACSA), and this was used to estimate the potential turnover per week for each particular route.
To estimate seat numbers per week, the ‘average seats per flight’ (130) was multiplied by the 131.56
(average number of flights to and from Johannesburg to each South African domestic destination) and
then multiplied by each routes demand estimate. This calculated the estimated number of seats that
would be demanded on each particular route. From the estimated turnover and seat numbers per week,
an average ticket price per seat per flight was estimated.
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Table 2.4-8 Potential Turnover and Seat Numbers Airport Demand
Estimate Average Seats / flight
Minimum Price
Estimated Turnover / flight
Capacity take up of 75%
Distance (km)
Turnover per km
Turnover per Km / Demand estimate
Potential Turnover per week
Seat Numbers per week
Average Ticket Price per flight
Cape Town
Durban 0.8630 123 R 480.00 R 59,040.00 R 44,280.00 1,277.00 R 34.68 R 40.18 R 6,336,564.47 7,361 R 430.42
Cape Town
Johannesburg 0.8706 136 R 480.00 R 65,440.00 R 49,080.00 1,271.43 R 38.60 R 44.34 R 6,364,160.74 7,425 R 428.55
Durban Johannesburg 0.8722 130 R 200.00 R 25,933.33 R 19,450.00 478.59 R 40.64 R 46.60 R 2,400,018.47 7,439 R 161.31
Average: 130 R 43.71 8,529
2.4.2.2 Passenger Time Saving
This section focuses on the benefit to passenger if an air transport liberalisation agreement is implemented in SADC. Passengers firstly benefit
from the decrease in airfares (due to increased competition among airlines), secondly from time saving now that airlines can bypass hub airports
and land in destinations of their choice. Due to the lack of the current aviation information collected from the survey questionnaires provided by
airlines it is impossible to determine the benefit that would accrue to passengers from a decrease in aviation prices. This price decrease would
also happen over a period of time and only as competition increases; competition currently is marginal in SADC and therefore it would be guess
work or complete speculation to predict how the competition would increase over time. Figure 2.4-3 displays how the passengers’ benefits fit
into the overall impact.
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Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology
The time benefit to passengers has been calculated by assuming that in order for a person to currently
travel between various locations in SADC they are required to travel through the major airports in each
country. This therefore means that a person wanting to travel from Durban, South Africa to Beira,
Mozambique would need firstly to travel OR Tambo, Johannesburg and then to Maputo, Mozambique
before connecting to Beira. This assumption has been followed for each potential origin and destination
in SADC. Due to the sheer volume of potential routes that are available under the regulation allowed by
an air transport liberalisation agreement, and the complexities of air travel in SADC this simplified
assumption has been adopted. Under an air transport liberalisation agreement in SADC flying from
origin to destination would be shortened because airline are allowed to fly directly from Durban, South
Africa to Beira, Mozambique, thus there is massive time saving due to the direct flight offered.
Figure 2.4-4 overleaf illustrates the assumption of current air travel around SADC. It can be seen that all
air traffic filters through a central hub within each country (yellow/gold lines to and from red points) and
then through the central airport hub in SADC, namely OR Tambo in Johannesburg (red lines to the
largest red point.) From this figure it can be seen that travelling around SADC can be costly in terms of
tickets, airport taxes and time. An air transport liberalisation agreement in SADC would eventually do
away with the large number of connecting flights and passengers could connect directly to their ultimate
destination.
With the distances travelled by passengers prior to an air transport liberalisation agreement in SADC and
the distances travelled post an air transport liberalisation agreement in SADC, there is saving in the
distance travelled by passenger (this distance saved can be translated into the amount of kilometres
saved in travel.) This distance can be converted into time when we take into account the average
cruising speed of a commercial aircraft. The current average cruising speed of a commercial Airbus,
Boeing or McDonald Douglas Aircraft is 900 kilometres per hour. With the amount of time saved in
Open Skies Direct Impacts
Airlines
Airports
Passengers Benefit Time Saving
Freight
Customs
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terms of air travel known and now converted into time savings per hour it is easy to calculate the time
saving benefit if you know the value of a passengers time in hours. Assuming the value of an hour for a
passenger is a tricky undertaking due to the cross section of passengers that make use of air travel
(these is an infinite number of reasons passenger fly and each of these would vary the value of time.)
For the purposes of this study it has assumed that a person utilising air transportation would values an
hour at R 200 (this is a completely arbitrary amount and a further study is required to understand a
passengers value time saved.)
Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in SADC
Source: adapted, Google Earth 2010
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2.4.2.3 Direct Costs to Airlines
The direct impacts likely to be experienced by airlines are divided into costs and benefits. For this study,
these costs have been broken down into five categories – cancellation costs, diversion costs, cost of fuel,
aircraft operation costs and increased accidents and incidents.
All data has been derived from the EUROCONTROL 2007 document1 and the Standard Economic Values
Guidelines report2. Where applicable, values sourced from these two documents have been converted
into 2009 Rands3.
The table below summarises the monetary value of the abovementioned costs. The cost of fuel and the
effect of an increase in the rate of fuel burn have been excluded from the table, and will be discussed
separately below.
Table 2.4-9 The Monetary Value of Costs Details Minimum Maximum Value
Cancellation Costs
The cost of cancelling the flight of a 120 seat narrow body jet aircraft
- - R 172,033.02
Diversion Costs
The cost of diverting a regional flight R 8,028.28 R 57,344.83 -
The cost of diverting a continental flight R 11,468.97 R 86,017.24 -
Aircraft operating costs
Estimated aircraft operating costs / hour in Rands (excluding fixed annual overheads) for an average aircraft
- - R 23,330.00
Accidents/ incidents
The average cost to an airline of a fatality - - R 26,378,620.74
The average cost to an airline of an injury
Minor injury - R 406,001.38 -
Major injury - R 5,502,809.67 -
Note: all values are expressed in constant 2009 Rands.
The first aspect of direct costs that must be taken into account is the cost of cancellation.
Cancellation costs refer to the cost of abandoning a commercial scheduled flight on the day of
operation. With more flights expected to be scheduled in an air transportation liberalisation
environment, cancellation costs can be expected to rise following implementation of an air transport
liberalisation agreement in SADC. These costs include service recovery costs, interline costs, loss of
1 Standard Inputs for EUROCONTROL Cost Benefit Analyses, 2007 Edition
2 Australian Government, Civil Aviation Safety Authority, Standard Economic Values Guidelines, Version 1.0: 2007
3 2007 AUD $ inflated by 6.25% to equal 2009 AUD $. 2009 AUD $ multiplied by 6.8106 to equal 2009 ZAR Rands.
2007 €’s inflated by 6.09% to equal 2009 €’s. 2009 €’s multiplied by 10.8106 to equal 2009 ZAR Rands.
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future value and decrease in operational savings4. The cost above is specifically for a 120 seat narrow
body aircraft and is estimated at R172,033.02 per cancellation.
The next cost category considered is the average cost per flight diversion, estimated separately for
regional and continental flights. This is the cost of diverting a commercially-scheduled flight. As with
cancellations, with more flights expected to be scheduled in an air transportation liberalisation
environment, the costs of diversions can be expected to rise following implementation of an air
transport liberalisation agreement in SADC. These values are estimated by means of a minimum-
maximum bracket, as they can vary depending on the nature of the diversion. For regional flights, the
range of cost is R8,028.28 to R 57,344.83, while for continental flights; the range is R 11,468.97 to R
86,017.24.
The cost of fuel, and subsequently the increased rate of fuel burn have been excluded from the table for
two reasons. Firstly, data that was available on the cost of jet fuel was extremely generalised and thus
generated no valuable information. Secondly, all data that was available in this area was gathered as
fuel usage according to the tonnes per flight or kilograms per landing/take-off phase. Information on
fuel use per kilometre was not available at this time. For these reasons, the cost of fuel has been
excluded.
Aircraft operating costs refers to the average estimated cost of running an aircraft per hour. This cost
has been estimated per hour at R 23,330.00. This value excludes all fixed annual overheads.
The value for accidents and incidents is an estimation of the cost to an airline in the event of an
accident, whether resulting in injury or death. The possibility exists that implementing an air transport
liberalisation agreement in SADC will result in more fatalities, from more flights operating at each
airport. The cost to an airline in the event of such accidents and incidents must then be taken into
account.
The estimated cost of a fatality is R 26,378,620.74. The cost of injury is estimated with an upper limit
only. The cost of a minor injury is R 406,001.38 and the cost of a major injury is R 5,502,809.67. These
estimates are the cost incurred to the airline in the event of an injury or a fatality.
4 Source: Cost-Benefit Analysis Methodology, Graham Muller Associates, 2010
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2.4.3 Indirect Impacts
2.4.3.1 Security
The indirect costs of increased air travel within the SADC region would include an increase in the
amount of security personnel and infrastructure required to handle increased traffic.
There is currently no public information available for security costs across the SADC region; however a
report on security costs in Australia5, a large common flying area revealed some interesting costs on a
per passenger basis.
Airport security costs have some element of economies of scale and the per passenger charge in the
Australian study was significantly lower for larger airports. Every airport will require security scanners
and personnel to man them, but the throughput for an airport with a constant stream of arrivals versus
one with few daily flights will obviously vary greatly.
Security mandates at airports under an air transportation liberalisation agreement should adhere to
standardised security protocols and procedures and thus costing could be assumed to be similar through
all airports of a similar size.
High fixed costs mean that smaller airports have to charge more for the same security functions as
larger airports. Additionally international passengers have more security procedures to complete and
thus international arrivals cost more. The variation in price for Australia varied from A$16 for a small
international airport passenger arrival to A$4 for large airports handling domestic passengers.
Airports pass onto airlines the costs of operating the facilities based on passenger numbers and freight
volumes and airlines therefore consider security costs when deciding on which airports to utilise.
Additionally there are two elements to the costing of airport security, one is the cost borne by the
airlines and relates directly to their security costs and the other relates to the security of the country as
a whole and thus some of the security costs are carried by national government.
The increased flights will result in a turnover in security costs of A$4,90 per passenger for domestic
flights and A$8 for international flights. That will account for increased spending of R32,93 per
passenger boarding or disembarking for domestic flights and R53,76 for international flights.
5http://www.infrastructure.gov.au/aviation/nap/files_green_paper/Government_of_Northern_Territory-
Access%20Economics_att.pdf
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2.4.3.2 Transport
Benefits of an air transportation liberalisation policy to the travel and transport industry will extend to
both tourism and freight. The impacts of increased freight would be an increase in the number of air
freight routes and more timely arrival of freight to a variety of destinations. However current patterns of
air traffic suggest that air freight transportation is dependent on an established passenger air travel
service. The impact on the transport industry can be predicted on its own in relation to air arrivals,
however the tourism impact section accounts for these impacts by estimating the change in passenger
arrivals will have on the country of destination as a whole. The tourism impact includes transport
spending and thus in order to avoid double counting we can assume that the impact on the transport
section is included in the tourism section.
Some statistics from a Detroit Metropolitan Wayne County Airport Impact Study conducted in 2006
indicate the transport patterns of traveller arrivals. Tourists accounted for 33% of air arrivals and
residents accounted for 63% of arrivals. For tourists, the average stay was 3.5 days. Half of tourists, or
16% or air arrivals rented a car for the average 3,14 days. The average spend on car rental was the
equivalent of R770 per stay.
2.4.3.3 Pollution
A further consideration as a negative externality which is difficult to quantify is the impact of an air
transportation liberalisation policy on pollution in the SADC region.
The standard inputs for EUROCONTROL Cost benefit Analyses 2007 edition suggests two types of
pollution; noise emanating from aircraft engines and air pollutants from the of burning fuel.
For the fuel portion they suggest the following rate of pollution:
Table 2.4-10 Cost of Fuel
Pollutant per kg of fuel burned6 Cost
7 Burn Rate
8 (737- 800) Cost per hour of
flying time
CO2 3.149 kg R360 per tonne 2,572 tonnes/h R925,92
H20 1.230 kg R101 per tonne 2,572 tonnes/h R259,72
Total: R1185,67
The 737-800 aircraft was used as it is one of the most likely planes to be used on the SADC routes.
6 http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note_2001_08.pdf
7 “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”,
CE, Solutions for environment, economy and technology, Delft, The Netherlands
8 http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf
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Furthermore noise pollution levels in the EUROCONTROL study are costed at R693 per take off and an
additional R693 per landing. It must be noted that aircrafts used in Europe are generally newer and
therefore create less pollution. The study has maintained the levels set by the EUROCONTROL study, as
there is no data that is more relevant to the South African aviation situation.
2.4.3.4 Tourism Impact
Implementation of an air transport liberalisation agreement in SADC will result in increased visitor
arrivals and increased overnight visitor stays boosting the tourism industry in participating countries. To
estimate the impact of this effect on the economy of the countries involved in the study, tourism data
was obtained from the World Travel and Tourism website9. The website contains tourism data for
thirteen of the fifteen countries in SADC. The countries omitted are Mozambique and Seychelles, for
these countries the data for Tanzania in Mozambique’s case and Mauritius in Seychelles case was used.
The economic data search tool on the website allows this data to be edited into a suitable format. The
figures for the total impact of tourism on the economy (including indirect and induced spending) in
terms of gross domestic product (GDP) and employment, as well as the direct tourism industry impact
on GDP and employment for the period 1988 to 2010 was acquired. In addition numbers of international
visitors and overnight visitors’ data was obtained in order to translate seat numbers within the model
into an overnight tourism figure.
In order to arrive at a usable “multiplier” for the seat numbers data produced by the routes demand
model, the following process is carried out. First each data set for each country is averaged over the
period (1988 – 2010). As data does not exist for Mozambique and Seychelles, the averages from
Tanzania and Mauritius were used respectively, as these countries are likely to have similar
circumstances in terms of tourism. This average, for example the total average impact of the tourism
industry on a country’s GDP, is divided by the total number of overnight visitors to give the total impact
of the tourism industry on a country’s GDP by one overnight visitor. The percentage of the increase in
seat numbers from the model that can apply to tourism spend is translated into an overnight visitor
figure by taking the average percentage of international visitors between 1988 and 2010 and dividing it
by the average overnight visitors for the period. This gives an estimate of how many of the new
passengers will contribute to the tourism industry.
The methodology is applied to generate a forecast of total impact of tourism on employment, and direct
impact of tourism on GDP and employment. To arrive at the aggregate estimated impact of increased
levels of tourism activity resulting from implementation of an air transport liberalisation agreement in
SADC for ten five year periods totalling fifty years in all. The results of this process are included in
chapter 4.
9 http://www.wttc.org/
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The methodology the WTTC employed to arrive at the figures in the council’s database that the study
team used in this process can be found on the WTTC website10.
2.4.4 Airport and Navigational Infrastructure
Adequate airport and navigational infrastructure is essential in creating the platform for airlines to take
advantage of air transport liberalisation regulations. Airport capacity and navigational infrastructure is
mostly below international standards beyond the borders of South Africa in the SADC region. Airport
and navigational infrastructure would need to be upgraded or installed throughout the region to create
capacity for all the additional flights and passengers due to air transport liberalisation within the SADC
region. All the information and data regarding infrastructure requirements and costs have been
provided by Air Traffic & Navigational Services (ATNS) and the Airports Company South Africa (ACSA).
The navigational infrastructure costs have been broken into two parts: the first being the navigational
equipment required per route; and the second being the navigational equipment required per airport.
The airport infrastructure costs are purely an airport cost to create the capacity to handle increased
number of passengers.
2.4.4.1 Navigational Infrastructure per Route
Navigational equipment is not only required at the various airports but also at various intervals along
each route. The navigational equipment required depends on the nautical miles (NM) separation
between aircrafts and the flight level being flown by aircrafts. For the purpose of this study we’ve
assumed that all navigational equipment needs to be standardised across the SADC region at South
African specifications. This would entail navigational equipment being installed with the technological
stipulations to allow aircrafts to travel 5 NM apart from each other. The navigational equipment
requirements has been listed in Table 2.4-11 below for 5 NM distance between aircrafts, it can be seen
the unit cost has been provided for each piece of equipments, as well as their theoretical coverage in
kilometres and the number of these units required to accommodate a distance of 5 NM per aircraft.
With this information displayed in Table 2.4-11 it is possible to calculate the cost of navigational
equipment per kilometre for each route within the SADC region. This information has been calculated
for both the 145 and 195 flight levels (the upper and lower range of flight levels.) Although the cost of
navigational infrastructure is a cost that is incurred every 15 years, for the purpose of our study this cost
has been broken down into a weekly cost and can be compared with the other costs and benefits.
10http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_res
earch_metho.pdf
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Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM11 Navigational Equipment
Unit Costs Theoretical Coverage (KM) 5 NM Navigational Requirement
FL 145 FL 195 FL 145 FL 195
DVOR/DME 6,000,000 180 200 1 1
SSR 25,000,000 230 315 2 2
VHF 150,000 230 315 1 1
2.4.4.2 Airport Navigational Equipment Costs
Airport navigational costs have been provided by ATNS. The airport navigational infrastructure that
ATNS has recommended is aligned with the navigational systems and standards currently adopted in
South African airports. The navigational airport infrastructure has a 15 year life span, after which the
navigational equipment needs to be replaced. Table 2.4-12 lists the navigational equipment required
depending on the type of airport.
Table 2.4-12 Airport Navigational Equipment Required per Airport Type Facilities Unit Cost Type 1 Type 2 Type 3
DVOR/DME 6,000,000 1 1 1
VDF (Class C) 350,000 1 1
SSR 25,000,000 1 1
PSR 35,000,000 1
VHF 150,000 1 2 3
TCU 10,000,000 1
The number of flights determines the amount of navigational equipment required. For the purposes of
this report the airports have been separated into three categories based on the number of passengers
passing through the terminals annually. The simplified definitions of the three types of airports are: Type
1 airports have low number of annual passengers; type 2 airports have medium number of annual
passengers; and type 3 airports are the major airports in the SADC region. The various classifications of
airports have been listed in Table 2.4-13 to Table 2.4 -16.
This information helps determine the cost navigational equipment cost per airport. As this is a sunk
capital cost every 15 years, the profitability per airport will be determined over the 50 year period to
assess the overall impact of the infrastructure installed per airport.
11 The rand value’s are based on a Euro Rand exchange rate of R11=1 Euro at July 2010prices
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Table 2.4-13 Type 1 Airports in the SADC Region Type 1
Location Country Location Country Location Country
Dundo Angola Gemena D.R. Congo Mariental Namibia
Huambo Angola Goma D.R. Congo Ondangwa Namibia
Kuito Angola Isiro-Matari D.R. Congo Rundu Namibia
Lubango Angola Kananga D.R. Congo Mafikeng South Africa
Luena Angola Kindu D.R. Congo Polokwane South Africa
Malanje Angola Mbandaka D.R. Congo Pilanesberg South Africa
Menongue Angola Mbuji-Mayi D.R. Congo Umtata South Africa
Namibe Angola Nosy Be Madagascar Welkom South Africa
Ondjiva Angola Toliara Madagascar Mtwara Tanzania
Saurimo Angola Chimoio Mozambique Mwanza Tanzania
Soyo Angola Cuamba Mozambique Kitwe Zambia
Uíge Angola Mueda Mozambique Mfuwe Zambia
Kasane Botswana Tete Mozambique Ndola Zambia
Bukavu D.R. Congo Karabib Namibia Hwange Zimbabwe
Buta-Zega D.R. Congo Katima Mulilo Namibia
Gbadolite D.R. Congo Keetmanshoop Namibia
Table 2.4-14 Type 2 Airports in the SADC Region Type 2
Location Country Location Country Location Country
Cabinda Angola Beira Mozambique Nelspruit South Africa
Catumbela Angola Lichinga Mozambique Port Elizabeth South Africa
Francistown Botswana Moçimboa da Praia Mozambique Upington South Africa
Maun Botswana Nampula Mozambique Manzini Swaziland
Kisangani D.R. Congo Grootfontein Namibia Dodoma Tanzania
Lubumbashi D.R. Congo Bisho South Africa Kilimanjaro Tanzania
Maseru Lesotho Bloemfontein South Africa Livingstone Zambia
Mahajanga Madagascar George South Africa Bulawayo Zimbabwe
Toamasina Madagascar Johannesburg (Lanseria) South Africa Victoria Falls Zimbabwe
Blantyre Malawi Kimberley South Africa
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Table 2.4-15 Type 3 Airports in the SADC Region Type 3
Location Country Location Country Location Country
Luanda Angola Maputo Mozambique Dar-Es-Salaam Tanzania
Gaborone Botswana Windhoek Namibia Zanzibar Tanzania
Kinshasa D.R. Congo Seychelles Seychelles Lusaka Zambia
Antanànarìvo Madagascar Cape Town South Africa Harare Zimbabwe
Lilongwe Malawi Durban South Africa
Port Louis Mauritius Johannesburg South Africa
2.4.4.3 Airport capacity constraints and expansions
Airports are constrained by peak hour capacity limits, as there are a limited number of bays for
aeroplanes and a limited amount of trained staff to deal with passengers. Therefore, it is important to
assess the additional capacity required based on the demand predicted by this study and determine the
cost of airport infrastructure. This study has utilised the ACSA estimate that determines it would roughly
cost R 600 million to create an additional airport capacity for one million passengers.
Verifying the capacities for all the airports in the SADC region is extremely difficult, as only the ACSA
airports capacities are known. Therefore, capacities have been assumed based on the capacity
information provided by ACSA. Table 2-20 SADC airport capacities display the assumed capacities for the
airports in the SADC region. Major airports outside of South Africa have been given a 14 million annual
passenger capacity (in line with Cape Town International), medium sized airports have been given an
annual capacity of 4.5 million passengers (in line with King Shaka International), and small airports have
been given an annual capacity of 720,000 passengers (an average of all the smaller ACSA airports.)
The investment in airport infrastructure has been linked with the forecasted number of passengers
utilising the airports annually over the 50 year period. As passenger numbers exceed capacities
displayed in Table 2.4-16 the ratio of R 600 million for every one million extra passengers is applied. This
would yield an increased airport capacity aligned with the passenger forecast growth over the 50 years.
The ACSA airports where annual passenger capacities are known are highlighted in red in Table 2.4-16.
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Table 2.4-16 SADC Airport Capacities Location Annual Capacity Location Annual Capacity Location Annual Capacity
Cabinda 720,000 Mbuji-Mayi 720,000 Durban 4,500,000
Catumbela 4,500,000 Maseru 4,500,000 George 900,000
Dundo 720,000 Antanànarìvo 14,000,000 Lanseria 720,000
Huambo 720,000 Mahajanga 4,500,000 Johannesburg 28,000,000
Kuito 720,000 Nosy Be 720,000 Kimberley 200,000
Luanda 14,000,000 Toamasina 4,500,000 Mafikeng 720,000
Lubango 720,000 Toliara 720,000 Nelspruit 720,000
Luena 720,000 Blantyre 4,500,000 Polokwane 720,000
Malanje 720,000 Lilongwe 14,000,000 Port Elizabeth 2,000,000
Menongue 720,000 Port Louis 14,000,000 Pilanesberg 40,000
Namibe 720,000 Beira 4,500,000 Umtata 720,000
Ondjiva 720,000 Chimoio 720,000 Upington 100,000
Saurimo 720,000 Cuamba 720,000 Welkom 720,000
Soyo 720,000 Lichinga 720,000 Manzini 4,500,000
Uíge 720,000 Maputo 14,000,000 Dar-Es-Salaam 14,000,000
Francistown 720,000 Moçimboa da Praia 720,000 Dodoma 720,000
Gaborone 14,000,000 Mueda 720,000 Kilimanjaro 4,500,000
Kasane 720,000 Nampula 4,500,000 Mtwara 720,000
Maun 4,500,000 Tete 720,000 Mwanza 720,000
Bukavu 720,000 Grootfontein 4,500,000 Zanzibar 720,000
Buta-Zega 720,000 Karabib 720,000 Kitwe 720,000
Gbadolite 720,000 Katima Mulilo 720,000 Livingstone 4,500,000
Gemena 720,000 Keetmanshoop 720,000 Lusaka 14,000,000
Goma 720,000 Mariental 720,000 Mfuwe 720,000
Isiro-Matari 720,000 Ondangwa 720,000 Ndola 720,000
Kananga 720,000 Rundu 720,000 Bulawayo 720,000
Kindu 720,000 Windhoek 14,000,000 Harare 14,000,000
Kinshasa 14,000,000 Seychelles 14,000,000 Hwange 720,000
Kisangani 4,500,000 Bisho 1,200,000 Victoria Falls 4,500,000
Lubumbashi 4,500,000 Bloemfontein 600,000
Mbandaka 720,000 Cape Town 14,000,000
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2.5 Cost-Benefit Analysis Results
2.5.1 Direct Impacts
2.5.2 Benefit to airlines
As explained in the methodology the number of flights added, at each five year interval, is determined
by whether the demand estimate per route is greater than the progressive 0.05 decrease in the demand
estimate hurdle rate assumed by the model for every five year period into the future. The model
therefore predicts that flights yielding a higher demand will be taken up by airlines in the early stages of
implementation of an air transport liberalisation agreement in SADC as they offer the prospect of lowest
commercial risk and the highest return in terms of profitability.
During the 35 to 50 year period post full implementation of an air transport liberalisation agreement in
SADC, flights still being added by airlines will effectively be serving progressively higher commercial risk
and lower profit routes. The reason for this is that all the major routes will be fully operational and there
will be reduced market share for additional airlines or additional flights. Airlines will therefore seek to
grow their market share by offering flights on these commercially riskier and less profitable routes. Of
course, in reality, air fares are likely to be higher on these routes to reflect the higher commercial risk,
because fewer airlines will be attracted to the routes with lower commercial potential.
Table 2.5-1, below, shows the forecasted turnover, seat numbers and flights (per week) over a 50 year
period starting from the day an air transport liberalisation agreement in SADC is broadly implemented in
SADC. This gross turnover included existing turnover on routes flown prior to implementation of an air
transport liberalisation agreement in SADC. Unfortunately, for reasons of confidentiality, the airlines
responding to the study questionnaire were not willing to disclose existing turnover figures. In
consequence, the study only forecasted the gross turnover projections post implementation of an air
transport liberalisation agreement in SADC. It can be observed that over a 50 year period the forecasted
turnover per week for low cost carriers would total R 21.8 billion (2009 prices).
Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week)
Years Turnover Seat Numbers Number of flights
5 R 395,592,569.17 1,157,834 13,024
10 R 615,030,014.60 2,155,705 22,628
15 R 631,437,961.30 2,253,469 23,680
20 R 1,055,829,325.19 3,634,050 39,598
25 R 3,194,221,298.65 7,059,728 82,222
30 R 8,886,816,358.07 15,622,239 197,596
35 R 15,354,301,000.26 24,847,174 333,625
40 R 20,306,047,606.09 32,446,460 456,498
45 R 21,592,032,312.26 34,280,245 489,124
50 R 21,804,364,460.93 34,697,974 498,464
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On average 34.6 million passengers would travel within SADC weekly and there would be almost half a
million flight operating across all SADC routes per week. Turnover grows rapidly, especially from the
15th year and indicates the significant benefit to airlines of implementing an air transport liberalisation
agreement in SADC.
Figure 2.5-1, below, displays the growth in turnover for low cost carriers over the 50 year period
following the implementation of an air transport liberalisation agreement in SADC. It is expected that
the graph would encompass an S-bending curve because the initial take up after liberalisation would be
slow due to airlines adjusting to the new regulatory environment. It can also be expected that the
lower commercial risk and higher return routes will be added to airlines’ routes flown in the early stages
of liberalisation, before the higher commercial risk and lower return routes are added. This is reflected
in what the model predicts – as shown in Figure 2.5-1. This graph shows that between implementation
and 35 years turnover would increase at an increasing rate and then from the 35th to the 50th year
turnover would increase at a decreasing rate.
Figure 2.5-1 Forecasted Turnover
The marginal turnover graph can be seen in Figure 2.5-2. This graph shows the amount of additional
turnover added at each 5 year interval. It can be seen that at 35 years the amount of turnover being
added begins to decrease. This reflects that during the first 35 years route and flight additions would
focus on the commercially more feasible and low risk routes. There would be heavy competition
amongst airlines operating in the SADC region. The routes added beyond 35 years of implementing an
air transport liberalisation agreement in SADC would be higher risk and lower demand and would only
be taken up by airlines once the major routes are completely serviced, but airlines seek to further
extend their aviation market share.
R -
R 5,000,000,000.00
R 10,000,000,000.00
R 15,000,000,000.00
R 20,000,000,000.00
R 25,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
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The marginal cost curves and all other marginal benefit curves, with the exception of the marginal
benefit to passengers graph display a similar shape, peaking at 35 years. The marginal benefit to
passengers did not peak at the 35 year. This graph is displayed and discussed at a later stage in this
section.
The rest of these graphs have not been included in this report but can be viewed in the accompanying
Microsoft Excel economic forecast model.
Figure 2.5-2 Marginal turnover
Figure 2.5-3, overleaf, indicates the growth in seat numbers purchased over a 50 year period after
implementing an air transport liberalisation agreement in SADC based on the assumption that 75% of
seats on offer are taken up. Similarly to Figure 2.5-1, which indicates growth in turnover over the same
50 year time frame, an s-bend curve is observed. As seat numbers are closely correlated with turnover
the s-bend similar to that of turnover is expected.
R -
R 1,000,000,000.00
R 2,000,000,000.00
R 3,000,000,000.00
R 4,000,000,000.00
R 5,000,000,000.00
R 6,000,000,000.00
R 7,000,000,000.00
5 10 15 20 25 30 35 40 45 50
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Figure 2.5-3 Growth in Seat Numbers
It can also be expected that growth in the number of flights per week over the 50 year period following
the implementation of an air transport liberalisation agreement in SADC will increase in a similar way to
that of turnover and seat numbers, since the number of flights is directly related to the number of seats
demanded and sold. The s-bending curve for the number of flights per week can be seen in Figure 2.5-4,
below. Once again the same reasoning is applicable, where flights are added to the low commercial risk
and high return routes during the initial 35 year period and thereafter, with limited opportunity for
additional flights on these routes, flights being added to the higher commercial risk and lower return
routes are embarked on in the 35 to 50 year period.
Figure 2.5-4 Growth in Number of Flights per Week
-
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
5 10 15 20 25 30 35 40 45 50
Year
-
100,000
200,000
300,000
400,000
500,000
600,000
5 10 15 20 25 30 35 40 45 50
Year
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2.5.3 Benefits to passengers
As discussed in the methodology there are primarily two benefits that would accrue to passengers
following a liberalisation of aviation regulations. Firstly the benefit of decreased ticket prices and
secondly time savings from flights bypassing hub airports and flying directly from the points of origin to
destinations that passengers actually want to fly to. It has already been noted that it proved impossible
to account for the benefit from the decrease in ticket prices due to the limited commercial information
received from airlines currently operating in SADC. However the study team has calculated the time
saving benefit that would accrue to passengers due to time savings of flying directly to a destination,
bypassing hub airports and flying directly.
2.5.3.1 Time savings
The assumptions that are spelled out in the methodology section of this report have informed the
results that follow. It has been estimated that there will be a 7.9 million kilometre (per week) decrease
in the distance flown by passengers to reach their final destinations. If the average cruising speed of an
aircraft is 900km/h then approximately 8805 hours would be saved in air travel for all routes within
SADC. Table 2.5-2 below shows how this time saving was estimated in 2009 Rands if a person values an
hour saved at the entirely notional value of R200 per hour. Table 2.5-2 indicates that time saving by
passengers over a 50 year period would total R 13.9 billion. Regardless of the notional value per hour
chosen for passenger time this indicates that the value of this aggregate benefit will be substantial.
Table 2.5-2 Passenger Time Saving Benefit Years Value of Passenger Time Saved at a
Value of R200/hour
5 R 80,704,142.39
10 R 148,353,788.17
15 R 152,429,875.57
20 R 265,108,382.22
25 R 766,732,401.87
30 R 2,961,410,846.08
35 R 7,207,220,265.68
40 R 12,429,642,407.48
45 R 13,703,434,148.72
50 R 13,957,174,567.04
Once again, as can be seen in Figure 2.5-5 overleaf, an S-bend shaped curve describes the relationship
between the values of passengers’ time saved over a 50 year period. Again this is expected as initially
routes that exhibit generally low commercial risk and high returns would be adopted by low cost
carriers. As the results from the model indicate that routes operating to or from hub airports generally
exhibit lower commercial risk and higher returns due to higher population concentrations and higher
levels of business activities, this means that relatively limited time savings to passengers would be
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generated in the early years post implementation of an air transport liberalisation agreement in SADC. A
number of these routes are currently being operated by national flag carriers and therefore a low cost
carrier operating on these routes would be able to fairly easily win business, at relatively low
commercial risk, on these routes, in a de-regulated operating environment. As more commercially
challenging routes that bypass the hub airports, are added in later years, time savings to passengers
would begin to increase, exponentially at first and then tapering off as the overall SADC aviation market
approaches saturation.
Figure 2.5-5 Passengers Time Saving Benefit
Figure 2.5-6 shows the marginal benefits resulting from passengers’ time saving in each five year period
post implementation of an air transport liberalisation agreement in SADC. As mentioned earlier in the
report, the 5 year marginal benefit from passengers’ time peaks at year 40 post implementation of an
air transport liberalisation agreement in SADC, somewhat later than for other benefits predicted by the
cost-benefit model, the quantum of which peak in year 35 post implementation of an air transport
liberalisation agreement in SADC. This is again a reflection that the largest time benefits to passengers
are experienced as the highest commercial risk and lowest return routes (which tend to be those that
bypass hub airports) are added to the route networks of low cost carriers.
R -
R 2,000,000,000.00
R 4,000,000,000.00
R 6,000,000,000.00
R 8,000,000,000.00
R 10,000,000,000.00
R 12,000,000,000.00
R 14,000,000,000.00
R 16,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
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Figure 2.5-6 Marginal benefits from passengers’ time saving
2.5.3.2 Ticket pricing and distances flown per week
Table 2.5-3 below displays the average ticket price per flight, the distance flown per week and the
average distance flown per flight. Each of the columns in Table 2.5-3 has been graphed and this is
displayed in Figures 2.5-7, 2.5-8, and 2.5-9.
Table 2.5-3 Additional flight information Years Average Ticket Price per flight
(2009 Rands) Distance flown per week (km)
Average distance flown per flight (km)
5 R 341.67 13,727,109.91 1,053.99
10 R 285.30 20,009,690.53 884.31
15 R 280.21 20,536,909.37 867.27
20 R 290.54 35,158,912.46 887.89
25 R 452.46 114,571,046.97 1,393.43
30 R 568.86 343,103,208.33 1,736.38
35 R 617.95 627,218,254.45 1,880.01
40 R 625.83 865,880,913.94 1,896.79
45 R 629.87 934,034,723.71 1,909.61
50 R 628.40 948,018,098.80 1,901.88
Figure 2.5-7 shows the average ticket price per flight in constant 2009 Rands. Initially the average ticket
price decreases to R280 and then increases before stabilising at roughly R625. One of the key
R -
R 1,000,000,000.00
R 2,000,000,000.00
R 3,000,000,000.00
R 4,000,000,000.00
R 5,000,000,000.00
R 6,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Year
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determinants of the price of an air ticket is the distance flown. The model predicts that domestic routes
that are by their nature relatively shorter are targeted first as these are commercially less risky.
Figure 2.5-7 Average ticket price per flight
This is confirmed in Figure 2.5-9, where the average distance flown per flight correlates. As more
routes, including international routes that involve longer distances and flying times are added there will
be a associated increase in the average price of air tickets sold in the region. The average air ticket prices
stabilise at around 35 years post implementation of an air transport liberalisation agreement in SADC, as
routes with origins and destinations further apart are added by the low cost airlines. Once these are
added the effects of distance on the average price of air tickets is reflected it is once again moderated.
The total distance flown per week over the 50 year period is reflected in Figure 2.5-8 overleaf.
R -
R 100.00
R 200.00
R 300.00
R 400.00
R 500.00
R 600.00
R 700.00
5 10 15 20 25 30 35 40 45 50
Year
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Figure 2.5-8 Total distance flown per week (km)
Figure 2.5-9 shows the predicted average distance flown per flight throughout SADC over the 50 year
period post implementation of an air transport liberalisation agreement in SADC. Figure 2.5-9 confirms
that initially shorter routes are adopted by low cost airlines; this directly lowers the price of air tickets
and allows airlines to attract new customers. As longer routes are added, it can be seen that the average
distance flown increases and this directly impacts the average price of tickets throughout the region.
The average price of tickets graph rises steeply at first from year 20 to year 30 post implementation of
an air transport liberalisation agreement in SADC and then rises more moderately from year 35 post
implementation.
Figure 2.5-9 Average distance flown per flight (km)
-
100,000,000.00
200,000,000.00
300,000,000.00
400,000,000.00
500,000,000.00
600,000,000.00
700,000,000.00
800,000,000.00
900,000,000.00
1,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Year
-
500.00
1,000.00
1,500.00
2,000.00
2,500.00
5 10 15 20 25 30 35 40 45 50
Year
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Tables 2.5-4 and 2.5-5 below show the direct costs to airlines and the projection of these costs over a 50
year period. In Table 2.5-4, the five direct costs to an airline are listed in the first column. In the second
column, an estimate of the frequency, in terms of how often the airline would incur this cost, is
provided. This is estimated by means of a percentage of the flights within the region over the 50 year
period and then the costs have been calculated to reflect a per week cost to an airlines. For example, if
0.1% of flights in a week are diverted, that cost is estimated by the study team at R32,686.56 per week.
The third column of Table 2.5-4 shows the estimated cost per week in 2009 Rands.
Table 2.5-4 Assumptions, Weights, Proportions and Figures Used COST TO AIRLINES Frequency Cost to an Airline per week (2009 Rands)
Cost of flight cancellation 1.0% R 172,033.02
Cost of flight diversion 0.1% R 32,686.56
Cost of fatality 0.0000321% R 26,378,620.74
Cost of minor injury 0.0000321% R 406,001.38
Cost of major injury 0.0000321% R 5,502,809.67
Table 2.5-5 below shows all the direct costs to airlines over a 50 year period in 2009 Rands. To
determine these costs, the frequency of each cost has been multiplied by the projected number of
flights projected under an air transportation liberalisation agreement, and then multiplied by the
estimated cost in Rands, over the next 50 years. For example, if it is projected that in the next 5 years,
there will be 9649 flights and 1% if those flights will be cancelled, then there will be 96.49 cancelled
flights. If the cost is estimated at R172,033.02 per cancellation, then the cost to airlines of cancellations
in the first 5 years is R16,598,813.09. In Table 2.5-4 above, the most prominent of all costs is the cost of
cancellation. This is not surprising since it is also the cost with the highest predicted frequency of
occurrence. The cost of diversion is the second highest cost, followed by the cost of fatality, major injury
and then minor injury. A graphed comparison of these costs in relation to each other is shown in the
figure overleaf.
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Table 2.5-5 Results Over 50 Year Period
Years Cost of flight cancellations
Cost of flight diversions
Cost of accident resulting in fatality
Cost of minor injury during flight
Cost of major injury during flight
5 R 16,598,813.09 R 315,380.21 R 81,714.64 R 1,257.69 R 17,046.38
10 R 30,904,371.61 R 315,380.21 R 95,086.12 R 1,447.96 R 17,703.70
15 R 32,305,924.57 R 768,932.95 R 199,229.61 R 3,066.40 R 41,561.03
20 R 52,098,054.07 R 1,204,203.34 R 312,007.65 R 4,802.20 R 65,087.51
25 R 101,208,861.28 R 2,207,196.63 R 571,882.02 R 8,802.01 R 119,299.56
30 R 223,961,749.86 R 4,561,179.38 R 1,181,796.15 R 18,189.38 R 246,532.95
35 R 356,211,204.63 R 7,081,209.60 R 1,834,732.98 R 28,238.93 R 382,741.25
40 R 465,155,209.94 R 9,153,406.58 R 2,371,636.76 R 36,502.58 R 494,744.05
45 R 491,444,508.29 R 9,652,907.63 R 2,501,056.88 R 38,494.53 R 521,742.21
50 R 497,433,106.58 R 9,766,691.99 R 2,530,538.28 R 38,948.28 R 527,892.29
Figure 2.5-10 Total Costs to Airlines
Over the 50 year period, the cost of cancelled flights would be the most significant cost to airlines under
an air transportation liberalisation agreement (Figure 2.5-10).
The trend in Table 2.5-5 above follows a distinctive S bend in the curve, in that marginal cost to airlines
will increase over time, reach a peak and then decrease in later years. The graphs of each cost indicate
that the steepest point on all graphs (the point of inflection) is between the 30 year and 35 year mark.
R -
R 100,000,000.00
R 200,000,000.00
R 300,000,000.00
R 400,000,000.00
R 500,000,000.00
R 600,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
Cost of major injury during flight
Cost of minor injury during flight
Cost of accident resulting in fatality
Cost of flight diversions
Cost of flight cancellation
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Even before the costs to airlines are increasing at an increasing rate, in that the difference in cost
between each consecutive year gets bigger. After the inflection point in the graph, the difference in the
cost between consecutive years gets smaller. The reason for the S bend shape is that as the air
transportation liberalisation agreement matures in the SADC region, more flights would be added each
year. For the first 30-35 years of an air transportation liberalisation operation, more flights would be
added in each 5-year period. The flights added in this period will be the most attractive to airlines, and
which will therefore also tend to be the most profitable. In the years after the inflection point (at 30-35
years and beyond) the number of flights added per five year period will tend to be fewer and fewer each
year, as these are the routes that are less popular with airlines, being the less profitable, generally
longer and lower trafficked routes. Because more flights are added in the earlier period, the direct costs
to airlines will also be higher in this period (because the cost to airlines is correlated with the number of
flights undertaken). In the later period, fewer flights added per 5 years will also translate into lower
additional direct cost to airlines in each 5 year period.
Figure 2.5-11 Cost of Flight Cancellation
The cost of flight cancellations is illustrated in Figure 2.5-11 above. The steepest point on the curve is
between 30 and 35 years. This reflects a cost of flight cancellation between R 223.9 million and R 356.2
million respectively.
R -
R 100,000,000.00
R 200,000,000.00
R 300,000,000.00
R 400,000,000.00
R 500,000,000.00
R 600,000,000.00
5 10 15 20 25 30 35 40 45 50
Year
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Figure 2.5-12 Cost of Flight Diversions
The cost of flight diversions is shown above in Figure 2.5-12. As above, the steepest point on the curve is
between 30 and 35 years. This reflects a cost of flight diversions between R 4.5 million and R 7 million
respectively.
Figure 2.5-13 Cost of Accident Resulting in Fatality
The cost of accident resulting in fatality has been illustrated in Figure 2.5-13 above. The S-bend can be
seen clearly in this figure, reaching its steepest point at 30-35 years. This reflects a cost of accident
resulting in fatality between R 1.1 million and R 1.8 million respectively.
R -
R 2,000,000.00
R 4,000,000.00
R 6,000,000.00
R 8,000,000.00
R 10,000,000.00
R 12,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
R -
R 500,000.00
R 1,000,000.00
R 1,500,000.00
R 2,000,000.00
R 2,500,000.00
R 3,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
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Figure 2.5-14 Cost of Accident Resulting in Minor Injury
Figure 2.5-14 shows the cost of accidents resulting in minor injury. The steepest point on the line is
between 30 and 35 years after implementation of an air transport liberalisation agreement in SADC, as
in the previous figure. This reflects a cost of accident resulting in minor injury between R 18,189 and R
28,238 respectively.
Figure 2.5-15 Cost of Accident Resulting in Major Injury
Figure 2.5-15 shows the cost of accidents resulting in major injury. The curve follows the same shape as
previous figures – an S-bend with the steepest point between 30 and 35 years after implementation of
R -
R 5,000.00
R 10,000.00
R 15,000.00
R 20,000.00
R 25,000.00
R 30,000.00
R 35,000.00
R 40,000.00
R 45,000.00
5 10 15 20 25 30 35 40 45 50
Years
R -
R 100,000.00
R 200,000.00
R 300,000.00
R 400,000.00
R 500,000.00
R 600,000.00
5 10 15 20 25 30 35 40 45 50Years
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YD, as in the previous figures. This reflects a cost of accident resulting in major injury between R 0.25
million and R 0.38 million respectively.
Figure 2.5-16 Potential Turnover and Costs to Airlines
The final figure above, Figure 2.5-16, shows these costs in relation to airline turnover. Although the
costs look quite large when graphed alone, relative to turnover, the identified costs are minimal.
However, expect the graph to change after aircraft operational costs are incorporated (this information
was not provided by the airlines.)
2.5.4 Indirect Impacts
2.5.4.1 Tourism Impact Over 50 Years
The SADC airport routes demand forecast model is able to give the impact on tourism, measured as
impact on GDP and impact on Employment, of various routes opening up for different countries at
different times. The below Table 2.5-6 is an aggregate summary of the impact an air transport
liberalisation agreement in SADC would have on the economies of the countries within SADC, from five
years after implementation to fifty years after implementation.
R -
R 5,000,000,000.00
R 10,000,000,000.00
R 15,000,000,000.00
R 20,000,000,000.00
R 25,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
Potential Turnover
Total Costs To Airlines
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Table 2.5-6 Tourism Impact Over 50 Years Tourism impact
Years Total Impact On GDP (2009 Rands)
Direct Impact On GDP (2009 Rands)
Total Impact on Employment
Direct Impact on Employment
5 38 153 667 234 7 552 340 410 18 834 396 2 946 352
10 52 495 280 062 13 205 292 139 20 148 872 3 552 166
15 56 242 018 920 13 673 144 858 22 474 400 3 803 567
20 168 404 489 659 28 251 360 599 96 497 793 11 969 962
25 283 584 702 100 50 738 372 512 153 113 422 20 618 568
30 592 312 694 411 105 672 816 915 292 815 107 42 028 595
35 965 917 528 251 165 457 639 030 479 527 314 70 831 341
40 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448
45 1 398 653 761 279 228 121 055 753 662 282 465 101 085 855
50 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069
The data illustrates that there are four distinct growth periods over the next fifty years in terms of
tourism which will impact GDPs of countries within SADC. For the first fifteen years growth is lower as
few routes would have been opened up or had little time to establish new tourist industries, but as
more routes are enabled growth would pick up between years fifteen and twenty-five. Beyond year
twenty-five these routes would have established new tourism areas and industries, and even more
routes would be opening up leading to the steep growth seen on the following figures. At around year
forty most of the routes that would have been established and given the restraints built into the model
it can be seen that growth slows which could reflect a maturing tourism situation within SADC. Overleaf
is the graphical representation of the total and direct impact on GDP and employment over the fifty
years. Each of the four stages impact data is represented in the following sub-sections.
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Figure 2.5-17 Total and Direct Impact on GDP (2009 Rands)
Figure 2.5-18 Total and Direct Impact on Employment
R -
R 200 000 000 000.00
R 400 000 000 000.00
R 600 000 000 000.00
R 800 000 000 000.00
R 1 000 000 000 000.00
R 1 200 000 000 000.00
R 1 400 000 000 000.00
R 1 600 000 000 000.00
5 10 15 20 25 30 35 40 45 50
Years
Total & Direct Impact on GDP (2009 Rands)
Total Impact On GDP (2009 Rands)
Direct Impact On GDP (2009 Rands)
-
100 000 000
200 000 000
300 000 000
400 000 000
500 000 000
600 000 000
700 000 000
800 000 000
5 10 15 20 25 30 35 40 45 50
Years
Total & Direct Impact of Employment
Total Impact on Employment
Direct Impact on Employment
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2.5.4.1.1 Year 5
Table 2.5-7 below, which has been derived from the routed forecast model, shows the impact that
tourism will have on SADC countries five years after an air transport liberalisation agreement in SADC
has been implemented.
Table 2.5-7 Tourism Impact in Year 5 Countries Routes Total Impact On
GDP (2009 Rands) Direct Impact On GDP (2009 Rands)
Total Impact of Employment
Direct Impact of Employment
Angola 15 22 542 071 514 2 732 989 045 15 303 371 1 618 571
Botswana 7 460 066 146 145 079 268 44 953 19 510
Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928
Lesotho 1 87 726 912 31 076 572 10 485 4 247
Madagascar 5 1 208 731 887 492 479 095 731 726 298 908
Malawi 3 204 833 615 81 897 543 76 255 31 919
Mauritius 3 491 704 994 188 788 352 59 760 25 475
Mozambique 8 1 329 509 622 541 169 345 771 621 319 812
Namibia 0 0 0 0 0
Seychelles 2 347 137 813 142 322 615 39 656 18 154
South Africa 33 5 855 278 401 2 302 594 211 633 534 285 533
Swaziland 0 0 0 0 0
Tanzania 6 945 480 236 385 258 461 571 007 236 433
Zambia 3 92 097 194 32 674 791 31 413 11 540
Zimbabwe 4 120 584 561 46 120 769 19 835 8 322
Total 97 38 153 667 234 7 552 340 410 18 834 396 2 946 352
There would be ninety seven routes opened, thirty three of which would be in South Africa and fifteen
from Angola. The results are distorted due to Angola’s figures, which are much higher than any of the
other countries leading to a shift in the overall impact on tourism. Angola is an oil-producing country
which has benefitted massively from the oil production and increased business being attracted because
of this. The model is suggesting it will be one of the major beneficiaries of air transportation
liberalisation. It also has the effect of skewing forecast data since it is unlikely to have the same level of
economic performance as it has had in recent years; however it is this data which has to be used in
forecasting.
2.5.4.1.2 Year 15
Ten years from an air transport liberalisation agreement in SADC it would be seen that 81 routes would
be expected to have opened up, increasing the impact of tourism on total GDP by R18 billion and on jobs
by 4 million, in SADC. The major differences are between the year five scenario and the year fifteen
scenario, the 73 new routes available to and from South Africa, which would have a major impact on
South Africa’s GDP and employment increasing total impact on GDP almost 4 fold to R20 billion and total
impact of employment almost 3 fold to 1.9 million.
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Table 2.5-8 Tourism Impact in Year 15 Countries Routes Total Impact On
GDP (2009 Rands) Direct Impact On GDP (2009 Rands)
Total Impact of Employment
Direct Impact of Employment
Angola 17 25 828 044 557 3 124 166 392 17 549 572 1 855 239
Botswana 8 509 009 242 158 356 285 49 901 21 590
Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928
Lesotho 1 87 726 912 31 076 572 10 485 4 247
Madagascar 5 1 208 731 887 492 479 095 731 726 298 908
Malawi 3 204 833 615 81 897 543 76 255 31 919
Mauritius 3 491 704 994 188 788 352 59 760 25 475
Mozambique 8 1 329 509 622 541 169 345 771 621 319 812
Namibia 5 411 822 719 63 398 355 74 380 12 653
Seychelles 2 347 137 813 142 322 615 39 656 18 154
South Africa 106 20 196 891 229 7 955 545 940 1 948 009 891 346
Swaziland 0 0 0 0 0
Tanzania 6 945 480 236 385 258 461 571 007 236 433
Zambia 3 92 097 194 32 674 791 31 413 11 540
Zimbabwe 4 120 584 561 46 120 769 19 835 8 322
Total 178 56 242 018 920 13 673 144 858 22 474 400 3 803 567
2.5.4.1.3 Year 25
Twenty five years after the implementation of air transportation liberalisation, there would be a total of
623 routes available to airlines (445 more than the previous scenario). The impact on GDP would have
increased by over five times its level at year fifteen, and employment by an even larger margin.
Table 2.5-9 Tourism Impact in Year 25 Countries Routes Total Impact On
GDP (2009 Rands) Direct Impact On GDP (2009 Rands)
Total Impact of Employment
Direct Impact of Employment
Angola 176 206 275 515 037 26 296 691 304 137 284 187 14 687 694
Botswana 67 6 197 312 531 2 229 768 612 650 991 285 051
Democratic Republic of Congo 25 17 354 854 704 1 697 127 175 2 092 519 264 345
Lesotho 2 177 302 632 62 808 070 21 191 8 583
Madagascar 23 5 171 444 341 2 099 346 216 2 947 490 1 205 281
Malawi 9 735 139 917 292 620 305 208 890 88 334
Mauritius 19 3 203 946 435 1 279 421 571 415 698 185 774
Mozambique 37 5 900 823 034 2 392 080 268 3 052 249 1 268 299
Namibia 71 7 028 653 501 1 886 638 075 971 494 254 526
Seychelles 15 2 499 592 802 1 024 805 052 285 548 130 721
South Africa 156 26 327 026 112 10 380 713 543 3 619 753 1 594 586
Swaziland 0 0 0 0 0
Tanzania 15 2 468 401 787 1 006 351 685 1 500 286 621 194
Zambia 4 124 104 705 43 879 868 43 292 15 857
Zimbabwe 4 120 584 561 46 120 769 19 835 8 322
Total 623 283 584 702 100 50 738 372 512 153 113 422 20 618 568
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A significant difference between this scenario and the previous is that ten of the fourteen countries
would have had a significant increase in the number of routes opened up, which would result in the
steep increase in the impact from this scenario to the next (year forty).
This could be due to the fact that other SADC countries (other than South Africa) would require a
significantly higher level of investment in infrastructure in order to let certain routes open up. Since the
number of routes within this analysis is based on the factors set out by the routes demand forecast
model, it is clear that by twenty five years after implementation of an air transport liberalisation
agreement in SADC these factors would have all improved to a level that tourism within SADC would
have a widespread impact.
2.5.4.1.4 Year 40
Table 2.5-10 Tourism Impact in Year 40 Countries Routes Total Impact On GDP
(2009 Rands) Direct Impact On GDP (2009 Rands)
Total Impact of Employment
Direct Impact of Employment
Angola 1 086 840 729 260 494 110 081 377 944 530 634 836 60 918 028
Botswana 276 36 180 665 295 8 039 926 585 7 650 628 2 500 990
Democratic Republic of Congo 640 274 261 929 632 33 068 514 393 39 027 428 7 328 414
Lesotho 49 3 326 557 540 1 124 708 069 1 179 321 462 570
Madagascar 244 39 294 600 212 15 655 428 090 22 254 205 9 058 674
Malawi 90 5 865 157 643 2 243 125 495 2 614 027 1 065 563
Mauritius 47 6 852 074 474 2 699 642 431 1 394 296 593 033
Mozambique 352 42 555 722 679 16 687 713 112 19 760 528 8 130 856
Namibia 260 22 798 196 513 6 712 238 710 4 728 699 1 571 337
Seychelles 29 4 124 427 991 1 698 478 633 714 190 313 647
South Africa 310 42 777 340 455 16 879 369 876 7 688 656 3 318 649
Swaziland 12 559 326 724 197 665 089 262 611 107 940
Tanzania 52 5 327 530 384 2 153 568 234 3 088 480 1 274 761
Zambia 16 414 380 714 149 128 603 127 870 47 630
Zimbabwe 5 150 076 178 57 400 621 24 686 10 358
Total 3 468 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448
The routes open would have increased by 2845 and the impact on the economies of the SADC countries
would have increased by a large amount from year 25, as can be seen in Table 2.5-10.
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2.5.4.1.5 Year 50
Table 2.5-11 Tourism Impact in Year 50 Countries Routes Total Impact On
GDP (2009 Rands) Direct Impact On GDP (2009 Rands)
Total Impact of Employment
Direct Impact of Employment
Angola 1 123 862 950 838 267 112 675 025 388 543 271 426 62 293 308
Botswana 280 36 270 819 793 8 067 334 439 7 669 855 2 508 281
Democratic Republic of Congo 815 330 399 812 171 40 350 699 246 49 313 945 9 817 931
Lesotho 54 3 524 207 131 1 191 180 670 1 269 359 498 283
Madagascar 265 41 633 774 979 16 606 041 230 23 760 119 9 673 330
Malawi 96 5 982 259 593 2 289 193 433 2 689 300 1 096 182
Mauritius 48 6 923 003 100 2 727 923 957 1 405 943 598 009
Mozambique 381 44 448 322 970 17 438 104 141 20 800 309 8 557 940
Namibia 273 23 214 179 360 6 802 166 393 4 815 759 1 593 254
Seychelles 30 4 189 945 857 1 725 545 242 725 092 318 304
South Africa 321 43 445 362 666 17 137 934 573 7 779 967 3 356 839
Swaziland 14 590 922 702 206 202 692 267 877 109 959
Tanzania 62 5 919 157 876 2 390 848 574 3 417 929 1 410 268
Zambia 20 475 776 685 171 648 848 144 106 53 824
Zimbabwe 5 150 076 178 57 400 621 24 686 10 358
Total 3 787 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069
Table 2.5-11 displays the impact increased tourism as a result of an air transport liberalisation
agreement would have on SADC in the final year of the forecast. There would be 3787 routes open, and
the impact on GDP and Employment in the region would have increased greatly over the fifty year
period.
2.5.4.2 Impact of Atmospheric Pollution, Noise Pollution and Security Over 50 Years
Three major indirect costs were highlighted in this study. An air transportation liberalisation policy will
increase atmospheric pollutants in the air, create more noise pollution and increase the burden of
security at airports. These costs have been calculated using the impact model and the results are shown
in Table 2.5-12. The calculations for the units used in the model are discussed in Section 2.4.3. The
results are in Table 2.4-10.
In the US the Federal Aviation Agency defines airline noise pollution as that which is loud enough to
disturb a family watching television. This definition is used to define noise pollution in this study as well.
Noise pollution impacts on property values and quality of life. The Eurocontrol measure of noise
pollution places it at R693 per takeoff and landing and as air transportation liberalisation policy takes
effect the impact will increase significantly over time, reaching R345m per annum in fifty years from
implementation. The short term (5 year) impact is rather small at R8,8m per annum and relatively
insignificant in terms of the overall positive impact.
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Table 2.5-12 Cost of Pollution and Security
Figure 2.5-19 Cost of Noise Pollution
Aircraft pollution from emissions is an emotive issue as people often have the perception that
aeroplanes are large contributors to CO2 emissions. However, currently aircraft atmospheric emissions
(70% of which are CO2) contribute only 3% of EU total CO2 emissions. The total calculated cost of
pollution in the fifth year of air transportation liberalisation implementation is R8,9m rising steadily with
an exponential increase from the 17th year as the impact of an air transportation liberalisation policy
takes effect. The total cost of pollution increases to R645m at the fifty year mark as total flying hours
R -
R 50,000,000.00
R 100,000,000.00
R 150,000,000.00
R 200,000,000.00
R 250,000,000.00
R 300,000,000.00
R 350,000,000.00
R 400,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
Indirect Costs
Years Cost of Pollution Cost of noise pollution Cost of Security
5 R 8,913,136.87 R 8,843,296.00 R 44,638,920.25
10 R 13,051,507.63 R 15,498,560.00 R 77,498,800.90
15 R 13,398,789.61 R 16,227,904.00 R 80,718,169.30
20 R 23,030,384.28 R 27,259,232.00 R 132,556,756.40
25 R 75,339,598.46 R 56,797,664.00 R 306,044,392.79
30 R 225,875,002.76 R 136,752,000.00 R 753,253,360.05
35 R 413,023,162.06 R 231,019,712.00 R 1,247,466,816.32
40 R 570,231,581.77 R 316,170,624.00 R 1,656,004,413.96
45 R 615,124,874.90 R 338,780,288.00 R 1,754,588,698.25
50 R 624,335,801.75 R 345,253,216.00 R 1,777,045,808.69
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increase. This total is nearly double that of the noise pollution total as the calculation is based on flying
hours and not number of flights.
Figure 2.5-20 Cost of Pollution
Currently most security costs are carried by the carrier airlines and vary between international flights
(R53.76) and domestic flights (R32.93). These costs are based on the Australian costing model and are
per passenger. Not all costs are carried by airlines and some of the total spending would be a burden of
the state where the flights originate and end. Airline security is a national security interest. Airport
security costs as a result of air transportation liberalisation policy will rise to R1,8bn in the fiftieth year,
and as such will become a large industry as a result of the air transportation liberalisation policy across
the SADC region. Even in the fifth year a boost of R45m into regional airports will contribute significantly
to employment. An increase in airport security costs will be good for the economy as it will lead to
increased spending on employment.
R -
R 100,000,000.00
R 200,000,000.00
R 300,000,000.00
R 400,000,000.00
R 500,000,000.00
R 600,000,000.00
R 700,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
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Figure 2.5-21 Cost of Security
Whilst the security costs will be the largest contributor to indirect costs it is the easiest one to quantify.
The true cost of noise and fuel burning pollution could be much higher. From a fairly modest level of
R63m in the fifth year, indirect costs from an air transportation liberalisation policy will balloon up to
R2,7bn at current prices by the fiftieth year of operation.
R -
R 200,000,000.00
R 400,000,000.00
R 600,000,000.00
R 800,000,000.00
R 1,000,000,000.00
R 1,200,000,000.00
R 1,400,000,000.00
R 1,600,000,000.00
R 1,800,000,000.00
R 2,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
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Figure 2.5-22 Total Indirect Costs
2.5.5 Airport and navigational infrastructure
2.5.5.1 Navigational infrastructure per route
As discussed in the methodology we can estimate the cost of navigational infrastructure required per
route at flight level 145 and 195. The weekly costs for this infrastructure is displayed in Table 2.5-13
below, as can be observed the weekly costs exceed R 1 billion after 50 years as the number of routes
being flown increases. The weekly cost of navigational infrastructure per route has been graphically
represented by Figure 2.5-23. The graph once again adopts the s bend curve that is present in all the
graphs before.
R -
R 500,000,000.00
R 1,000,000,000.00
R 1,500,000,000.00
R 2,000,000,000.00
R 2,500,000,000.00
R 3,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
Cost of Security
Cost of noise pollution
Cost of Pollution
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Table 2.5-13 Weekly cost navigational infrastructure per route Years Flight Level 145 Flight Level 195
5 R 20,021,153.85 R 16,192,628.21
10 R 30,307,051.28 R 27,660,512.82
15 R 31,258,269.23 R 29,897,051.28
20 R 53,547,307.69 R 50,750,128.21
25 R 162,721,282.05 R 141,441,858.97
30 R 473,688,910.26 R 384,301,410.26
35 R 858,029,358.97 R 683,673,269.23
40 R 1,184,967,692.31 R 937,951,794.87
45 R 1,277,056,025.64 R 1,009,440,641.03
50 R 1,296,504,038.46 R 1,024,944,166.67
Figure 2.5-23 Weekly cost navigational infrastructure per route
2.5.5.2 Airport navigational infrastructure
All the results up to this point have been exhibited as per route weekly costs. In order to correctly
estimate the cost of airport navigational infrastructure and the cost of airport expansions to increase
airport capacity we’ve calculated these costs annually and per airport. These results are to be viewed
separately from previous results, and will be brought in line with other results in sections to come.
R -
R 200,000,000.00
R 400,000,000.00
R 600,000,000.00
R 800,000,000.00
R 1,000,000,000.00
R 1,200,000,000.00
R 1,400,000,000.00
5 10 15 20 25 30 35 40 45 50
Flight Level 145
Flight Level 195
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Figure 2.5-24 below displays the cost of airport navigational infrastructure over the 50 year period. As
the number of origin and destination airports increase, the costs for navigational infrastructure at the
various airports in the SADC region are required.
Figure 2.5-24 Airport navigational infrastructure
Table 2.5-14 displays the total airport navigational infrastructure costs over the 50 year forecast. The
cost are higher at airports with higher passenger numbers. It can be seen that in excess of R 12 billion
(2009 Rands) would be required to cover the airports navigational infrastructure costs over the 50 year
period.
R 1,130,000,000.00
R 1,140,000,000.00
R 1,150,000,000.00
R 1,160,000,000.00
R 1,170,000,000.00
R 1,180,000,000.00
R 1,190,000,000.00
R 1,200,000,000.00
R 1,210,000,000.00
R 1,220,000,000.00
R 1,230,000,000.00
5 10 15 20 25 30 35 40 45 50
Airport Navigational Infrastructure
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Table 2.5-14 Airport Navigational Infrastructure Location Airport Navigational
Infrastructure Location Airport
Navigational Infrastructure
Location Airport Navigational Infrastructure
Cabinda R 105,500,000.00 Mbuji-Mayi R 21,666,666.67 Durban R 521,500,000.00
Catumbela R 105,500,000.00 Maseru R 105,500,000.00 George R -
Dundo R - Antanànarìvo R 521,500,000.00 Lanseria R 105,500,000.00
Huambo R 21,666,666.67 Mahajanga R 105,500,000.00 Johannesburg R 521,500,000.00
Kuito R 21,666,666.67 Nosy Be R 13,000,000.00 Kimberley R 105,500,000.00
Luanda R 521,500,000.00 Toamasina R 105,500,000.00 Mafikeng R 21,666,666.67
Lubango R 21,666,666.67 Toliara R 21,666,666.67 Nelspruit R 105,500,000.00
Luena R 21,666,666.67 Blantyre R 105,500,000.00 Polokwane R 21,666,666.67
Malanje R 21,666,666.67 Lilongwe R 521,500,000.00 Port Elizabeth R 105,500,000.00
Menongue R 21,666,666.67 Port Louis R 521,500,000.00 Pilanesberg R 19,500,000.00
Namibe R 21,666,666.67 Beira R 105,500,000.00 Umtata R 21,666,666.67
Ondjiva R 21,666,666.67 Chimoio R 15,166,666.67 Upington R 105,500,000.00
Saurimo R 21,666,666.67 Cuamba R 13,000,000.00 Welkom R 19,500,000.00
Soyo R 21,666,666.67 Lichinga R 105,500,000.00 Manzini R 105,500,000.00
Uíge R 17,333,333.33 Maputo R 521,500,000.00 Dar-Es-Salaam
R 521,500,000.00
Francistown R 105,500,000.00 Moçimboa da Praia R 105,500,000.00 Dodoma R 105,500,000.00
Gaborone R 521,500,000.00 Mueda R 13,000,000.00 Kilimanjaro R 105,500,000.00
Kasane R 21,666,666.67 Nampula R 105,500,000.00 Mtwara R 21,666,666.67
Maun R 105,500,000.00 Tete R 21,666,666.67 Mwanza R 21,666,666.67
Bukavu R 13,000,000.00 Grootfontein R 84,400,000.00 Zanzibar R 521,500,000.00
Buta-Zega R 13,000,000.00 Karabib R 15,166,666.67 Kitwe R -
Gbadolite R 21,666,666.67 Katima Mulilo R 17,333,333.33 Livingstone R 105,500,000.00
Gemena R 13,000,000.00 Keetmanshoop R 17,333,333.33 Lusaka R 521,500,000.00
Goma R 13,000,000.00 Mariental R 15,166,666.67 Mfuwe R 8,666,666.67
Isiro-Matari R 13,000,000.00 Ondangwa R 17,333,333.33 Ndola R 21,666,666.67
Kananga R 13,000,000.00 Rundu R 17,333,333.33 Bulawayo R 105,500,000.00
Kindu R 13,000,000.00 Windhoek R 521,500,000.00 Harare R 521,500,000.00
Kinshasa R 521,500,000.00 Seychelles R 521,500,000.00 Hwange R 21,666,666.67
Kisangani R 105,500,000.00 Bisho R 105,500,000.00 Victoria Falls R 105,500,000.00
Lubumbashi R 105,500,000.00 Bloemfontein R 105,500,000.00 TOTAL R 12,076,400,000.00
Mbandaka R 13,000,000.00 Cape Town R 521,500,000.00
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2.5.5.3 Airport Infrastructure Costs
As explained in the previous section airport infrastructure costs have been reported per airport
displaying all costs incurred over the 50 year period. The airport infrastructure costs have been pegged
to the forecasted number of passengers per airport over the 50 year period. When the number of
forecasted passengers exceeds the airports annual capacity, the airport infrastructure costs are incurred
(the cost ratio applied for addition infrastructure is one million additional passenger capacity is the
equivalent of R 600 million spend on airport infrastructure.) Figure 2.5-25 displays the escalation of
airport infrastructure costs over the 50 year period as additional routes are added thereby increasing
the number of passengers utilising air transport as it becomes increasingly cheaper to fly and as flights
become more direct.
Figure 2.5-25 Airport Infrastructure Costs
Table 2.5-15 below indicates the total investment required in airport infrastructure over the 50 year
period per airport. It can be seen that mostly the South African airports require the largest investment
over the 50 year period; this is due to the higher demand for flights from other SADC regions to South
Africa, as business and leisure activities are more developed and available when compared to other
SADC partners. Interestingly Lanseria Airport in Johannesburg requires the largest investment in airport
infrastructure to take advantage of all the added demand for flights in and out of the
Johannessburg/Pretoria area.
R -
R 100,000,000,000.00
R 200,000,000,000.00
R 300,000,000,000.00
R 400,000,000,000.00
R 500,000,000,000.00
R 600,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Year
Airport Infrastructure Costs
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Table 2.5-15 Airport Infrastructure Costs Location Airport Infrastructure
Costs Location Airport Infrastructure
Costs Location Airport Infrastructure Costs
Cabinda R 30,762,646,164.32 Mbuji-Mayi R 24,753,794,341.17 Durban R 38,705,155,564.19
Catumbela R 21,704,608,870.95 Maseru R 15,845,658,240.17 George R -
Dundo R - Antanànarìvo R 8,121,960,885.89 Lanseria R 50,916,414,646.06
Huambo R 32,799,705,107.64 Mahajanga R 16,996,112,278.87 Johannesburg R -
Kuito R 31,326,914,030.96 Nosy Be R 21,804,839,914.27 Kimberley R 44,083,043,709.13
Luanda R 14,454,353,582.72 Toamasina R 19,094,988,395.56 Mafikeng R 40,811,869,973.20
Lubango R 31,374,951,738.71 Toliara R 22,937,552,849.95 Nelspruit R 42,677,327,210.89
Luena R 27,386,961,412.25 Blantyre R 17,641,591,388.30 Polokwane R 42,265,713,353.11
Malanje R 31,857,532,088.63 Lilongwe R 6,055,562,817.46 Port Elizabeth R 41,889,245,560.08
Menongue R 30,677,820,412.50 Port Louis R 12,345,883,086.00 Pilanesberg R 40,046,339,330.98
Namibe R 31,967,122,412.18 Beira R 20,113,697,084.71 Umtata R 40,306,034,452.31
Ondjiva R 29,117,281,210.36 Chimoio R 23,705,642,728.46 Upington R 42,797,693,603.02
Saurimo R 30,955,943,213.46 Cuamba R 21,423,216,316.07 Welkom R 42,529,814,312.88
Soyo R 29,976,647,083.97 Lichinga R 23,590,797,888.70 Manzini R 17,821,283,568.37
Uíge R 30,352,589,997.88 Maputo R 7,783,416,063.19 Dar-Es-Salaam R 8,424,782,414.41
Francistown R 35,135,585,164.11 Moçimboa da Praia
R 19,933,260,259.03 Dodoma R 24,775,748,996.14
Gaborone R 11,489,436,347.38 Mueda R 19,705,744,750.39 Kilimanjaro R 21,088,863,923.42
Kasane R 27,894,701,088.10 Nampula R 20,528,698,093.77 Mtwara R 24,211,283,509.89
Maun R 26,245,742,033.60 Tete R 23,765,714,787.34 Mwanza R 27,957,419,377.31
Bukavu R 20,836,679,462.91 Grootfontein R 21,432,237,428.37 Zanzibar R 27,027,185,020.59
Buta-Zega R 18,670,970,710.90 Karabib R 24,282,126,980.62 Kitwe R -
Gbadolite R 19,005,255,956.46 Katima Mulilo R 28,014,954,576.04 Livingstone R 18,800,111,355.35
Gemena R 21,174,304,236.40 Keetmanshoop R 28,306,690,156.58 Lusaka R 8,921,260,503.81
Goma R 21,571,107,574.57 Mariental R 27,107,878,848.06 Mfuwe R 8,502,307,048.99
Isiro-Matari R 21,672,433,830.73 Ondangwa R 27,454,733,325.99 Ndola R 27,766,951,019.44
Kananga R 23,874,821,942.88 Rundu R 29,184,572,232.87 Bulawayo R 23,414,456,927.59
Kindu R 21,663,633,278.31 Windhoek R 9,559,680,304.59 Harare R 6,518,897,872.57
Kinshasa R 8,183,067,356.52 Seychelles R 8,749,277,162.18 Hwange R 17,155,638,948.89
Kisangani R 17,332,241,664.06 Bisho R 38,724,314,820.06 Victoria Falls R 10,761,251,323.26
Lubumbashi R 19,548,909,955.13 Bloemfontein R 42,568,700,235.46 TOTAL R 2,133,076,262,959.25
Mbandaka R 22,957,803,412.03 Cape Town R 19,395,099,852.65
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2.6 Impact of an air transport liberalisation agreement in the Southern
African Development Community (SADC)
In this section of the report the focuses on the overall impact of implementing an air transport
liberalisation agreement in SADC.
2.6.1 Total Computable Benefits
Table 2.6-1 below shows the total computable benefits (in constant 2009 Rands) arising from
implementation of an air transport liberalisation agreement in SADC. It can be seen that initially the
total computable benefit occurring throughout SADC equals R 8 billion per week. After 50 years this
would grow to R 265 billion per week. In calculating total impact of an air transport liberalisation
agreement on SADC, the direct impact of tourism on GDP was used as this captures the direct impact
felt by the tourism industry as the number of passengers using air travel increase over the 50 year
period.
Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC
Years* BENEFITS
Potential Turnover Time Saving (Rand per KM)
Direct Impact On GDP (2009 Rands)
TOTAL BENEFITS
5 R 395,592,569.17 R 80,704,142.39 R 7,552,340,410.36 R 8,028,637,121.92
10 R 615,030,014.60 R 148,353,788.17 R 13,205,292,139.30 R 13,968,675,942.07
15 R 631,437,961.30 R 152,429,875.57 R 13,673,144,858.21 R 14,457,012,695.08
20 R 1,055,829,325.19 R 265,108,382.22 R 28,251,360,598.84 R 29,572,298,306.25
25 R 3,194,221,298.65 R 766,732,401.87 R 50,738,372,511.99 R 54,699,326,212.51
30 R 8,886,816,358.07 R 2,961,410,846.08 R 105,672,816,915.10 R 117,521,044,119.25
35 R 15,354,301,000.26 R 7,207,220,265.68 R 165,457,639,030.49 R 188,019,160,296.43
40 R 20,306,047,606.09 R 12,429,642,407.48 R 217,448,285,885.45 R 250,183,975,899.02
45 R 21,592,032,312.26 R 13,703,434,148.72 R 228,121,055,753.45 R 263,416,522,214.43
50 R 21,804,364,460.93 R 13,957,174,567.04 R 229,837,249,446.98 R 265,598,788,474.95
*post implementation of an air transport liberalisation agreement in SADC
Figure 2.6-1 exhibits the breakdown of total benefit incurred by the implementation of an air transport
liberalisation agreement in SADC. It can be seen that the largest contributor to total benefits is the
impact on the tourism industry followed by the benefit accruing to airlines. The passengers benefit due
to time saving is relatively minimal, however if the anticipated general decrease in airline ticket prices
was quantifiable and was taken into account this would increase the benefits considerably.
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Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC
R -
R 50,000,000,000.00
R 100,000,000,000.00
R 150,000,000,000.00
R 200,000,000,000.00
R 250,000,000,000.00
R 300,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Year
Direct Impact On GDP (2009 Rands)
Time Saving (Rand per KM)
Potential Turnover
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2.6.2 Total Costs
The breakdown of total computable costs arising from the implementation of an air transport liberalisation agreement in SADC is shown in Table
2.6-2 below. When both direct and indirect costs are totalled initially cost incurred total R 99 million per week, this increases to R 4.5 billion per
week after 50 years.
Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight
cancellation Cost of flight diversions
Cost of accident resulting in fatality
Cost of minor injury during flight
Cost of major injury during flight
Cost of Pollution
Cost of noise pollution
Cost of Security Navigation Route Costs (FL 145)
TOTAL COSTS
5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719
10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421
15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847
20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835
25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979
30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721
35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177
40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812
45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596
50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042
*post implementation of an air transport liberalisation agreement in SADC
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As can be seen in Figure 2.6-2, below, the cost of navigational infrastructure per route, security,
pollution, noise pollution and flight cancellation make up the largest proportions of total costs incurred.
Due to low proportion of aircraft accidents and injuries, the cost of accidents resulting in fatality, minor
injury and major injury per flight is relatively inconsequential. Likewise the cost of diverting a flight is
slight due to infrequency of such flights.
Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC
2.6.3 Impact of an air transport liberalisation agreement in the Southern African
Development Community
The impact of implementation of an air transport liberalisation agreement in SADC is overwhelming
positive when one considers the total benefits and costs computed in Table 2.6-1 and 2.6-2 above. It
must be noted that aircraft operational costs have been excluded due to lack of information provided by
airlines. Computable benefits are larger than computable costs by a factor ranging between 1000 during
the first five year period to 78 at the end of the 50 year modelling period. This is because the existence
of excess capacity in aviation infrastructure within SADC at the start of the implementation process
keeps initial costs relatively modest. The required investment to sustain implementation of an air
transport liberalisation agreement in SADC also grows substantially over the 50 year study period.
Nevertheless the net benefit at the end of the 50 year study period still totals a very significant R249.7
billion per week, growing from an initial net benefit totalling R7.8 billion per week during the first 5
years post the an air transport liberalisation agreement implementation. This would indicate that over
a 50 year period the net benefit would grow at a real rate of 7.98% annually, an annual real growth rate
R -
R 500,000,000
R 1,000,000,000
R 1,500,000,000
R 2,000,000,000
R 2,500,000,000
R 3,000,000,000
R 3,500,000,000
R 4,000,000,000
R 4,500,000,000
R 5,000,000,000
5 10 15 20 25 30 35 40 45 50
Year
Navigation Route Costs (FL 145)
Cost of Security
Cost of noise pollution
Cost of Pollution
Cost of major injury during flight
Cost of minor injury during flight
Cost of accident resulting in fatality
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somewhat higher than the annual real GDP growth currently anticipated and experienced in SADC. In
2009 the SADC Gross Domestic Product was estimated at R 4.4 trillion12 . At this level the aviation
industry would be contributing 0.18% of total GDP (2009 Rands) in the first 5 years post an air transport
liberalisation agreement implementation and 5.64% of total GDP (2009 Rands) post 50 years of an air
transport liberalisation agreement implementation.
Figure 2.6-3 below, graphs the total computable impact of an air transport liberalisation agreement in
SADC over the 50 year period. It can be seen that total costs (in red) are slight in comparison to total
benefits (in blue). The net computable benefits comprise the blue area alone. The total computable
benefits are signified by the red and blue areas put together, while the red area alone indicates total
computable costs.
Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in the Southern African Development community
12 International Monetary Fund, 2007. http://www.imf.org/external/pubs/ft/weo/2007/02/weodata/index.aspx
R -
R 50,000,000,000.00
R 100,000,000,000.00
R 150,000,000,000.00
R 200,000,000,000.00
R 250,000,000,000.00
R 300,000,000,000.00
5 10 15 20 25 30 35 40 45 50
Years
TOTAL BENEFITS
TOTAL COSTS
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2.7 Impact of an air transport liberalisation agreement reflecting the
investment and capital expenditure in airport and navigational
infrastructure
Table 2.7-1 below displays the total impact of air transport liberalisation over the 50 year period per
airport. The benefit less costs column takes into account all the weekly benefits less costs mentioned in
previous sections, this displays the impact per airport. The airport infrastructure costs indicate the total
cost of expanding annual passenger capacities over the 50 year period per airport. The airport
navigational systems column display the total cost of navigational infrastructure per airport over the 50
year period. The last column ‘Total impact after infrastructure costs’ measures the financial impact of air
transport liberalisation in SADC when taking into account all capital and infrastructural investments
required to take advantage of this liberalisation.
Most importantly there are 5 airports that have a negative impact over the 50 year period; these
airports are Cabinda, Catumbela, Huambo and Kuito from Angola; and Kitwe from Zambia. Although
these airports have a negative impact over the 50 year period, the total impact in the region is
overwhelmingly positive, even when taking into account the additional airport and navigational
infrastructural requirements. For a comprehensive and detailed list of impacts over the 50 year period
per airport please refer to Appendix G.
Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport
infrastructure Airport navigational systems
Total impact after infrastructure costs
Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288
Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492
Dundo R - R - R - R -
Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703
Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227
Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601
Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471
Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724
Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245
Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591
Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150
Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695
Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126
Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072
Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524
Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539
Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231
Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838
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Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482
Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622
Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118
Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459
Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852
Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857
Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789
Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255
Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127
Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582
Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224
Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952
Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731
Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576
Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984
Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392
Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962
Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001
Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493
Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915
Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904
Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469
Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466
Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448
Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776
Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105
Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016
Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071
Moçimboa da Praia
R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085
Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631
Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935
Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812
Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814
Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929
Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458
Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115
Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521
Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379
Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501
Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578
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Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462
Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847
Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766
Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539
Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959
George R - R - R - R -
Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229
Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969
Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808
Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627
Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189
Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465
Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311
Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507
Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786
Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693
Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194
Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927
Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976
Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566
Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871
Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588
Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426
Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528
Kitwe R -770,778,388 R - R - R -770,778,388
Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937
Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427
Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300
Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446
Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191
Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338
Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837
Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462
TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266
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Conclusion
There is overwhelming evidence that implementation of an air transport liberalisation agreement in
SADC will produce significant and sustainable benefits to the economy of the region (even when the
additional infrastructural requirements are taken into account.) The forecast growth in the aviation
market and tourism markets together with the wider economic benefits that will flow from this are so
vast and far reaching that not only are the computable costs to be regarded as insignificant (when
excluding the aircrafts operational costs), but in all likelihood, it can be considered that the
unquantifiable costs identified as associated with such an initiative will, similarly, be no obstacle to
success.
Based on the results discussed in this study an air transport liberalisation agreement in the Southern
African Development Community would have an overwhelming impact in this region. It would
encourage and stimulate tourism and the numbers of passengers utilising air transport as a primary
means of transport between two major cities in SADC would increase significantly. The only potential
inhibitor to this agreement would be the additional navigational and airport infrastructure required to
make an agreement such as this successful, this would need to be funded by airports authorities or
governments in the region. Furthermore, the establishment of a regional regulatory and competition
authority is essential to monitor the implementation of this agreement and ensure that no country or
airlines acts in an uncompetitive manner.
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References
List of References
World Trade and Tourism Website
o http://www.wttc.org/
o http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_research_metho.pdf
Source for pollutant volumes: “Forecasting Civil Aviation Fuel Burn and Emissions in Europe, EEC
Note No. 8/2001”, EUROCONTROL Experimental Centre, May 2001
http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note
_2001_08.pdf
Source for cost of pollutants: “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”, CE, Solutions for environment, economy and technology, Delft, The Netherlands. Draft preliminary study, 2 May 2001 suggests the medium costs of aviation pollution as follows:
Source for Burn Rate: “Evaluating the true cost to airlines of one minute of airborne or ground delay”, University of Westminster, May 2004
(http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf)
Type here (replace this text)
Conversions are based on the following websites
Australian Dollar (AUD) inflation
http://www.rateinflation.com/consumer-price-index/australia-historical-cpi.php?form=auscpi
Australian Dollar - South African Rand (AUD-ZAR) exchange rate history
http://www.exchangerates.org.uk/AUD-ZAR-exchange-rate-history.html
Average for last 150 days (from 5 March, back 150 days)
Euro inflation
http://www.ecb.europa.eu/stats/prices/hicp/html/inflation.en.html
Euro – South African Rand (EUR-ZAR) exchange rate history
http://www.exchangerates.org.uk/EUR-ZAR-exchange-rate-history.html
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Average for last 150 days (from 14 March, back 150 days)
Bureau of Transportation Statistics
http://www.bts.gov/press_releases/2003/dot016_03.html
“The consumer report includes BTS data on the number of domestic flights cancelled by the reporting carriers. In
January, the carriers cancelled 2.5 percent of their scheduled domestic flights, higher than the 2.3 percent rate
recorded in January 2009 but lower than December 2009's rate of 2.8.”
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List of Tables
Table 1.1-1 Definition of air freedom rights ................................................................................................ vi
Table 1.1-2 Total number of domestic and international airline passengers, by region ............................ vii
Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement
in SADC ....................................................................................................................................................... xvii
Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in
SADC ............................................................................................................................................................ xix
Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport .............. xxii
Table 1.2-1 Definition of air freedom rights ................................................................................................. 4
Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002 .......................................................... 21
Table 1.5-2 Summary of Intra-EU transport packages ................................................................................ 21
Table 1.5-3 : Capacity Shares of Low Cost Carriers ..................................................................................... 22
Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons ........... 24
Table 1.6-1 Section analysis of regression on transport costs .................................................................... 28
Table 1.6-2 Forecasts in North-East Asian travel to North America ........................................................... 31
Table 2.2-1 Airports in SADC – Total Passengers ........................................................................................ 64
Table 2.3-1 Airlines Data ............................................................................................................................. 70
Table 2.3-2 Airports Data ............................................................................................................................ 74
Table 2.3-3 Stakeholders Data .................................................................................................................... 77
Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices ....................................................... 83
Table 2.4-2 Urban Population by Country .................................................................................................. 84
Table 2.4-3 Business, Political and Development Indicators for SADC Country ......................................... 85
Table 2.4-4 Tourism Infrastructure Index by Country ................................................................................ 86
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Table 2.4-5 Airport Infrastructure ............................................................................................................... 86
Table 2.4-6 Example of Calculated Indices by Airport ................................................................................ 90
Table 2.4-7 Determining the Demand Estimate for Routes ........................................................................ 91
Table 2.4-8 Potential Turnover and Seat Numbers .................................................................................... 94
Table 2.4-9 The Monetary Value of Costs ................................................................................................... 97
Table 2.4-10 Cost of Fuel .......................................................................................................................... 100
Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM ................................................ 103
Table 2.4-12 Airport Navigational Equipment Required per Airport Type ............................................... 103
Table 2.4-13 Type 1 Airports in the SADC Region ..................................................................................... 104
Table 2.4-14 Type 2 Airports in the SADC Region ..................................................................................... 104
Table 2.4-15 Type 3 Airports in the SADC Region ..................................................................................... 105
Table 2.4-16 SADC Airport Capacities ....................................................................................................... 106
Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week) .................................. 107
Table 2.5-2 Passenger Time Saving Benefit .............................................................................................. 111
Table 2.5-3 Additional flight information ................................................................................................. 113
Table 2.5-4 Assumptions, Weights, Proportions and Figures Used .......................................................... 116
Table 2.5-5 Results Over 50 Year Period ................................................................................................... 117
Table 2.5-6 Tourism Impact Over 50 Years ............................................................................................... 122
Table 2.5-7 Tourism Impact in Year 5 ....................................................................................................... 124
Table 2.5-8 Tourism Impact in Year 15 ..................................................................................................... 125
Table 2.5-9 Tourism Impact in Year 25 ..................................................................................................... 125
Table 2.5-10 Tourism Impact in Year 40 ................................................................................................... 126
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Table 2.5-11 Tourism Impact in Year 50 ................................................................................................... 127
Table 2.5-12 Cost of Pollution and Security .............................................................................................. 128
Table 2.5-13 Weekly cost navigational infrastructure per route .............................................................. 132
Table 2.5-14 Airport Navigational Infrastructure ..................................................................................... 134
Table 2.5-15 Airport Infrastructure Costs ................................................................................................. 136
Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC
.................................................................................................................................................................. 137
Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in
SADC .......................................................................................................................................................... 139
Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport .... 142
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List of Figures
Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport
liberalisation agreement in SADC ............................................................................................................. xviii
Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation
agreement in SADC ...................................................................................................................................... xx
Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the
Southern African Development community ............................................................................................... xxi
Figure 1.3-1 South African Airways International Route Map ...................................................................... 6
Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly ........................................................... 8
Figure 1.3-3 Total number of domestic and international airline passengers, by region .......................... 11
Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs .................................... 12
Figure 1.4-1 Gravity forecast fails to fit actual data, European Region ...................................................... 17
Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers ...................................................... 19
Figure 1.5-2 Growth in UK-India direct services 2000-2006 ....................................................................... 23
Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006 ......................................... 24
Figure 1.5-4 Growth of direct point-to-point markets from the UK to India .............................................. 25
Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time 30
Figure 1.6-2 Actual air travel between North-East Asia and North America .............................................. 31
Figure 2.2-1 Fleet size – Airlines in Angola ................................................................................................. 36
Figure 2.2-2 Air Botswana Financial data.................................................................................................... 37
Figure 2.2-3 Air Botswana Domestic and International departures ........................................................... 38
Figure 2.2-4 Air Botswana Domestic and International passengers ........................................................... 38
Figure 2.2-5 Air Botswana Fleet .................................................................................................................. 39
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Figure 2.2-6 Fleet size – DRC Airlines .......................................................................................................... 40
Figure 2.2-7 Air Lesotho Domestic and International Departures .............................................................. 40
Figure 2.2-8 Air Madagascar Domestic and International departures ....................................................... 41
Figure 2.2-9 Air Madagascar Domestic and International passenger numbers ......................................... 42
Figure 2.2-10 Air Madagascar Financial Data ............................................................................................. 43
Figure 2.2-11 Fleet size – Madagascar airlines ........................................................................................... 43
Figure 2.2-12 Air Malawi domestic and international departures ............................................................. 44
Figure 2.2-13 Air Malawi Domestic and International Passengers ............................................................. 44
Figure 2.2-14 Air Malawi Fleet .................................................................................................................... 45
Figure 2.2-15 Air Mauritius Domestic and International departures ......................................................... 46
Figure 2.2-16 Air Mauritius Domestic and International passengers ......................................................... 46
Figure 2.2-17 Air Mauritius Fleet ................................................................................................................ 47
Figure 2.2-18 LAM Domestic and International Departures ....................................................................... 48
Figure 2.2-19 LAM Domestic and International Passengers ....................................................................... 48
Figure 2.2-20 LAM Fleet .............................................................................................................................. 49
Figure 2.2-21 Air Namibia Domestic and International Departures ........................................................... 49
Figure 2.2-22 Air Namibia Domestic and International Passengers ........................................................... 50
Figure 2.2-23 Air Namibia Fleet .................................................................................................................. 50
Figure 2.2-24 Air Seychelles Domestic and International Departures ........................................................ 51
Figure 2.2-25 Air Seychelles Domestic and International passengers ........................................................ 52
Figure 2.2-26 Air Seychelles Fleet ............................................................................................................... 52
Figure 2.2-27 South African Airways Domestic and International departures ........................................... 53
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Figure 2.2-28 South African Airways Domestic and International passengers ........................................... 54
Figure 2.2-29 SA Airlink Domestic and International departures ............................................................... 54
Figure 2.2-30 SA Airlink Domestic and International passengers ............................................................... 55
Figure 2.2-31 Comair Domestic and International departures ................................................................... 56
Figure 2.2-32 Comair Domestic and International passenger numbers ..................................................... 56
Figure 2.2-33 Fleet size – South African Airlines ......................................................................................... 57
Figure 2.2-34 Air Tanzania Domestic and International departures ........................................................... 58
Figure 2.2-35 Air Tanzania Domestic and International Passengers .......................................................... 58
Figure 2.2-36 Air Tanzania Financial data ................................................................................................... 59
Figure 2.2-37 Fleet size – Tanzania airlines................................................................................................. 60
Figure 2.2-38 Zambia Airways Domestic and International departures ..................................................... 60
Figure 2.2-39 Zambezi Airlines Fleet ........................................................................................................... 61
Figure 2.2-40 Air Zimbabwe Domestic and International Departures ........................................................ 62
Figure 2.2-41 Air Zimbabwe Domestic and International passengers ........................................................ 62
Figure 2.2-42 Air Zimbabwe Financial Data ................................................................................................ 63
Figure 2.2-43 Airports with highest frequency: .......................................................................................... 65
Figure 2.2-44 Airports with mid to high frequency: ................................................................................... 66
Figure 2.2-45 International Airports with low frequency: .......................................................................... 67
Figure 2.2-46 Domestic Airports with low frequency: ................................................................................ 67
Figure 2.2-47 Fleet Size (2007) .................................................................................................................... 69
Figure 2.4-1 GDP per Capita Index .............................................................................................................. 88
Figure 2.4-2 Flow chart showing methodology for the section .................................................................. 92
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Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology .................................... 95
Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in
SADC ............................................................................................................................................................ 96
Figure 2.5-1 Forecasted Turnover ............................................................................................................. 108
Figure 2.5-2 Marginal turnover ................................................................................................................. 109
Figure 2.5-3 Growth in Seat Numbers ...................................................................................................... 110
Figure 2.5-4 Growth in Number of Flights per Week ................................................................................ 110
Figure 2.5-5 Passengers Time Saving Benefit ........................................................................................... 112
Figure 2.5-6 Marginal benefits from passengers’ time saving .................................................................. 113
Figure 2.5-7 Average ticket price per flight .............................................................................................. 114
Figure 2.5-8 Total distance flown per week (km) ..................................................................................... 115
Figure 2.5-9 Average distance flown per flight (km)................................................................................. 115
Figure 2.5-10 Total Costs to Airlines ......................................................................................................... 117
Figure 2.5-11 Cost of Flight Cancellation .................................................................................................. 118
Figure 2.5-12 Cost of Flight Diversions ..................................................................................................... 119
Figure 2.5-13 Cost of Accident Resulting in Fatality ................................................................................. 119
Figure 2.5-14 Cost of Accident Resulting in Minor Injury ......................................................................... 120
Figure 2.5-15 Cost of Accident Resulting in Major Injury ......................................................................... 120
Figure 2.5-16 Potential Turnover and Costs to Airlines ............................................................................ 121
Figure 2.5-17 Total and Direct Impact on GDP (2009 Rands) ................................................................... 123
Figure 2.5-18 Total and Direct Impact on Employment ............................................................................ 123
Figure 2.5-19 Cost of Noise Pollution ....................................................................................................... 128
Figure 2.5-20 Cost of Pollution ................................................................................................................. 129
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Figure 2.5-21 Cost of Security ................................................................................................................... 130
Figure 2.5-22 Total Indirect Costs ............................................................................................................. 131
Figure 2.5-23 Weekly cost navigational infrastructure per route ............................................................ 132
Figure 2.5-24 Airport navigational infrastructure ..................................................................................... 133
Figure 2.5-25 Airport Infrastructure Costs ................................................................................................ 135
Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport
liberalisation agreement in SADC ............................................................................................................. 138
Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation
agreement in SADC ................................................................................................................................... 140
Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in
the Southern African Development community ....................................................................................... 141
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List of Boxes
Box 2.4-1 ..................................................................................................................................................... 87
Box 2.4-2 ..................................................................................................................................................... 87
Box 2.4-3 ..................................................................................................................................................... 90
Box 2.4-4 ..................................................................................................................................................... 91
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Appendix A – Signing States of the Chicago Convention 1944
Afghanistan Democratic Republic of the Congo
Lithuania Saint Vincent and the Grenadines
Albania Denmark Luxembourg Samoa
Algeria Djibouti Macedonia San Marino
Andorra Dominican Republic Madagascar Sao Tome and Principe
Angola Ecuador Malawi Saudi Arabia
Antigua and Barbuda Egypt Malaysia Senegal
Argentina El Salvador Maldives Serbia
Armenia Equatorial Guinea Mali Seychelles
Australia Eritrea Malta Sierra Leone
Austria Estonia Marshall Islands Singapore
Azerbaijan Ethiopia Mauritania Slovakia
Bahamas Fiji Mauritius Slovenia
Bahrain Finland Mexico Solomon Islands
Bangladesh France Micronesia (Federated States of)
Somalia
Barbados Gabon Monaco South Africa
Belarus Gambia Mongolia Spain
Belgium Georgia Montenegro Sri Lanka
Belize Germany Morocco Sudan
Benin Ghana Mozambique Suriname
Bhutan Greece Myanmar Swaziland
Bolivia Grenada Namibia Sweden
Bosnia and Herzegovina Guatemala Nauru Switzerland
Botswana Guinea-Bissau Nepal Syrian Arab Republic
Brazil Guinea Guyana Netherlands Tajikistan
Brunei Haiti Honduras New Zealand Thailand
Darussalam Hungary Iceland Nicaragua Timor-Leste
Bulgaria India Nigeria Togo
Burkina Faso Indonesia Niger Tonga
Burundi Iran (Islamic Republic of) Norway Trinidad and Tobago
Cambodia Iraq Oman Tunisia
Cameroon Ireland Pakistan Turkey
Canada Israel Palau Turkmenistan
Cape Verde Italy Panama Uganda
Central African Republic Jamaica Papua New Guinea Ukraine
Chad Japan Paraguay United Arab Emirates
Chile Jordan People's Republic of Korea United Kingdom
China Kazakhstan Peru United Republic of Tanzania
Colombia Kenya Philippines United States
Comoros Kiribati Poland Uruguay
Congo Kuwait Portugal Uzbekistan
Cook Islands Kyrgyzstan Qatar Republic of Vanuatu
Costa Rica Lao People's Korea Republic of Moldova Venezuela
Croatia Democratic Republic Latvia Romania Viet Nam
Cuba Lebanon Russian Federation Yemen
Cyprus Lesotho Rwanda Zambia
Czech Republic Liberia Saint Kitts and Nevis Zimbabwe
Côte d'Ivoire Democratic Libyan Arab Jamahiriya Saint Lucia
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Appendix B – United States Air transportation liberalisation Partners
and status of the agreement
Partner Application Date Concluded
All-cargo 7th air freedom
Albania In Force 9/24/2003 Yes
Armenia C&R 8/7/2010 Yes
Aruba In Force 9/18/1997 Yes
Australia C&R 2/14/2008 Yes
Austria In Force 6/14/1995
Bahrain In Force 5/24/1999 Yes
Belgium Provisional 3/1/1995
Benin N/A 11/28/2000 Yes[1]
Bosnia and Herzegovina In Force 11/22/2005 Yes
Brunei In Force 6/20/1997 Yes
Bulgaria Provisional 3/30/08
4/30/2007 Yes
Burkina Faso In Force 2/9/2000 Yes1
Cameroon In Force 2/16/2006 Yes1
Canada In Force 7/12/2003 Yes
Cape Verde In Force 6/21/2002 Yes1
Chad Provisional 5/31/2006 Yes1
Chile In Force 10/28/1997 Yes
Cook Islands In Force 2/28/2006 Yes
Costa Rica In Force 5/8/1997
Croatia N/A 3/13/2008 Yes
Cyprus Provisional 3/30/08
4/30/2007 Yes
Czech Republic In Force 12/8/1995 Yes
Denmark In Force 4/26/1995
El Salvador In Force 5/8/1997 Yes
Estonia Provisional 3/30/08
4/30/2007 Yes
Ethiopia Provisional 5/17/2005 Yes
Finland In Force 3/24/1995
France In Force 10/19/2001 Yes
Gabon In Force 5/26/2004 Yes1
Gambia In Force 5/2/2000 Yes1
Georgia In Force 7/6/2012 Yes
Germany Provisional 2/29/1996 Yes
Ghana In Force 3/16/2000 Yes1
Greece Provisional 3/30/08
4/30/2007 Yes
Guatemala In Force 5/8/1997 Yes
Honduras Provisional 5/8/1997 Yes
Hungary Provisional 3/30/08
4/30/2007 Yes
Iceland In Force 6/14/1995 Yes
India In Force 1/15/2005 Yes
Indonesia C&R 7/26/2004 Yes
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Ireland Provisional 3/30/08
4/30/2007 Yes
Italy C&R 11/11/1998
Jamaica In Force 10/30/2008
Jordan In Force 11/10/1996
Kenya C&R 5/30/08 --[1]
Korea In Force 4/23/1998
Kuwait In Force 5/27/2007 Yes
Laos C&R 8/3/2010 Yes
Latvia Provisional 3/30/08
4/30/2007 Yes
Liberia In Force 2/15/2007 Yes
Lithuania Provisional 3/30/08
4/30/2007 Yes
Luxembourg In Force 6/6/1995 Yes
Madagascar Provisional 4/10/2003 Yes1
Malaysia In Force 6/21/1997 Yes
Maldives In Force 5/5/2005 Yes
Mali In Force 10/17/2005 Yes1
Malta In Force 10/12/2000 Yes
Morocco In Force 10/5/2000 Yes
Namibia C&R 2/4/2000 1
Netherland Antilles In Force 7/14/1998 Yes
Netherlands In Force 10/14/92
New Zealand In Force 5/29/1997 Yes
Nicaragua In Force 5/8/1997 Chart Only
Nigeria Provisional 8/26/2000 Yes1
Norway In Force 4/26/1995
Oman C&R 9/16/2001 Yes
Pakistan In Force 4/29/1999 Yes
Panama In Force 5/8/1997 Yes
Paraguay In Force 5/2/2005 Yes
Peru In Force 6/10/1998 Yes
Poland In Force 5/31/2001 Yes
Portugal In Force 12/22/1999 Yes
Qatar Provisional 1/3/2010 Yes
Romania In Force 7/15/1998
Rwanda N/A 10/11/2000 Yes1
Samoa In Force 2/4/2007 Yes
Senegal C&R 12/15/2000 Yes1
Singapore In Force 1/22/1997 Yes
Slovak Republic In Force 1/7/2000 Yes
Slovenia Provisional 3/30/08
4/30/2007 Yes
Spain Provisional 4/30/2007 Yes
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3/30/08
Sri Lanka In Force 1/1/2011
Sweden In Force 4/26/1995
Switzerland In Force 6/15/1995
Taiwan In Force 2/28/1997
Tanzania Provisional 11/3/1999 Yes[2]
Thailand In Force 9/19/2005 Yes
Tonga In Force 9/19/2003 Yes
Turkey In Force 3/22/2000
U.A.E. In Force 4/13/1999 Yes
Uganda C&R 2/4/2006 Yes1
United Kingdom Provisional 3/30/08
4/30/2007 Yes
Uruguay Provisional 10/20/2004 Yes
Uzbekistan In Force 2/27/1998 Yes
Source: http://www.state.gov/e/eeb/rls/othr/ata/114805.htm, accessed 17/07/2009
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Appendix C – State ownership for international flag carriers
Country Airline Designated State-owned
Afghanistan Ariana Afghan Airlines Yes Majority
Albania Albanian Airlines Yes Joint-Venture
Andorra AeroKing Andorra Yes Joint-Venture
Algeria Air Algérie Yes Majority[1]
Angola TAAG Angola Airlines Yes Full1
Åland Islands Air Åland
Argentina Aerolíneas Argentinas Yes Full
Armenia Armavia Yes No
Australia Qantas Yes No
Austria Austrian Airlines Yes Minority (42.75%)
Azerbaijan Azerbaijan Airlines Yes Full
Bahamas Bahamasair Yes Full
Bahrain Gulf Air Yes Full
Bangladesh Biman Bangladesh Airlines Yes Full
Barbados LIAT No No
Belarus Belavia Yes Full
Belgium Brussels Airlines Yes No
Belize Maya Island Air No No
Benin Benin Golf Air Yes No1
Bhutan Drukair Yes Full
Bolivia AeroSur Yes Minority (48%)
Bosnia and Herzegovina B&H Airlines Yes Majority (51%)
Botswana Air Botswana Yes Full1
Brazil TAM Airlines Yes No
Brunei Royal Brunei Airlines Yes Full
Bulgaria Bulgaria Air Yes No
Hemus Air Yes No
Burkina Faso Air Burkina Yes Majority1
Burundi Air Burundi Yes Full1
Cambodia Royal Khmer Airlines Yes Full
Cameroon Cameroon Airlines Yes
Canada Air Canada Yes No (privatised in 1988)
Cape Verde TACV Cabo Verde Airlines Yes Full1
Cayman Islands Cayman Airways Yes
Chad Toumaï Air Tchad 1
Chile LAN Airlines No
China Air China Yes Majority
Colombia Avianca Yes No
Comoros Air Comores International
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Republic of the Congo Trans Air Congo Full[2]
Democratic Republic of the Congo
Hewa Bora Airways Full1
Costa Rica Lacsa (now part of TACA)
Côte d'Ivoire Air Ivoire 1
Croatia Croatia Airlines Yes Majority
Cuba Cubana de Aviación Yes Full
Cyprus Cyprus Airways Yes Majority
Northern Cyprus Cyprus Turkish Airlines
Czech Republic Czech Airlines Yes Full
Denmark Scandinavian Airlines System Yes Joint-Venture
Djibouti Air Djibouti 1
Dominican Republic Air Dominicana Yes Minority (33%)
Ecuador TAME
Egypt EgyptAir Yes Full
El Salvador TACA
Equatorial Guinea Ecuato Guineana
Eritrea Eritrean Airlines Yes Full
Estonia Estonian Air Yes Minority
Ethiopia Ethiopian Airlines Yes Full1
Faroe Islands Atlantic Airways
Fiji Air Pacific
Finland Finnair Yes Majority
France Air France No Minority
French Guiana Air Guyane Yes
French Polynesia Air Tahiti Nui Yes
Gabon Gabon Airlines 1
Gambia Gambia International Airlines
Yes 1
Georgia Georgian Airways Yes
Guernsey Aurigny Air Services Yes Full
Germany Lufthansa Yes No
Ghana Ghana International Airlines Yes 1
Greece Olympic Airlines Yes Majority
Greenland Air Greenland Yes
Guadeloupe Air Caraïbes
Guam Continental Micronesia
Guatemala Aviateca (now part of TACA)
Guinea Air Guinee Express Yes
Guyana Caribbean Airlines No
Haiti Tortug' Air
Honduras TACA
Hong Kong Cathay Pacific Yes No
Hungary Malév Yes No
Iceland Icelandair Yes No
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Indonesia Garuda Indonesia Yes Full
India Air India Yes Full
Indian Yes Full
Iran Iran Air Yes Full
Iraq Iraqi Airways Yes Full
Ireland Aer Lingus Yes Minority (28%)
Israel El Al Yes Minority (30%)
Italy Alitalia Yes No (Privatised in 2009)
Jamaica Air Jamaica Yes
Japan Japan Airlines Yes No
Jordan Royal Jordanian Airlines Yes
Kazakhstan Air Astana Yes 0.51
Kenya Kenya Airways Yes [3]
Kiribati Air Kiribati Yes
North Korea Air Koryo Yes Full
South Korea Korean Air Yes No
Kuwait Kuwait Airways Yes Full
Kyrgyzstan Kyrgyzstan Airlines Yes Majority
Laos Lao Airlines Yes Full
Latvia Air Baltic Yes Majority
Lebanon Middle East Airlines Full
Liberia Air Liberia Yes 1
Libya Libyan Arab Airlines Yes 1
Lithuania
Luxembourg Luxair Yes Minority
Macau Air Macau Yes No
Macedonia MAT Macedonian Airlines Yes No
Madagascar Air Madagascar Yes Majority1
Malawi Air Malawi Yes Full1
Malaysia Malaysia Airlines Yes Minority
Maldives Maldivian Yes Full
Mali Air Mali International Yes No
Malta Air Malta Yes Majority
Marshall Islands Air Marshall Islands Yes Full
Martinique Air Caraïbes Yes No
Mauritania Mauritania Airways Minority
Mauritius Air Mauritius Yes Minority1
Mexico Aeromexico
Mexicana Yes
Federated States of Micronesia
Continental Micronesia
Moldova Air Moldova Yes
Mongolia MIAT Mongolian Airlines Yes
Montenegro Montenegro Airlines Yes
Montserrat Air Montserrat
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Morocco Royal Air Maroc Yes
Mozambique Linhas Aéreas de Moçambique
Yes Full[4]
Myanmar Myanma Airways Yes Yes
Namibia Air Namibia Yes Majority1
Nauru Our Airline Yes
Nepal Nepal Airlines Yes
Netherlands KLM Yes No
Netherlands Antilles Dutch Antilles Express
New Caledonia Aircalin
New Zealand Air New Zealand Yes Majority
Nicaragua NICA (now part of TACA) Yes
Nigeria Virgin Nigeria Airways Yes No1
Norway Scandinavian Airlines System Yes Minority
Oman Oman Air Yes Majority (82.4%)
Pakistan Pakistan International Airlines (PIA)
Yes Majority (87%)
Palestinian Authority Palestinian Airlines Full
Panama Copa Airlines Yes No
Papua New Guinea Air Niugini
Paraguay Regional Paraguaya Yes No
Peru Air Perú
Philippines Philippine Airlines Yes Joint-Venture
Poland LOT Polish Airlines Yes Majority (67.97%)
Portugal TAP Portugal Yes Full
Qatar Qatar Airways Yes
Republic of China China Airlines[8] No Majority (54%)
Réunion Air Austral
Romania TAROM Yes Majority (95%)
Russia Rossiya Yes Full
Aeroflot Yes Majority (51%)
Rwanda Rwandair Express Yes 1
Samoa Polynesian Blue
São Tomé and Príncipe STP Airways 1
Saudi Arabia Saudi Arabian Airlines Yes Full
Senegal Air Sénégal International Yes 1
Serbia Jat Airways Yes Full
Seychelles Air Seychelles Yes 1
Sierra Leone Sierra National Airlines Yes [5]
Singapore Singapore Airlines Yes Majority (54%)
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Slovakia Air Slovakia
Slovenia Adria Airways
Solomon Islands Solomon Airlines Yes
Somalia Somali Airlines[10] Yes
South Africa South African Airways Yes Full1
Spain Iberia Yes Minority (5%)
Sri Lanka SriLankan Airlines Yes
Sudan Sudan Airways Yes 1
Suriname Surinam Airways Yes
Sweden Scandinavian Airlines System Yes Joint-Venture
Swaziland Royal Swazi National Airways
1
Switzerland Swiss International Air Lines [12]
Yes No
Syria Syrian Air Yes Full
Tajikistan Tajik Air Yes
Tanzania Air Tanzania Yes
Thailand Thai Airways International Yes Majority (53%)
Togo Air Togo Yes
Tonga
Trinidad and Tobago Caribbean Airlines Yes Full
Tunisia Tunisair Yes
Turkey Turkish Airlines Yes Majority
Turkmenistan Turkmenistan Airlines Yes
Turks and Caicos Islands Air Turks and Caicos Yes
Uganda Air Uganda Yes 1
Ukraine Ukraine International Airlines
Yes Majority
United Arab Emirates Etihad Airways Yes Yes
Emirates Yes Yes
United Kingdom British Airways Yes No (Privatised in 1987)
United States N/A N/A N/A
Uruguay PLUNA Yes Minority (25%)
Uzbekistan Uzbekistan Airways Yes Majority
Vanuatu Air Vanuatu Yes
Venezuela Conviasa Yes Full
Vietnam Vietnam Airlines Yes Full
Yemen Yemenia Yes
Zambia Zambian Airways Yes 1
Zimbabwe Air Zimbabwe Yes 1
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Appendix D – Spider Diagram
Impact of YD (SADC)
Direct Impacts
Airlines
Benefits
New Routes
Expansion on existing routes
Costs
Increase in cancellations
Increase in diversions
Increase in minor/major
injury
Increase in fatalities
Passengers Benefits
Reduction in time travelled
Reduction in airfares
Indirect Impacts
Tourism Impacts Benefits
Direct impact on GDP
Total impact on GDP
Security Cost
International security
personnel
Domestic security personnel
Pollution CostIncreased fuel
burn
Noise Pollution Cost Increased flights
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Appendix E – Questionnaires
Air transportation liberalisation Questionnaire for Southern African Airlines
Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows.
The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:
1. Determine the understanding that airlines within Southern Africa have of the Yamoussoukro Decision (an African aviation agreement from 1999)
2. Determine the information about all the current routes flown by airlines in Southern Africa 3. Determine the effects of an air transportation liberalisation agreement among the SADC
countries.
It would be greatly appreciated if you could take 20 minute to complete this questionnaire and return it to Graham Muller Associates (no later than a week from receiving the questionnaire, please). Answers are to be completed in the boxes that follow the questions.
Please NOTE that answer boxes will expand in size as you type your answers.
1. Please complete the following information:
Company/Organisation
Country of airport
Name
Position held
Email address
Contact number
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Date completed
2. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick
can be cut and pasted).
TICK BRIEFLY EXPLAIN
National flag carrier
Low cost carrier Domestic
International
High end (luxury) carrier
Domestic
International
Freight Carrier Domestic
International
Chartered Carrier
Franchise Who are you franchised from?
Code Sharing Who are code sharing partners? Both domestic and international?
Alliance Who are your alliance partners? Both domestic and international?
Block Space Who do you have block space agreements with? Both domestic and international?
a. If your airline does not fall within the above categories please explain?
b. Very briefly explain the functions of your company/organisation and how it fits into the
aviation industry within the Southern African Region?
3. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)
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4. Please √ tick the correct box and explain where necessary?
QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN
a. Has your airline been subsidised by government in the last 5 years?
What was the subsidy you received in proportion to your turnover?
b. Is your airline wholly or partly owned by government?
What is the percentage of government ownership?
c. Is your airline privately owned?
Please tick the structure of private ownership for your airline
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
d. Is your airline owned by a FOREIGN government?
What is the percentage of foreign governments’ ownership?
e. Is your airline privately owned by FOREIGN owners or shareholders?
Please tick the structure of private ownership for your airline
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
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5. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?
Yes: No:
6. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:
Yes: No:
7. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate:
Yes: No:
If your answer to either question 6 or 7 is yes, please answer questions 7a – 7h. These questions relate directly to the Yamoussoukro Decision, which looks to establish an air transportation liberalisation agreement between African countries for African airlines. Otherwise if you’ve answered “ NO” for both questions 6 and 7 please continue to question 8:
a. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
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OWNERS Eg. %
Domestic Government 33%
Foreign Government 0%
Domestic Private Ownership 50%
Foreign Private Ownership 17%
b. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
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c. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please tick as appropriate
Lack of government commitment to YD
Airport security concerns
Lack of SACD commitment to YD
OTHER PLEASE SPECIFY BELOW:
National flag carriers disapproval of YD
Lack of competition law regionally
Lack of competition law within your country
Corruption
Poor legislation
Political instability in other African countries
Poor/substandard airport infrastructure in Africa
d. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?
e. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?
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f. How do you see the Yamoussoukro Decision impacting on your company?
i. Frequency of flights
ii. Capacity (number of seats on offer)
iii. Pricing
iv. Volume of freight business
v. No. of competitors on each route
vi. Your market share on each route
a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?
AIRLINES EXPLAIN
Most benefit from YD
Least benefit from YD
b. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:
(Please answer yes or no and give a reason for ‘yes’ answers)
YES / NO: EXPLAIN WHERE ‘YES’:
Air traffic control
Airport runway capacity (slots)
Airport runway length
Baggage handling
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Security
Freight logistics capacity
Other (specify):
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8. Could you please list the following airline fleet information in the table below: a. What aircrafts does your fleet consist of? b. What runway lengths are required for the takeoff and landing of each aeroplane model,
at various capacities? (eg. 100% full, 90% full or 80% full)
AEROPLANE MODEL NUMBER IN FLEET
RUNWAY LENGTH (ft)
CAPACITY
100% 90% 80%
Eg. Airbus A320 3 TAKE OFF 6600 5400 4300
LANDING 4800 4225 3650
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
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LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
9. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate)
TICK
Air traffic control
Baggage Handling
Customs facilities
Airport Security
Other (please
specify)
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10. How many passengers were served in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
11. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
12. How many flights operated in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
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13. What routes do you currently cover both domestically and internationally? (please answer this in table below)
BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM
a. On these various routes please detail the: i. Airport code of origin and destination?
ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)?
vi. Volume of freight business? vii. No. of competitors on each route?
viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement? x. How would this route change under an air transportation liberalisation agreement?
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ii. No. of flights per week
iii. Weekly Capacity (number of seats on offer)
iv. Pricing
v. Demand (take up of capacity)
vi. Volume of freight business
vii. No. of competitors on route
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viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
Eg. Would fly 10 more flights on this route per month
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iv. Pricing
v. Demand (take up of capacity)
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vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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iv. Pricing
v. Demand (take up of capacity)
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vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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iii. Weekly Capacity (number of seats on offer)
iv. Pricing
v. Demand (take up of capacity)
vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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i. Airport Code
ii. No. of flights per week
iii. Weekly Capacity (number of seats on offer)
iv. Pricing
v. Demand (take up of capacity)
vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
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x. Change under air transportation liberalisation agreement
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The following question looks at the possible changes in the aviation industry if the Southern African Development Community (SADC) had a regional air transportation liberalisation agreement. This would give SADC airlines the option of flying to ANY airport within the SADC region an unlimited amount of times.
14. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:
b. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers?
Please add rows if needed
NEW ROUTE FREQUENCY OF FLIGHTS
PASSENGER CAPACITY FREIGHT CAPACITY PRICE
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c. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed
CHANGE TO CURRENT ROUTES
FREQUENCY OF FLIGHTS
PASSENGER CAPACITY
FREIGHT CAPACITY PRICE
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Air transportation liberalisation Questionnaire for Southern African Airlines
Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows.
The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:
1. Determine the understanding that airlines within Southern Africa have of the Yamoussoukro Decision (an African aviation agreement from 1999)
2. Determine the information about all the current routes flown by airlines in Southern Africa 3. Determine the effects of an air transportation liberalisation agreement among the SADC
countries.
It would be greatly appreciated if you could take 20 minute to complete this questionnaire and return it to Graham Muller Associates (no later than a week from receiving the questionnaire, please). Answers are to be completed in the boxes that follow the questions.
Please NOTE that answer boxes will expand in size as you type your answers.
4. Please complete the following information:
Company/Organisation
Country of airport
Name
Position held
Email address
Contact number
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Date completed
5. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick
can be cut and pasted).
TICK BRIEFLY EXPLAIN
National flag carrier
Low cost carrier Domestic
International
High end (luxury) carrier
Domestic
International
Freight Carrier Domestic
International
Chartered Carrier
Franchise Who are you franchised from?
Code Sharing Who are code sharing partners? Both domestic and international?
Alliance Who are your alliance partners? Both domestic and international?
Block Space Who do you have block space agreements with? Both domestic and international?
c. If your airline does not fall within the above categories please explain?
d. Very briefly explain the functions of your company/organisation and how it fits into the aviation industry within the Southern African Region?
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6. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)
7. Please √ tick the correct box and explain where necessary?
QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN
a. Has your airline been subsidised by government in the last 5 years?
What was the subsidy you received in proportion to your turnover?
b. Is your airline wholly or partly owned by government?
What is the percentage of government ownership?
c. Is your airline privately owned?
Please tick the structure of private ownership for your airline
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
d. Is your airline owned by a FOREIGN government?
What is the percentage of foreign governments’ ownership?
e. Is your airline privately owned by FOREIGN owners or shareholders?
Please tick the structure of private ownership for your airline
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
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8. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?
OWNERS Eg. %
Domestic Government 33%
Foreign Government 0%
Domestic Private Ownership 50%
Foreign Private Ownership 17%
9. Are you familiar with the air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:
Yes: No:
10. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate:
Yes: No:
If your answer to either question 6 or 7 is yes, please answer questions 7a – 7h. These questions relate directly to the Yamoussoukro Decision, which looks to establish an air transportation liberalisation agreement between African countries for African airlines. Otherwise if you’ve answered “ NO” for both questions 6 and 7 please continue to question 8:
g. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
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h. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
i. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please
tick as appropriate
Lack of government commitment to YD
Airport security concerns
Lack of SACD commitment to YD
OTHER PLEASE SPECIFY BELOW:
National flag carriers disapproval of YD
Lack of competition law regionally
Lack of competition law within your country
Corruption
Poor legislation
Political instability in other African countries
Poor/substandard airport infrastructure in Africa
j. What role should governments be playing to successfully implement the Yamoussoukro Decision
or an air transportation liberalisation agreement between African countries specifically for African airlines?
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k. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?
l. How do you see the Yamoussoukro Decision impacting on your company?
i. Frequency of flights
ii. Capacity (number of seats on offer)
iii. Pricing
iv. Volume of freight business
v. No. of competitors on each route
vi. Your market share on each route
a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?
AIRLINES EXPLAIN
Most benefit from YD
Least benefit from YD
b. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:
(Please answer yes or no and give a reason for ‘yes’ answers)
YES / NO: EXPLAIN WHERE ‘YES’:
Air traffic control
Airport runway capacity (slots)
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Airport runway length
Baggage handling
Security
Freight logistics capacity
Other (specify):
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11. Could you please list the following airline fleet information in the table below: c. What aircrafts does your fleet consist of? d. What runway lengths are required for the takeoff and landing of each aeroplane model,
at various capacities? (eg. 100% full, 90% full or 80% full)
AEROPLANE MODEL NUMBER IN FLEET
RUNWAY LENGTH (ft)
CAPACITY
100% 90% 80%
Eg. Airbus A320 3 TAKE OFF 6600 5400 4300
LANDING 4800 4225 3650
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
TAKE OFF
LANDING
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12. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate)
TICK
Air traffic control
Baggage Handling
Customs facilities
Airport Security
Other (please
specify)
13. How many passengers were served in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
14. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
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15. How many flights operated in the various markets from 2004 to 2008?
2004 2005 2006 2007 2008
Domestic
SADC Region
Africa
Rest of the world
TOTAL
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16. What routes do you currently cover both domestically and internationally? (please answer this in table below)
BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM
d. On these various routes please detail the: i. Airport code of origin and destination?
ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)?
vi. Volume of freight business? vii. No. of competitors on each route?
viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement? x. How would this route change under an air transportation liberalisation agreement?
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vi. Volume of freight business
vii. No. of competitors on route
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viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
Eg. Would fly 10 more flights on this route per month
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iv. Pricing
v. Demand (take up of capacity)
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vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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v. Demand (take up of capacity)
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vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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iii. Weekly Capacity (number of seats on offer)
iv. Pricing
v. Demand (take up of capacity)
vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
x. Change under air transportation liberalisation agreement
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iv. Pricing
v. Demand (take up of capacity)
vi. Volume of freight business
vii. No. of competitors on route
viii. Current market share of route
viii. Has market share increased or decreased?
Please answer Increase or decrease
ix. Does route operate under air transportation liberalisation?
Please answer YES or NO
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x. Change under air transportation liberalisation agreement
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The following question looks at the possible changes in the aviation industry if the Southern African Development Community (SADC) had a regional air transportation liberalisation agreement. This would give SADC airlines the option of flying to ANY airport within the SADC region an unlimited amount of times.
17. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:
e. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers?
Please add rows if needed
NEW ROUTE FREQUENCY OF FLIGHTS
PASSENGER CAPACITY FREIGHT CAPACITY PRICE
f. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed
CHANGE TO CURRENT ROUTES
FREQUENCY OF FLIGHTS
PASSENGER CAPACITY
FREIGHT CAPACITY PRICE
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Air transportation liberalisation Questionnaire for other Southern Africa
Aviation Industry Stakeholders
Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows.
The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine two things:
1. Determine the understanding that your company/organisation has of the Yamoussoukro Decision (an African aviation agreement from 1999)
2. Determine the effects of an air transportation liberalisation agreement among the SADC countries will have on your company/organisation.
It would be greatly appreciated if you could take 20 minute to complete this questionnaire and return it to Graham Muller Associates (no later than a week from receiving the questionnaire, please). Answers are to be completed in the boxes that follow the questions.
Please NOTE that answer boxes will expand in size as you type your answers.
3. Please complete the following information:
Company/Organisation
Country
Name
Position held
Email address
Contact number
Date completed
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4. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)
5. Please list your main sources of income?
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6. Please tick √ the correct box and explain where necessary? (Tick can be cut and pasted).
QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN (if necessary)
a. Has your company been subsidised by government in the last 5 years?
What was the subsidy you received in proportion to your turnover?
b. Is your company wholly or partly owned by government?
What is the percentage of government ownership?
c. Is your company privately owned?
Please tick the structure of private ownership for your company
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
d. Is your company owned by a FOREIGN government?
What is the percentage of foreign governments’ ownership?
e. Is your company privately owned by FOREIGN owners or shareholders?
Please tick the structure of private ownership for your company
Sole proprietorship
A partnership
Close Corporation
Company
Non-profit
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7. Please ONLY answer this question if there is more than one shareholder. If the ownership of your business(es) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?
OWNERS Eg. %
Domestic Government 33%
Foreign Government 0%
Domestic Private Ownership 50%
Foreign Private Ownership 17%
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8. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:
Yes: No:
9. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate:
Yes: No:
If your answer to either question 6 or 7 is yes, please answer questions 7a – 7h. These questions relate directly to the Yamoussoukro Decision, which looks to establish an air transportation liberalisation agreement between African countries for African airlines. Otherwise if you’ve answered “ NO” for both questions 6 and 7 please continue to question 8:
m. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
n. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:
Very poor
Why?
Poor
Fair
Good
Very good
o. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please
tick as appropriate
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Lack of government commitment to YD
Airport security concerns
Lack of SACD commitment to YD
OTHER PLEASE SPECIFY BELOW:
National flag carriers disapproval of YD
Lack of competition law regionally
Lack of competition law within your country
Corruption
Poor legislation
Political instability in other African countries
Poor/substandard airport infrastructure in Africa
p. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?
q. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?
r. How do you see the Yamoussoukro Decision impacting on your company?
Please explain in detail in the space below, which will expand as you type.
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s. Which companies/organistions would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?
COMPANIES/ORGANISATIONS EXPLAIN
Most benefit from YD
Least benefit from YD
t. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:
(Please answer yes or no and give a reason for ‘yes’ answers)
YES / NO: EXPLAIN WHERE ‘YES’:
Air traffic control
Airport runway capacity (slots)
Airport runway length
Baggage handling
Security
Freight logistics capacity
Other (specify):
The following question looks at the possible changes in the aviation industry if the Southern African Development Community (SADC) had a regional air transportation liberalisation agreement. This would give SADC airlines the option of flying to ANY airport within the SADC region an unlimited amount of times.
10. If the ‘Southern African Development Community’ (SADC) had a comprehensive air transportation liberalisation agreement, how would your company change?
Please answer in detail, specify staff, infrastructure and capital changes:
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Appendix F – Destinations within SADC
City COUNTRY POPULATION
Luanda Angola 3,060,137
Huambo Angola 220,835
Lobito Angola 174,785
Benguela Angola 171,096
Namibe Angola 169,061
Kuito Angola 112,834
Lubango Angola 96,424
Malanje Angola 91,082
M'banza-Kongo Angola 85,993
Uige Angola 62,332
Cabinda Angola 56,990
Saurimo Angola 52,410
Lucapa Angola 45,668
Chissamba Angola 40,580
Waku-Kungo Angola 37,908
Sumbe Angola 32,438
Caxito Angola 31,293
Soyo Angola 30,021
Menongue Angola 29,512
Caala Angola 29,131
Caluquembe Angola 28,368
N'dalatando Angola 28,368
Longonjo Angola 25,060
Catabola Angola 23,152
Catumbela Angola 20,989
Luena Angola 20,481
Luau Angola 17,428
Camacupa Angola 16,919
Catchiungo Angola 16,156
Leua Angola 15,901
N'zeto Angola 15,138
Camabatela Angola 14,756
Cazaje Angola 14,375
Lumeje Angola 14,247
Ondjiva Angola 12,721
Caconda Angola 10,304
Gaborone Botswana 191,223
Francistown Botswana 85,360
Molepolole Botswana 56,141
Selibe Phikwe Botswana 51,255
Maun Botswana 45,027
Serowe Botswana 43,686
Kanye Botswana 41,770
Mahalapye Botswana 40,812
Mochudi Botswana 38,034
Mogoditshane Botswana 33,723
Lobatse Botswana 30,561
Palapye Botswana 27,016
Tlokweng Botswana 21,747
Ramotswa Botswana 21,268
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Thamaga Botswana 18,586
Moshupa Botswana 17,436
Tonota Botswana 16,095
Jwaneng Botswana 15,616
Letlhakane Botswana 15,424
Bobonong Botswana 15,041
Tutume Botswana 14,083
Mmadinare Botswana 11,209
Gabane Botswana 10,730
Ghanzi Botswana 10,251
Orapa Botswana 9,389
Kasane Botswana 7,856
Shoshong Botswana 7,664
Tsabong Botswana 6,802
Gumare Botswana 6,227
Letlhakeng Botswana 6,227
Lerala Botswana 5,940
Kopong Botswana 5,748
Maitengwe Botswana 5,461
Otse Botswana 5,365
Mmankgodi Botswana 5,173
Molapowabojang Botswana 4,982
Tsienyane Botswana 4,694
Mmathethe Botswana 4,503
Shakawe Botswana 4,503
Tati Botswana 4,503
Tumasera Seleka Botswana 4,407
Lotlhakane Botswana 4,311
Nata Botswana 4,311
Sefhare Botswana 4,311
Gweta Botswana 4,215
Metsimotlhaba Botswana 4,215
Lentsweletau Botswana 4,120
Mathangwane Botswana 4,120
Bokaa Botswana 3,928
Hukuntsi Botswana 3,928
Sefophe Botswana 3,928
Kang Botswana 3,832
Mmopane Botswana 3,641
Nkange Botswana 3,641
Ramokgonami Botswana 3,641
Mogoditshane Botswana Defence Force Botswana 3,545
Oodi Botswana 3,545
Tsetsebjwe Botswana 3,545
Kumakwane Botswana 3,257
Manyana Botswana 3,257
Maunatlala Botswana 3,257
Masunga Botswana 3,161
Mopipi Botswana 3,161
Water Util-Dukwe Refugee Camp Botswana 3,161
Borolong Botswana 3,066
Pitsane Botswana 3,066
Chadibe Botswana 2,970
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Good Hope Botswana 2,970
Sowa Botswana 2,970
Sebina Botswana 2,874
Digawana Botswana 2,778
Morwa Botswana 2,778
Radisele Botswana 2,778
Etsha Botswana 2,682
Mandunyane Botswana 2,682
Moiyabana Botswana 2,682
Ranaka Botswana 2,682
Thebephatshwa Botswana 2,682
Lecheng Botswana 2,587
Ramotswa Station-Taung Botswana 2,587
Senete Botswana 2,587
Modipane Botswana 2,491
Rasesa Botswana 2,491
Malolwane Botswana 2,395
Mookane Botswana 2,395
Thabala Botswana 2,395
Kalamare Botswana 2,299
Lesetlhane Botswana 2,299
Ratholo Botswana 2,299
Serule Botswana 2,299
Lesenepole Botswana 2,203
Shashe Mooke Botswana 2,203
Khakhea Botswana 2,108
Machaneng Botswana 2,108
Mmathubudukwane Botswana 2,108
Mogobane Botswana 2,108
Mogorosi Botswana 2,108
Paje Botswana 2,108
Shashe-Semotswane Botswana 2,108
Sojwe Botswana 2,108
Etsha 13 Botswana 2,012
Nlakhwane Botswana 2,012
Werda Botswana 2,012
Charles Hill Botswana 1,916
Dukwi Botswana 1,916
Khudumelapye Botswana 1,916
Mathathane Botswana 1,916
Ditshegwane Botswana 1,820
Mabeleapudi Botswana 1,820
Mogapi Botswana 1,820
Mokobeng Botswana 1,820
Molalatau Botswana 1,820
Moroka Botswana 1,820
Mosolotshane Botswana 1,820
Nswazwi Botswana 1,820
Ntlhantlhe Botswana 1,820
Tobane Botswana 1,820
Kazungula Botswana 1,724
Kobojango Botswana 1,724
Lehututu Botswana 1,724
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Mabutsane Botswana 1,724
Majwaneng Botswana 1,724
Matshelagabedi Botswana 1,724
Mosetse Botswana 1,724
Nshakashokwe Botswana 1,724
Salajwe Botswana 1,724
Seronga Botswana 1,724
Tsamaya Botswana 1,724
Mabule Botswana 1,629
Makwate Botswana 1,629
Mapoka Botswana 1,629
Marapong Botswana 1,629
Mmashoro Botswana 1,629
Nokaneng Botswana 1,629
Pandamatenga Botswana 1,629
Pitshane Molopo Botswana 1,629
Sikwane Botswana 1,629
Takatokwane Botswana 1,629
Xhumo Botswana 1,629
Artisia Botswana 1,533
Dagwi Botswana 1,533
Makopong Botswana 1,533
Morope Botswana 1,533
Motokwe Botswana 1,533
Ramokgwebana Botswana 1,533
Sehithwa Botswana 1,533
Sepopa Botswana 1,533
Sese Botswana 1,533
Tshesebe Botswana 1,533
Tshimoyapula Botswana 1,533
Zwenshambe Botswana 1,533
Gootau Botswana 1,437
Kgomokasitwa Botswana 1,437
Matsiloje Botswana 1,437
Mogapinyana Botswana 1,437
Moletemane Botswana 1,437
Moshopha Botswana 1,437
Ncojane Botswana 1,437
Nkoyaphiri Botswana 1,437
Senyawe Botswana 1,437
Themashanga Botswana 1,437
Tsootsha Botswana 1,437
Gaphatshwa Botswana 1,341
Kgagodi Botswana 1,341
Kudumatse Botswana 1,341
Lokgwabe Botswana 1,341
Makuta Botswana 1,341
Marobela Botswana 1,341
Matobo Botswana 1,341
Mohembo West Botswana 1,341
Mokoboxane Botswana 1,341
Moshaneng Botswana 1,341
Motlhabaneng Botswana 1,341
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Nxamasere Botswana 1,341
Pilikwe Botswana 1,341
Seolwane Botswana 1,341
Sesung Botswana 1,341
Siviya Botswana 1,341
Topisi Botswana 1,341
Tsao Botswana 1,341
Kinshasa Democratic Republic Of Congo 5,874,688
Lubumbashi Democratic Republic Of Congo 984,609
Mbuji-Mayi Democratic Republic Of Congo 840,292
Kolwezi Democratic Republic Of Congo 745,638
Kananga Democratic Republic Of Congo 498,880
Kisangani Democratic Republic Of Congo 463,752
Likasi Democratic Republic Of Congo 343,056
Boma Democratic Republic Of Congo 324,886
Tshikapa Democratic Republic Of Congo 308,880
Bukavu Democratic Republic Of Congo 212,669
Matadi Democratic Republic Of Congo 203,670
Kikwit Democratic Republic Of Congo 202,200
Uvira Democratic Republic Of Congo 191,557
Mwene-Ditu Democratic Republic Of Congo 188,443
Mbandaka Democratic Republic Of Congo 187,751
Butembo Democratic Republic Of Congo 138,953
Goma Democratic Republic Of Congo 138,607
Isiro Democratic Republic Of Congo 124,504
Bunia Democratic Republic Of Congo 121,389
Gemena Democratic Republic Of Congo 111,266
Kindu Democratic Republic Of Congo 109,622
Bandundu Democratic Republic Of Congo 107,805
Ilebo Democratic Republic Of Congo 97,423
Kalemie Democratic Republic Of Congo 95,087
Beni Democratic Republic Of Congo 90,934
Gandajika Democratic Republic Of Congo 83,839
Bumba Democratic Republic Of Congo 79,426
Mbanza-Ngungu Democratic Republic Of Congo 78,648
Kipushi Democratic Republic Of Congo 75,792
Kamina Democratic Republic Of Congo 64,372
Lisala Democratic Republic Of Congo 63,939
Lodja Democratic Republic Of Congo 61,689
Binga Democratic Republic Of Congo 54,768
Kabinda Democratic Republic Of Congo 53,297
Kasongo Democratic Republic Of Congo 46,548
Kalima Democratic Republic Of Congo 46,462
Mweka Democratic Republic Of Congo 46,116
Gbadolite Democratic Republic Of Congo 46,029
Bulungu Democratic Republic Of Congo 44,126
Buta Democratic Republic Of Congo 41,876
Basoko Democratic Republic Of Congo 40,059
Lusambo Democratic Republic Of Congo 37,464
Nioki Democratic Republic Of Congo 37,117
Inongo Democratic Republic Of Congo 36,598
Tshela Democratic Republic Of Congo 35,387
Mangai Democratic Republic Of Congo 33,916
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Kenge Democratic Republic Of Congo 33,743
Bukama Democratic Republic Of Congo 33,397
Yangambi Democratic Republic Of Congo 32,618
Manono Democratic Republic Of Congo 32,359
Aketi Democratic Republic Of Congo 32,272
Luebo Democratic Republic Of Congo 32,013
Kambove Democratic Republic Of Congo 31,580
Lubao Democratic Republic Of Congo 30,196
Mushie Democratic Republic Of Congo 30,196
Kabare Democratic Republic Of Congo 29,850
Boende Democratic Republic Of Congo 29,244
Kampene Democratic Republic Of Congo 28,033
Yakoma Democratic Republic Of Congo 27,773
Kongolo Democratic Republic Of Congo 27,514
Yandongi Democratic Republic Of Congo 26,822
Simba Democratic Republic Of Congo 26,648
Titule Democratic Republic Of Congo 26,562
Kutu Democratic Republic Of Congo 26,475
Businga Democratic Republic Of Congo 26,389
Kabalo Democratic Republic Of Congo 25,697
Moba Democratic Republic Of Congo 25,697
Bolobo Democratic Republic Of Congo 25,437
Kasangulu Democratic Republic Of Congo 25,437
Kaniama Democratic Republic Of Congo 25,351
Libenge Democratic Republic Of Congo 24,658
Gwane Democratic Republic Of Congo 24,572
Watsa Democratic Republic Of Congo 22,495
Faradje Democratic Republic Of Congo 22,149
Demba Democratic Republic Of Congo 20,246
Basankusu Democratic Republic Of Congo 19,640
Shinkolobwe Democratic Republic Of Congo 19,640
Kasongo-Lunda Democratic Republic Of Congo 18,256
Idiofa Democratic Republic Of Congo 17,737
Tshilenge Democratic Republic Of Congo 17,650
Mobayi-Mbongo Democratic Republic Of Congo 17,218
Niangara Democratic Republic Of Congo 17,218
Bodalangi Democratic Republic Of Congo 16,439
Bondo Democratic Republic Of Congo 16,352
Kahemba Democratic Republic Of Congo 16,352
Kama Democratic Republic Of Congo 16,179
Itoko Democratic Republic Of Congo 16,006
Wamba Democratic Republic Of Congo 15,920
Yumbi Democratic Republic Of Congo 15,574
Dilolo Democratic Republic Of Congo 15,314
Katako-Kombe Democratic Republic Of Congo 15,228
Lubefu Democratic Republic Of Congo 15,141
Lusanga Democratic Republic Of Congo 15,141
Aba Democratic Republic Of Congo 14,968
Kole Democratic Republic Of Congo 14,622
Mambasa Democratic Republic Of Congo 14,622
Muanda Democratic Republic Of Congo 14,622
Kimpese Democratic Republic Of Congo 14,536
Tshofa Democratic Republic Of Congo 14,016
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Bosobolo Democratic Republic Of Congo 13,238
Mongbwalu Democratic Republic Of Congo 13,065
Bafwasende Democratic Republic Of Congo 12,459
Kazumba Democratic Republic Of Congo 12,459
Kibombo Democratic Republic Of Congo 12,372
Nyunzu Democratic Republic Of Congo 12,372
Gungu Democratic Republic Of Congo 12,286
Makanza Democratic Republic Of Congo 12,199
Madimba Democratic Republic Of Congo 12,113
Kiri Democratic Republic Of Congo 11,940
Zongo Democratic Republic Of Congo 11,853
Ikela Democratic Republic Of Congo 11,680
Ubundu Democratic Republic Of Congo 10,296
Djugu Democratic Republic Of Congo 10,209
Poko Democratic Republic Of Congo 10,209
Banalia Democratic Republic Of Congo 10,036
Sakania Democratic Republic Of Congo 9,950
Le Marinel Democratic Republic Of Congo 8,739
Mwanza Democratic Republic Of Congo 8,479
Malemba-Nkulu Democratic Republic Of Congo 7,614
Lubudi Democratic Republic Of Congo 7,527
Mulongo Democratic Republic Of Congo 7,441
Kikondjo Democratic Republic Of Congo 7,354
Dibaya Democratic Republic Of Congo 4,153
Bongandanga Democratic Republic Of Congo 3,720
Maseru Lesotho 132,168
Mafeteng Lesotho 26,653
Maputsoa Lesotho 24,122
Teyateyaneng Lesotho 21,508
Hlotse Lesotho 17,712
Mohale's Hoek Lesotho 15,519
Quthing Lesotho 11,386
Butha Buthe Lesotho 7,928
Qacha's Nek Lesotho 6,241
Mokhotlong Lesotho 5,651
Thaba-Tseka Lesotho 4,723
Antananarivo Madagascar 1,161,056
Toamasina Madagascar 187,057
Antsirabe Madagascar 167,563
Fianarantsoa Madagascar 150,667
Mahajanga Madagascar 141,755
Toliary Madagascar 106,200
AntsiranìˆAna Madagascar 76,772
Antanifotsy Madagascar 66,561
Ambovombe Madagascar 64,704
Amparafaravola Madagascar 47,159
TaolanìˆAro Madagascar 43,724
Ambatondrazaka Madagascar 39,454
Soavinandriana Madagascar 38,061
Mananara Madagascar 37,690
Nosy Varika Madagascar 37,226
Mahanoro Madagascar 36,483
Soanierana Ivongo Madagascar 35,926
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Morondava Madagascar 35,648
Manakara Madagascar 35,555
Faratsiho Madagascar 35,369
Amboasary Madagascar 34,998
Antalaha Madagascar 34,162
Vavatenina Madagascar 33,791
Ikongo Madagascar 32,491
Sambava Madagascar 31,563
Fandriana Madagascar 31,470
Ambanja Madagascar 30,635
Ambositra Madagascar 30,449
Betioky Madagascar 30,171
Manjakandriana Madagascar 29,985
Marovoay Madagascar 29,799
Tsihombe Madagascar 28,871
Ambalavao Madagascar 28,128
Betafo Madagascar 28,035
Mananjary Madagascar 27,757
Ambatolampy Madagascar 26,829
Moramanga Madagascar 26,736
Ambatofinandrahana Madagascar 26,086
Tsiroanomandidy Madagascar 25,529
Ankazoabo Madagascar 25,158
Ampanihy Madagascar 24,879
Farafangana Madagascar 24,786
Anosibe An'ala Madagascar 24,136
Marolambo Madagascar 23,951
Vangaindrano Madagascar 23,579
Vohibinany Madagascar 23,208
Belon'i Tsiribihina Madagascar 23,115
Antsirambazaha Madagascar 22,651
Beloha Madagascar 22,280
Maroantsetra Madagascar 21,816
Ambato Boina Madagascar 21,444
Sakaraha Madagascar 21,166
Andapa Madagascar 20,794
Arivonimamo Madagascar 20,702
Antsohihy Madagascar 20,330
Miandrivazo Madagascar 19,959
Vondrozo Madagascar 19,959
Fenoarivo Atsinanana Madagascar 19,216
Manandriana Madagascar 19,031
Fenoarivo Madagascar 18,474
Andilamena Madagascar 18,102
Beroroha Madagascar 18,010
Anjozorobe Madagascar 17,917
Ifanadiana Madagascar 17,545
Ihosy Madagascar 16,988
Bealanana Madagascar 16,153
Tsaratanana Madagascar 15,967
Ikalamavony Madagascar 15,596
Ankazobe Madagascar 14,853
Ambilobe Madagascar 14,668
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Ambodifototra Madagascar 10,861
Andevoranto Madagascar 9,562
Blantyre Malawi 520,101
Lilongwe Malawi 474,232
Mzuzu Malawi 94,698
Zomba Malawi 69,729
Karonga Malawi 30,241
Mangochi Malawi 29,408
Kasungu Malawi 28,391
Salima Malawi 22,102
Nkhotakota Malawi 21,085
Nsanje Malawi 18,403
Liwonde Malawi 17,109
Dedza Malawi 16,554
Balaka Malawi 15,629
Rumphi Malawi 15,167
Mzimba Malawi 15,074
Mulanje Malawi 13,687
Mchinji Malawi 12,485
Mponela Malawi 10,820
Chilumba Malawi 10,728
Nkhata Bay Malawi 10,265
Luchenza Malawi 9,618
Monkey Bay Malawi 9,525
Mwanza Malawi 8,785
Ntcheu Malawi 8,785
Chitipa Malawi 7,768
Chikwawa Malawi 7,398
Ntchisi Malawi 5,826
Thyolo Malawi 5,826
Livingstonia Malawi 5,179
Dowa Malawi 4,901
Phalombe Malawi 2,774
Chipoka Malawi 2,404
Chiradzulu Malawi 1,665
Machinga Malawi 1,387
Port Louis Mauritius 140,310
Beau Bassin-Rose Hill Mauritius 108,164
Vascoas-Phoenix Mauritius 102,008
Curepipe Mauritius 78,070
Quatre Bornes Mauritius 74,748
Triolet Mauritius 21,594
Goodlands Mauritius 19,933
Bel Air Mauritius 17,295
Central Flacq Mauritius 16,708
Le Hochet Mauritius 16,611
Saint Pierre Mauritius 14,950
Mahebourg Mauritius 14,852
Baie Du Tombeau Mauritius 14,266
Bambous Mauritius 12,604
Rose Belle Mauritius 11,823
Chemin Grenier Mauritius 11,725
Surinam Mauritius 11,725
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Grand Baie Mauritius 11,627
Pailles Mauritius 11,432
Plaine Magnien Mauritius 11,041
Riviere Du Rempart Mauritius 10,553
Terre Rouge Mauritius 10,455
New Grove Mauritius 10,064
Lalmatie Mauritius 9,673
Petit Raffray Mauritius 9,185
Riviere Des Anguilles Mauritius 8,892
Grand Bois Mauritius 8,208
Pointe Aux Piments Mauritius 8,208
Montagne Blanche Mauritius 7,914
Moka Mauritius 7,817
Beau Vallon Mauritius 7,719
L'escalier Mauritius 7,719
Pamplemousse Mauritius 7,719
Dagotiere Mauritius 7,426
Plaines Des Papayes Mauritius 7,328
Bon Accueil Mauritius 7,230
Nouvelle France Mauritius 7,035
Grand Gaube Mauritius 6,937
Medine-Camp De Masque Mauritius 6,937
Long Mountain Mauritius 6,644
Brisee Verdiere Mauritius 6,449
Laventure Mauritius 6,351
Poste De Flacq Mauritius 6,253
Quatre Cocos Mauritius 6,253
Quartier Militaire Mauritius 6,156
Ecroignard Mauritius 6,058
Port Mathurin Mauritius 5,960
Trou D'eau Douce Mauritius 5,960
Morcellement Saint Andre Mauritius 5,569
Fond Du Sac Mauritius 5,374
Poudre D'or Mauritius 5,374
Roches Noires Mauritius 5,374
Cap Malheureux Mauritius 5,276
Sebastopol Mauritius 5,276
Chamouny Mauritius 5,179
Calebasses Mauritius 4,983
Camp Diable Mauritius 4,983
Piton Mauritius 4,983
Midlands Mauritius 4,788
Mare D'albert Mauritius 4,690
D'epinay Mauritius 4,495
Belle Vue Maurel Mauritius 4,397
Petite Riviere Mauritius 4,397
Richelieu Mauritius 4,397
Camp Ithier Mauritius 4,299
Notre Dame Mauritius 4,201
Camp De Masque Pave Mauritius 4,104
Trois Boutiques Mauritius 4,006
Union Park Mauritius 4,006
Souillac Mauritius 3,908
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Tamarin Mauritius 3,908
Lataniers-Mont Lubin Mauritius 3,811
Plaine Des Roches Mauritius 3,811
Bois Cheri Mauritius 3,615
Petit Gabriel Mauritius 3,615
Saint Hubert Mauritius 3,615
Olivia Mauritius 3,518
The Vale Mauritius 3,518
Cottage Mauritius 3,420
Roche Terre Mauritius 3,420
Quatre Soeurs Mauritius 3,322
Albion Mauritius 3,224
Saint Julien D'hotman Mauritius 3,224
Riviere Des Creoles Mauritius 3,127
Providence Mauritius 3,029
Old Grand Port Mauritius 2,931
Riviere Cocos Mauritius 2,931
Dubreuil Mauritius 2,834
Gros Cailloux Mauritius 2,834
Mangues-Quatre Vents Mauritius 2,834
Plaine Corail-La Fouche Corail Mauritius 2,834
Ripailles Mauritius 2,834
Port Sud-Est Mauritius 2,736
Saint Julien Mauritius 2,736
Arsenal Mauritius 2,638
Creve Coeur Mauritius 2,638
Mare Tabac Mauritius 2,638
Oyster Bay Mauritius 2,638
Amaury Mauritius 2,540
Camp De Masque Mauritius 2,540
Cascavelle Mauritius 2,540
Queen Victoria Mauritius 2,540
Bel Ombre Mauritius 2,443
L'avenir Mauritius 2,443
Amitie-Gokhoola Mauritius 2,247
Baie Du Cap Mauritius 2,247
Riviere Du Poste Mauritius 2,247
Villebague Mauritius 2,247
Benares Mauritius 2,150
Grand River South East Mauritius 2,150
Grand Sable Mauritius 2,150
Camp Thorel Mauritius 2,052
Clemencia Mauritius 2,052
Esperance Trebuchet Mauritius 2,052
Flic En Flac Mauritius 2,052
Poudre D'or Hamlet Mauritius 2,052
Roche Bon Dieu-Trefles Mauritius 2,052
Coromandel-Graviers Mauritius 1,954
Grande Riviere Noire Mauritius 1,954
Mare La Chaux Mauritius 1,954
Maputo Mozambique 1,060,424
Matola Mozambique 483,997
Beira Mozambique 452,940
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Nampula Mozambique 345,726
Chimoio Mozambique 194,994
Nacala Mozambique 180,395
Quelimane Mozambique 168,120
Tete Mozambique 115,118
Xai-Xai Mozambique 113,351
Garue Mozambique 111,305
Maxixe Mozambique 106,656
Lichinga Mozambique 97,729
Pemba Mozambique 96,799
Dondo Mozambique 70,019
Angoche Mozambique 66,393
Cuamba Mozambique 65,184
Montepuez Mozambique 64,347
Mocuba Mozambique 61,371
Inhambane Mozambique 59,419
Chokwe Mozambique 56,722
Chibuto Mozambique 52,631
Mocambique Mozambique 48,353
Manica Mozambique 22,689
Quissico Mozambique 19,620
Lumbo Mozambique 17,110
Nazombe Mozambique 16,645
Inharrime Mozambique 16,087
Panda Mozambique 13,576
Macia Mozambique 12,925
Marrupa Mozambique 12,181
Chongoene Mozambique 10,694
Homoine Mozambique 10,136
Manhica Mozambique 10,136
Bela Vista Mozambique 10,043
Guija Mozambique 9,950
Magude Mozambique 9,485
Zumbo Mozambique 9,206
Jangamo Mozambique 9,020
Maniamba Mozambique 9,020
Marracuene Mozambique 9,020
Moamba Mozambique 9,020
Mandimba Mozambique 8,927
Namaacha Mozambique 8,927
Chidenguele Mozambique 8,741
Manjacaze Mozambique 8,648
Windhoek Namibia 245,334
Rundu Namibia 46,675
Walvis Bay Namibia 44,146
Oshakati Namibia 29,658
Swakopmund Namibia 26,352
Katima Mulilo Namibia 23,824
Rehoboth Namibia 22,365
Otjiwarongo Namibia 20,615
Grootfontein Namibia 17,309
Keetmanshoop Namibia 16,336
Okahandja Namibia 14,878
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Gobabis Namibia 14,586
Tsumeb Namibia 13,808
Luderitz Namibia 12,544
Mariental Namibia 10,988
Ondangwa Namibia 10,696
Khorixas Namibia 10,599
Oranjemund Namibia 10,016
Bethanien Namibia 9,043
Ongwediva Namibia 8,363
Omaruru Namibia 6,515
Karasburg Namibia 6,321
Outjo Namibia 6,321
Arandis Namibia 5,834
Opuwo Namibia 5,737
Karibib Namibia 5,543
Okakarara Namibia 5,056
Otavi Namibia 4,765
Usakos Namibia 4,570
Otjimbingwe Namibia 3,792
Aranos Namibia 3,501
Eenhana Namibia 3,403
Ongandjera Namibia 3,014
Outapi Namibia 2,820
Oshikango Namibia 2,723
Maltahohe Namibia 2,625
Warmbad Namibia 2,431
Henties Bay Namibia 2,139
Okombahe Namibia 2,139
Victoria Seychelles 26,974
Anse Royal Seychelles 3,914
Cascade Seychelles 2,539
Takamaka Seychelles 2,327
Anse Boileau Seychelles 2,116
Cape Town South Africa 2,901,473
Durban South Africa 2,461,210
Johannesburg South Africa 1,920,800
Pretoria South Africa 1,432,992
Soweto South Africa 1,424,630
Port Elizabeth South Africa 754,319
Benoni South Africa 474,196
Vereeniging South Africa 449,985
Pietermaritzburg South Africa 445,027
East London South Africa 411,774
Tembisa South Africa 366,172
Bloemfontein South Africa 339,336
Boksburg South Africa 338,461
Vanderbijlpark South Africa 328,641
Newcastle South Africa 300,833
Krugersdorp South Africa 264,857
Welkom South Africa 239,286
Brakpan South Africa 222,367
Carltonville South Africa 214,297
Springs South Africa 208,658
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Uitenhage South Africa 193,295
Witbank South Africa 193,004
Alberton South Africa 191,934
Botshabelo South Africa 180,753
Paarl South Africa 168,599
Midrand South Africa 164,029
Kimberley South Africa 161,501
Klerksdorp South Africa 158,195
Verwoerdburg South Africa 148,666
Westonaria South Africa 148,666
Somerset West South Africa 135,151
Bisho South Africa 134,082
Randfontein South Africa 127,373
Middelburg South Africa 120,275
Rustenburg South Africa 119,594
Nigel South Africa 119,011
Potchefstroom South Africa 118,719
George South Africa 113,080
Nelspruit South Africa 109,288
Phalaborwa South Africa 106,079
Emnambithi South Africa 103,551
Pietersburg South Africa 101,120
Potgietersrus South Africa 98,009
Epumalanga South Africa 94,995
Mabopane South Africa 93,925
Worcester South Africa 92,370
Embalenhle South Africa 89,939
Kroonstad South Africa 88,286
Richards Bay South Africa 84,397
Orkney South Africa 84,299
Louis Trichardt South Africa 84,202
Umtata South Africa 76,813
Sasolburg South Africa 75,160
Stellenbosch South Africa 71,659
Garankuwa South Africa 66,312
Oudtshoorn South Africa 64,367
Standerton South Africa 63,589
Lichtenburg South Africa 63,492
Grahamstown South Africa 62,520
Virginia South Africa 61,936
Vryheid South Africa 61,839
Stilfontein South Africa 59,992
Atlantis South Africa 59,019
Bethlehem South Africa 58,144
Kutlwanong South Africa 57,950
Brits South Africa 57,269
Heidelberg South Africa 54,255
Queenstown South Africa 54,255
Saldanha South Africa 53,574
Mosselbay South Africa 52,408
Upington South Africa 52,213
Mmabatho South Africa 49,491
Bethal South Africa 49,393
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Temba South Africa 45,504
Parys South Africa 44,143
Ermelo South Africa 43,365
Thohoyandou South Africa 42,684
Phuthaditjhaba South Africa 42,587
Delmas South Africa 41,809
Esikhawini South Africa 38,212
Vryburg South Africa 38,212
Thaba Nchu South Africa 37,726
Kgotsong South Africa 37,142
Knysna South Africa 37,045
Warmbad South Africa 36,170
Ekangala South Africa 35,684
Stanger South Africa 35,684
Beaufort-West South Africa 34,420
Graaff-Reinet South Africa 34,420
Siyabuswa South Africa 34,420
Harrismith South Africa 34,225
Port Shepstone South Africa 33,739
Butterworth South Africa 33,545
Margate South Africa 33,156
Mondlo South Africa 32,961
Piet Retief South Africa 31,795
Fochville South Africa 31,308
Richmond South Africa 31,211
Wembezi South Africa 29,947
Schweizer Reneke South Africa 29,461
Cradock South Africa 29,364
Secunda South Africa 29,364
Dundee South Africa 28,975
Barberton South Africa 28,683
Empangeni South Africa 28,683
Ceres South Africa 27,225
Malmesbury South Africa 26,252
Bronkhorstspruit South Africa 25,961
Lulekani South Africa 25,863
Phola South Africa 25,863
Fort Beaufort South Africa 25,669
De Aar South Africa 25,572
Lebohang South Africa 24,988
Wolmaranstad South Africa 24,794
Heilbron South Africa 24,599
Lady Frere South Africa 24,502
Lebowakgomo South Africa 24,502
Kokstad South Africa 24,405
Viljoenskroon South Africa 24,405
Balfour South Africa 24,113
Cullinan South Africa 24,113
Hermanus South Africa 24,016
Duiwelskloof South Africa 23,822
Wesselsbron South Africa 23,822
Volksrust South Africa 23,335
Scottsburgh South Africa 23,044
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Aliwal North South Africa 22,655
Giyani South Africa 22,558
Hennenman South Africa 22,266
Robertson South Africa 21,099
Pampierstad South Africa 21,002
Theunissen South Africa 20,710
Lydenburg South Africa 20,613
Ekuphumleni South Africa 20,516
Mpophomeni South Africa 20,516
Frankfort South Africa 20,321
Stutterheim South Africa 20,224
Nylstroom South Africa 19,932
Allanridge South Africa 19,738
Bulfontein South Africa 19,738
Senekal South Africa 19,641
Umkomaas South Africa 19,641
Messina South Africa 19,543
Nkowakowa South Africa 19,349
Grabouw South Africa 19,252
Kruisfontein South Africa 18,571
Plettenberg Bay South Africa 18,571
Ezibeleni South Africa 17,891
Middelburg South Africa 17,696
Howick South Africa 17,599
Port Alfred South Africa 17,502
Warrenton South Africa 17,404
Ncotshane South Africa 17,307
Postmasburg South Africa 17,210
Zeerust South Africa 17,113
Christiana South Africa 16,918
Ladybrand South Africa 16,821
Ballitoville South Africa 16,627
Bloemhof South Africa 16,529
Tzaneen South Africa 16,432
Reitz South Africa 16,238
Somerset East South Africa 15,751
Randvaal South Africa 15,168
Ventersdorp South Africa 15,168
Witrivier South Africa 15,168
Hendrina South Africa 15,071
Ellisras South Africa 14,876
Ulundi South Africa 14,779
Eshowe South Africa 14,293
Kriel South Africa 14,293
Vrede South Africa 14,293
Bredasdorp South Africa 14,196
Sundumbili South Africa 14,196
Vredendal South Africa 14,099
Ekuvukeni South Africa 13,807
Swellendam South Africa 13,710
Empuluzi South Africa 13,418
Greytown South Africa 13,418
Needscamp South Africa 13,321
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Jan Kempdorp South Africa 13,126
Letsopa South Africa 13,126
Glencoe South Africa 13,029
Hoopstad South Africa 12,348
Burgersdorp South Africa 12,251
Mankweng South Africa 12,154
Zastron South Africa 12,154
Clocolan South Africa 12,057
Colesberg South Africa 12,057
Deneysville South Africa 12,057
Adelaide South Africa 11,959
Breyten South Africa 11,862
Brandfort South Africa 11,765
Whittlesea South Africa 11,765
Koster South Africa 11,668
Elliot South Africa 11,570
Jeffreys Bay South Africa 11,473
Barkly West South Africa 11,279
Belfast South Africa 11,279
Thulamahashe South Africa 11,279
Koppies South Africa 11,182
Mogwase South Africa 11,182
Villiers South Africa 10,987
Prieska South Africa 10,890
Winburg South Africa 10,793
Ilinge South Africa 10,598
Marquard South Africa 10,598
Ventersburg South Africa 10,404
Vredefort South Africa 10,404
Springbok South Africa 10,112
Thabazimbi South Africa 10,015
Kirkwood South Africa 9,918
Koffiefontein South Africa 9,918
Mooreesburg South Africa 9,918
Danielskuil South Africa 9,820
Molteno South Africa 9,820
Mooi River South Africa 9,723
Ritchie South Africa 9,723
Alice South Africa 9,529
Dordrecht South Africa 8,945
Kathu South Africa 8,945
Wepener South Africa 8,945
Kuruman South Africa 8,848
Paulpietersburg South Africa 8,265
Heidelberg South Africa 8,070
Victoria-West South Africa 7,973
Calvinia South Africa 7,876
Vredenburg South Africa 7,487
Inyala South Africa 7,390
Barkly East South Africa 7,292
Ixopo South Africa 7,195
Velddrif South Africa 7,098
Willowmore South Africa 6,903
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Keimoes South Africa 6,709
Hertzogville South Africa 6,223
Mandeni South Africa 5,931
Umzimvubu South Africa 5,834
Carnarvon South Africa 5,639
Matatiele South Africa 5,639
Komga South Africa 5,542
Tarkastad South Africa 4,959
Manzini Swaziland 87,492
Mbabane Swaziland 64,453
Matsapha Swaziland 19,839
Big Bend Swaziland 10,422
Mhlume Swaziland 8,502
Malkerns Swaziland 8,228
Nhlangano Swaziland 7,222
Hluti Swaziland 6,491
Simunye Swaziland 6,217
Pigg's Peak Swaziland 5,120
Siteki Swaziland 4,663
Ngomane Swaziland 4,297
Lobamba Swaziland 4,023
Vuvulane Swaziland 4,023
Kwaluseni Swaziland 3,017
Mondi Swaziland 3,017
Bhunya Swaziland 2,926
Mhlambanyatsi Swaziland 2,834
Thabankulu Swaziland 2,834
Bulembu Swaziland 2,743
Tshaneni Swaziland 2,468
Mpaka Swaziland 2,377
Hlatikulu Swaziland 2,286
Kubuta Swaziland 1,920
Sidvokodvo Swaziland 1,737
Ezulwini Swaziland 1,554
Lavumisa Swaziland 1,280
Mankayane Swaziland 1,189
Nsoko Swaziland 1,097
Ngwenya Swaziland 914
Dar Es Salaam Tanzania 2,419,179
Mwanza Tanzania 381,544
Zanzibar Tanzania 354,951
Arusha Tanzania 285,181
Mbeya Tanzania 258,874
Morogoro Tanzania 223,227
Tanga Tanzania 210,550
Dodoma Tanzania 160,605
Kigoma Tanzania 146,117
Moshi Tanzania 145,545
Tabora Tanzania 136,395
Songea Tanzania 109,707
Musoma Tanzania 109,135
Iringa Tanzania 107,610
Uvinza Tanzania 106,466
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Katumba Tanzania 100,080
Shinyanga Tanzania 93,694
Mtwara Tanzania 93,408
Kilosa Tanzania 88,833
Ushirombo Tanzania 88,547
Sumbawanga Tanzania 81,017
Bagamoyo Tanzania 71,867
Bukoba Tanzania 62,145
Mpanda Tanzania 60,811
Singida Tanzania 58,618
Uyovu Tanzania 56,712
Kalangalala Tanzania 52,900
Makambako Tanzania 51,470
Mishoma Tanzania 50,517
Sengerama Tanzania 50,231
Buseresere Tanzania 49,564
Mererani Tanzania 48,420
Bunda Tanzania 46,609
Katoro Tanzania 46,418
Ifakara Tanzania 46,037
Utengule Usongwe Tanzania 44,512
Siha Kati Tanzania 42,796
Njombe Tanzania 42,701
Lindi Tanzania 41,938
Nkome Tanzania 39,270
Kiranyi Tanzania 39,174
Nkololo Tanzania 39,079
Vwawa Tanzania 38,126
Gairo Tanzania 35,934
Kidadu Tanzania 35,552
Nguruka Tanzania 35,171
Tunduma Tanzania 34,790
Masasi Tanzania 34,504
Korogwe Tanzania 34,409
Kidodi Tanzania 34,123
Kasulu Tanzania 33,932
Mafinga Tanzania 33,932
Newala Tanzania 33,646
Isagehe Tanzania 33,360
Mikindani Tanzania 33,265
Missungwi Tanzania 33,265
Mlimba Tanzania 33,169
Igunga Tanzania 33,074
Chalinze Tanzania 32,788
Kahama Tanzania 32,598
Lusaka Zambia 1,210,941
Ndola Zambia 418,345
Kitwe Zambia 406,047
Kabwe Zambia 197,374
Chingola Zambia 164,578
Mufulira Zambia 136,582
Luanshya Zambia 129,083
Livingstone Zambia 108,886
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Kasama Zambia 82,889
Chipata Zambia 81,589
Chililabombwe Zambia 60,892
Kalulushi Zambia 58,892
Mazabuka Zambia 52,593
Kafue Zambia 51,193
Mongu Zambia 49,493
Mansa Zambia 45,794
Choma Zambia 45,094
Kansanshi Zambia 37,995
Kapiri Mposhi Zambia 30,396
Mpika Zambia 28,896
Monze Zambia 27,496
Nchelenge Zambia 23,097
Kawambwa Zambia 19,997
Samfya Zambia 19,697
Mbala Zambia 18,898
Mumbwa Zambia 17,798
Petauke Zambia 16,298
Sesheke Zambia 15,498
Siavonga Zambia 14,598
Chambishi Zambia 14,498
Kaoma Zambia 13,798
Maamba Zambia 12,898
Chinsali Zambia 12,798
Isoka Zambia 12,798
Kalomo Zambia 12,298
Mwinilunga Zambia 11,998
Mkushi Zambia 11,798
Mpongwe Zambia 11,798
Katete Zambia 11,598
Sinazongwe Zambia 11,598
Nakambala Zambia 10,999
Mwanzakombe Zambia 10,799
Nakonde Zambia 10,399
Senanga Zambia 10,299
Chilanga Zambia 10,199
Lundazi Zambia 10,199
Serenje Zambia 9,599
Kalabo Zambia 8,399
Limulunga Zambia 8,399
Mpulungu Zambia 8,399
Itezhi-Tezhi Zambia 7,699
Zambezi Zambia 7,499
Kalengwa Zambia 7,299
Mungwi Zambia 6,699
Kabompo Zambia 6,499
Luwingu Zambia 5,999
Mufumbwe Zambia 5,999
Chongwe Zambia 5,799
Kasempa Zambia 5,499
Namwala Zambia 4,499
Harare Zimbabwe 2,265,437
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Bulawayo Zimbabwe 1,150,485
Chitungwiza Zimbabwe 485,778
Mutare Zimbabwe 223,862
Gweru Zimbabwe 180,533
Kadoma Zimbabwe 126,431
Masvingo Zimbabwe 95,482
Kwekwe Zimbabwe 93,419
Marondera Zimbabwe 83,790
Zvishavane Zimbabwe 83,676
Chinhoyi Zimbabwe 69,806
Hwange Zimbabwe 67,285
Chegutu Zimbabwe 46,079
Redcliffe Zimbabwe 41,494
Kariba Zimbabwe 39,889
Bindura Zimbabwe 30,490
Victoria Falls Zimbabwe 27,739
Sakubva Zimbabwe 27,051
Norton Zimbabwe 26,593
Karoi Zimbabwe 23,957
Rusape Zimbabwe 23,727
Shurugwi Zimbabwe 22,008
Chiredzi Zimbabwe 16,735
Plumtree Zimbabwe 15,933
Mount Darwin Zimbabwe 15,016
Chipinge Zimbabwe 14,213
Gwanda Zimbabwe 14,099
Tuli Zimbabwe 12,723
Chimanimani Zimbabwe 11,692
Nyanga Zimbabwe 11,692
Chivhu Zimbabwe 10,431
Mutoko Zimbabwe 10,316
Gaths Zimbabwe 9,972
West Nicholson Zimbabwe 9,285
Mvuma Zimbabwe 8,368
Beitbridge Zimbabwe 6,075
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Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure
costs (R Millions)
Location 5 Years 10 Years 15 Years 20 Years 25 Years 30 Years 35 Years 40 Years 45 Years 50 Years TOTAL
Cabinda -3.41 -3.41 -3.41 -1555.07 -380.12 -2985.60 -2369.01 -4391.83 -1576.26 -4464.42 -17732.55
Catumbela -3.03 -3.03 -3.03 786.63 701.61 -883.63 -935.52 -3005.74 -325.72 -3002.72 -6674.16
Dundo 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Huambo 7.85 7.85 17.34 -577.23 60.07 -2373.49 -2945.19 -2697.68 -2573.37 -2779.25 -13853.10
Kuito 8.63 8.63 8.63 -424.35 684.54 -2371.07 -2098.33 -3403.71 -1589.07 -3483.26 -12659.37
Luanda 2034.37 2034.37 2038.57 2242.34 3053.54 983.09 2508.28 1497.87 2421.35 1522.48 20336.26
Lubango 683.08 683.08 683.08 1128.09 2237.11 -804.10 -445.62 -1665.40 153.34 -1741.87 910.80
Luena 784.40 784.40 784.40 2537.35 2772.99 1563.33 1487.84 -1026.67 1152.78 -852.84 9988.00
Malanje 335.97 335.97 335.97 1280.29 2597.23 -468.04 -8.15 -1676.01 560.87 -1754.25 1539.83
Menongue 813.28 813.28 813.28 2418.22 3866.02 1011.59 1575.99 -997.29 2226.29 -1045.76 11494.90
Namibe 739.40 739.40 1234.06 3778.53 4658.83 2051.70 1704.46 1776.21 2194.78 1699.74 20577.13
Ondjiva 936.77 936.77 936.77 3738.74 5643.66 3426.84 3971.10 955.87 4540.65 979.89 26067.06
Saurimo 800.76 800.76 800.76 5897.83 7118.67 4605.51 4851.32 2402.59 5534.29 2322.46 35134.95
Soyo 298.54 298.54 298.54 6448.73 8292.71 5855.36 6478.95 4211.64 7253.61 4164.63 43601.25
Uíge 0.00 0.00 216.68 4945.03 6660.87 3987.02 4795.89 2232.08 5270.35 2224.04 30331.95
Francistown 7.13 7.13 -157.54 -776.65 -141.47 14158.03 16080.64 16010.69 15984.09 16021.93 77193.97
Gaborone 429.29 429.29 429.29 466.31 2756.95 21836.15 21780.30 22453.88 21685.41 22469.22 114736.08
Kasane 779.36 779.36 1114.65 1274.34 1138.14 3261.45 10578.56 14905.53 10887.11 14814.82 59533.32
Maun 1431.80 1431.80 1431.80 1513.70 2403.98 12533.81 14244.64 14578.59 14330.77 14485.71 78386.60
Bukavu 0.00 0.00 0.00 0.00 22.27 -1231.81 5008.61 21032.85 23867.52 22425.68 71125.11
Buta-Zega 0.00 0.00 0.00 0.00 18.90 -800.48 4445.29 17524.50 24589.82 26410.83 72188.86
Gbadolite 16.03 16.03 16.03 16.03 16.03 -1051.33 5824.68 20717.28 26128.99 26933.68 78633.44
Gemena 0.00 0.00 0.00 0.00 13.47 -356.26 7768.70 22958.63 26508.32 24723.14 81616.00
Goma 0.00 0.00 0.00 0.00 23.48 939.59 8271.83 24135.17 28072.84 25685.91 87128.82
Isiro-Matari 0.00 0.00 0.00 0.00 23.61 1029.36 9439.06 27545.71 31309.00 29368.43 98715.18
Kananga 0.00 0.00 0.00 0.00 26.42 3247.67 10757.33 18278.27 22661.60 18319.06 73290.35
Kindu 0.00 0.00 0.00 0.00 16.96 1860.49 8620.85 21789.45 25073.49 23130.04 80491.27
Kinshasa 1036.57 1036.57 1036.57 1036.57 8816.88 15585.23 26360.21 27478.42 27832.52 27404.36 137623.91
Kisangani 1059.34 1059.34 1059.34 1059.34 1096.60 5374.53 13754.03 29045.85 31120.41 29147.73 113776.53
Lubumbashi 1401.39 1401.39 1401.39 1401.39 3513.78 13948.75 22247.96 29247.69 31956.38 29231.47 135751.60
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Impact of the Yamoussoukro Decision: 12th April 2010 - report prepared by Graham Muller Associates
Mbandaka 0.00 0.00 0.00 0.00 1886.95 6517.25 13732.70 26030.37 29799.95 26331.77 104299.00
Mbuji-Mayi 796.11 796.11 796.11 796.11 2167.66 7376.35 15821.63 22395.55 27079.87 22431.27 100456.76
Maseru -4.62 -4.62 -4.62 -4.62 1.12 2703.74 13514.55 34730.50 50640.41 49578.30 151150.16
Antanànarìvo 26.00 26.00 26.00 26.00 249.97 14290.87 54041.04 77559.25 77367.97 77479.66 301092.75
Mahajanga 309.03 309.03 309.03 309.03 373.12 5371.20 21127.29 52829.00 67420.96 66531.44 214889.13
Nosy Be 0.00 0.00 0.00 0.00 623.64 99.78 14787.69 50160.31 69519.63 68093.99 203285.05
Toamasina 164.64 164.64 164.64 164.64 1192.46 7777.80 42703.68 71554.37 76224.14 76396.59 276507.60
Toliara 565.42 565.42 565.42 565.42 2738.42 6124.57 19340.62 49468.13 69202.73 67162.89 216299.03
Blantyre 36.33 36.33 36.33 36.33 108.07 4062.34 22534.33 46544.15 49257.69 49829.11 172481.01
Lilongwe 169.25 169.25 169.25 169.25 267.18 4536.03 25507.92 45154.77 50486.87 48124.81 174754.57
Port Louis 1265.37 1265.37 1265.37 1438.94 15548.12 84419.78 121950.90 122102.56 121872.83 122134.97 593264.22
Beira 15.88 15.88 15.88 15.88 175.83 5358.12 30068.20 51392.45 54724.95 55133.79 196916.86
Chimoio 0.00 0.00 0.00 10.79 -340.17 2914.28 11695.73 34957.00 50340.81 47596.54 147174.97
Cuamba 0.00 0.00 0.00 0.00 525.75 -213.44 6141.83 31797.32 50863.46 48643.72 137758.65
Lichinga 14.29 14.29 14.29 14.29 1002.50 2011.79 12167.71 38209.56 51652.98 48946.13 154047.81
Maputo 1986.45 1986.45 1986.45 2662.00 3899.75 12546.66 44782.34 69101.47 68832.98 69017.50 276802.06
Moçimboa da Praia 1587.63 1587.63 1587.63 1587.63 2553.51 3648.92 11386.06 37976.22 60575.29 59930.55 182421.06
Mueda 0.00 0.00 0.00 0.00 2428.66 3395.27 10716.64 36354.23 57121.00 57704.57 167720.35
Nampula 2011.91 2011.91 2011.91 2011.91 4815.73 11478.20 37113.11 59868.76 64279.95 63460.16 249063.56
Tete 1624.01 1624.01 1624.01 1624.01 2455.77 6949.10 14089.50 38751.64 53181.07 50177.64 172100.75
Grootfontein 0.00 0.00 -4.18 48.01 176.90 5282.55 32235.21 63212.93 62891.32 63133.15 226975.89
Karabib 0.00 0.00 0.00 237.03 -303.33 3765.55 13720.43 48537.65 67146.98 64556.87 197661.18
Katima Mulilo 0.00 0.00 15.17 798.92 925.91 4694.36 28177.42 55373.46 56333.15 55288.43 201606.82
Keetmanshoop 0.00 0.00 6.13 1215.27 1452.25 7199.55 36821.76 77893.59 79110.54 77818.75 281517.84
Mariental 0.00 0.00 0.00 1015.76 1216.69 5698.82 25077.46 66502.11 72718.36 70530.68 242759.88
Ondangwa 0.00 0.00 7.54 2104.58 2432.52 7831.16 29422.19 60570.18 65170.77 63889.69 231428.64
Rundu 0.00 0.00 8.68 2450.58 2587.75 6860.17 32837.05 61098.66 61393.78 61016.42 228253.09
Windhoek 3617.00 3617.00 6357.30 6658.80 10827.12 36606.53 74693.33 82555.89 79033.03 82469.88 386435.89
Seychelles 102.46 102.46 102.46 236.68 10266.94 60259.99 140264.25 161552.92 159863.16 161479.56 694230.88
Bisho 38.15 -1647.26 179.89 -1647.26 12825.12 64464.75 112410.19 108321.27 112325.13 108345.44 515615.41
Bloemfontein -280.00 -1292.03 325.47 972.41 17467.61 69399.41 99550.96 94970.10 99457.88 94990.75 475562.55
Cape Town 17212.70 17396.75 17396.75 21759.01 74988.69 135447.41 138013.11 135358.67 138045.44 135358.67 830977.21
Durban 2769.71 2455.64 2883.35 14698.58 62987.35 111209.99 110772.43 111110.68 110794.61 111110.68 640793.03
George 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Lanseria 15263.41 17662.18 15318.49 19411.69 48125.01 88453.01 90511.29 93564.91 90528.67 93564.91 572403.57
D e p a r t m e n t o f T r a n s p o r t P a g e | 235
Impact of the Yamoussoukro Decision: 12th April 2010 - report prepared by Graham Muller Associates
Johannesburg 2144.65 3453.98 3453.98 15075.88 66228.86 101775.09 101775.09 101793.12 101793.12 101793.12 599286.89
Kimberley 1489.32 1326.70 2899.43 1326.70 16027.41 63351.65 99702.98 95326.13 99612.05 95346.67 476409.03
Mafikeng 527.70 2007.42 4324.18 2007.42 13526.42 48925.35 88576.40 83824.97 88483.57 83841.70 416045.12
Nelspruit 908.73 3759.50 6298.77 3759.50 18700.07 62309.05 95784.23 90750.70 95688.43 90766.44 468725.43
Polokwane 300.68 4036.25 6572.51 4036.25 15491.01 50548.42 86533.32 81735.57 86437.42 81748.89 417440.32
Port Elizabeth 1088.46 7440.16 9094.35 15217.50 51391.24 108832.21 132010.30 129465.13 131921.00 129492.81 715953.16
Pilanesberg 0.00 3579.72 5873.56 3579.72 14968.05 47145.88 87800.81 83642.19 87707.22 83657.50 417954.66
Umtata 1372.29 5411.66 7719.39 5411.66 19750.05 63165.63 113296.58 109882.02 113210.13 109904.05 549123.46
Upington 1308.87 8212.50 10349.20 8212.50 21439.74 57166.35 105055.27 102400.43 104968.74 102421.96 521535.57
Welkom 0.00 4509.04 6874.97 4509.04 21166.99 66837.52 100729.91 95714.36 100636.52 95733.63 496711.98
Manzini 510.17 510.17 510.17 510.17 2064.23 14215.41 47651.11 81765.32 85462.82 86061.53 319261.09
Dar-Es-Salaam 3332.27 3332.27 3332.27 5570.79 29180.71 64818.11 119827.06 134255.85 133478.46 134166.97 631294.77
Dodoma 345.40 345.40 345.40 91.25 4192.22 34671.37 64264.35 103795.05 115272.77 112703.35 436026.56
Kilimanjaro -3.66 -3.66 -3.66 767.50 14710.11 52384.64 110811.12 134074.65 133405.28 133992.14 580134.45
Mtwara 356.83 356.83 356.83 1116.95 3008.64 33636.63 63939.98 104318.89 117167.73 114583.95 438843.27
Mwanza 3163.74 3163.74 3163.74 3692.37 15924.03 53018.10 101985.22 128784.99 129744.46 128703.55 571343.95
Zanzibar 642.27 642.27 642.27 1301.20 13689.13 48691.20 99145.39 127719.37 128165.44 127636.67 548275.21
Kitwe -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -770.78
Livingstone 2525.99 2525.99 2525.99 2536.90 4640.43 21610.36 54967.69 86976.14 86805.54 86976.14 352091.17
Lusaka 2428.44 2428.44 2428.44 3523.06 21561.07 44754.28 82799.13 96355.77 94773.22 96355.77 447407.62
Mfuwe 0.00 0.00 0.00 0.00 0.00 0.00 882.18 5101.67 19585.42 61253.02 86822.29
Ndola 231.69 231.69 231.69 800.19 9881.81 34333.10 77186.75 94157.68 91932.11 94157.68 403144.39
Bulawayo 519.34 569.36 519.34 569.36 953.23 12563.28 32803.83 67823.72 85170.24 82798.67 284290.37
Harare 6022.29 6022.29 6022.29 6022.29 9762.06 25050.44 53280.88 83853.89 91076.30 88592.52 375705.24
Hwange 997.51 997.51 997.51 997.51 997.51 3934.91 16905.05 45261.05 73228.30 77412.33 221729.21
Victoria Falls 728.39 728.39 728.39 728.39 728.39 4057.69 18915.69 40772.00 72817.74 77916.00 218121.07
TOTAL 93752.97 127970.55 152841.86 211310.85 746270.63 2020195.17 3668038.46 4848948.65 5310977.47 5240560.13 22420866.74