Determinants of FDI:

Lessons from the African Economies

Journal of Applied Business and Economics, Vol. 9, No. 1, 2009

FDI in Africa

(UNCTAD 2005). Africa accounts for:– Just 2 to 3 % of global FDI inflows,

– Down from a peak of 6 percent in the mid-1970s, and

– Less than 9 percent of developing-country flow receipts compared to an earlier peak of 28 percent in 1976

Foreign Direct Investment by region 1999-2003

Volume of FDI that flows into Africa:

– Only very low as a share of total global FDI flows or even as a share of FDI flows to developing countries,

– Also the share is on a steadily declining for several decades in the past.

FDI (BoP current billion US$)

0

100

200

300

400

500

600

700

North America East Asia &Pacific

Europe &Central Asia

EuropeanMonetary Union

Middle East &North Africa

South Asia Sub-SaharanAfrica

1,999

2,000

2,001

2,002

2,003

Source: UNCTAD (2006)

Foreign Direct Investment by region 2005-06

In 2006, FDI inflow to Africa rose by 20%, twice the amount recorded in 2004.

– Following substantial increases in commodity prices, many TNCs significantly expanded their activities in oil, gas, and mining industries (UNCTAD (2007))

75% of FDI inflows to Africa go to S.Africa and oil- and mineral-abundant countries.

Source: UNCTAD (2007)

Existing Studies

Some Studies deal with the issues of FDI and their potential benefits for developing countries– in terms of employment opportunities, technology

transfers, and growth and development.

Several studies on the determinants of FDI in developed countries and developing countries, – Developed countries or developing countries cannot be

grouped together given their different economic and socio-political conditions.

Some studies concentrate on a region, but few on the African region.

Determinants of FDI – Dunning (1981, 1988) ‘electric theory’

Determinants of FDI

3 set of factors

1. Firm-specific Advantage

2. Location- specific Advantage

3. Internalisation Advantage

1. Economic factors

2. Policy framework

3. Business facilitation measures

benefits for the firm in exploiting its competitive advantages & location advantages by investing in foreign affiliates that they control rather than dealing with unrelated firms located abroad

1. Economic factors

2. Policy framework

3. Business facilitation measures

1. Economic factors

2. Policy framework

3. Business facilitation measures

1. Economic factors

2. Policy framework

3. Business facilitation measures

1. Economic factors

2. Policy framework

3. Business facilitation measures

1. Economic factors

2. Policy framework

3. Business facilitation measures

advantage that the firm has over its rivals in terms of its brand name, patent, or knowledge of technology and marketing

Research focused on the determinants of FDI identified the following factors as attracting FDI:

Comparative labour costs, Level of skills and Expertise, country size, economic openness nature of exchange rate regimes, return on investment, and political factors. Ease of Doing business

Benchmarking starting a business in COMESA countries      

Starting a Business

Region Ease of Doing Business Rank

Overall Ranking: Starting a Business

Procedures to start a Business (Number)

Time to start a Business (Days)

Cost to start a Business (% Income per Capita)

Minimum Capital to Start a Business (% Income per Capita)

World 1st Singapore New Zeland 1 1 0.4 0

  2nd New Zeland Canada 1 5 0.5 0

SSA 1st Mauritius (24 th) Mauritius (7 th) 5 6 5 0

COMESA

Burundi 177 138 11 43 215 0

Comoros 155 160 11 23 188 280

DRC 181 154 13 155 435 0

Djibouti 153 173 11 37 200 514

Egypt 114 41 6 7 18 2

Eritria 173 178 13 84 102 396

Ethiopia 116 118 7 16 30 693

Kenya 82 109 12 30 40 0

Madagascar 144 58 5 7 11 289

Malawi 134 122 10 39 125 0

Mauritius 24 7 5 6 5 0

Rwanda 139 60 8 14 108 0

Seychelles 104 68 9 38 8 0

Sudan 147 107 10 39 51 0

Swaziland 108 153 13 61 35 0.6

Uganda 111 129 18 25 100 0

Zambia 100 71 6 18 28 1.5

Zimbabwe 158 164 10 96 4.32 84

3 Specific Policies determining FDI

1. Rules and regulations governing the entry and establishment of foreign investors in a host country

– e.g., prohibition of entry, restrictions on ownership (joint venture requirement) or liberalization of entry

2. Treatment of foreign investors– non-discrimination in the treatment of foreign and domestic

firms (NT)– preferential treatment of foreign or domestic firms (e.g.,

incentives)– distinguish treatment before and after entry

3. Protection of foreign investors– expropriation and nationalization; fund transfers; and dispute

settlement are key issues in protection

METHODOLOGY

Independent Variables included in the Study

Regression Equation

ititititit

itititit

compolserxmgdp

wagesizeresfdi

7654

321

METHODOLOGY

Natural Resource Intensity (RES): – As posited by the eclectic theory, all else equal,

countries that are endowed with natural resources would receive more FDI.

– Omission of a measure of natural resources from the estimation, may cause the estimates to be biased

– We include the share of minerals and oil in total exports to capture the availability of natural resource endowments.

– A positive determinant is expected

Market Size: – The size of the host market, which also represents the

host country’s economic conditions and the potential demand for their output as well, is an important element in FDI decision-makings.

– Quoting Scaperlanda and Mauer (1969) FDI responds positively to the market size ‘once it reaches a

threshold level that is large enough to allow economies of scale and efficient utilization of resources’.

– To proxy for market size (SIZE), we follow the literature and use real GDP per capita.

The expected sign is positive.

Labour cost: – Labour cost (wage) has always been argued to be a

major component of total production cost Nominal wage rate (WAGE) as a proxy for labour cost. We

would generally expect a negative sign on the coefficient

However, the use of wage may not be entirely correct - Skilled Labour

Human Capital: – Foreign direct investors are also concerned with the

quality of the labour force in addition to its cost.

– A more educated labor force can learn and adopt new technology faster and is generally more productive.

– Higher level of human capital is a good indicator of the availability of skilled workers, which can significantly boost the locational advantage of a country.

– We control and test for the impact of labor quality, using the general secondary education enrollment rate (SER).

corporate tax rates (TAX):– Higher tax levels of the host country would be expected

to deter potential FDI.

– However, there seems to be mixed empirical results as for instance Kemsley (1998) and Billington (1999) have found the host country tax rate to be a significant factor in determining FDI inflows. Wheeler and Mody’s (1992) have found the tax rate of the host country to be insignificant.

Openness (xmgdp): – It is a standard hypothesis that openness promotes FDI

– Empirical evidences (Jun and Singh, 1996) exist to back up the hypothesis that higher levels of exports lead to higher FDI inflows.

– Trade/GDP has been included in the regression to examine the impact of openness on FDI.

Political instability (POL)

– Political instability and the frequent occurrences of disorder ‘create an unfavorable business climate which seriously erodes the risk-averse foreign investors' confidence in the local investment climate and thereby repels FDI away’ (Schneider and Frey 1985).

– Political risk rating as provided by the International Country Risk Guide (2006) has been used as a proxy for Political Instability.

Regression Equation

The dependent variable, FDI, is measured as the net foreign direct investment inflow as a percentage of GDP (see Adeisu,2002; Quarzi, 2005; Goospeed et al, 2006).

ititititit

itititit

compolserxmgdp

wagesizeresfdi

7654

321

DATA SOURCE

The main sources of data series are:– International Monetary Fund’s International Financial

Statistics (IFS) (2006),

– World Development Indicators (WDI) (2006).

– Political risk ratings are obtained from internal country Risk Guide (2006).

ANALYSIS

The Panel data techniques have been employed.

The use of panel data technique allows us to determine the temporal evolution of groups of countries rather than analyzing the temporal behaviour of each of them.

Panel data may have group effects, time effects, or both. These effects are either fixed effect or random effect.

The Hausman test specification, the test recommends the use of fixed effects model

Panel data estimates : Fixed effects

(20 countries x 16 years (1990-2005)) Independent Variables Fixed effect estimates

Constant Res size wage xmgdp pol Ser

-3.64(-1.75)*

0.063(2.26)**

0.19(2.46)**-0.086

(-2.13)**0.34

(4.13)***-0.12

(-2.25)**0.19

(2.22)* 

R2

 Number of obs  Hausman Test

0.45 

320 

Prob>chi2=0.052