competitive cities...marketplace, but come together on common interests, (e.g. lobbying for...
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Competitive Cities HOW CAN CITIES GENERATE MORE JOBS?
Stefano Negri, Austin Kilroy, Megha Mukim
October 15, 2014
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Overview
Footer Information 2
• Centers for job creation
• Cities have powers to influence and act
Recap: Why are cities important?
Initial results on 3 key questions 1. “How have other cities created jobs and growth?”
2. “What should be top priorities for my city?”
3. “How can I get it done?”
Piloted engagements
• Counties in Kenya
• City of Johannesburg
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SIMPLE VERSION Recap: Why are cities important?
RECAP RESULTS PILOTS NEXT STEPS
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Recap: Why are cities important?
RECAP RESULTS PILOTS NEXT STEPS
“No country has ever reached middle-income status
without a significant population shift into cities”
(Commission on Growth and Development)
5
15
25
35
45
55
65
75
85
95
5 6 7 8 9 10 11
Urb
an
po
pu
lati
on
as %
of
tota
l (2
012)
GDP per capita 2012 (log)
• Many Cities are
not fully
harnessing their
potential.
But….
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Recap: Something is going wrong…
RECAP RESULTS PILOTS NEXT STEPS
• Urban share of poverty in developing
world has jumped from 17% to 28%.
• The world’s urban population continues
to increase by one billion in 10 years.
• How will one billion new jobs be
created?
“What’s all this about competitive/smart/
innovative/productive/global cities, and how can I
make [Kano/Kigali/Karachi] into one?”
“Why is my city 139th on the
Mercer’s/EIU/McKinsey/Brookings city
index? (and does it matter?)”
“How do I make my city into a
nanotechnology/aeronautics cluster?”
“How do I generate jobs in
the next 3 months?”
“I invested $300m in a BRT.
Why isn’t the industrial zone
growing?”
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Mayor’s Wedge
Factor
markets
Output
markets
Firm-level
performance
Agglomeration
We need to understand how cities can leverage their scope and capabilities
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SIMPLE VERSION Team work: Configuring a city resource base
RECAP RESULTS PILOTS NEXT STEPS
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Scope: subnational policy levers to facilitate job creation
A competitive city…
…uses its administrative leverage and capacity
…to make the most of resources at its disposal
…in order to facilitate the private sector
…to grow, create jobs, improve incomes of employees
…and adapt to external shocks through innovation, improved productivity and access to external markets.
STRATEGY SCOPE
& CAPACITY
CATALYZING
FIRMS
PRIORITIZATION GROWTH
PATHWAYS
RECAP RESULTS PILOTS NEXT STEPS
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…generates our three workstreams
STRATEGY SCOPE
& CAPACITY
CATALYZING
FIRMS
PRIORITIZATION GROWTH
PATHWAYS
3. Implementation
• “How do I get it done?”
• (Policy levers; Implementation structures)
2. Decision Support
• “What should be the top priorities for my city?”
• (Diagnostics; Prioritization)
1. Analytics
• “How have other cities created jobs & growth?”
• (Data analysis; Case studies)
RECAP RESULTS PILOTS NEXT STEPS
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SIMPLE VERSION What have we found so far?
RECAP RESULTS PILOTS NEXT STEPS
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SIMPLE VERSION
#1: “How have other cities
created jobs and growth?”
RECAP RESULTS PILOTS NEXT STEPS
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Most cities follow countries in moving up income brackets. But there are some
pioneers that lead the way up…
Low income (<= $1,035 GDP pc)
78 cities
Lower middle income ($1,036-$4,085 GDP pc)
112 cities
Upper middle income ($4,086-$12,615 GDP pc)
75 cities
High income (> $12,615 GDP pc)
137 cities
Low income (<= $1,035 GDP pc)
16 cities
Lower middle income ($1,036-$4,085 GDP pc)
161 cities
Upper middle income ($4,086-$12,615 GDP pc)
59 cities
High income (> $12,615 GDP pc)
166 cities
1
43
14
11
137
5
50
37
2000 2012
= Slow-mover (country progressed but city did not)
= Tide-rider (city moved/not moved with country) = Pioneer (city advanced but country did not)
*Sample set encompasses 400 cities and excludes cities from Argentina, Malaysia, Morocco, Peru, Russia, Serbia, South Africa, Turkey, UAE, Ukraine, USA,
Venezuela because of data availability. China was also excluded because it dominates the upward momentum (including leapfrogging) along the income path.
= Catch-up (city moved after country)
10
3
8
1
48
9
10
5
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SUMMARY DATASETS & INDICES HOLY GRAIL PATH DEPENDENCY GOING FORWARD
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Sectoral shares change as city income levels rise
0%
20%
40%
60%
80%
100%
Se
cto
r S
ha
re o
f To
tal G
VA
(2
01
2)
Each band contains 15 cities in sequential income brackets
High-End Services
Public Services
Consumer Services
Industry and Mining
Agriculture
$1,000 $5,000 $10,000 $20,000 $2,500 $50,000
At early stages of
development cities serve
as a multi-function hub
that involves all sectors.
Then industry starts to dominate
but its share of the GVA tends to
decline as cities grow richer.
High-end services begin to
increase their dominance.
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Key predictors of city outcomes vary by income level
RECAP RESULTS PILOTS NEXT STEPS
Low & lower middle cities:
Institutions and regulations
Upper-middle income
cities:
Innovation
High-income cities:
Human capital
Positive and significant correlation Negative and significant correlation
Determinants of City
Competitiveness
Low to Lower Middle Income Cities
(<$4,085 )
Upper Middle Income Cities
($4,085-$12,615)
High Income Cities
(>$12,615)
Disp.
Income
Labor
Prod.
GDP
Growth
Job
Growth
Disp.
Income
Labor
Prod.
GDP
Growth
Job
Growth
Disp.
Income
Labor
Prod.
GDP
Growth
Job
Growth
Institutions & Regulations (EIU institutional effectiveness: level
of corruption, transparency, fiscal
autonomy)
Physical Infrastructure (EIU and UN infrastructure index:
public transport, telecom; Doing
business: cost of electricity)
Social Infrastructure (UN Quality of Life; EIU social and
cultural index; Healthcare index)
Human Capital (Education; EIU human capital:
healthcare, entrepreneurship,
working age population)
Innovation (Number of patents)
Access to Finance (Doing business: Credit bureau
coverage; EIU financial maturity:
breadth and depth of financial
cluster)
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Case studies are designed to understand the ‘how’
Case Studies document how and why actions led to growth and job creation.
We chose one top performing city in each Region (database of 750 cities).
Focus on ‘teachable moments’ for other cities.
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• 5 of 7 case
studies have been
completed.
• Each case study =
background research
+ two weeks
fieldwork interviews
15 RECAP RESULTS PILOTS NEXT STEPS
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Strategic interventions; growth coalitions; and leverage
Mayor’s Wedge
Factor
markets
Output
markets
Firm-level
performance
Agglomeration
• Co-created with
private sector;
• Role of public
sector to incentivize
quality and uptake.
• Effective internal
management
structures;
• Fostering
productive inter-
institutional
collaboration.
• Appropriate and
effective
infrastructure;
• Lobbying &
leveraging
national and
provincial
investments.
• Reinvesting
profits in local
economy;
• Leveraging
national support
programs.
RECAP RESULTS PILOTS NEXT STEPS
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What does it look like in practice? Gaziantep, Turkey
Local firms:
• Fierce rivals in
marketplace, but
come together on
common interests,
(e.g. lobbying for
infrastructure
upgrades)
Two main business
chambers (commerce
and industry):
• Large professional
staffs, budgets, and
political influence.
• Help determine
priorities, build
consensus, and
advocate on behalf
of business
interests.
Municipality:
• Supportive, not
dominating
• Business-friendly,
not highly educated!
(70% with degrees
in 1989; down to
35% in 1999)
City Council:
• Forum for
information sharing
and consensus.
• >300 members,
(80% private sector,
universities, or civil
society;
20% public sector).
• Several thematic
working groups
issuing
recommendations.
Credible individuals with a track record of
success (e.g. President of Sanko Holdings,
one of the largest firms in Turkey—based in
Gaziantep).
Firms said “we did it ourselves”…
But on investigation we found good instruments:
• Effective Organized Industrial Zones
• Funding for education and research
• Tax incentives (six-tier system of regions)
• Subsidies to travel to trade fairs
• SME and entrepreneurial assistance
RECAP RESULTS PILOTS NEXT STEPS
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• Kigali: apex city for the country; aiming to
become a regional center in Great Lakes;
• Bucaramanga: innovation center for oil
industry in neighboring Barrancabermeja;
regional center of higher learning;
• Coimbatore: functional synergies in textile
industry (production in neighboring Tirupur;
product design, training, management in
Coimbatore);
• Gaziantep: pistachios grown near Hakkari, but
processed in Gaziantep; cotton grown in Urfa,
but processed in Gaziantep; regional node on
the ‘silk road’…
• Changsha: leading city in a cluster of
Xiangtan and Zhuzhou.
Effective cities build competitive advantage with their hinterlands
RECAP RESULTS PILOTS NEXT STEPS
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SIMPLE VERSION #2: “What should be the top priorities for
your city?”
RECAP RESULTS PILOTS NEXT STEPS
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Systematic frame for diagnostics and decision support
RECAP RESULTS PILOTS NEXT STEPS
1. Combine a city snapshot…
3. Clarify the logic of interventions…
2. …with diagnostics on growth pathways.
4. …and support decisions with multiple criteria
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Level 1:
Highlight city-
wide
competitiveness
factors
Level 2: Dissect industry structure
Level 3: Reality check on industry needs
Competitiveness
factors
Sectors Sizeband Ownership
Manuf.
(E.G.)
ICT
(E.G.)
SMEs
(E.G.)
MNCs
(E.G.)
Foreign
owned
Local
busine
ss
Institutions and
regulations
Taxes, licenses, duties
Legal system
Market regulations
Local government
Infrastructure
Physical infrastructure
Social Infrastructure
Housing
Skills and
Innovation
Human Capital
Education & research
Networks
Access to Finance Financial maturity
Cost of credit
Agglomeration Industrial mix/clustering
Local supply chains
Other
Endowments
Location, & history, amenities
City image and other Intangibles
3 levels of
diagnostics
CONTEXT DIAGNOSTICS PRIORITIZATION CONCLUSIONS
Constraints and opportunities can be examined at city-wide and
industry-level scales…
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SIMPLE VERSION #3: “How do I get it done?”
RECAP RESULTS PILOTS NEXT STEPS
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Mayor’s Wedge can take a toolbox approach to implementation
RECAP RESULTS PILOTS NEXT STEPS
Leverage scope and capacity
= Government powers and functions
+ Ability to perform functions well
Learn from implementation techniques
i. Turnaround cities: Projectized initiatives, and a sense of urgency to organize, lead and deliver.
ii. Economic development agencies: Aggregating priority efforts in a single accountable organization
(with powers). Professionalized service offering.
iii. Day-to-day management: Performance and efficiency improvements for cities to manage their
basic functions.
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The Mayor’s Wedge matters to city competitiveness
Scope: Local
Spending (as a %
of total spending)
Financial
Autonomy:
Local Revenue
(as a % of total
revenue)
Correlation co-efficient (unit: % change) -0.004 -0.002 0 0.002
INCOME
GDP
JOBS
PRODUCTIVITY
• Delegating more public functions
to mayors, i.e. expanding the
scope of a mayor’s administrative
remit is associated with higher
levels of employment.
• However, financial autonomy is
negatively associated with
economic outcomes! (i.e. to
avoid mismatch of local functions
and budgets, cities do better when
central governments still provide
transfers to local governments…).
How did cities in China use their Mayor’s Wedge?
Tax and fees - Cities enjoyed a higher urban construction tax
- Could collect the surcharges levied on the issuing of motorcycle registration.
Land-related policies - Cities generally convert more land to construction use and retain a larger
share of revenue from land sale.
Administrative powers - Cities have more authority on foreign trade and exchange management.
- Could establish branches of custom and large state-owned banks.
- Could approve projects with a higher investment cap.
Government size;
Rank and salary;
Reputation
- Cities could establish more branches of government and have a larger
number of government employees.
- Cities generally carry greater prestige and are more attractive to
investors from outside.
Findings in China:
• Scope is a necessary,
but not sufficient
condition for city
competitiveness
Scope alone does
not lead to better
firm level outcomes;
Scope combined
with capacity does
help firms grow
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What can we learn from success? Turnaround Cities
Key success factors
Lagos goes from
failing to functioning
megacity….
• Lagos State Government began reforms with the civil service:
removing “ghost workers”;
reassigning staff based on their expertise;
increasing salaries and helping workers afford large life expenses
(such as saving for a home) to boost morale;
• City’s inept tax agency was replaced entirely, and new agency
functioned like a private sector company:
flexible hiring and firing (replacing permanent appointments);
rotating roles for officials to avoid corruption;
complaints’ office and public phone number (encouraging citizens to
pay taxes by offering customer service);
• Increasing tax collection—by creating special govt department for
formal and informal taxpayers:
government met regularly with stakeholder groups, to agree on such
things as tax rates for informal workers);
• Lagos’ turnaround followed a plan for about 10 years (through two
administrations):
adequately budgeted for the plan;
monitored its success with performance-based approaches;
led by a proactive leadership of Governors Tinubu and Fashola.
RECAP RESULTS PILOTS NEXT STEPS
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SIMPLE VERSION Where are we currently using this approach?
RECAP RESULTS PILOTS NEXT STEPS
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Engagements on technical support and lending are growing
Engagement in progress (RAS, ESW, NLTA)
Initial discussions
South Africa RAS (TTL: David Sislen; co-TTL Austin Kilroy). • Phase 1 completed in Johannesburg; Phase 2 commencing.
• Phase 1 commencing in Cape Town.
• Other cities forthcoming.
Burundi Urbanization Review (TTL: Jonas Parby / co-TTL Megha Mukim).
• CCKB assisting on city and industry
diagnostics, prioritization framework and
implementation strategies
Engagement being planned
Sfax NLTA being requested
Rwanda lending operation
under discussion Tanzania lending
operation
under discussion
Shanghai 2050 (TTL: Paul Procee).
• CCKB providing technical inputs.
Kenya Urbanization Review
(TTL: Dean Cira / Sheila Kamunyori).
• CCKB assisting on Kenyan
counties’ competitive advantages
and implementation strategies.
Malaysia RAS (TTL: Judy Baker).
• CCKB providing technical inputs
to RAS team.
RECAP RESULTS PILOTS NEXT STEPS
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SIMPLE VERSION Pilot: Diagnostics for Kenyan counties
RECAP RESULTS PILOTS NEXT STEPS
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1. WE BENCHMARKED COMPETITIVENESS ACROSS COUNTIES
0
0.05
0.1
0.15
Counties gaining competitiveness
Jobs in old firms Jobs in new firms
0
0.1
0.2
0.3
0.4
0.5
Counties becoming less competitive
Jobs in old firms Jobs in new firms
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08Difference beetween shares of national total of jobs in new fims and in old firms
Source: Team analysis of Kenya Census of Industrial Production 2010
RECAP RESULTS PILOTS NEXT STEPS
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2. WE ANALYZED FIRM-LEVEL DATA: COUNTIES ARE GAINING/LOSING SHARE
Nakuru
Machakos Nairobi
Existing Firms Emerging firms
Source: Team analysis of Kenya Census of Industrial Production 2010
RECAP RESULTS PILOTS NEXT STEPS
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3. WE ANALYZED COUNTY DYNAMISM
RECAP RESULTS PILOTS NEXT STEPS
Exis
tin
g F
irm
s
Em
erg
ing
Fir
ms
Investment Sales
Nairobi 52%
Kiambu 2%
Mombasa 1%
Machakos 1%
Nakuru 1%
The rest -43%
Nairobi 71% Kiambu
5%
Mombasa 0%
Machakos
1%
Nakuru 0%
The rest 23%
Nairobi 58%
Kiambu 9%
Kericho 2%
Bomet 1%
Kajiado 1%
The rest 29%
Nairobi 40%
Kiambu 15%
Kericho 4%
Bomet 2%
Kajiado 0%
The rest 39%
Nairobi 17%
Kiambu 13%
Kericho 10%
Bomet 7%
Kajiado 5%
The rest 48%
Nairobi 16%
Kiambu 5%
Kericho 20%
Bomet 13%
Kajiado 0%
The rest 46%
Export
Source: Kenya Census of Industrial Production 2010
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4. WE MADE A STRUCTURED CRITIQUE OF COUNTY ECON DEVT PLANNING
Global experience
suggests city strategies
need….
How does Kenyan county economic development
plans compare?
Commitment of local
government First plans prepared too quickly; county govts not really bought-in
Institutional structure Is present, but in many just depicts the status quo
Use analytics Most use analytics, but a lot lack good data
Leveraging local assets Only the Nairobi plan includes a review of ongoing policies and
existing institutions
Clear measurable, realistic
goals/ evaluation Most plans lack this, even though M&E and clear goals are ‘required’
Balance between strategic
goals and quick wins Quick wins and pragmatic approach sometimes lacking.
Engagement of local actors
from early stages Participatory process somewhat pursued, but not very efficiently.
Secure stream of funding, and
budgetary process Most counties create a wish list nor linked to funding.
Links to the national process All plans start from linking cities objectives to Kenya 2030
Institutionalization Uncertain if plans ensure continuity
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SIMPLE VERSION Pilot: RAS with City of Johannesburg
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1. WE IDENTIFIED RELEVANT COMPARATORS
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• Except for the period of extremely strong job creation in 2005-2006 Joburg has been behind its direct comparators.
The nature of the incredibly fast growth 2005-06 needs to be investigated further.
• Johannesburg was severely hit by crisis and experienced the highest jobs loss among its direct comparators in
2009
• However Joburg has been recovering strongly since 2009 and has been performing better than Shanghai and
Santiago, cities where jobs growth has slowed down rather dramatically.
-5%
0%
5%
10%
15%
20%
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
An
nu
al
gro
wth
rate
of
em
plo
ym
en
t Johannesburg
Santiago
Sao Paulo
Shanghai
Warsaw
Belo Horizonte
Copenhagen
Hangzhou, Zhejiang
Kuala Lumpur
Frankfurt
Hong Kong
London
New York
Source: World Bank team analysis of World Bank and Oxford Economics Data,. N.B. Data are estimated for 'metropolitan areas' which do not always correspond to administrative
boundaries of each city. In Johannesburg's case, the metropolitan area covers City of Johannesburg plus some neighboring parts of Gauteng.
2. WE BENCHMARKED CITY-LEVEL PERFORMANCE OVER TIME
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3. WE DISSECTED THE STRUCTURE OF JOHANNESBURG’S ECONOMY
Source: Quarterly Labor market survey 2013 Q3, Statistics South Africa
N.B.:
Location Quotient (LQ)
measures to what extent
an industry is over or
under represented by
jobs in the city relative to
jobs in the national
economy.
Here, we take key
opportunities as being
sectors with high LQ and
high absolute
employment numbers.
Priority sectors
may be existing
concentrations,
plus Green and
Logistics?
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4. WE IDENTIFIED SOME POTENTIAL ‘STRATEGIC BETS’
Industry Reason for selection / non-selection
Primary focus
industries
R&D • Existing specialization
• Potential for creation of jobs with high multiplier effects
• Opportunity to link local academic and industrial expertise
Special
Equipment
manufacturing
• Existing specialization
• High value added and job multipliers
• Link to local academic strength
Logistics • Favorable geographic location
• Proximity to a major port
• Potential for middle-range skill job creation.
Construction • Potential for large scale low skilled job creation
• Relative underrepresentation in the local economy
Small and
medium
enterprises
• Key job creators
• While needs differ by industry, often face similar growth
barriers.
Secondary focus
Financial
Services
• Has potential to build on the role of a regional financial
center
• But far behind global leaders
Legal Service • Opportunity based on expanding demand from real sector
across South Africa
IT – services/
BPO
• Has good IT infrastructure, and skilled population
• But labor costs are too high, and possibly is too late to
move into this market.
Green economy Addressed in a separate presentation
Following
slides
zoom
into
these
sectors
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5. WE BENCHMARKED EACH ‘STRATEGIC BET’
Ongoing Internationalization of R&D is driven by several factors:
• Increased mobility of knowledge and technology, means that companies need to be at the global frontier
to compete.
• At the same time with liberalization and emergence of new centers of expertise (including those in
developing world) the nature of corporate R&D offshoring changed from “home-base-exploiting” – when
knowledge is generated centrally and then exploited on foreign markets, to “home-base augmenting” –
exploiting expertise in external locations to generate new knowledge and use it on home markets.
• While codified knowledge is easily transferable, transfer of tacit knowledge (that is essential for
innovation) relies on proximity. At the same time modern communication technology supports
coordination of research projects even if the teams are spread around the world.
• “Pull” factors that attract R&D activities may vary. In some cases proximity to center of expertise (TATA
motors), in others it is proximity to manufacturing and centers of production (IBM).
Source: Asalkawa, K. (2006) http://www.rieti.go.jp/en/special/policy-update/024_2.html ; Ernst, D. (2006). Innovation
Offshoring Global Innovation Networks.
Tata motors - Indian car manufacturer locates its R&D
labs in Coventry, UK and Torino, Italy – established
centres for vehicle engineering and Design
IBM has to R&D labs in China, where most of its chips
are manufactured, this allows for faster feedback
loops with local contractors.
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Key enabling
factors Why?
Producing
knowledge
Top Universities
and academic
stars
R&D labs benefit from proximity to leading reserves in their field. This allows them exchange
information and ideas informally and makes formal collaboration easier. Research by Moretti has
shown that production of cutting edge innovation relies immensely on presence of world leading
scholars.
Talent You can’t rely on academic superstars alone to do the heavy lifting. Running a large R&D operation
requires a relatively large pool of qualified specialists.
Business
environment
Transport and IT
infrastructure
Staying connected and keeping the information flowing is essential for research. This means being
able to communicate digitally, as well as being able to catch a plain to key destinations in the world,
as well as to easily get to the nearby University for a meeting or a lab test.
Competition and
entrepreneurship
Vibrant entrepreneurial scene where academic ideas are quickly picked up by dynamic businesses ,
developed and taken to the markets offers great opportunities to large R&D operators. Both in terms
of enlarging pull of ideas and labor, and in terms of acquiring products and innovations.
Finance
R&D operations require long term high risk investment. Corporations may have various sources of
financing their R&D activity, start-ups and university spin-offs require mature financial institutions, that
can offer products that are adjusted to their needs.
Regulations
R&D business need to be able to move quickly to stay at the cutting edge. Bureaucratic barriers may
slow them down. Efficient IP registration and protection, open immigration regime, low import-export
barriers will be of significant importance for a R&D business.
Quality of
life
Safety, housing
affordability.
Establishing an overseas R&D lab means transferring your key managers there and attracting top
global talent to the location. Quality of life, affordability of housing and safety are factors that will
influence these decisions.
• Overall, international corporate R&D is most likely to seek locations where cutting edge expertise in the
subject is combined with conducive institutional environment and good infrastructure and quality of life.
• So: how does Johannesburg score on innovation, business environment and quality of life?
[See the following three slides]
Source: Moretti, E., Wilson, D. J., & Berkeley, E. M. (2013). Star Scientists and Jobs : Evidence from Biotech, Clayton, N., &
Sivaev, D. (2013). Driving growth : innovation in Coventry and Warwickshire, (May).
5. WE BENCHMARKED EACH ‘STRATEGIC BET’ (continued)
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0
2
4
6
8
10
12
14
16
Num
be
r o
f U
niv
ers
itie
s m
en
tio
ne
d
in g
lob
al ra
nkin
gs Number of Universities
in Times HE top 400
Number of schools InShanghai ranking (top400)
Number of schools inQS ranking
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%
Johannesburg
Sao Paulo
Belo Horizonte
London
New York
Warsaw
Hong Kong
Share of working age population with university degrees
1 4 6 0
105
140
13 1
21 4 0 1
0
20
40
60
80
100
120
140
160
Num
ber
of academ
ic s
tars
work
ing
for
local academ
ic in
stitu
tio
ns
0
20
40
60
80
100
120
140
Num
ber
of N
atu
ral scie
nce, Life s
cie
nce o
r m
ath
depart
ments
in
QS
depart
ment
rankin
g
Does Johannesburg have the skills base and the research capacity to become an R&D hub?
• Johannesburg is behind comparators both in terms of strength of academic institutions and
education levels of the labor force
Source: http://academic.research.microsoft.com/ ; http://ideas.repec.org/; http://www.timeshighereducation.co.uk/ ;
http://www.shanghairanking.com; http://www.topuniversities.com, and various national statistics agencies
5. WE BENCHMARKED EACH ‘STRATEGIC BET’ (continued)
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Can Johannesburg offer business environment that R&D investors would require?
0
1
2
3
4
5
6
7
8
9
Pro
pe
rty r
igh
ts p
rote
ctio
n in
de
x
(na
tio
na
l le
ve
l)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Tota
l assets
of
larg
e inte
rnational
financia
l in
stitu
tions h
eadquart
ere
d i
n the c
ity
(mill
ion
$U
S)
SM
E lendin
g a
s s
hare
f G
DP
SME lendingas a shsre ofGDP (nationallevel)
Total assets oftop 500financialinstitutionspresent in thecity (proxi forfinancialmaturity of the place)
0 5000 10000 15000
Johannesburg
Santiago
Sao Paulo
Belo Horizonte
London
New York
Frankfurt
Warsaw
Hong Kong
Shanghai
Hangzhou
Kuala Lumpur
Average internet download speed (kbps)
0
10
20
30
40
50
60
0
5
10
15
20
25
30
Pers
on
al
Inco
me t
ax
Corp
ora
te T
ax
CoporateIncometax rate
PersonalIncometax rate
• High taxes and quality of internet infrastructure may be limiting Johannesburg’s competitiveness?
• However financial sector is relatively mature, and South Africa performs well on property rights protection.
Source: Propperty rights index (national level) http://www.internationalpropertyrightsindex.org/data; GaWC 2012 data. On headquarters of
financial institutions in the city, http://www.lboro.com/gawc/, Doing Business, World bank; http://www.numbeo.com/cost-of-living/
5. WE BENCHMARKED EACH ‘STRATEGIC BET’ (continued)
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In Johannesburg these were--
Spatial policy lens…..
“How to leverage the BRT corridors for industrial development around nodes?”
Structured case profiles of Cleveland, OH; Austin, TX
Investment policy that matches city priorities with firm needs (sector profiles)
…and link to Land & Housing colleagues to advise on structuring land transactions
Industry policy lens…..
“What are the plausible growth paths for Soweto?”
Emphasis on realistic objectives; “starting from where you already are” (industries, capabilities)
Proactive strategies for investment promotion:
(a) portfolio approach; (b) anchor ‘mothership’; (c) upgrade existing SMEs.
Emphasis on competitive advantage through differentiation and tradable goods & services
“How do we grow a Green hub?”
Cautionary tales of mismatched training and overestimated product demand
Guidance on flexible industry partnerships, with built-in feedback loops
Technical inputs for a US$1m catalytic fund to spur industry-research collaborations
Procurement policy lens…..
“Can we use city procurements for local economic benefit?”
Programmatic approach:
(i) buyer coordination; (ii) matchmaking; (iii) diagnostics; (iv) upgrading.
6. WE CALLED IN TECHNICAL EXPERTS TO DO DEEP DIVES ON KEY ISSUES
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SIMPLE VERSION Next steps…..
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Products under development…
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1. Evidence base
• Nuancing of analytic work (lag-times; inflection points; new data)
• Consolidated case studies
2. Diagnostics & Decision Support
• More detail and variety for industry diagnostics
• Finesse prioritization tools (help us focus this on your priorities)
3. Implementation support
• Consolidated literature on public sector management for cities
• Mayor’s Wedge framework with institutional assessment
• Case studies and critical pitfalls (help us focus this on your priorities)
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SIMPLE VERSION APPENDIX
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Competitive Advantages and Proactive Sector Targeting Successful cities have demonstrated an understanding of their competitive advantages and utilized
proactive strategies to support specific growth industries.
City Existing
Industries Analysis Leveraged
Targeted
Industries
Proactive
Interventions
Bu
cara
man
ga
Shoe &
apparel
manufacturin
g, food
processing/
agribusiness,
petroleum-
related
Chamber of
Commerce
analysis
(global
competition to
existing
industries,
existing firm
capacity, etc.)
1. Existing knowledge
and capacity in science
and engineering (oil
industry)
2. High levels of human
capital from historically
strong education
system
3. Existing firm capacity
1. Medical Devices,
Precision
Mechanical Parts
2.Knowledge
Service
Outsourcing
3. Higher Value-
Added
Confectionery
4. Medical Tourism
1. Vocational
training
partnerships
2. FDI attraction
3. Strengthening of
industry-academia
linkages,
technology
commercialization
4.Place marketing
Co
imb
ato
re
Mechanical
engineering,
textiles, food,
jewelry
Private SEZ
developer
analyzed
market trends,
identified
opportunities to
attract MNCs
from 1st tier
Indian cities
(spillover)
1. High levels of human
capital, esp. engineers
2. Low business costs
3. Decent infrastructure
4. Geographic proximity
to auto cluster in
Chennai
5. Engaged private
sector
6. Supportive
ecosystem
1. IT/ITES/BPO
2. Mechanical
engineering
3. Tourism
4. Logistics
1. Infrastructure
upgrades (e.g. new
airport, SEZs)
2. FDI attraction by
private SEZ
developer
3. R&D and testing
facilities
4. Trade fair
complex
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City Existing
Industries
Analysis Leveraged Promoted
Industries
Proactive Strategies
Kig
ali
Tourism,
trade services
(agriculture),
construction
and real
estate
National gov.
analyzed
constraints
(competition to
existing industries,
constraints to
manufacturing)
1. Existing firm
capacity in
tourism services
2. Large youth
population
3. Donor funding
1. Niche, high-
end gorilla
tourism
2. ICT industry -
ongoing
development
1. Tourism permit fees to
keep demand up/supply
low
2. Attraction of educational
programs (CMU)
3. Industry specific
infrastructure (4G)
Gazia
nte
p Carpets,
food, plastics,
chemicals,
textiles,
shoes, metal
machinery,
construction
National SME
agency, chambers
of industry and
commerce, GAP,
Silk Road Dev’t
Agc
1. Existing firms
2. Strategic
geog. location
(border)
3. International
ties (incl. family)
4. Low costs
1.
Manufacturing
(carpets, food,
const.
materials)
2. Tourism
3. Healthcare
1. Organized IZs
2. Land allocation pref
3. Improved infrastructure
4. Trade fairs
5. Inbound & outbound
trade missions, GTO office
6. Sister-city agreements
Ch
an
gs
ha
Construction
engineering,
low value add
manufacturin
g, historically
agriculture
City analyzed lack
of industry
diversification,
need for low &
high skill level jobs
(and analyzed in
light of nationally
targeted
industries)
1. Skills from
construction
engineering &
existing firm
capacity
2. Low cost
manufacturing
and large
consumer mkt
1. Construction
engineering
2. Automobile
parts
manufacturing
3. Higher value
added
manufacturing
(electronics)
1. Promoted international
linkages to input suppliers
and new market
opportunities
2. Preferential policies in
SEZs
3. Linkages to local input
suppliers and vocational
training programs
Competitive Advantages and Proactive Sector Targeting
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Institutions &
Regulations Infrastructure Financing
Skills &
Innovation
PRIVATE
SECTOR
CITY GOVT
NATL GOVT
City Roads
Water
Public Transport
Sanitation
Highways
Ports, Airports
National Grid
PPP Laws
Bidding for,
implementing
Infrastructure
Projects
Raising capital
Knowledge hubs
Linking firms with
academia
Talent
Recruitment
Training
Programs
R&D
Immigration
Policies to attract
talent
National Skills
Development
Plan
National Tax
Revenues
Fiscal
Management
Municipal Tax
Revenues
Road, Water
Taxes
City Bonds
Equity and
Debt
Lobbying for
industry-specific
policy changes
Land use
planning
Taxes &
incentives
Coordination &
performance
Macroeconomic
management
Inter-Ministerial
coordination
What can cities do about it? [“Mayor’s wedge”]
“Mayor’s
wedge”:
Highly
variable by
country
and by
type of city;
in some
cases very
small
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Africa
9%
EU
25% Asia
18%
Philippines
14%
Uganda
34%
Brazil
26%
Mexico
7%
South
Africa
17%
Moldova
25%
Belarus
36%
INTRODUCTION MAYOR’S WEDGE INSIGHTS THE “HOW”
Local government spending (as a % of total government spending).
Source: UCLG 2009 (based on IMF Government Finance Statistics).
Cities powers and resources to act vary worldwide
Darker the shade of blue = larger mayor’s wedge.
LAC 11%
• Strong devolution to
cities (with extensive
co-sharing);
• Relatively high city
spending and revenue;
• Directly elected mayors
• Cities dependent on
strong States;
• Low city spending
and revenue;
• (but country is now
decentralizing…)
China
50%
ECA
27%
• Strong national
and state
agencies;
• Substantial
devolution;
• Cities can
impose array of
taxes
• Government organized in interdependent spheres;
• Metro cities with considerable revenue;
• Metros have issued bonds
• Low city revenue;
• But high levels of
local govt spending
(conditional
transfers);