Industrial and Structural Transformation in Sub-Saharan Africa - Melo Jaime de, Scientific Director, FERDI Fondation pour les études et ...
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Jaime de Melo
December 16 2015 | Nairobi, Kenya
Industrial and Structural Transformation in Sub-Saharan Africa
Melo Jaime de, Scientific Director, FERDI (Fondation pour les études et
Recherches sur le développement international)
Summary of study commissioned by AFD (1)
Reforms, Growth and poverty
• End of lost generation (70-95); reforms picked up
and macroeconomic distortions fell (here)
• … growth picked up; poverty down sharply (here)
• … but the poverty gap with other regions persists
(here)
• The elasticity of poverty reduction to growth is
varied across regions and lower in SSA (here)
• Are we witnessing another resource-driven
boom-bust cycle? (here)
2
Summary of study commissioned by AFD(2)
Trade and industrialization patterns
• SSA export basket diversified «as expected» (here)
• Export surges have ratchet effect and associated
with real exchange rate depreciation (here)
• Industrialization is poverty reducing mostly in
initally high-poverty countries (here)
• Premature de-industrialization confirmed (here)
• …as in Ethiopia and Mauritius (here)
• Labor has not shifted to high productivity growth
sectors (here) 3
Summary of study commissioned by AFD(3)
De-industrialization but possible convergence by
services activities
• As latecomers, SSA have lower levels of mfg. VA
and employment at mfg. peak (here)
• High labor costslow mfg. Employment ? (here)
• Lack of conditional convergence (here)
• Convergence in services, a possible structural
transformation paradigm for SSA? (here)
• TFA: improve customs &reduce trade costs(here)
4
Summary & Recommendations
• Reforms, favorable external environment growth ↑ and
poverty ↓ (although the elasticity of poverty reduction to
growth is low in SSA)
• Manufacturing has contributed to poverty reduction
especially for those with initially high poverty
• Ressources have not shifted towards high productivity
growth sectors
• SSA has not taken up labor intensive activities (Labor costs
too high because of lack of appropriate skills?)
• Can the service sector (now increasingly tradable) help
convergence?
• Trade costs are high. Take up opportunity offered by TFA to
reduce customs-releated trade costs
5Thank you
6Industrial and Structural
Transformation in Sub-
Saharan Africa
Jaime de Melo
FERDI
Nairobi, The Future of Financing for Development Opportunities: Challenges and
December 16 2015
Danish Priorities for Financing Development in the Next DecadesExtra Material
8Macroeconomic Distorsions and Reforms in SSA 1960-2010
Black Market Premium (%) Reform Index : Giuliano et al. (2013)
Black Market Reform Index
Premium (left axis) (right axis)
Source: Cadot et al. (2015). Figure 4 from UNECA (2014) based on Giuliano, Mishra and
Spilimbergo (2013) 9
(back)GDP Growth and Poverty
GDP per capita growth by
region (1950-2010)
60 1700
58
1600
56
Real GDP per capita
Poverty Headcount
54 1500
Source: Cadot et al. (2015). Figure 2(a) from Rodrik (2011).
52 1400
50
1300
GDP per capita and 48
46 1200
poverty headcount ratio 44
1100
42
in SSA 40 1000
1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011
Poverty Headcount Ratio at $1.25 a day (PPP)
GDP per capita (constant 2011$)
10
Source: Cadot et al. (2015). Figure 2(b) from PovcalNet and WDI. (back)Poverty Headcount Ratio by Region, 1981-2011
80
70
60
Poverty Headcount
50
40
30
20
10
0
1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011
East Asia & Pacific Europe & Central Asia Latin America & the Caribbean
Middle East & North Africa South Asia Sub-Saharan Africa
Note: Poverty headcount ratio at 1.25$ per day (2005 PPP)
Source: Cadot et al. (2015) Figure 5 from PovecalNet. 11
(back)Poverty Reduction (HC) vs. GDP per capita Growth
20%
0%
0% 2% 4% 6% 8%
SSA
15% -10%
y = -3.5631x - 0.0406 y = -4.8361x - 0.4157
-20%
10% SSA
-30%
5%
-40%
0% -50%
ECA SA
-2% -1% 0% 1% 2% 3%
-60% LAC
EAP -5%
MENA
ECA -70%
-10%
MENA -80%
LAC SA EAP
-15% -90%
GDP per capita growth GDP per capita growth
Note: Poverty line at 1.25$ per day (PPP). 101 countries ( 43 SSA). HC= head count
Source: Cadot et al. (2015). Figure 6 from PovcalNet. 12
(back)Resource Abundance and Growth
South is Africa excluded.
RP have had a
relatively stable growth
≈ 5% p.a.
Running out of
steam is attributable to
RR group
Note: Resource-rich = Resource rents > 15% of GDP
Source: Cadot et al. (2015). Figure 7(b) from WDI. 13
(back)Export Concentration in SSSA is driven by RR Countries
8
6
4
2
4 6 8 10 12
GDP per capita (log), PPP
Other Countries Resource-Poor (SSA)
Resource-Rich (SSA) Fitted values
14
Source: Cadot et al. (2015). Figure 9 from IMF, Diversification Toolkit. (back)Export Surges in SSA
(event analysis results)
12
11 Export surges have a
10
ratchet effect on the
9
level of exports…
4.68
8
4.66
7
-5 -4 -3 -2 -1 0 1 2 3 4 5
REER (log)
Sub-Saharan Africa Other Countries 4.64
Source: Cadot et al.(2015). Figure 11 from Woldemichael (2015) 4.62
… and seem to be 4.6
associated with a 4.58
temporary REER -5 -4 -3 -2 -1
Sub-Saharan Africa
0 1 2 3
Other Countries
4 5
depreciation
Source: Cadot et al. (2015). Figure 13 from Woldemichael (2015)
15
(back)In SSA, industrialization is poverty-reducing mostly
in countries with high initial poverty rates
Source: Cadot et al. (2015). Figure 15 from PovcalNet and WDI. 16
(back)Premature de-Industrialization in SSA
.5
.4
SWZ
.3
.2
MUS
.1
0
4 6 8 10 12
GDP per capita (log)
Other Countries Resource-Poor (SSA)
Resource-Rich (SSA) Trend (Other Countries)
Trend (Resource-Poor, SSA) Trend (Resource-Rich, SSA)
Source: Cadot et al. (2015). Figure 16 from WDI. 17
(back)Mauritius and Ethiopia trajectories confirm premature
de-industrialization
Mauritius Ethiopia
10.0 12.0 14.0 16.0 18.0 20.0 22.0 24.0 26.0
8.0
1987
1988 1997
1990 1998 1999
1986 1989 1992 1996
1991 2000
1993 1995 1997 2001
7.0
1994 2002
Manufacturing VA (% GDP)
2003
1985
2004
2005 2002
1999 .
6.0
2006 .
1984 2000
2008 2004
2009 1998 1996
2007 1987
2011 2013
1983
1981
1982 2010 1988 . 2005
1980 2012 1995
1976 2006 2007
5.0
1979
1977
1978 1989 1990
1986 1981
1994
1982 1983
1985 2008
1993 2010 2011
4.0
2013
2009
2012
1991
8.0
3.0
1992
2000 3000 4000 5000 6000 7000 100 150 200 250 300
GDP per capita GDP per capita
Source: Cadot et al. (2015). Figure 18 from WDI. 18
(back)Decomposition of productivity growth in SSA 1960-2010
4
3
2
Static labor reallocation effect
Within-sector effect
1
Dynamic labor reallocation effect
0
1960-1975 1975-1990 1990-2010
-1
-2
Source: Cadot et al. (2015). Figure 22 adapted from Timmer et al (2014). 19
(back)SSA countries are latecomers in
industrialization. They exhibit lower levels of
manufacturing VA and employment at peak
share in GDP
Manufacturing VA (% GDP) Employment in manufacturing
50
.5
Employment in Manufacturing at its peak
40
.4
ZMB
MUS
30
.3
ZWE
MUS
ZAF
CMR LSO
GNB MWI SYC
20
.2
RWA SEN
BFA MOZ
GHA CIV NAM GHA
TCD
BDI
CPV KEN
BEN AGO MRT CAF ERI TZA MDG KEN
BWA NGA
10
.1
SOM GAB TGO SLE SDN UGA
COG SEN
LBR ETH STP NGA BWA
MLI GIN ETH
NER COM ZMB MWI
0 TZA
0
1960 1970 1980 1990 2000 2010 1940 1960 1980 2000 2020
Peak Year Peak Year
Other Countries Sub-Saharan Africa, uncensored
Other Countries Sub-Saharan Africa
Sub-Saharan Africa, censored Fitted values
Trend, Sub-Saharan Africa Trend, Other Countries
Source: Cadot et al. (2015). Figure 23(a) from WDI Source: Cadot et al. (2015). Figure 23(b) from
Groningen Growth and Development Center 20
(back)High labor costs in Sub-Saharan Africa seem to explain
the lack of employment creation in manufacturing
Country comparisons : high mfg. labor costs
… a pattern confirmed by regression
in selected SSA countries …
analysis
2500
8000
GDP per capita (2005 $)
Labor costs in manufacturing, 2005 $
2000
Labor cost, annual
6000
1500
4000
1000
AGO
2000
KEN
ZMB
UGA TZA SEN
500 MLI NGA
ETH MOZ
0 GHA
5 6 7 8 9
0 GDP per capita (log)
Zambia Tanzania Kenya Nigeria Bangladesh India
Other Countries Sub-Saharan Africa
Fitted values Fitted values
Source: Cadot et al. (2015). Figure 25 from
Gelb et al. (2013) Source: Cadot et al. (2015). Figure 26 adapted
from Gelb et al. (2013) 21
(back)Lack of Conditional Convergence in SSA
(positive slope)
10
GNQ
ETH
5
TCD
MOZ GHA CPV
MUS
BFA LSO NAM BWA
SYC
NER GIN KEN MRT
SWZ
0
MWI GNB
TGO
ERI
ZWE
-5
6 8 10 12
GDP per capita PPP in 2000
Other countries Resource-Rich (SSA)
Resource-Poor (SSA) Fitted values
Fitted values, Resource-Rich (SSA)
Note: Slope of the line is the marginal effect of the initial level of GDP per capita
(2000) on subsequent growth (2000-2012) after controlling for human capital
Source: Cadot et al. (2015). Figure 28(b) from WDI. 22
(back)Convergence in services, a possible structural transformation
paradigm for Sub-Saharan Africa?
23
Source: Cadot et al. (2015) Figure 31 (back)OECD Trade Facilitation Indicators for Customs (range : 0-2)
LDCs non-LDCs
Information availability (A)
Involvement of trade community (B)
Advance rulings (C)
Appeal procedures (D)
Fees and charges (E)
Formalities - documents (F)
Formalities - automation (G)
Formalities - procedures (H)
Border agency cooperation - internal (I)
Border agency cooperation - external (J)
Governance and impartiality (L)
Average of OECD TF Indicators
0 .5 1 1.5 2 0 .5 1 1.5 2
Landlocked non-Landlocked LDCs Non-LDCs
Median time in import customs (in days) 5 2 5 2
Median time in export customs (in days) 3 2 3 2
24
Source: De Melo and Wagner (2015). Table 4 (back)References
Cadot, Olivier, Jaime de Melo, Patrick Plane, Laurent Wagner, Martha Tesfaye
Woldemichael, (2015) “Industrialisation et Transformation Structurelle: L’Afrique
sub-saharienne peut-elle se développer sans usines?”, AFD, no 2015-10
http://www.afd.fr/webdav/shared/PUBLICATIONS/RECHERCHE/Scientifiques/Pa
piers%20de%20recherche/10-papiers-recherche.pdf
De Melo and Wagner (2015), “Aid for Trade and Trade Facilitation: What they can
do for LDCs”, FERDI
Gelb, Alan, C. Meyer and B. Ramachandran (2013), “Does Poor Mean Cheap? A
Comparative Look at Africa’s Labor Costs”, CGDEV
Giuliano, P.; P. Mishra et A. Spilimbergo (2013), “Democracy and Reforms:
Evidence from a New Dataset”, NBER working paper 18117.
Groningen Growth and Development Center, 10-Sector Database
http://www.rug.nl/research/ggdc/data/10-sector-database
25References (2)
IMF, Diversification Toolkit: Export Diversification and Quality Databases
https://www.imf.org/external/np/res/dfidimf/diversification.htm
Timmer, M.; G. de Vries et K. de Vries (2014), “Patterns of Structural Change in
Developing Countries”; GGDC Research Memorandum 149.
UNECA (2014), Economic Report on Africa 2014, Addis Ababa, 2014.
Woldemichael, Martha (2015), “Export Accelerations and the Exchange Rate” (in
progress).
World Bank, PovecalNet Database. http://iresearch.worldbank.org/PovcalNet/
World Bank, World Development Indicators Database.
http://data.worldbank.org/data-catalog/world-development-indicators
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