divergence big time: geography matters nicholas crafts the maddison lecture, october 9, 2013
TRANSCRIPT
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Divergence Big Time: Geography Matters
Nicholas CraftsThe Maddison Lecture, October 9, 2013
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Modern Economic Growth
• Post industrial revolution era
• Driven by technological progress that has substantial impact on productivity growth
• Need appropriate institutions and policies to take advantage of the opportunity
• Penalty for getting it wrong gets much bigger; income divergence is not new but increases dramatically
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Real GDP/Person ($1990GK)
1870 1913 1950 1973 2010
Asian Tigers 394 603 1010 3631 23313
China 530 552 448 838 8032
India 533 673 619 853 3372
Africa 648 908 889 1387 2034
W. Europe 2006 3488 4517 11346 20889
USA 2445 5301 9561 16689 30491
Source: The Maddison Project (2013)
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Divergence Big Time
• 20th century growth unprecedented; GDP gap
much greater than ever before
• Clearly not unconditional β-convergence so
the pure neoclassical prediction does not work
• Conditional β-convergence is a viable
hypothesis – but what are the key conditions?
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The Solow Model in a Globalized World
• Y/L = A(K/L)a
• Diminishing returns to capital accumulation
• Technology universal
• Factors mobile, K/L equalized across countries
• Beta and sigma convergence
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20th vs. 21st Century
• “The restoration of inter-society income equality will be one of the major economic events of the century to come” (Lucas, 2000)
• So divergence will be superseded by convergence and normal (neoclassical) service will be resumed
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Lucas’s Underlying Argument
• Obstacles to growth removed through imitation of good policies, institutions
• In a globalized world, capital mobility and financial liberalization relax the savings constraint
• Speed of catch-up growth will increase markedly and K/L and TFP gaps will be rapidly reduced
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Why Might the Solow Model Be Wrong?
• TFP is not the same across all countriesbecause either efficiency or technology is not universal
• Obstacles to factor mobility prevent equalization of K/L
• Geography, institutions or economic policies differ
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The North/Acemoglu View
• Institutions which affect investment and innovation are the underlying determinants of economic performance
• Institutions are formal and informal constraints that structure behaviour
• Property rights are the key to high incomes today and thus to divergence over time
• Institutions are persistent
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Rule of Law Scores (-2.5 to +2.5)Kaufmann et al. (2013)
1996 2012 1996 2012
Brazil -0.33 -0.11 Netherlands 1.65 1.84
China -0.43 -0.49 Nigeria -1.26 -1.18
India 0.26 -0.10 Singapore 1.28 1.77
Russia -0.87 -0.82 USA 1.45 1.60
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Institutions and Growth
• Important but surely not all that matters
• Institutional quality may not be well measured but growth regressions do not suggest it dominates recent differences in performance
• Policy plays a part and so too does geography
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Growth of Real GDP/Person, 1960-2000
(% per year)
Resource-Scarce &Coastal
Resource-Scarce &Landlocked
Resource-Rich
Africa 0.50 (33)
-0.36 (33)
0.29 (33)
Other Developing
3.79(88)
1.40(1)
2.89(11)
Source: Collier (2007); numbers in parentheses refer to percentages of population in each category
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Divergence Big Time
• Persistent and widening income gaps characterize modern economic growth era
• Institutional/policy failures matter much more when growth opportunities increase BUT there is a strong spatial correlation of development outcomes
• Does this mean that geography undermines the mainstream assumption of a ‘level playing field’ for development ?
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Geography and Income
• Geography may preclude full convergence
• Natural resources and market access; 1st and 2nd nature aspects
• Direct and indirect effects
• Indirect effects may work through institutions, e.g. ‘natural resource curse’
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New Economic Geography: Key Ideas
• Agglomeration Benefits
• Market Potential
• Trade Costs
• Globalization may imply divergence
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Transport Costs and the Location of Economic Activity
• Very High or Very Low: everything dispersed
• Intermediate: centralization of industry based on location in larger market with increasing returns and external economies of scale
• So New Economic Geography says that even with perfect institutions everywhere integration of markets may lead to divergence
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Globalization and the Inequality of Nations (Krugman & Venables, 1995)
• Manufacturing goods are subject to increasing returns and are used both as final and as intermediate goods
• As transport costs fall, self-reinforcing advantage of larger market leads to country-specific external economies of scale and lower costs for manufacturing in core relative to periphery
• Eventually, if trade costs fall enough and/or wages in the core rise enough, manufacturing returns to (parts of) the periphery
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Market Potential
• Market access matters for industrial location decisions; operationalized by ‘market potential’ which is distance (transport costs) -weighted GDP
MPi = ∑GDPjdijγ
• If data permit, can estimate γ using gravity model; traditionally assumed that γ = -1
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Late 20th Century Empirics (Redding & Venables, 2004)
• There is a high correlation between location and income so, following Acemoglu’s strategy, this also might explain divergence big time
• Market potential elasticity around 0.3
• Location effects largely robust to including institutional quality
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Figure 4 : GDP per capita and MA = DMA(3) + FMAln
GD
P p
er c
apita
(U
S d
olla
rs)
ln MA = ln(DMA(3) + FMA)13.183 22.754
6.1569
10.2581
ARG
ARM
AUS AUT
BGD
BGR
BLX
BOL
BRA
CAF
CANCHE
CHL
CHN
CIVCMR
COG
COLCRI
CZE
GERDNK
DZA
ECUEGY
ESP
EST
ETH
FIN FRA
GAB
GBR
GRC
GTM
HKG
HND
HRV
HUN
IDN
IND
IRL
ISL
ISRITA
JAMJOR
JPN
KAZ
KEN
KGZ
KOR
LKA
LTULVA
MAC
MAR
MDA
MDG
MEX
MKD
MNG
MOZ
MUS
MWI
MYS
NIC
NLD
NOR
NPL
NZL
PAK
PANPER
PHL
POL
PRT
PRY
ROM RUS
SAU
SDN SEN
SGP
SLV
SVK
SVN
SWE
SYR
TCD
THATTO
TUN
TUR
TWN
TZA
URY
USA
VEN
YEM
ZAF
ZMB
ZWE
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A Prediction
If Zimbabwe were re-located to Hungary, real GDP per person would rise by 80 per cent
Redding & Venables (2004)
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Changes in 19th-Century Economic Geography
• Industrialization and de-industrialization in globalizing world
• Concentration of world manufacturing production and, even more so, exports
• Changes in location influenced by transport costs; manufacturing cities proliferated in Europe and North America; mass production and mass distribution
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Source: Harley (1988)
Real Cost of Ocean Shipping (1910=100)
0
50
100
150
200
250
300
350
1750 1830 1870 1910
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Shares of World Manufacturing Output (%)
1750 1830 1880 1913
Europe 23.2 34.2 61.3 56.6UK 1.9 9.5 22.9 13.6USA 0.1 2.4 14.7 32.0China 32.8 29.8 12.5 3.6India 24.5 17.6 2.8 1.4
Source: Bairoch (1982)
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Historiography (Rodrik, 2013)
• The explanations for 19th century continental divergence are as follows:
Imperialist exploitation (Mandel, 1975) Institutions (Acemoglu et al., 2002) Dutch Disease (Williamson, 2011) Directed technical change (Allen, 2012)
• But could NEG core-periphery have anything to do with it?
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Market Access Then and Now(Redding & Venables, 2002; Liu & Meissner, 2013)
1910 1995
USA 100 North America 100
UK 88 Western Europe 92
India 31 South Asia 40
Indonesia 13 Latin America 35
Argentina 7 Africa 34
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Market Potential and GDP 100 Years Ago
• Has similar impact on real GDP/person to late 20th century with elasticity of about 0.3 in whole world countries sample (Liu & Meissner, 2013) or in European regions sample (Caruana-Galizia, 2013)
• Core Europe has much greater market potential than peripheral Asia (and Southern Europe) at least in late 19th century
• Liu & Meissner’s estimates suggest the following quote may not be entirely accurate
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A Quotation
“No deus ex machina translates endowments into political outcomes. If that were so, Argentina would be as rich as the United States”
North et al. (2000)
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Location of Manufacturing
• The ‘manufacturing belt’ in the United States is locked into place by market potential which interacts with scale and linkage effects (Klein & Crafts, 2012)
• Catalonia industrializes to a much greater extent than the rest of Spain as a result of favourable market size (Roses, 2003)
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Location of British Cotton Textiles in 1838 (Crafts & Wolf, 2013)
• In 1850, UK had 69% world spindles (58% in 1900)
• In 1850 Lancashire had 66% of UK spindles (79% in 1903) and about 46% of world spindles (same in 1903)
• Lancashire is 1.3% of UK land mass and 0.002% of world land mass
• Cotton is classic example of core-periphery in the ‘1st Unbundling’
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Why Lancashire?: Traditional
• “The original advantages of Lancashire comprised its poverty, its climate, its water supply, its textile tradition and its mechanical inventions. The acquired advantages included its supply of coal [!], machinery and labour, its access to the markets of Liverpool and Manchester, its low transport cost, and its auxiliary industries”
(Farnie, 1979)
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Why Lancashire?: Econometrics
• Celtic fringes have better 1st-nature attributes apart from cheap coal; it’s definitely not humidity
• Adequate source of power is ‘necessary condition’ but market access has powerful effect
• Cotton industry concentrates on a subset of its original locations to which it becomes ‘locked in’
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Results
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Poisson Cotton mills Cotton employment
Coefficient (robust SE) Coefficient (robust SE)
LnHumidity -34.917 (24.551) -27.197 (17.963)
LnRugged 1.249 (0.462)*** 0.580 (0.375)
Lnq95 0.314 (0.035)*** 0.255 (0.043)***
LnCoalprice -0.426 (0.745) -1.081 (0.651)*
LnDistweight -3.823 (0.962)*** -3.292 (1.302)**
LnMP01 4.405 (1.073)*** 4.561 (0.845)***
LnInnovations 0.788 (0.032)*** 0.804 (0.030)***
Constant + Reg Dum Yes Yes
# of Obs 148 148
Pseudo R2 0.762 0.760
Robust SE adjusted for 10 regional clusters, * , **, *** ind. sign. at 10, 5, 1%
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Lancashire Textiles and Globalization (Leunig, 2005)
• Lancashire a high wage industry: 6 x India and Japan in 1910
• But continued to dominate world trade (60% world market share in cottons in 1910)
• Unit costs lower than India or Japan even before adjusting for output quality
• Lancashire flourished because of agglomeration benefits ..... its productivity exceeded other British locations by 33%
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Path Dependence
• Economic historians like the idea – ‘history matters’ – so less optimistic than neoclassical economists about future convergence
• Technological historians think of QWERTY
• The NIEH tradition sees institutions as the ‘carriers of history’
• The NEG approach highlights 2nd-nature geography as a source of potential lock-in
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Death of Distance?
• Would have truly dramatic effect on world distribution of economic activity and income
• But “greatly exaggerated”
• ICT enables some things to go to the periphery (‘the 2nd unbundling’) but enhances the strengths of the core at the same time
• Like steam, ICT rearranges geography but doesn’t abolish it
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Concluding Questions
• Is the now-dominant institutional explanation for “divergence big time” over-sold ?
• Does market potential also play a key role – perhaps after a threshold level of institutional quality is reached ?
• Can we construct a new geography-based narrative to (partly) explain industrialization and de-industrialization since ‘globalization began’ ?