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Globalization and the Great Divergence
Jeffrey G. Williamson Harvard University and the University of Wisconsin
Inaugural Lecture
Universitat Pompeu Fabra
October 8 2008
Motivation
In David Landes’ (1998) words, why is the Third World periphery in the South so poor, and the industrial OECD core in the North so rich?
The competing explanations or fundamentals:
Culture: Polyani 1944; Landes 1998; Clark 2007
Geography: Diamond 1997; Sachs 2000, 2001; Easterly & Levine 2003
Institutions: North & Weingast 1989; AJR 2001, 2002, 2005
Problems
Fundamentals don’t change very much over time.
So, what explains the timing of the great divergence between Core and Periphery? Why did the gap open so fast 1800-1913?
One possible explanation: the world was --
Closed and anti-global pre-1800
Open and pro-global 1800-1913
Closed and anti-global 1913-1950
Open and pro-global 1950-2008
The rise of the North-South gap
Rise in the Core-Periphery Income Per Capita Gap 1820-1998
0
2
4
6
8
10
12
14
1820 1870 1913 1950 1973 1998
WesternEurope/Africa
Western Europe/Asia
Western Europe/LatinAmerica
Parity
Source: Maddison (2001,
Table B-21)
… and extending backwards with
real wages
Table 1. The Great Divergence: Income Per Capita Gaps 1775-1913
1775 1820 1870 1913
Western Europe 100 100 100 100
Southern Europe 75.2 62.4 52.7 47.3
Eastern Europe 70.0 58.1 48.8 42.0
Latin America 75.2 55.3 37.9 40.9
Asia 56.4 42.6 27.5 20.0
Africa 46.1 34.8 22.7 15.5
Poor Periphery Average 64.6 50.6 37.9 33.1
Four Big Facts
Fact 1: Rise in the Core-Periphery Income Per
Capita Gap
Fact 2: De-Industrialization in the Poor Periphery
Do Industrial Countries Get Richer?
Current GDP per capita 1820-1950 and Industrialization 50 or 70 Years Before
Per Capita Levels of Industrialization 1750-1953
1750 1800 1860 1913 1953
European Core 8 8 17 45 90
Asian and Latin American Periphery 7 6 4 2 5
Ratio Core/Periphery 1.1 1.3 4.3 22.5 18
Source: Bairoch (1982, Table 4, p. 281). The European core contains: Austria-Hungary, Belgium,
France, Germany, Italy, Russia, Spain, Sweden, Switzerland, United Kingdom. The Asian and Latin
American periphery contains: China, India (plus Pakistan in 1953), Brazil and Mexico.
More de-industrialization figures
Textiles
Percent of Home Market Supplied by
Imports Domestic Industry
India 1833 5 95
India 1887 58-65 35-42
Ottoman 1820s 3 97
Ottoman 1870s 62-89 11-38
Mexico 1800s 25 75
Mexico 1879 40 60
Four possible causes of de-industrialization
in the Poor Periphery
● World market integration (e.g. globalization)
induces greater specialization (e.g. a new economic
order); implies tot improvement for periphery
● Rapid industrial productivity growth in Europe:
implies tot improvement for periphery
● Deterioration in industrial productivity and
competitiveness in periphery; implies no tot
improvement for periphery
● Improved productivity in primary product export
sector in periphery; implies no tot improvement for
periphery
Four Big Facts
Fact 1: Rise in the Core-Periphery Income Per
Capita Gap
Fact 2: De-Industrialization in the Poor
Periphery
Fact 3: Secular Terms of Trade Boom and Bust
in the Periphery
Some more than others
Figure 4. The Poor Periphery: Net Barter Terms of Trade 1796-1913
0
50
100
150
200
250
1796 1802 1808 1814 1820 1826 1832 1838 1844 1850 1856 1862 1868 1874 1880 1886 1892 1898 1904 1910
Te
rms
of
Tra
de
Middle East
Latin America
Southeast Asia
European Periphery
South Asia
And the terms of trade bust, as seen
from Latin America 1811-1939 Figure 1
Latin American Terms of Trade 1811-1939
0
20
40
60
80
100
120
140
160
1811
1815
1819
1823
1827
1831
1835
1839
1843
1847
1851
1855
1859
1863
1867
1871
1875
1879
1883
1887
1891
1895
1899
1903
1907
1911
1915
1919
1923
1927
1931
1935
1939
Year
Px/
Pm
Average LA TOT Unadjusted
Average LA TOT Adjusted
Source: Unadjusted--Clingingsmith and Williamson (2004), Figure 9, based on data in Coatsworth and Williamson (2004a); Adjusted--see Appendix
1.
What caused the 120-year secular boom-
bust in terms of trade for primary-
product producers?
World market integration generated by a
world-wide transport revolution caused CPC,
lowered Pm and raised Px. Very fast initially,
then a slow-down to steady state.
First
Figure 2.2: Real Global Freight Rate Index(1869-1997) (1884=1.00)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1870
-187
4
1875
-187
9
1880
-188
418
84
1885
-188
9
1890
-189
4
1895
-189
9
1900
-190
4
1905
-190
9
1910
-191
4
1915
-191
9
1920
-192
4
1925
-192
9
1930
-193
4
1935
-193
9
1940
-194
4
1945
-194
9
1950
-195
4
1955
-195
9
1960
-196
4
1965
-196
9
1970
-197
4
1975
-197
9
1980
-198
4
1985
-198
9
1990
-199
4
Second
Diffusion of the industrial revolution in core raised
GDP growth rates there, and thus in the derived
demand for luxury foodstuffs.
Growth rates of manufacturing were even greater
in core – since its share in GDP was rising, and
thus so too was derived demand for primary
product intermediates.
Manufacturing growth slowed down in core as
industrial transition was completed there, and
thus so too did the derived demand for primary
product intermediates.
Third
Manufacturing searched for new technologies
and synthetic products to save on or even
replace the increasingly expensive primary
products. It finally found them adding further
to the demand-led terms of trade bust.
Four Big Facts
Fact 1: Rise in the Core-Periphery Income Per
Capita Gap
Fact 2: De-Industrialization in the Poor
Periphery
Fact 3: Secular Terms of Trade Boom and Bust
in the Periphery
Fact 4: Terms of Trade Volatility Much Bigger
in the Periphery
Core vs Poor Periphery
Region Before 1820 1820-1870 1870-1913
United Kingdom 11.985 2.910 2.006
Average Periphery 6.460 9.176 7.089
European Periphery 4.036 10.720 7.058
Italy 0.922 19.003 11.214
Russia 3.226 10.722 6.104
Spain 7.959 6.472 6.023
Latin America 3.728 6.429 8.140
Argentina 4.409 6.961 8.303
Brazil N/A 2.174 10.283
Mexico 1.658 5.531 5.379
Middle East 2.902 13.611 7.316
Egypt 2.982 17.861 11.760
Ottoman Turkey 2.821 6.549 3.289
South Asia 11.876 9.628 5.364
Ceylon 17.860 7.590 7.532
India 5.891 11.666 3.196
Southeast Asia 7.788 6.977 7.303
Philippines 7.992 9.778 6.603
Siam 7.583 7.951 6.732
East Asia 15.554 10.527 4.952
China 15.554 19.752 4.311
Japan N/A 1.302 5.592
Table 3. Terms of Trade Volatility 1782-1913
Four Big Facts
Fact 1: Rise in the Core-Periphery Income Per
Capita Gap
Fact 2: De-Industrialization in the Poor
Periphery
Fact 3: Secular Terms of Trade Boom and Bust
in the Periphery
Fact 4: Terms of Trade Volatility Much Bigger
in the Periphery
One Big Question
Are the correlations spurious
or are they causal?
So, what about the theory,
and what about the magnitudes?
What’s the Impact of a Secular Improvement in the
Terms of Trade for a Primary Product Exporter?
Short Run: unambiguous income
increase Medium Run: unambiguous income increase
via resource allocation and specialization
response, e.g. de-industrialization
Long Run: ambiguous impact on growth due to
de-industrialization and the belief that industry
is a carrier of modern economic growth
Net Impact: theory ambiguous, history must
resolve the issue
What’s the Impact of a Secular Improvement in the
Terms of Trade for an Exporter of Manufacturers?
Short Run: unambiguous income increase
Medium Run: unambiguous income increase via
resource allocation and specialization response, e.g.
more industrialization
Long Run: unambiguous impact on growth due to
industrialization and the belief that industry is a
carrier of modern economic growth
Net Impact: theory unambiguous
So …
What Should We Find in History?
Asymmetric impact
of secular terms of trade improvement
Core versus Periphery!
What’s the Impact of Terms of Trade
Volatility on the Exporter of Manufactures in
the Rich Core?
Exporters of manufactures in the rich core can
insure against price volatility cheaply since:
● they face well developed capital markets;
● governments have varied revenue sources;
● rich families can consumption smooth;
● they export many products, spreading risk;
● their export prices are less volatile.
What’s the Impact of Terms of Trade
Volatility on the Primary Product Exporter in
the Poor Periphery?
Poor primary product exporters cannot insure
against price volatility cheaply since:
● they face undeveloped capital markets;
● governments rely very heavily on import
duties and export taxes;
● poor families cannot consumption smooth;
● they export few products, so more vulnerable to
price shocks;
● their export prices are more volatile.
What Should We Find In History?
Asymmetric impact
of terms of trade volatility
Core versus Periphery!
Identification Assumptions: Two Concerns
First
Was the terms of trade exogenous everywhere in
the periphery? Was every poor country a price
taker? No, but results are robust to exclusion of
suspected price-makers e.g.
● remove any with 33% of world exports of any
commodity: Australia, Brazil, Chile, China,
India, Philippines, Russia; same result
● plus, remove any with 25% of world exports of
any commodity: Argentina, Canada, Japan; same
result.
Second
Did some fundamental – institutions, geography or
culture -- drive both the choice of export product and
growth? Maybe, but so what?
● captured by country fixed effects, since export
“choice” was made long before 1870 and persisted
until 1939
● anyway, no correlation between price volatility and
institutional quality
A new historical database, annual, 35
countries, 1870-1939
6 Core industrial leaders: AH, Fr, Ger, It, UK, USA
8 European Periphery: Den, Grc, Nor, Port, Serb, Sp, Swe, Rus
8 Latin American Periphery: Arg, Brz, Col, Ch, Cuba, Mex, Per, Ur
10 Asia-MidEast: Bur, Cey, Egy, Ind, Indo, Jap, Phil, Siam, Turk
3 English-speaking European Offshoots: Aus, Can, NZ
Covers more than 85% of world population
and more than 95% of world GDP in 1914.
Results are insensitive to alternative Core
versus Periphery allocations.
Periphery Core
TOT Growth 0.05 0.63
[0.119] [0.251]**
TOT Volatility -0.08 0.02
[0.033]** [0.058]
Observations 167 32
R-squared 0.35 0.74
Decade Dummies Yes Yes
Country Dummies Yes Yes
Controls Yes Yes
Summary Statistics:
GDP Growth
1.05
[1.66]
1.59
[1.28]
TOT Growth -0.28 0.3
[1.46] [1.02]
TOT Volatility 8.8 6.82
[5.17] [4.86]
Impact on Growth:
TOT Growth 0.07 0.64
TOT Volatility -0.39 0.11
Growth and the Terms of Trade 1870-1939
(Dependent variable: Decadal average GDP per capita growth)
Robust standard errors in
brackets
** significant at 5%
Periphery Core
TOT Growth 0.05 0.63
[0.119] [0.251]**
TOT Volatility -0.08 0.02
[0.033]** [0.058]
Observations 167 32
R-squared 0.35 0.74
Decade Dummies Yes Yes
Country Dummies Yes Yes
Controls Yes Yes
Summary Statistics:
GDP Growth
1.05
[1.66]
1.59
[1.28]
TOT Growth -0.28 0.3
[1.46] [1.02]
TOT Volatility 8.8 6.82
[5.17] [4.86]
Impact on Growth:
TOT Growth 0.07 0.64
TOT Volatility -0.39 0.11
Growth and the Terms of Trade 1870-1939
(Dependent variable: Decadal average GDP per capita growth)
Robust standard errors in
brackets
** significant at 5%
Periphery Core
TOT Growth 0.05 0.63
[0.119] [0.251]**
TOT Volatility -0.08 0.02
[0.033]** [0.058]
Observations 167 32
R-squared 0.35 0.74
Decade Dummies Yes Yes
Country Dummies Yes Yes
Controls Yes Yes
Summary Statistics:
GDP Growth
1.05
[1.66]
1.59
[1.28]
TOT Growth -0.28 0.3
[1.46] [1.02]
TOT Volatility 8.8 6.82
[5.17] [4.86]
Impact on Growth:
TOT Growth 0.07 0.64
TOT Volatility -0.39 0.11
Growth and the Terms of Trade 1870-1939
(Dependent variable: Decadal average GDP per capita growth)
Robust standard errors in
brackets
** significant at 5%
Periphery Core
TOT Growth 0.05 0.63
[0.119] [0.251]**
TOT Volatility -0.08 0.02
[0.033]** [0.058]
Observations 167 32
R-squared 0.35 0.74
Decade Dummies Yes Yes
Country Dummies Yes Yes
Controls Yes Yes
Summary Statistics:
GDP Growth
1.05
[1.66]
1.59
[1.28]
TOT Growth -0.28 0.3
[1.46] [1.02]
TOT Volatility 8.8 6.82
[5.17] [4.86]
Impact on Growth:
TOT Growth 0.07 0.64
TOT Volatility -0.39 0.11
Growth and the Terms of Trade 1870-1939
(Dependent variable: Decadal average GDP per capita growth)
Robust standard errors in
brackets
** significant at 5%
Periphery Core
TOT Growth 0.05 0.63
[0.119] [0.251]**
TOT Volatility -0.08 0.02
[0.033]** [0.058]
Observations 167 32
R-squared 0.35 0.74
Decade Dummies Yes Yes
Country Dummies Yes Yes
Controls Yes Yes
Summary Statistics:
GDP Growth
1.05
[1.66]
1.59
[1.28]
TOT Growth -0.28 0.3
[1.46] [1.02]
TOT Volatility 8.8 6.82
[5.17] [4.86]
Impact on Growth:
TOT Growth 0.07 0.64
TOT Volatility -0.39 0.11
Growth and the Terms of Trade 1870-1939
(Dependent variable: Decadal average GDP per capita growth)
Robust standard errors
in brackets
** significant at 5%
Note:
Percentage point
impact of 1 st. dev.
change
What About pre-1870 History?
The data aren’t sufficient to estimate impact
as we did for 1870-1938.
But terms of trade volatility was even bigger
pre-1870 than post-1870, so bigger negative
impact on growth if the post-1870 impact
conditions also held for the pre-1870 period.
Core vs Poor Periphery
Region Before 1820 1820-1870 1870-1913
United Kingdom 11.985 2.910 2.006
Average Periphery 6.460 9.176 7.089
European Periphery 4.036 10.720 7.058
Italy 0.922 19.003 11.214
Russia 3.226 10.722 6.104
Spain 7.959 6.472 6.023
Latin America 3.728 6.429 8.140
Argentina 4.409 6.961 8.303
Brazil N/A 2.174 10.283
Mexico 1.658 5.531 5.379
Middle East 2.902 13.611 7.316
Egypt 2.982 17.861 11.760
Ottoman Turkey 2.821 6.549 3.289
South Asia 11.876 9.628 5.364
Ceylon 17.860 7.590 7.532
India 5.891 11.666 3.196
Southeast Asia 7.788 6.977 7.303
Philippines 7.992 9.778 6.603
Siam 7.583 7.951 6.732
East Asia 15.554 10.527 4.952
China 15.554 19.752 4.311
Japan N/A 1.302 5.592
Table 3. Terms of Trade Volatility 1782-1913
What About pre-1870 History?
The data aren’t sufficient to estimate impact as we did for 1870-1938.
But terms of trade volatility was even bigger pre-1870 than post-1870, so bigger negative impact on growth if the post-1870 impact conditions also held for the pre-1870 period.
In addition, the de-industrialization conditions were much greater pre-1870 during terms of trade boom then during post-1870 terms of trade bust, implying even greater negative impact on growth before 1870 than after.
Reminder: Terms of trade boom
versus bust (in Latin America) Figure 1
Latin American Terms of Trade 1811-1939
0
20
40
60
80
100
120
140
160
1811
1815
1819
1823
1827
1831
1835
1839
1843
1847
1851
1855
1859
1863
1867
1871
1875
1879
1883
1887
1891
1895
1899
1903
1907
1911
1915
1919
1923
1927
1931
1935
1939
Year
Px/
Pm
Average LA TOT Unadjusted
Average LA TOT Adjusted
Source: Unadjusted--Clingingsmith and Williamson (2004), Figure 9, based on data in Coatsworth and Williamson (2004a); Adjusted--see Appendix
1.
Bottom Lines
● Did globalization experience contribute to the Great
Divergence before 1940? Absolutely!
● How much of the gap in growth rates between core
and periphery 1870-1940 was explained by different tot
growth and volatility impact? Big: a third to a half.
● Would we expect the same tot impact pre-1870?
Bigger: secular tot boom, not bust, and tot volatility at
least as big.
Lessons of History?
Would we expect the same today after five
decades (1950-2008) in to the second global
century?
No! The effect has almost certainly vanished
today since the old economic order has also
vanished everywhere in the poor periphery
except Africa, where it is vanishing.