Globalization and Deindustrialization in the Third World Before The

Inaugural Lecture Universitat Pompeu Fabra October 8 2008

Jeffrey G. Williamson Harvard University and the University of Wisconsin

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 Four Big Facts

Fact 1: Rise in the Core-Periphery Income Per Capita Gap The rise of the North-South gap

Rise in the Core-Periphery Income Per Capita Gap 1820-1998

10 Western Europe/Africa 8 Western Europe/Asia

Western Europe/Latin 6 America Parity 4

2 Source: Maddison (2001, Table B-21) 0 1820 1870 1913 1950 1973 1998 … 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 The 18th c calm before the storm … The 19th c storm … Some more than others

Figure 4. The Poor Periphery: Net Barter Terms of Trade 1796-1913

250

200

150

100 Terms of Trade of Terms

Middle East

50 Latin America Southeast Asia European Periphery South Asia

0 1796 1802 1808 1814 1820 1826 1832 1838 1844 1850 1856 1862 1868 1874 1880 1886 1892 1898 1904 1910 And the terms of trade bust, as seen from Latin America 1811-1939

Figure 1 Latin American Terms of Trade 1811-1939

160

140

120

100

80 Px/Pm

40 Average LA TOT Unadjusted Average LA TOT Adjusted 20

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 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?

First

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. The 19th Century Transport Revolution on Sea Lanes

And then a slow approach to steady state … Figure 2.2: Real Global Freight Rate Index(1869-1997) (1884=1.00)

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

1884

1870-18741875-18791880-1884 1885-18891890-18941895-18991900-19041905-19091910-19141915-19191920-19241925-19291930-19341935-19391940-19441945-19491950-19541955-19591960-19641965-19691970-19741975-19791980-19841985-19891990-1994 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 Table 3. Terms of Trade Volatility 1782-1913 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 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.

And risk-aversion begats lower accumulation!

So ….

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. Growth and the Terms of Trade 1870-1939 (Dependent variable: Decadal average GDP per capita growth)

Periphery Core