Project
Unfair Trade? Globalization, Institutions and Inequality in Southeast Asia, 1830-1940
Global trade and colonial institutions are often asserted as key long-run drivers of within-country economic inequality in developing countries. Economic inequality, in turn, has had a notable negative impact on the long-term development prospects of poor countries. Trade and institutional theorists suggest that the way these factors affected inequality depends on initial endowments in the factors of production – land, labour and capital – as well as the type of commodity exported. However, the empirical evidence on which these theories are based is thin and the precise causal mechanisms that underlie these connections remain unclear.
This NWO Veni project is the first to use regional-level data to shed light on the dynamic relationship between globalization, institutions and inequality. It gathers new historical evidence to measure incomes of different population groups (using data on wages, prices, rents, land distribution, and tax records) from colonial archives in order to understand how global trade (the export of various cash crops) and colonial institutions (the laws organizing factor and commodity markets) affected within-country inequality in Southeast Asia between c. 1830 and 1940 (the “first age of globalization”).
The choice of time-period and region provides an unparalleled opportunity to systematically test the theoretical assumptions in the literature because of the large variety in institutional conditions and export specialization in a geographically confined area. Southeast Asia was one of the areas of the globe most heavily affected by globalization and colonization in the 19th century. The project will employ a comparative case-study approach, focusing on specific regions within Indonesia, Malaysia and Vietnam. The chosen comparisons exploit the variations between these regions in terms of factor endowments and the commodities produced for export, which may account for the diversity in their development paths. I will combine statistical techniques with an in-depth historical analysis to uncover the long-term drivers of within-country inequality.