Publication: Pre-industrial Inequality
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Date
2011
ISSN
00130133
Published
2011
Author(s)
Williamson, Jeffrey G.
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Abstract
Is inequality largely the result of the Industrial Revolution? Or, were pre-industrial incomes as unequal as they are today? This article infers inequality across individuals within each of the 28 pre-industrial societies, for which data were available, using what are known as social tables. It applies two new concepts: the inequality possibility frontier and the inequality extraction ratio. They compare the observed income inequality to the maximum feasible inequality that, at a given level of income, might have been 'extracted' by those in power. The results give new insights into the connection between inequality and economic development in the very long run.
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Publication Measuring Ancient Inequality(World Bank, Washington, DC, 2007-11)Is inequality largely the result of the Industrial Revolution? Or, were pre-industrial incomes and life expectancies as unequal as they are today? For want of sufficient data, these questions have not yet been answered. This paper infers inequality for 14 ancient, pre-industrial societies using what are known as social tables, stretching from the Roman Empire 14 AD, to Byzantium in 1000, to England in 1688, to Nueva España around 1790, to China in 1880 and to British India in 1947. It applies two new concepts in making those assessments - what the authors call the inequality possibility frontier and the inequality extraction ratio. Rather than simply offering measures of actual inequality, the authors compare the latter with the maximum feasible inequality (or surplus) that could have been extracted by the elite. The results, especially when compared with modern poor countries, give new insights in to the connection between inequality and economic development in the very long run.Publication Revisiting Between-Group Inequality Measurement: An Application to the Dynamics of Caste Inequality in Two Indian Villages(2011)Standard approaches to decomposing how much group differences contribute to inequality rarely show significant between-group inequality, and are of limited use in comparing populations with different numbers of groups. We apply an adaptation to the standard approach that remedies these problems to longitudinal household data from two Indian villages-Palanpur in the north and Sugao in the west. In Palanpur we find that the largest Scheduled Caste group failed to share in the gradual rise in village prosperity. This would not have emerged from standard decomposition analysis. However, in Sugao the alternative procedure does not yield any additional insights because income gains have applied relatively evenly across castes.Publication Reinterpreting Between-Group Inequality(2008)We evaluate observed inequality between population groups against a benchmark of the maximum between-group inequality attainable given the number and relative sizes of those groups under examination. Because our measure is normalized by these parameters, drawing comparisons across different settings is less problematic than with conventional inequality decompositions. Moreover, our measure can decline with finer sub-partitioning of population groups. Consequently, the exact manner in which one groups the population acquires greater significance. Survey data from various countries suggest that our approach can provide a complementary perspective on the question of whether (and how much) a particular population breakdown is salient to an assessment of inequality in a country.Publication Poverty and Civil War: Revisiting the Evidence(2010)Previous research has interpreted the correlation between per capita income and civil war as evidence that poverty is a main determinant of conflict. In this paper, we find that the relationship between poverty and civil war is spurious and is accounted for by historical phenomena that jointly determine income evolution and conflict. In particular, the statistical association between poverty and civil wars disappears once we include country fixed effects. Also, using cross-section data for 1960 to 2000, we find that once historical variables like European settler mortality rates and the population density in 1500 are included in civil war regressions, poverty does not have an effect on civil wars. These results are confirmed using longer time series from 1825 to 2000.Publication Finance and Inequality : Theory and Evidence(2009)In this paper, we critically review the literature on finance and inequality, highlighting substantive gaps in the literature. Finance plays a crucial role in the preponderance of theories of persistent inequality. Unsurprisingly, therefore, economic theory provides a rich set of predictions concerning both the impact of finance on inequality and about the relevant mechanisms. While subject to ample qualifications, the bulk of empirical research suggests that improvements in financial contracts, markets, and intermediaries expand economic opportunities and reduce inequality. Yet, there is a shortage of theoretical and empirical research on the potentially enormous impact of formal financial sector policies, such as bank regulations and securities law, on persistent inequality. Furthermore, we lack a conceptual framework for considering the joint and endogenous evolution of finance, inequality, and economic growth.
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