Abstract
This paper attempts a number of tasks that will further the study of world-historical human inequality, by arguing for a comprehensive understanding of inequality and by informally comparing and aggregating multiple datasets. The paper briefly surveys and critiques the existing corpus of inequality data, noting areas of overlap, opportunities for harmonization of data, and the coverage of the historical information. The inclusion of micro-level data from historical scholarship that is not in communication with the social scientific studies is essential to further the field. The paper concludes with a regional and global narrative of human inequality over the last two centuries.
Highlights
This paper attempts a number of tasks that will further the study of world-historical human inequality, by arguing for a comprehensive understanding of inequality and by informally comparing and aggregating multiple datasets
I argue for a comprehensive understanding of inequality, including both economic and social categories of data as well as comparing aggregate and distributional data
I advocate for the better inclusion of micro-level data from historical scholarship that is not in communication with the social scientific studies generally associated with the study of inequality and suggest several priorities for further research and sites for methodological improvement
Summary
Inequality among humans is entangled with divisions by age, health, geography, citizenship, gender, race, and class. The pioneering work in distributional studies of well-being was first done by examining national accounts data, tax-returns records and wage surveys. These types of data only cover a very small fraction of humans over the last two centuries. The Gini index is a useful and simple starting point for measuring the distribution of any type of inequality. It is a single number between 0, representing perfect equality, and 1, meaning perfect inequality. Historical inequality research must consider less social scientific descriptions, such as simple counts and divisions of persons by profession, class, or income bracket
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