A Hierarchical Bayesian Approach for Estimating Gini Coefficients from House Floor Area: A Case Study from Prehistoric Japan

Summary

This is an abstract from the "To Have and Have Not: A Progress Report on the Global Dynamics of Wealth Inequality (GINI) Project" session, at the 88th annual meeting of the Society for American Archaeology.

Robust quantitative measures of wealth inequality are pivotal for investigating long-term social and economic changes from a comparative perspective. Notwithstanding criticisms on its reliability as a proxy of wealth inequality, the application of Gini coefficients on house size data has successfully enabled cross-cultural comparisons that would otherwise have not been possible. Still, robust estimates of these coefficients require relatively large sample sizes, and the uncertainties associated with the estimates themselves are typically ignored in the subsequent level of analyses when multiple sites and geographic areas are compared against each other. Here we introduce a hierarchical Bayesian approach to tackle this methodological challenge, using a log-logistic distribution model (in which the shape parameter is the reciprocal of the Gini coefficient) and taking into account the hierarchical structure of our data. We apply this approach to the household record of the Jomon and Yayoi periods in prehistoric Japan, to determine (1) whether the increasing evidence of social complexity suggested for the latter half of the Jomon period is reflected in house size distribution, and (2) whether the distinct response to the introduction of agriculture in western and eastern Japan has also led to divergent socioeconomic trajectories as inferred from the household data.

This Resource is Part of the Following Collections

• To Have and Have Not: A Progress Report on the Global Dynamics of Wealth Inequality (GINI) Project   •
• Society for American Archaeology 88th Annual Meeting, Portland, OR (2023)

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Record Identifiers

Abstract Id(s): 35545.0