A Cross-Cultural Study of Variability in Economic Prosperity using Machine-Learning and Statistical Analysis

The causes and consequences of material wealth inequality are topics of primary interest across the social sciences, and of great relevance to policymakers and the public. Longstanding hypotheses assert the importance of the social determinants of inequality, delineating the routes through which individuals and households rely on their social networks to buffer subsistence risks or leverage their positions within these networks for personal gain. This project advances a cross-cultural, longitudinal study, collecting comprehensive economic, demographic, and social support network data in over fifty communities in over thirty countries around the globe. The core aim of this research is an empirical test of theories derived from economics and sociology, which predict that a household’s material wealth---as indexed by the value of its material possessions---is influenced both by its social connections and the structure of its local community. With such tests, this study elucidates sources of variation in economic prosperity within and between this sample of communities. This project is already underway, with the first and some of the second wave of data collection completed. This funding enables the completion of the second wave of data collection in the remaining communities and the integration of these data with previously collected data facilitate longitudinal analysis. The study sites are extremely varied, so analyzing these data entails novel analytical challenges. For this reason, a second objective is to apply and develop new machine learning and statistical methods that ensure meaningful comparison and inferences with the multilevel, high-dimensional data. The funding also facilitates an interdisciplinary workshop to bring together statisticians, economists, and network scientists with the anthropologists who collected the primary data. Another objective is to prepare the full dataset for deposition in an open-access repository, thereby offering a valuable resource for the social and economic sciences, as well as other interested stakeholders. This study entails hiring a professional database specialist to ensure maximal security, accessibility, and usability. The project sheds new light on the role of social structure in determining economic inequality by working with anthropologists committed to gathering longitudinal data in communities that are diverse in their institutional, cultural, and economic arrangements, as well as their ecologies. Coupled with standardized survey instruments, these anthropologists’ contributions generate insights into the different mechanisms by which communities experience variation in economic prosperity. The project develops new statistical models that are both ethnographically-informed and tackle longstanding measurement issues in social network analysis. More generally, the study contributes a unique data resource, which will be of broad utility across disciplines. Inequality---whether of income, health, wealth, or opportunity---has existed across societies and over human history. Understanding the dynamics whereby inequality emerges at a local scale, and how it is experienced, is a crucial societal task. This project increases engagement from both the public and policymakers in these topics by highlighting both consistent patterning and examples of successful mitigation of inequality through the planned outputs. By making the data easily available, the project invites broader participation among scientists from a wide array of disciplines and institutions. Key insights are to be conveyed to community partners and to diverse public audiences, including students via open-access curricular modules.