Dr. David B. Huffman
The GPS is a new data set produced in some recent research by myself and collaborators, see the paper "Global Evidence on Economic Preferences." Now that the paper is published the data are publicly available. The GPS provides measures of fundamental economic preferences -- time discounting, risk preference, altruism, positive reciprocity, negative reciprocity, and trust -- from around the world. The data include representative samples from 76 countries, with roughly 80,000 total respondents. The documentation, provided online, includes surveys in the relevant local languages.
My research lies at the intersections of behavioral economics, labor economics, and personnel economics. One strand of my research has been basic research on the determinants of human decision making, especially preferences regarding risk, time, and social interactions, as well as trust and motivated beliefs. My research has shown how such preferences vary around the world as well as within diverse sets of cultures, and has explored determinants of preference differences, including the role of parental transmission. Another strand has been more applied, bringing insights from behavioral economics to central questions in labor, personnel economics, and industrial organization. Topics include how workers respond to incentives, how relational contracting operates in different institutional environments, determinants of involuntary unemployment, and mechanisms underlying gender differences in labor market outcomes. Much of my recent research has been focused on studying behavioral economics within firms, combining the internal data of firms with measures of traits and biases of employees and managers. I am particularly interested in how behavioral biases and bounded rationality may influence the strategic behaviors of firms. I use a wide variety of methodologies, including field experiments, laboratory experiments, surveys, and analysis of large, observational datasets with econometric techniques including machine learning and natural language processing.
(Updated October, 2023)
Citations: 17,653; Citations since 2018: 10,108; h-index: 32; i-10 index: 42
Publications in Journals
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