We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision-making. We elicit 21 behaviors using an incentivized survey on a representative sample (n=1,000) of the U.S. population. Our data show a clear and relatively simple structure underlying the correlations between these measures. Using principal components analysis, we reduce the 21 variables to six components corresponding to clear clusters of high correlations. We examine the relationship between these components, cognitive ability, and demographics, and discuss the theoretical implications of the structure we uncover and find a number of relations that partly confirm, but also add nuance, to previous findings.
We thank Douglas Bernheim, Benedetto De Martino, Stefano Della Vigna, Xavier Gabaix, Daniel Gottlieb, Eric Johnson, David Laibson, Graham Loomes, Ulrike Malmandier, Matthew Rabin, Peter Wakker, Michael Woodford, and the participants of seminars and conferences for their useful comments and suggestions. Daniel Chawla provided excellent research assistance. Camerer, Ortoleva, and Snowberg gratefully acknowledge the financial support of NSF Grant SMA-1329195. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Jonathan Chapman & Mark Dean & Pietro Ortoleva & Erik Snowberg & Colin Camerer, 2023. "Econographics," Journal of Political Economy Microeconomics, vol 1(1), pages 115-161.