A Large-Scale, Interdisciplinary Meta-Analysis on Behavioral Economics Parameters EconomicsSSMART
Colin Camerer and Taisuke Imai
We propose to conduct large-scale meta-analyses of published and unpublished researches in economics, psychology and neuroscience (and any other fields which emerge) to cumulate knowledge about measured parameters explaining preferences over risk and time. In the risk section, we will locate and meta-analyze studies which estimate parameters associated with curvature of utility and loss-aversion (the ratio between disutility of loss and utility of gain). In the time section, we will locate and meta-analyze studies which estimate parameters associated with near- and long-term discounting (exponential, hyperbolic, and quasi-hyperbolic parameters). Meta-analysis is the proper tool because: It is technologically easier than ever before; there are standard methods to weigh different estimates according to study quality; if unpublished work is found, it can help estimate whether there are biases in favor of publishing certain types of confirmatory bias (or a bias against publishing null results); and looking at a broad range of studies is the most efficient way to help resolve debates about how preference parameters vary across populations (e.g., how much less patient are young people?) and across methods (e.g., are time preferences inferred from monetary rewards different than non-monetary rewards?).