From brain imaging data one obtains new economic theory with economically relevant policy implications. In particular, one would like to use data from a small number of subjects in an imaging experiment to predict a larger population’s response to proposed policy changes. This paper develops a method by which one can combine behavioral and imaging experiments’ data to provide empirical content to economic theory and improve econometric policy analysis. I develop probability bounds on the behavioral effects of a policy change, and show that these bounds depend on the probability that certain brain activation patterns are present. Moreover, I show that these activation probabilities can be estimated from a combination of behavioral and imaging experiments, so long as decisions in the behavioral experiment are sufficiently dependent on the activation patterns of interest.
More papers in 2007 Meeting Papers from Society for Economic Dynamics Address: Society for Economic Dynamics Christian Zimmermann Economic Research Federal Reserve Bank of St. Louis PO Box 442 St. Louis MO 63166-0442 USA Contact information at EDIRC. Series data maintained by Christian Zimmermann ().