Titel: Combining Brain and Behavioral Data to Improve Econometric Policy Analysis
Autor: Daniel Houser / Daniel Schunk / Erte Xiao
Human behaviour may be governed by rules, but it is possible that these rules simply encode preferences. [...] Many psychologists argue that behaviour is far too sensitive to context and affect to be usefully related to stable preferences. However, if there are underlying preferences, then even if the link from preferences to rules is quite noisy it may be possible to recover these preferences and use them to correctly evaluate economic policies, at least as an approximation that is good enough for government policy work.
Daniel L. McFadden (Nobel Prize Lecture 2002)
Abstract: For an economist, ultimate goals of neuroeconomic research include improving economic policy analysis. One path toward this goal is to use neuroeconomic data to advance economic theory, and productive efforts have been made towards that end. Equally important, though less studied, is how neuroeconomics can provide quantitative evidence on policy, and in particular the way in which it might inform structural econometric inference. This paper is a first step in that direction. We suggest here that key forms of preference (or decision strategy) heterogeneity can be identified by brain imaging studies and, consequently, linked stochastically to observable individual characteristics. Then, recognizing that brain-imaging studies are substantially costly, we derive conditions under which the probabilistic link between observable characteristics and type, a quantity critical to policy analysis, can be estimated more precisely by combining data from traditional and brain-based decision studies.