The University of Chicago
To elicit and study experts’ prior predictions about the outcomes of experiments in behavioral economics
What do behavioral economists really know? Lessons learned so far seem more about isolated, but intriguing, examples rather than coherent or unifying principles. What counts as accepted doctrine is based almost exclusively on empirical results about particular phenomena such as loss aversion, probability weighting, altruism, hyperbolic discounting, and social comparisons. One would expect, therefore, that experts would be rather good at predicting the outcomes of standard experiments about standard topics in behavioral economics. This grant funds a research project by Devin Pope of Chicago and Stefano DellaVigna of Berkeley that test that hypothesis. First, Pope and DellaVigna will ask experts to forecast the effects of 17 different behavioral interventions or “nudges” in standard, simple, familiar, and carefully specified experiments. Second, they will run these experiments as described in a common setting. A large number of subjects will be asked to perform an effortful 10-minute task online. Each will be assigned to one of the 17 different framings, incentive structures, or other treatments. Just by keeping everything else equal except these behavioral interventions, the experimenters will be able to draw conclusions about the relative magnitudes and probabilities of various effects. Third, they will compare the expert forecasts with the experimental results. It is possible, of course, that all the predictions will turn out to be quite accurate—or not. In any case, such an exercise should help identify what behavioral economists do agree upon and, therefore, what we have learned from behavioral economics.