Department of Economics
California Institute of Technology
Pasadena, CA 91125
Information about this author at RePEc
NBER Working Papers and Publications
|October 2017||Artificial Intelligence and Behavioral Economics|
in Economics of Artificial Intelligence, Ajay K. Agrawal, Joshua Gans, and Avi Goldfarb, editors
|April 2015||Bankruptcy Rates among NFL Players with Short-Lived Income Spikes|
with Kyle Carlson, Joshua Kim, Annamaria Lusardi: w21085
One of the central predictions of the life cycle hypothesis is that individuals smooth consumption over their economic life cycle; thus, they save when income is high, in order to provide for when income is likely to be low, such as after retirement. We test this prediction in a group of people—players in the National Football League (NFL)—whose income profile does not just gradually rise then fall, as it does for most workers, but rather has a very large spike lasting only a few years. We collected data on all players drafted by NFL teams from 1996 to 2003. Given the difficulty of directly measuring consumption of NFL players, we test whether they have adequate savings by counting how many retired NFL players file for bankruptcy. Contrary to the life-cycle model predictions, we find that...
Published: Kyle Carlson & Joshua Kim & Annamaria Lusardi & Colin F. Camerer, 2015. "Bankruptcy Rates among NFL Players with Short-Lived Income Spikes," American Economic Review, American Economic Association, vol. 105(5), pages 381-84, May. citation courtesy of
|August 2013||Neural Activity Reveals Preferences Without Choices|
with Alec Smith, B. Douglas Bernheim, Antonio Rangel: w19270
We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to "non-choice" neural responses and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach.
Published: Alec Smith & B. Douglas Bernheim & Colin F. Camerer & Antonio Rangel, 2014. "Neural Activity Reveals Preferences without Choices," American Economic Journal: Microeconomics, American Economic Association, vol. 6(2), pages 1-36, May. citation courtesy of
|November 2012||Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility|
with Cary Frydman, Nicholas Barberis, Peter Bossaerts, Antonio Rangel: w18562
We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the "realization utility" theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market while we measured their brain activity. We find that all subjects exhibit a strong disposition effect in their trading, even though it is suboptimal. Consistent with the realization utility explanation for this behavior, we find that activity in the ventromedial prefrontal cortex, an area known to encode the value of options during choices, correlates with the capital gains of potential trades; that the neural measures of realization utility correlate across subjects with their individual tendency ...
Published: Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility CARY FRYDMAN, NICHOLAS BARBERIS, COLIN CAMERER, PETER BOSSAERTS andANTONIO RANGEL† Article first published online: 17 MAR 2014 DOI: 10.1111/jofi.12126 © 2014 the American Finance Association Issue The Journal of Finance The Journal of Finance Volume 69, Issue 2, pages 907–946, April 2014