Estimating Time Preferences from Convex Budgets
- Creators
- Andreoni, James
- Sprenger, Charles
Abstract
Experimentally elicited discount rates are frequently higher than what seems reasonable for economic decision-making. Such high rates are often attributed to present-biased discounting. A well-known bias of standard measurements is the assumption of linear consumption utility. Attempting to correct this bias using measures of risk aversion to identify concavity, researchers find reasonable discounting but at the cost of exceptionally high utility function curvature. We present a new methodology for identifying time preferences, both discounting and curvature, from simple allocation decisions. We find reasonable levels of both discounting and curvature and, surprisingly, dynamically consistent time preferences.
Additional Information
© 2012 American Economic Association. We are grateful for the insightful comments of four anonymous referees, and our many colleagues, including Nageeb Ali, Douglas Berhneim, Michèlle Cohen, Tore Ellingsen, Ed Glaeser, Glenn Harrison, David Laibson, Antonio Rangel, Al Roth, Andrew Schotter, and participants at the Economics and Psychology lecture series at Paris 1, the Psychology and Economics segment at Stanford Institute of Theoretical Economics 2009, the Amsterdam Workshop on Behavioral and Experimental Economics 2009, the Harvard Experimental and Behavioral Economics Seminar, and members of the graduate experimental economics courses at Stanford University and the University of Pittsburgh. We also acknowledge the generous support of the National Science Foundation, grant SES-0962484 (Andreoni) and grant SES-1024683 (Andreoni and Sprenger).Attached Files
Published - aer.102.7.3333.pdf
Supplemental Material - 20101222_app.pdf
Files
Name | Size | Download all |
---|---|---|
md5:6f992bbd5d5ebe718b20c7bcd4a3942d
|
1.3 MB | Preview Download |
md5:eabb1fbb90f46a66d6323618d5e1b261
|
1.3 MB | Preview Download |
Additional details
- Eprint ID
- 104574
- Resolver ID
- CaltechAUTHORS:20200724-132913042
- NSF
- SES-0962484
- NSF
- SES-1024683
- Created
-
2020-07-24Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field