Published July 2021
| Submitted + Supplemental Material
Journal Article
Open
Recovering Preferences from Finite Data
Abstract
We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying "true" preference. Our conditions are weak and, therefore, valid in a wide range of economic environments. We develop applications to expected utility theory, choice over consumption bundles, and menu choice. Our framework unifies the revealed preference tradition with models that allow for errors.
Additional Information
© 2021 The Econometric Society. Manuscript received 15 November, 2019; final version accepted 24 March, 2021; available online 31 March, 2021. An early version circulated under the title "Preference Identification." We are particularly grateful to Jeroen Swinkels, the coeditor and six anonymous referees for insightful comments and suggestions. We are thankful to Pathikrit Basu for finding a mistake in a prior draft of the paper and for valuable suggestions. We thank seminar participants at many institutions, the audiences of conferences and workshops at HEC Paris, Paris School of Economics, UC Berkeley, University of Pennsylvania, University of Warwick, University of York, Oxford University, and Virginia Tech. Echenique thanks the National Science Foundation for financial support (Grants SES-1558757 and CNS-518941), and the Simons Institute at UC Berkeley for its hospitality. Lambert thanks Microsoft Research and the Cowles Foundation at Yale University for their hospitality and financial support.Attached Files
Submitted - 1909.05457.pdf
Supplemental Material - ecta200321-sup-0001-onlineappendix.pdf
Files
1909.05457.pdf
Files
(534.5 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:e667196758a4afbfb88edcb549f44db1
|
423.0 kB | Preview Download |
|
md5:49f2a3d40348da00aba61164cbdd750e
|
111.5 kB | Preview Download |
Additional details
- Eprint ID
- 108296
- DOI
- 10.3982/ECTA17845
- Resolver ID
- CaltechAUTHORS:20210303-151215927
- SES-1558757
- NSF
- CNS-518941
- NSF
- Simons Institute
- Microsoft Research
- Cowles Foundation
- Created
-
2021-03-03Created from EPrint's datestamp field
- Updated
-
2021-08-12Created from EPrint's last_modified field