We derive conditions under which a demand function with nonseparable unobserved heterogeneity in tastes can be estimated consistently by nonparametric quantile regression subject to the shape restriction from the Slutsky inequality. We consider nonparametric estimation of the nonseparable demand for gasoline in the U.S. The estimated function detects differences in behavior between heavy and moderate gasoline users, and reveals systematic variation in the responsiveness of demand to plausible changes in prices across the income distribution. We test for exogeneity of prices and develop a new method for estimating quantile instrumental variables to allow for endogeneity of prices. The empirical results illustrate the improvements in finite-sample performance of a nonparametric estimator from imposing shape restrictions based on economic theory.
This article is forthcoming.
Authors
CPP Co-Director
Richard is Co-Director of the Centre for the Microeconomic Analysis of Public Policy (CPP) and Senior Research Fellow at IFS.
Northwestern University
Research Fellow University of Surrey
Matthias is a research Fellow of the IFS, a Professor in the School of Economics at the University of Surrey and a Research Fellow at the IZA.
Journal article details
- DOI
- 10.1162/REST_a_00636
- Publisher
- MIT Press Journals
- JEL
- C14, C21, D12
- Issue
- Volume 99, Issue 2, May 2017, pages 291-304
Suggested citation
R, Blundell and J, Horowitz and M, Parey. (2017). 'Nonparametric estimation of a nonseparable demand function under the Slutsky inequality restriction' 99, Issue 2(2017), pp.291–304.
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