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Identification and nonparametric estimation of a transformed additively separable model

Jacho-Chávez, David and Lewbel, Arthur and Linton, Oliver (2010) Identification and nonparametric estimation of a transformed additively separable model. Journal of Econometrics, 156 (2). pp. 392-407. ISSN 0304-4076

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Identification Number: 10.1016/j.jeconom.2009.11.008

Abstract

Let r(x,z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses the identification and consistent estimation of the unknown functions H, M, G and F, where r(x,z)=H[M(x,z)], M(x,z)=G(x)+F(z), and H is strictly monotonic. An estimation algorithm is proposed for each of the model’s unknown components when r(x,z) represents a conditional mean function. The resulting estimators use marginal integration to separate the components G and F. Our estimators are shown to have a limiting Normal distribution with a faster rate of convergence than unrestricted nonparametric alternatives. Their small sample performance is studied in a Monte Carlo experiment. We apply our results to estimate generalized homothetic production functions for four industries in the Chinese economy.

Item Type: Article
Official URL: http://www.elsevier.com/wps/find/journaldescriptio...
Additional Information: © 2010 Elsevier B.V.
Subjects: H Social Sciences > HB Economic Theory
Sets: Research centres and groups > Financial Markets Group (FMG)
Collections > Economists Online
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Departments > Economics
Date Deposited: 23 Jul 2010 10:55
Last Modified: 04 May 2017 09:35
URI: http://eprints.lse.ac.uk/id/eprint/28711

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