Identification and nonparametric estimation of a transformed additively separable model

David Jacho-Chávez, Arthur Lewbel and Oliver Linton

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Let r (x, z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses identification and consistent estimation of the unknown functions H, M, G and F, where r (x, z) = H [M (x, z)] and M (x, z) = G(x) + F (z). 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, and 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 empirically apply our results to nonparametrically estimate and test generalized homothetic production functions in four industries within the Chinese economy.

Keywords: Partly separable models; Nonparametric regression; Dimension reduction; Generalized homothetic function; Production function. (search for similar items in EconPapers)
JEL-codes: C13 C14 C21 D24 (search for similar items in EconPapers)
Pages: 73 pages
Date: 2006-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://eprints.lse.ac.uk/4416/ Open access version. (application/pdf)

Related works:
Journal Article: Identification and nonparametric estimation of a transformed additively separable model (2010)
Working Paper: Identification and Nonparametric Estimation of a Transformed Additively Separable Model (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:4416

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().