Nonparametric Identification and Estimation of Nonadditive Hedonic Models

29 Pages Posted: 4 Aug 2009

See all articles by James J. Heckman

James J. Heckman

University of Chicago - Department of Economics; National Bureau of Economic Research (NBER); American Bar Foundation; Institute for the Study of Labor (IZA); CESifo (Center for Economic Studies and Ifo Institute)

Rosa L. Matzkin

University of California, Los Angeles (UCLA)

Lars Nesheim

University College London; Institute for Fiscal Studies (IFS)

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Abstract

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data.

Keywords: hedonic models, hedonic equilibrium, nonadditive models, identification, non-parametric estimation

JEL Classification: C14, D41, D58

Suggested Citation

Heckman, James J. and Matzkin, Rosa L. and Nesheim, Lars, Nonparametric Identification and Estimation of Nonadditive Hedonic Models. IZA Discussion Paper No. 4329. Available at SSRN: https://ssrn.com/abstract=1442644

James J. Heckman (Contact Author)

University of Chicago - Department of Economics ( email )

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Rosa L. Matzkin

University of California, Los Angeles (UCLA) ( email )

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Lars Nesheim

University College London ( email )

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Institute for Fiscal Studies (IFS)

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