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Nonparametric Identification and Estimation of Nonadditive Hedonic Models

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Listed:
  • James J. Heckman
  • Rosa L. Matzkin
  • Lars Nesheim

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.

Suggested Citation

  • James J. Heckman & Rosa L. Matzkin & Lars Nesheim, 2009. "Nonparametric Identification and Estimation of Nonadditive Hedonic Models," NBER Working Papers 15226, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:15226
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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