Arbeitspapier

Nonparametric estimation of nonadditive hedonic models

We analyze equilibria in hedonic economies and study conditions that lead to identification of structural preference parameters in hedonic economies with both additive and nonadditive marginal utility and marginal product functions. The latter class is more general, allows for heterogeneity in the curvature of consumer utility, and can result in conditions that lead to bunching. Such bunching has been largely ignored in the previous literature. We then present methods to estimate marginal utility and marginal product functions that are nonadditive in the unobservable random terms, using observations from a single hedonic equilibrium market. These methods are important when statistical tests reject additive specifications or when prior information suggests that consumer or firm heterogeneity in the curvature of utility or production functions is likely to be significant. We provide conditions under which these types of utility and production functions are nonparametrically identified, and we propose nonparametric estimators for them. The estimators are shown to be consistent and asymptotically normal. When the assumptions required to use single market methods are unjustified, we show how multimarket data can be used to estimate the structural functions.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP03/05

Klassifikation
Wirtschaft
Semiparametric and Nonparametric Methods: General
Market Structure, Pricing, and Design: Perfect Competition
Computable and Other Applied General Equilibrium Models
Thema
hedonic models , hedonic equilibrium , nonadditive models , bunching , identification , nonparametric estimation
Hedonischer Preisindex
Nichtparametrisches Verfahren

Ereignis
Geistige Schöpfung
(wer)
Heckman, James J.
Matzkin, Rosa Liliana
Nesheim, Lars
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2005

DOI
doi:10.1920/wp.cem.2005.0305
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Heckman, James J.
  • Matzkin, Rosa Liliana
  • Nesheim, Lars
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2005

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