Arbeitspapier

Semiparametric estimation of random coefficients in structural economic models

In structural economic models, individuals are usually characterized as solving a decision problem that is governed by a finite set of parameters. This paper discusses the nonparametric estimation of the probability density function of these parameters if they are allowed to vary continuously across the population. We establish that the problem of recovering the probability density function of random parameters falls into the class of non-linear inverse problem. This framework helps us to answer the question whether there exist densities that satisfy this relationship. It also allows us to characterize the identified set of such densities. We obtain novel conditions for point identification, and establish that point identification is generically weak. Given this insight, we provide a consistent nonparametric estimator that accounts for this fact, and derive its asymptotic distribution. Our general framework allows us to deal with unobservable nuisance variables, e.g., measurement error, but also covers the case when there are no such nuisance variables. Finally, Monte Carlo experiments for several structural models are provided which illustrate the performance of our estimation procedure.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP09/12

Klassifikation
Wirtschaft
Thema
Structural Models
Heterogeneity
Nonparametric Identification
Random Coefficients
Inverse Problems

Ereignis
Geistige Schöpfung
(wer)
Hoderlein, Stefan
Nesheim, Lars
Simoni, Anna
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2012

DOI
doi:10.1920/wp.cem.2012.0912
Handle
Letzte Aktualisierung
10.03.2025, 11:45 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

  • Hoderlein, Stefan
  • Nesheim, Lars
  • Simoni, Anna
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2012

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