Arbeitspapier

Endogenous semiparametric binary choice models with heteroscedasticity

In this paper we consider endogenous regressors in the binary choice model under a weak median exclusion restriction, but without further specification of the distribution of the unobserved random components. Our reduced form specification with heteroscedastic residuals covers various heterogeneous structural binary choice models. As a particularly relevant example of a structural model where no semiparametric estimator has of yet been analyzed, we consider the binary random utility model with endogenous regressors and heterogeneous parameters. We employ a control function IV assumption to establish identification of a slope parameter [beta] by the mean ratio of derivatives of two functions of the instruments. We propose an estimator based on direct sample counterparts, and discuss the large sample behavior of this estimator. In particular, we show '√'n consistency and derive the asymptotic distribution. In the same framework, we propose tests for heteroscedasticity, overidentification and endogeneity. We analyze the small sample performance through a simulation study. An application of the model to discrete choice demand data concludes this paper.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP34/09

Klassifikation
Wirtschaft
Thema
Semiparametric
Binary Choice
Endogeneity
Average Derivative
Control Function
Random Coefficients
Nichtparametrisches Verfahren
Präferenztheorie
Schätztheorie

Ereignis
Geistige Schöpfung
(wer)
Hoderlein, Stefan
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2009

DOI
doi:10.1920/wp.cem.2009.3409
Handle
Letzte Aktualisierung
20.09.2024, 08:21 MESZ

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
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2009

Ähnliche Objekte (12)