Arbeitspapier

Maximum score estimation of preference parameters for a binary choice model under uncertainty

This paper develops maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we estimate conditional expectations nonparametrically in the first stage and then the preference parameters in the second stage based on Manski (1975, 1985)'s maximum score estimator using the choice data and first stage estimates. The paper establishes consistency and derives the rate of convergence of the corresponding two-stage estimator, which is of independent interest for maximum score estimation with generated regressors. The paper also provides results of some Monte Carlo experiments.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP14/13

Klassifikation
Wirtschaft
Hypothesis Testing: General
Estimation: General
Semiparametric and Nonparametric Methods: General
Thema
discrete choice
maximum score estimation
generated regressor
preference parameters
M-estimation
cube root asymptotics

Ereignis
Geistige Schöpfung
(wer)
Chen, Le-Yu
Lee, Sokbae
Jae Sung, Myung
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2013

DOI
doi:10.1920/wp.cem.2013.1413
Handle
Letzte Aktualisierung
20.09.2024, 08:25 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

  • Chen, Le-Yu
  • Lee, Sokbae
  • Jae Sung, Myung
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2013

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