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Nonparametric Identification of Discrete Choice Models

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Author Info
John K. Dagsvik (Statistics Norway)

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Abstract

In this paper we give simple proofs of identification results in discrete choice models for the case where neither the deterministic part nor the distribution function of the random parts of the utility function is specified parametrically. The regularity conditions imposed are standard, but differ from conditions applied by other researchers, such as Matzkin (1992, 1993).

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Publisher Info
Paper provided by Research Department of Statistics Norway in its series Discussion Papers with number 222.

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Date of creation: Jul 1998
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Handle: RePEc:ssb:dispap:222

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Related research
Keywords: Nonparametric identification Discrete choice Random utility models

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models

References listed on IDEAS
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  1. Matzkin, Rosa L., 1993. "Nonparametric identification and estimation of polychotomous choice models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 137-168, July. [Downloadable!] (restricted)
  2. Thompson, T.S., 1989. "Identification Of Semiparametric Discrete Choice Models," Papers 249, Minnesota - Center for Economic Research.
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Statistics
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This page was last updated on 2008-10-10.

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