Nonparametric Identification of Discrete Choice Models

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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Year of publication:	1998
Authors:	Dagsvik, John K.
Publisher:	Oslo : Statistics Norway, Research Department
Subject:	Nonparametric identification \| Discrete choice \| Random utility models

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Series:	Discussion Papers ; 222
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	hdl:10419/192206 [Handle] RePEc:ssb:dispap:222 [RePEc]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C25 - Discrete Regression and Qualitative Choice Models
Source:	EconStor

Persistent link: https://www.econbiz.de/10011967994