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Dynamic invariant multinomial probit model : identification, pretesting and estimation

[Zeitschriftenartikel]

Liesenfeld, Roman; Richard, Jean-François

Zitationshinweis

Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):http://nbn-resolving.de/urn:nbn:de:0168-ssoar-267992

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Abstract "We present a new specification for the multinomial multiperiod Probit model with autocorrelated errors. In sharp contrast with commonly used specifications, ours is invariant with respect to the choice of a baseline alternative for utility differencing. It also nests these standard models as special cases, allowing for data based selection of the baseline alternatives for the latter. Likelihood evaluation is achieved under an Efficient Importance Sampling (EIS) version of the standard GHK algorithm. Several simulation experiments highlight identification, estimation and pretesting within the new class of multinomial multiperiod Probit models." [author's abstract]
Klassifikation Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Freie Schlagwörter Discrete choice; Efficient Importance sampling; Invariance; Monte-Carlo integration; Panel data; Simulated maximum likelihood;
Sprache Dokument Englisch
Publikationsjahr 2009
Seitenangabe S. 117-127
Zeitschriftentitel Journal of Econometrics, 155 (2009) 2
DOI http://dx.doi.org/10.1016/j.jeconom.2009.09.021
Status Postprint; begutachtet (peer reviewed)
Lizenz PEER Licence Agreement (applicable only to documents from PEER project)
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