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Dynamic invariant multinomial probit model: identification, pretesting and estimation
[journal article]
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 specia... view more
"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]... view less
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Discrete choice; Efficient Importance sampling; Invariance; Monte-Carlo integration; Panel data; Simulated maximum likelihood;
Document language
English
Publication Year
2009
Page/Pages
p. 117-127
Journal
Journal of Econometrics, 155 (2009) 2
DOI
https://doi.org/10.1016/j.jeconom.2009.09.021
Status
Postprint; peer reviewed
Licence
PEER Licence Agreement (applicable only to documents from PEER project)