Center for Economic Research, Department of Economics, University of Minnesota
The question of model identification is analyzed for the
semiparametric random utility model of discrete choice. Attention is focused
on settings where agents face a common choice between a set of J+l
alternatives, but where actual choices are only partially observed.
Necessary conditions are derived for the setting where the only data on
actual choices consists of a binary indicator for one of the alternatives.
Sufficient conditions are developed in this setting for a linear in
parameters specification of indirect utility. It is found that relative to
the parametric case, only a mild continuity restriction on the distribution
of regressors is needed in the semiparametric model. Under these
circumstances all of the choice probabilities are identified, even though
actual choices are only partially observed. It is shown that estimators that
rely only on the index structure of the model require substantially stronger
prior restrictions on the parameters for identification when the number of
alternatives is large. Finally, results on the model with partial
observability of choices are used to analyze the special case of full
Thompson, T.S., (1989), "Identification of Semiparametric Discrete Choice Models", Discussion Paper No. 249, Center for Economic Research, Department of Economics, University of Minnesota.
Thompson, T. Scott.
Identification of Semiparametric Discrete Choice Models.
Center for Economic Research, Department of Economics, University of Minnesota.
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