Asymptotic EÆciency in Parametric Structural Models with Parameter-Dependent Support
نویسندگان
چکیده
In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constructing eÆcient point estimators. We show that the ML estimator is generally ineÆcient, but that the Bayes estimator is eÆcient according to the usual local asymptotic minmax criterion. We provide intuition for this result using Le Cam's limits of experiments framework.
منابع مشابه
Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support∗
In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constru...
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