Abstract:
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Over-identification is a signature feature of the influential Generalized Method of Moments (Hansen, 1982) that flexibly allows more moment conditions than the model parameters. Investigating over-identification together with high-dimensional statistical problems is challenging and remains less explored. In this talk, we study two high-dimensional statistical problems with over-identification. The first one concerns statistical inferences associated with multiple components of the high-dimensional model parameters, and the second one is on developing a specification test for assessing the validity of the over-identified moment conditions.
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