nonlinear quantile regression

Smoothed GMM for quantile models

This paper develops theory for feasible estimation and testing of finite-dimensional parameters identified by general conditional quantile restrictions, under much weaker assumptions than previously seen in the literature.  This includes instrumental variables nonlinear quantile regression as a special case.  More specifically, we consider a set of unconditional moments implied by the conditional quantile restrictions, providing conditions for local identification.  Since estimators based on the sample moments are generally impossible to compute numerically in practice, we study feasible es

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