Local Partitioned Regression
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In this paper, we introduce a kernel-based estimation principle for nonparametric models named local partitioned regression (LPR). This principle is a nonparametric generalization of the familiar partition regression in linear models. It has several key advantages: First, it generates estimators for a very large class of semi- and nonparametric models. A number of examples that are particularly relevant for economic applications will be discussed in this paper. This class…