Nonparametric Regression Techniques in Economics

Abstract

This introduction to nonparametric regression emphasizes techniques that might be most accessible and useful to the applied economist. The paper begins with a brief overview of the class of models under study and central theoretical issues such as the curse of dimensionality, the bias-variance trade-off and rates of convergence. The paper then focuses on kernel and nonparametric least squares estimation of the nonparametric regression model, and optimal differencing estimation of the partial linear model. Constrained estimation and hypothesis testing is also discussed. Empirical examples include returns to scale in electricity distribution and hedonic pricing of housing attributes.