Nonparametric Estimation and Inference for Panel Data Models
McMaster University - Department of Economics Working Paper No. 2018-02
39 Pages Posted: 10 Jan 2018
Date Written: January 2, 2018
This chapter surveys nonparametric methods for estimation and inference in a panel data setting. Methods surveyed include profile likelihood, kernel smoothers, as well as series and sieve estimators. The practical application of nonparametric panel-based techniques is less prevalent that, say, nonparametric density and regression techniques. It is our hope that the material covered in this chapter will prove useful and facilitate their adoption by practitioners.
JEL Classification: C14
Suggested Citation: Suggested Citation