Nonparametric estimation and testing of fixed effects panel data models. (English) Zbl 1418.62158
Summary: In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics.
MSC:
| 62G08 | Nonparametric regression and quantile regression |
| 62G07 | Density estimation |
| 62G20 | Asymptotic properties of nonparametric inference |
| 62P20 | Applications of statistics to economics |
Keywords:
fixed effects models; model specification tests; nonparametric kernel method; panel data; partially linear model; profile method; random effects models; semiparametric efficiency boundReferences:
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