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Lee paper on estimation of the marginal effect in fixed-effect panel data models published in JMA

Apr 30, 2019

Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models

Yoonseok Lee, Debasri Mukherjee & Aman Ullah

Journal of Multivariate Analysis, April 2019

Yoonseok Lee

Yoonseok Lee

This paper considers multivariate local linear least squares estimation of panel data models when fixed effects are present. One-step estimation of the local marginal effect is of prime interest. A within-group nonparametric estimator is developed, where the fixed effects are eliminated by subtracting individual-specific locally weighted time average, i.e., the local-within-transformation. It is shown that the local-within-transformation-based estimator satisfies the standard properties of the local linear estimator. In comparison, nonparametric estimators based on the conventional (global) within-transformation or first difference result in estimators which are biased, even in large samples. The new estimator is used to examine the nonlinear relationship between income and nitrogen-oxide level (i.e., the environmental Kuznets curve) based on U.S. state-level panel data.