Nonparametric estimation of the marginal effect in fixed-effect panel data models
Debasri Mukherjee () and
Journal of Multivariate Analysis, 2019, vol. 171, issue C, 53-67
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 US state-level panel data.
Keywords: Environmental Kuznets curve; Fixed effects; Local-within-transformation; Multivariate local linear least squares; Nonparametric estimation; Panel data (search for similar items in EconPapers)
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Working Paper: Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:171:y:2019:i:c:p:53-67
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