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Nonparametric panel data regression with parametric cross-sectional dependence
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DOI：10.1093/ectj/utab016.png)
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In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sectional dependence. A generalised least squares (GLS)-type estimator is proposed by taking into account this dependence structure. Parameterising the cross-sectional dependence, a local linear estimator is shown to be dominated by this type of GLS estimator. Also, possible gains in terms of rate of convergence are studied. Asymptotically optimal bandwidth choice is justified. To assess the finite sample performance of the proposed estimators, a Monte Carlo study is carried out. Further, some empirical applications are conducted with the aim of analysing the implications of the European Monetary Union for its member countries.
Keyword:
Local linear estimation
panel data
cross-sectional dependence
generalised least squares
optimal bandwidth
pseudo-maximum likelihood estimation
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7
论文数:
567
被引数:
2.3K
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