文章基本信息

标题：Nonparametric Trending Regression with Cross-Sectional Dependence
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作者：Peter M Robinson
期刊名称：Distributional Analysis Publications
印刷版ISSN：1352-2469
出版年度：2010
卷号：2010
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have a common time trend. The time trend is of unknown form, the model includes additive, unknown, individual-specific components, and we allow for spatial or other cross-sectional dependence and/or heteroscedasticity. A simple smoothed nonparametric trend estimate is shown to be dominated by an estimate which exploits the availability of cross-sectional data. Asymptotically optimal choices of bandwidth are justified for both estimates. Feasible optimal bandwidths, and feasible optimal trend estimates, are asymptotically justified, the finite sample performance of the latter being examined in a Monte Carlo study. A number of potential extensions are discussed
关键词：Panel data; nonparametric time trend; cross-sectional ;dependence; generalized least squares; optimal bandwidth