Series estimation under cross-sectional dependence

Lee, Jungyoon and Robinson, Peter (2016) Series estimation under cross-sectional dependence. Journal of Econometrics, 190 (1). pp. 1-17. ISSN 0304-4076

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Abstract

An asymptotic theory is developed for series estimation of nonparametric and semiparametric regression models for cross-sectional data under conditions on disturbances that allow for forms of cross-sectional dependence and hetero-geneity, including conditional and unconditional heteroskedascity, along with conditions on regressors that allow dependence and do not require existence of a density. The conditions aim to accommodate various settings plausible in economic applications, and can apply also to panel, spatial and time series data. A mean square rate of convergence of nonparametric regression estimates is established followed by asymptotic normality of a quite general statistic. Data-driven studentizations that rely on single or double indices to order the data are justified. In a partially linear model setting, Monte Carlo investigation of finite sample properties and two empirical applications are carried out.

Item Type:	Article
Official URL:	http://www.journals.elsevier.com/journal-of-econom...
Additional Information:	© 2015 The Authors.
Divisions:	Economics
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C12 - Hypothesis Testing C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models
Date Deposited:	03 Sep 2015 09:08
Last Modified:	07 Nov 2024 17:03
Projects:	ES/J007242/1, ES/J007242/1
Funders:	Economic and Social Research Council, Economic and Social Research Council
URI:	http://eprints.lse.ac.uk/id/eprint/63380

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