Title

Nonparametric Estimation in Large Panels with Cross-Sectional Dependence

Department

Economics, Finance, & Quantitative Analysis

Document Type

Article

Publication Date

2013

Abstract

In this paper we consider nonparametric estimation in panel data under cross-sectional dependence. Both the number of cross-sectional units (N) and the time dimension of the panel (T) are assumed to be large, and the cross-sectional dependence has a multifactor structure. Local linear regression is used to filter the unobserved cross-sectional factors and to estimate the nonparametric conditional mean. A Monte Carlo simulation study shows that the proposed estimator yields good finite sample properties.

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