Nonparametric Estimation in Large Panels with Cross-Sectional Dependence
Xiao Huang
Econometric Reviews, 2013, vol. 32, issue 5-6, 754-777
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.
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1080/07474938.2013.740998 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:754-777
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20
DOI: 10.1080/07474938.2013.740998
Access Statistics for this article
Econometric Reviews is currently edited by Dr. Essie Maasoumi
More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().