Series Estimation under Cross-sectional Dependence

Jungyoon Lee and Peter M Robinson

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: An asymptotic theory is developed for nonparametric and semiparametric series estimation under general cross-sectional dependence and heterogeneity. A uniform rate of consistency, asymptotic normality, and sufficient conditions for convergence, are established, and a data-driven studentization new to cross-sectional data is justifi ed. The conditions accommodate various cross-sectional settings plausible in economic applications, and apply also to panel and time series data. Strong, as well as weak dependence are covered, and conditional heteroscedasticity is allowed.

Keywords: Series estimation; Nonparametric regression; Spatial data; Cross-sectional dependence; Uniform rate of consistency; Functional central limit the- orem; Data-driven studentization (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C21 (search for similar items in EconPapers)
Date: 2013-06
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
https://sticerd.lse.ac.uk/dps/em/em570.pdf (application/pdf)

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:cep:stiecm:570

Access Statistics for this paper

More papers in STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE
Bibliographic data for series maintained by ().