EconPapers    
Economics at your fingertips  
 

Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data

John Driscoll () and Aart Kraay ()

The Review of Economics and Statistics, 1998, vol. 80, issue 4, 549-560

Abstract: Many panel data sets encountered in macroeconomics, international economics, regional science, and finance are characterized by cross-sectional or "spatial" dependence. Standard techniques that fail to account for this dependence will result in inconsistently estimated standard errors. In this paper we present conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large. We illustrate the relevance of this approach using Monte Carlo simulations and a number of empirical examples. © 1998 by the President and Fellows of Harvard College and the Massachusetts Institute of Technolog

Date: 1998
References: Add references at CitEc
Citations View citations in EconPapers (654) Track citations by RSS feed

Downloads: (external link)
http://www.mitpressjournals.org/doi/pdf/10.1162/003465398557825 (application/pdf)
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: http://EconPapers.repec.org/RePEc:tpr:restat:v:80:y:1998:i:4:p:549-560

Ordering information: This journal article can be ordered from
http://mitpress.mit. ... me.tcl?issn=00346535

Access Statistics for this article

The Review of Economics and Statistics is currently edited by Daron Acemoglu, George J. Borjas, Dani Rodrik and Julio J. Rotemberg

More articles in The Review of Economics and Statistics from MIT Press
Series data maintained by Kristin Waites ().

 
Page updated 2017-08-08
Handle: RePEc:tpr:restat:v:80:y:1998:i:4:p:549-560