Economics at your fingertips  


C. Alan Bester, Timothy Conley (), Christian B. Hansen and Timothy Vogelsang ()

Econometric Theory, 2016, vol. 32, issue 1, 154-186

Abstract: This paper develops a method for performing inference using spatially dependent data. We consider test statistics formed using nonparametric covariance matrix estimators that account for heteroskedasticity and spatial correlation (spatial HAC). We provide distributions of commonly used test statistics under “fixed-b†asymptotics, in which HAC smoothing parameters are proportional to the sample size. Under this sequence, spatial HAC estimators are not consistent but converge to nondegenerate limiting random variables that depend on the HAC smoothing parameters, the HAC kernel, and the shape of the spatial region in which the data are located. We illustrate the performance of the “fixed-b†approximation in the spatial context through a simulation example.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed

Downloads: (external link) ... type/journal_article link to article abstract page (text/html)

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:

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Keith Waters ().

Page updated 2020-09-08
Handle: RePEc:cup:etheor:v:32:y:2016:i:01:p:154-186_00