A scan test for spatial groupwise heteroscedasticity in cross-sectional models with an application on houses prices in Madrid
Coro Chasco Yrigoyen (),
Julie Le Gallo () and
Fernando A. López
Regional Science and Urban Economics, 2018, vol. 68, issue C, 226-238
We propose a scan test for the presence of spatial groupwise heteroskedasticity in cross-sectional data. The scan approach has been used in different fields before, including spatial econometric models, to detect instability in mean values of variables or regression residuals. In this paper, we extend its use to second order moments. Using large Monte Carlo simulations, we check the reliability of the proposed scan procedure to detect instabilities in the variance, the size and power of the test and its accuracy to find spatial clusters of observations with similar variances. Finally, we illustrate the usefulness of this test to improve the specification search in a spatial hedonic model, with an empirical application on housing prices in Madrid.
Keywords: Spatial scan procedure; Spatial groupwise heteroskedasticity; Spatial variance clusters; Monte Carlo simulation; House prices; Madrid (search for similar items in EconPapers)
JEL-codes: C21 C52 C63 R15 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: A scan test for spatial groupwise heteroscedasticity in cross-sectional models with an application on houses prices in Madrid (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:68:y:2018:i:c:p:226-238
Access Statistics for this article
Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou
More articles in Regional Science and Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().