Embracing heterogeneity: the spatial autoregressive mixture model
Gary Cornwall and
Olivier Parent
Regional Science and Urban Economics, 2017, vol. 64, issue C, 148-161
Abstract:
In this paper a mixture distribution model is extended to include spatial dependence of the autoregressive type. The resulting model nests both spatial heterogeneity and spatial dependence as special cases. A data generation process is outlined that incorporates both a finite mixture of normal distributions and spatial dependence. Whether group assignment is completely random by nature or displays some locational “pattern”, the proposed spatial-mix estimation procedure is always able to recover the true parameters. As an illustration, a basic hedonic price model is investigated that includes sub-groups of data with heterogeneous coefficients in addition to spatially clustered elements.
Keywords: Mixture distributions; Spatial heterogeneity; Spatial models (search for similar items in EconPapers)
JEL-codes: C11 C21 R21 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166046216301004
Full text for ScienceDirect subscribers only
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:eee:regeco:v:64:y:2017:i:c:p:148-161
DOI: 10.1016/j.regsciurbeco.2017.03.004
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 ().