On model specification and parameter space definitions in higher order spatial econometric models

J.Paul Elhorst, Donald J. Lacombe and Gianfranco Piras

Regional Science and Urban Economics, 2012, vol. 42, issue 1-2, 211-220

Abstract: Higher-order spatial econometric models that include more than one weights matrix have seen increasing use in the spatial econometrics literature. There are two distinct issues related to the specification of these extended models. The first issue is what form the higher-order spatial econometric model takes, i.e. higher-order polynomials in the spatial weights matrices vs. higher-order spatial autoregressive processes. The second issue relates to the parameter space in such models and how this can affect the choice of model specification, estimation, and inference. We outline a procedure that is simple both mathematically and computationally for finding the stationary region for spatial econometric models with up to K weights matrices for higher-order spatial autoregressive processes. We also compare and contrast this approach with the parameter space for models that incorporate higher-order polynomials in the spatial weights matrices. Regardless of the model utilized in empirical practice, ignoring the relevant parameter region can lead to incorrect inferences regarding both the nature of the spatial autocorrelation process and the effects of changes in covariates on the dependent variable.

Keywords: Higher order spatial models; Parameter space; Spatial econometrics (search for similar items in EconPapers)
JEL-codes: C01 C18 C21 C63 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (65)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166046211001104
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:42:y:2012:i:1:p:211-220

DOI: 10.1016/j.regsciurbeco.2011.09.003

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 ().