Model selection strategies in a spatial context
Jesus Mur () and
Documentos de Trabajo from Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza
This paper follows on from the discussion of Florax, Folmer and Rey (2003) on the advantages and disadvantages of various specification strategies for econometric models in a spatial setting. Habitual practice has popularized a technique based on the well-known Lagrange Multipliers, which seems to give good results although its basis is entirely ad hoc. In this paper we also contemplate other alternatives which, from a strictly theoretical point of view, seem to be more elaborated. We focus attention on the problem of deciding which model should be specified once the initial one, generally static, presents symptoms of misspecification. There are two alternatives habitually contemplated, the Spatial Lag Model and the Spatial Error Model, which leads us to a classical decision problem. In the final part of the paper we present the results of a Monte Carlo exercise which has enabled us to clear up some doubts, although others still persist.
Keywords: Model selection; Spatial Econometrics; Cross-sectional dependence (search for similar items in EconPapers)
JEL-codes: C21 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (15) Track citations by RSS feed
Downloads: (external link)
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:zar:wpaper:dt2005-06
Access Statistics for this paper
More papers in Documentos de Trabajo from Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza Contact information at EDIRC.
Bibliographic data for series maintained by Vicente Pinilla ().