Second-order polynomial spatial error model. Global and local spatial dependence in unemployment in Andalusia

Lopez Fernando A ()

Economic Modelling, 2013, vol. 33, issue C, 270-279

Abstract: This paper analyses a second-order polynomial spatial structure in the residues of a regression model. We propose a new specification that captures spatial dependence on two different levels, adding a new autoregressive cycle to the errors of the classical spatial error model (SEM). The inference problems of the parameters are solved by means of maximum likelihood estimation. The model is confirmed to identify two spatial structures of spatial dependence, global and local, by an empirical application in the analysis of municipal unemployment in the Spanish region of Andalusia. Finally, Monte Carlo is implemented to evaluate the performance of this strategy in a context of finite size samples.

Keywords: Spatial econometric; Higher order spatial models; Instability spatial dependence; Local models; Unemployment; Andalusia (search for similar items in EconPapers)
JEL-codes: C31 E24 J64 R23 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:33:y:2013:i:c:p:270-279

DOI: 10.1016/j.econmod.2013.04.014

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