Spatio-Temporal Autoregressive Semiparametric Model for the analysis of regional economic data

Roman Mínguez (roman.minguez@uclm.es), María L. Durbán (mdurban@est-econ.uc3m.es) and Roberto Basile (robertobasile66@yahoo.it)
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Roman Mínguez: University of Castilla-La Mancha
María L. Durbán: Carlos III University

No 16126, Working Papers LuissLab from Dipartimento di Economia e Finanza, LUISS Guido Carli

Abstract: In this paper we propose an extension of the semiparametric P-Spline model to spatio-temporal data including a non-parametric trend, as well as a spatial lag of the dependent variable. This model is able to simultaneously control for func- tional form bias, spatial dependence bias, spatial heterogeneity bias, and omitted time-related factors bias. Specically, we consider a spatio-temporal ANOVA model disaggregating the trend in spatial and temporal main eects, and second and third order interactions between them. The model can include both linear and non-linear effects of the covariates, and other additional xed or random eects. Recent algorithms based on spatial anisotropic penalties (SAP) are used to estimate all the parameters in a closed form without the need of multidimensional optimization. An empirical case compares the performance of this model against alternatives models like spatial panel data models.

Keywords: : spatio-temporal trend; mixed models; P-splines; PS-ANOVA; SAR; spatial panel. (search for similar items in EconPapers)
JEL-codes: C14 C33 C63 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-ore and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:lui:lleewp:16126

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