An alternative semiparametric model for spatial panel data

Román Mínguez (), Roberto Basile and María Durbán
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Román Mínguez: University of Castilla-La Mancha
Roberto Basile: University of L’Aquila
María Durbán: University Carlos III of Madrid

Statistical Methods & Applications, 2020, vol. 29, issue 4, No 1, 669-708

Abstract: Abstract We propose a semiparametric P-Spline model to deal with spatial panel data. This model includes a non-parametric spatio-temporal trend, a spatial lag of the dependent variable, and a time series autoregressive noise. Specifically, we consider a spatio-temporal ANOVA model, disaggregating the trend into spatial and temporal main effects, as well as second- and third-order interactions between them. Algorithms based on spatial anisotropic penalties are used to estimate all the parameters in a closed form without the need for multidimensional optimization. Monte Carlo simulations and an empirical analysis of regional unemployment in Italy show that our model represents a valid alternative to parametric methods aimed at disentangling strong and weak cross-sectional dependence when both spatial and temporal heterogeneity are smoothly distributed.

Keywords: Spatial panel; Spatio-temporal trend; Mixed models; P-splines; PS-ANOVA (search for similar items in EconPapers)
JEL-codes: C14 C33 C63 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10260-019-00492-8

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