An alternative semiparametric model for spatial panel data Articles uri icon

publication date

  • December 2020

start page

  • 669

end page

  • 708


  • 29

International Standard Serial Number (ISSN)

  • 1618-2510

Electronic International Standard Serial Number (EISSN)

  • 1613-981X


  • 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.


  • spatial panel; spatio-temporal trend; mixed models; p-splines; ps-anova