RT Journal Article
T1 An alternative semiparametric model for spatial panel data
A1 Minguez, Román
A1 Basile, Roberto
A1 Durbán Reguera, María Luz
AB 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.
PB Springer
SN 1618-2510
YR 2020
FD 2020-12-01
LK https://hdl.handle.net/10016/39256
UL https://hdl.handle.net/10016/39256
LA eng
NO Funding was provided by Ministerio de Economía, Industria y Competitividad, Gobierno de España (Grant Nos. MTM2014-52184 and ECO2015-65826-P) and Grant 2019-GRIN-26913 provided by the University of Castilla- La Mancha (UCLM) and the European Fund for Regional Development (EFRD) to the Research Group “Applied Economics and Quantitative Methods”.
DS e-Archivo
RD 1 sept. 2024