An introduction to pspatreg: A new R package for semiparametric spatial autoregressive analysis

Román Mínguez, Roberto Basile and María Durbán

REGION, 2022, vol. 9, No 2, R1-R15

Abstract: This article introduces a new R package (pspatreg) for the estimation of semiparametric spatial autoregressive models. pspatreg fits penalized spline semiparametric spatial autoregressive models via Restricted Maximum Likelihood or Maximum Likelihood. These models are very flexible since they make it possible to simultaneously control for spatial dependence, nonlinearities in the functional form, and spatio-temporal heterogeneity. The package also allows to estimate parametric spatial autoregressive models for both cross sectional and panel data (with fixed effects), thus avoiding the use of different libraries. The official demos, vignettes, and tutorials of the package are distributed either in CRAN or GitHub. This article illustrates the potential of the package by using an application to cross-sectional data.

Date: 2022
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