Multiple Testing for Different Structures of Spatial Dynamic Panel Data Models

In the econometric field, spatio-temporal data is often modeled by spatial dynamic panel data models (SDPD). In the last decade, several versions of the SDPD model have been proposed, based on different assumptions on the spatial parameters and different properties of the estimators. In particular, the classic version of the model assumes that the spatial parameters are homogeneous over location. Another version, proposed recently and called generalized SDPD, assumes that the spatial parameters are adaptive over location. In this work we propose a strategy for testing the particular structure of the spatial dynamic panel data model, by means of a multiple testing procedure that allows to choose between the generalized version of the model and some specific versions derived from the general one by imposing particular constraints on the parameters. The multiple test is made using the Bonferroni technique and the distribution of the multiple test statistic is derived by a residual bootstrap resampling procedure