We illustrate the new splm package, aimed at providing a comprehensive resource for spatial panel econometrics. The package fills a gap in applied practice, as the relevant estimators and tests are well established in the literature but to date they lack user-friendly and widely available software implementations.
Building on the infrastructure for spatially referenced data in package spdep, we provide estimators for the standard panel models in the spatial econometrics literature: fixed and random effects with either a
spatial lag or spatial correlation in the error term, based on both the concurrent approaches prevailing in the literature, i.e. the Maximum Likelihood framework pioneered by Anselin (1988) and the Generalized Moments framework of Kapoor, Kelejian and Prucha (2007).
Some of the model estimation procedures are generalized to the case of spatially and serially correlated
error terms. GM estimators for systems of equations are also available.
We also provide the Lagrange Multiplier joint, marginal and conditional specification tests from the work
of Baltagi et al. (2003, 2007).
The user interface aims at consistency w.r.t. the spatial (non-panel) estimators in package spdep and the panel (non-spatial) estimators in package plm.
We briefly discuss code optimization aspects of the computationally heavy Maximum Likelihood routines
that have up to now hindered the practical implementation of these estimators. The GM approach, on its part, yields very fast estimators that can be applied to comparatively big datasets.
We conclude with an empirical illustration on a well-known data set from the panel data literature.
