splm: Spatial Panel Data Models in R

By Giovanni Millo, Gianfranco Piras. 2012

462 citations recorded by the source corpus.

splm is an R package for the estimation and testing of various spatial panel data specifications. We consider the implementation of both maximum likelihood and generalized moments estimators in the context of fixed as well as random effects spatial panel data models. This paper is a general description of splm and all functionalities are illustrated using a well-known example taken from Munnell (1990) with productivity data on 48 US states observed over 17 years. We perform comparisons with other available software; and, when this is not possible, Monte Carlo results support our original implementation.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/7ba7c157e16c4e8df78082aa2a22a5692364bbb9

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In Economics and Econometrics

Citations in the corpus

Coal and the European Industrial Revolution (2014, methodology): “The use of a spatial panel methodology necessitates the use of balanced panels Millo and Piras (2012).”
Spatial Panel-data Models Using Stata (2017, unknown): “To the best of our knowledge, while both R and Matlab oﬀer large suite of functions for the estimation of spatial panel data models (Millo and Piras 2012; LeSage and Pace 2009), with the notable exemption represented by the accompanying code of Kapoor et al. (2007), Stata’s capabilities include a…”
Comparing Implementations of Estimation Methods for Spatial Econometrics (2015, methodology): “Having compared implementations of GMM estimators, we move to cross-section maximum likelihood (ML) estimation, recalling that ML estimation for spatial panel models was compared for MATLAB and R implementations in Millo and Piras (2012).”
Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models (2016, methodology): “Estimations presented in this paper were performed using the splm package in R (see Millo and Piras 2012).12”