The generalized spatial random effects model in R

Giovanni Millo ()
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Giovanni Millo: DEAMS, University of Trieste

Journal of Spatial Econometrics, 2022, vol. 3, issue 1, 1-18

Abstract: Abstract We describe a user-friendly, production quality R implementation of the maximum likelihood estimator of the generalized spatial random effects (GSRE) model of Baltagi, Egger and Pfaffermayr within the well known ’splm’ package for spatial panel econometrics. We extend the maximum likelihood estimator for the GSRE to including a spatial lag of the dependent variable (SAR), and we discuss the theoretical and computational approach. This is the first implementation of the SAR+GSRE, and the second of the original GSRE. Until recently only estimators restricting the spatial structure of individual effects in an arbitrary way have been available and widely employed in applied practice. We present results from the SAR+GSRE and the restricted estimators side by side, drawing on some well-known examples from the spatial econometrics literature. The potential biases from imposing inappropriate restrictions to the spatial error process and/or from omitting the SAR term are illustrated by simulation.

Keywords: Generalized spatial panel; Random effects; Maximum likelihood; R (search for similar items in EconPapers)
JEL-codes: C23 R1 R15 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s43071-022-00024-9

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