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sphet: Spatial Models with Heteroskedastic Innovations in R

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  • Piras, Gianfranco

Abstract

sphet is a package for estimating and testing spatial models with heteroskedastic innovations. We implement recent generalized moments estimators and semiparametric methods for the estimation of the coefficients variance-covariance matrix. This paper is a general description of sphet and all functionalities are illustrated by application to the popular Boston housing dataset. The package in its current version is limited to the estimators based on Arraiz, Drukker, Kelejian, and Prucha (2010); Kelejian and Prucha (2007, 2010). The estimation functions implemented in sphet are able to deal with virtually any sample size.

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  • Piras, Gianfranco, 2010. "sphet: Spatial Models with Heteroskedastic Innovations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i01).
    • Handle: RePEc:jss:jstsof:v:035:i01
    DOI: http://hdl.handle.net/10.18637/jss.v035.i01
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    References listed on IDEAS

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    1. Luc Anselin & Nancy Lozano-Gracia, 2009. "Errors in variables and spatial effects in hedonic house price models of ambient air quality," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 5-34, Springer.
    2. Irani Arraiz & David M. Drukker & Harry H. Kelejian & Ingmar R. Prucha, 2010. "A Spatial Cliff‐Ord‐Type Model With Heteroskedastic Innovations: Small And Large Sample Results," Journal of Regional Science, Wiley Blackwell, vol. 50(2), pages 592-614, May.
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