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sphet: Spatial Models with Heteroskedastic Innovations in R

Author

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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.

Suggested Citation

  • 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

    as
    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. Conley, Timothy G. & Molinari, Francesca, 2007. "Spatial correlation robust inference with errors in location or distance," Journal of Econometrics, Elsevier, vol. 140(1), pages 76-96, September.
    3. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    4. 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.
    5. Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 252-277, April.
    6. Harrison, David Jr. & Rubinfeld, Daniel L., 1978. "Hedonic housing prices and the demand for clean air," Journal of Environmental Economics and Management, Elsevier, vol. 5(1), pages 81-102, March.
    7. Baltagi, Badi H. & Egger, Peter & Pfaffermayr, Michael, 2008. "Estimating regional trade agreement effects on FDI in an interdependent world," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 194-208, July.
    8. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    9. Pace, R. Kelley & LeSage, James P., 2004. "Chebyshev approximation of log-determinants of spatial weight matrices," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 179-196, March.
    10. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
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