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Econometría espacial usando Stata. Breve guía aplicada para datos de corte transversal

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  • Marcos Herrera Gomez

    (CONICET-IELDE/UNSa)

Abstract

This document aims to present the common tools within Stata to estimate and test spatial econometric models. This paper contains an exploratory analysis of spatial data and a range of simple and complex spatial regression models. The guide can be used as a manual to apply spatial econometrics in the context of Stata software. The database and codes used in the different sections are available to replicate step by step procedure.

Suggested Citation

  • Marcos Herrera Gomez, 2015. "Econometría espacial usando Stata. Breve guía aplicada para datos de corte transversal," Working Papers 13, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.
  • Handle: RePEc:slt:wpaper:13
    as

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    File URL: http://economicas.unsa.edu.ar/ielde/archivos/docTrabajo/items_upload_WPIelde_Nro13.pdf
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    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Stephen Gibbons & Henry G. Overman, 2012. "Mostly Pointless Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 172-191, May.
    3. Leen Hordijk, 1979. "Problems In Estimating Econometric Relations In Space," Papers in Regional Science, Wiley Blackwell, vol. 42(1), pages 99-115, January.
    4. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    5. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    6. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    7. Marcos Herrera & Jesús Mur & Manuel Ruiz, 2016. "Detecting causal relationships between spatial processes," Papers in Regional Science, Wiley Blackwell, vol. 95(3), pages 577-594, August.
    8. Roger Bivand, 2002. "Spatial econometrics functions in R: Classes and methods," Journal of Geographical Systems, Springer, vol. 4(4), pages 405-421, December.
    9. 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.
    10. David M. Drukker & Hua Peng & Ingmar Prucha & Rafal Raciborski, 2013. "Creating and managing spatial-weighting matrices with the spmat command," Stata Journal, StataCorp LP, vol. 13(2), pages 242-286, June.
    11. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    12. P. Wilner Jeanty, 2010. "SPLAGVAR: Stata module to generate spatially lagged variables, construct the Moran Scatter plot, and calculate Moran's I statistics," Statistical Software Components S457112, Boston College Department of Economics, revised 09 Aug 2012.
    13. Mur, Jesús & Angulo, Ana, 2009. "Model selection strategies in a spatial setting: Some additional results," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 200-213, March.
    14. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    15. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances," Stata Journal, StataCorp LP, vol. 13(2), pages 221-241, June.
    16. repec:rri:wpaper:201301 is not listed on IDEAS
    17. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
    18. P. Wilner Jeanty, 2010. "SPWMATRIX: Stata module to generate, import, and export spatial weights," Statistical Software Components S457111, Boston College Department of Economics, revised 15 Mar 2014.
    19. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "A command for estimating spatial-autoregressive models with spatial-autoregressive disturbances and additional endogenous variables," Stata Journal, StataCorp LP, vol. 13(2), pages 287-301, June.
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    Cited by:

    1. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
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    4. Carlos Daniel Navarro, 2015. "Migración y Desempleo: Un análisis espacial para el Noroeste Argentino," Working Papers 14, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.

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