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The SHAC estimator in panel data with group-specific spatial lags

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  • James Schmidt
  • Hoa Tran

Abstract

An adaptation of the spatial heteroskedasticity autocorrelation consistent (SHAC) estimator from the context of a single cross section to a panel data environment is presented. The spatial model involved with the SHAC estimator is generalized to allow spatial lag parameters and spatial weights to vary across groups of cross section members. A model of earnings growth in the 48 contiguous states of the U.S. grouped into eight subnational regions, is used as an illustration. The traditional production inputs of labor, physical capital, and human capital are significant determinants of earnings growth. Significant differences between the spatial lag parameters of subnational regions are found. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • James Schmidt & Hoa Tran, 2014. "The SHAC estimator in panel data with group-specific spatial lags," Letters in Spatial and Resource Sciences, Springer, vol. 7(2), pages 61-71, July.
    • Handle: RePEc:spr:lsprsc:v:7:y:2014:i:2:p:61-71
    DOI: 10.1007/s12076-013-0101-z
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    References listed on IDEAS

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    1. Carmichael, Benoît & Coën, Alain, 2008. "Asset pricing models with errors-in-variables," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 778-788, September.
    2. Coen, Alain & Racicot, Francois-Eric, 2007. "Capital asset pricing models revisited: Evidence from errors in variables," Economics Letters, Elsevier, vol. 95(3), pages 443-450, June.
    3. 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.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    5. Barbara Dettori & Emanuela Marrocu & Raffaele Paci, 2012. "Total Factor Productivity, Intangible Assets and Spatial Dependence in the European Regions," Regional Studies, Taylor & Francis Journals, vol. 46(10), pages 1401-1416, November.
    6. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, August.
    7. Dayton M. Lambert & Kevin T. McNamara, 2009. "Location determinants of food manufacturers in the United States, 2000–2004: are nonmetropolitan counties competitive?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(6), pages 617-630, November.
    8. Dagenais, Marcel G. & Dagenais, Denyse L., 1997. "Higher moment estimators for linear regression models with errors in the variables," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 193-221.
    9. Julie Le Gallo & Bernard Fingleton, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances : finite sample properties," Post-Print hal-00485035, HAL.
    10. Gasper A. Garofalo & Steven Yamarik, 2002. "Regional Convergence: Evidence From A New State-By-State Capital Stock Series," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 316-323, May.
    11. 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. Bernard Fingleton, 2022. "Modifying the linear two-step Windmeijer correction for the presence of spatial error dependence," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-18, December.

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    More about this item

    Keywords

    Spatial model; Panel data; Group weights; Earnings growth; C21; C23; C26; R15;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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