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Seemingly unrelated regressions with spatial error components


  • Badi Baltagi


  • Alain Pirotte



This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with spatial error correlation. The true data generating process is assumed to be SUR with spatial error of the autoregressive or moving average type. Moreover, the remainder term of the spatial process is assumed to follow an error component structure. Both maximum likelihood and generalized moments (GM) methods of estimation are used. Using Monte Carlo experiments, we check the performance of these estimators and their forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous versus homogeneous panel data models.
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(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Badi Baltagi & Alain Pirotte, 2011. "Seemingly unrelated regressions with spatial error components," Empirical Economics, Springer, vol. 40(1), pages 5-49, February.
  • Handle: RePEc:spr:empeco:v:40:y:2011:i:1:p:5-49 DOI: 10.1007/s00181-010-0373-8

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    References listed on IDEAS

    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. Baltagi, Badi H. & Rich, Daniel P., 2005. "Skill-biased technical change in US manufacturing: a general index approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 549-570, June.
    3. Howrey, E. Philip & Varian, Hal R., 1984. "Estimating the distributional impact of time-of-day pricing of electricity," Journal of Econometrics, Elsevier, vol. 26(1-2), pages 65-82.
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    5. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    6. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2007. "A Monte Carlo Study for Pure and Pretest Estimators of a Panel Data Model with Spatially Autocorrelated Disturbances," Annals of Economics and Statistics, GENES, issue 87-88, pages 11-38.
    7. Peter Egger & Michael Pfaffermayr, 2004. "Distance, trade and FDI: a Hausman-Taylor SUR approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 227-246.
    8. Baltagi, Badi H & Griffin, James M & Rich, Daniel P, 1995. "Airline Deregulation: The Cost Pieces of the Puzzle," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(1), pages 245-260, February.
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    10. Sickles, Robin C., 1985. "A nonlinear multivariate error components analysis of technology and specific factor productivity growth with an application to the U.S. Airlines," Journal of Econometrics, Elsevier, vol. 27(1), pages 61-78, January.
    11. Kinal, Terrence & Lahiri, Kajal, 1990. "A computational algorithm for multiple equation models with panel data," Economics Letters, Elsevier, vol. 34(2), pages 143-146, October.
    12. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    13. Beierlein, James G & Dunn, James W & McConnon, James C, Jr, 1981. "The Demand for Electricity and Natural Gas in the Northeastern United States," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 403-408, August.
    14. Avery, Robert B, 1977. "Error Components and Seemingly Unrelated Regressions," Econometrica, Econometric Society, vol. 45(1), pages 199-209, January.
    15. Brown, Philip & Kleidon, Allan W. & Marsh, Terry A., 1983. "New evidence on the nature of size-related anomalies in stock prices," Journal of Financial Economics, Elsevier, vol. 12(1), pages 33-56, June.
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    Cited by:

    1. AMBA OYON, Claude Marius & Mbratana, Taoufiki, 2017. "Simultaneous equation models with spatially autocorrelated error components," MPRA Paper 82395, University Library of Munich, Germany.
    2. Hailong Qian & Heather L. Bednarek, 2015. "Partial efficient estimation of SUR models," Economics Bulletin, AccessEcon, vol. 35(1), pages 338-348.
    3. Karolina Lewandowska-Gwarda, 2013. "Migracje zagraniczne w Polsce - analiza z wykorzystaniem przestrzennego modelu SUR," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 30, pages 43-57.
    4. Wang, Sicong & Wang, Shifeng, 2016. "Integrating spatial and biomass planning for the United States," Energy, Elsevier, vol. 114(C), pages 113-120.
    5. Chakir, Raja & Le Gallo, Julie, 2013. "Predicting land use allocation in France: A spatial panel data analysis," Ecological Economics, Elsevier, vol. 92(C), pages 114-125.
    6. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, Elsevier.
    7. repec:eee:ecolet:v:156:y:2017:i:c:p:138-141 is not listed on IDEAS
    8. Hauptmeier, Sebastian & Mittermaier, Ferdinand & Rincke, Johannes, 2012. "Fiscal competition over taxes and public inputs," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 407-419.
    9. Diana M. Hechavarría, 2016. "The impact of culture on national prevalence rates of social and commercial entrepreneurship," International Entrepreneurship and Management Journal, Springer, vol. 12(4), pages 1025-1052, December.
    10. W.E. Griffiths & Ma. Rebecca Valenzuela, 2004. "Gibbs Samplers for a Set of Seemingly Unrelated Regressions," Department of Economics - Working Papers Series 912, The University of Melbourne.
    11. Alexander Behar, 2011. "Price Discovery and Price Risk Management Before and After Deregulation of the South African Maize Industry," Working Papers 263, Economic Research Southern Africa.
    12. Baylis, Katherine R. & Paulson, Nicholas D. & Piras, Gianfranco, 2011. "Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(03), August.

    More about this item


    Seemingly unrelated regressions; Panel data; Spatial dependence; Heterogeneity; Forecasting; C33;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models


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