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A Spatial Cliff-Ord-Type Model With Heteroskedastic Innovations: Small And Large Sample Results

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  • Irani Arraiz
  • David M. Drukker
  • Harry H. Kelejian
  • Ingmar R. Prucha
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    Abstract

    In this paper, we specify a linear Cliff-and-Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate multistep GMM/IV-type estimation procedures for the parameters of the model. We also give the limiting distributions for our suggested estimators and consistent estimators for their asymptotic variance-covariance matrices. We conduct a Monte Carlo study to show that the derived large-sample distribution provides a good approximation to the actual small-sample distribution of our estimators. Copyright (c) 2009, Wiley Periodicals, Inc.

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    Bibliographic Info

    Article provided by Wiley Blackwell in its journal Journal of Regional Science.

    Volume (Year): 50 (2010)
    Issue (Month): 2 ()
    Pages: 592-614

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    Handle: RePEc:bla:jregsc:v:50:y:2010:i:2:p:592-614

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    Cited by:
    1. Gianfranco Piras & Paolo Postiglione & Patricio Aroca, 2012. "Specialization, R&D and productivity growth: evidence from EU regions," The Annals of Regional Science, Springer, vol. 49(1), pages 35-51, August.
    2. Suárez Cano, Patricia & Mayor Fernández, Matías & Cueto Iglesias, Begoña, 2011. "How important is access to employment offices in Spain? An urban and non-urban perspective," Investigaciones Regionales, Asociación Española de Ciencia Regional, issue 21, pages 119-140.
    3. Sueli Moro & Reginaldo J. Santos, 2013. "The characteristics and evolution of the Brazilian spatial urban system: empirical evidences for the long-run, 1970-2010," Textos para Discussão Cedeplar-UFMG 474, Cedeplar, Universidade Federal de Minas Gerais.
    4. OA. Carboni, 2012. "A Spatial Analysis of R&D: the Role of Industry Proximity," Working Paper CRENoS 201204, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Han, Xiaoyi & Lee, Lung-fei, 2013. "Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 250-271.
    6. Wang, Wei & Lee, Lung-fei, 2013. "Estimation of spatial panel data models with randomly missing data in the dependent variable," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 521-538.
    7. Shang, Qingyan & Poon, Jessie P.H. & Yue, Qingtang, 2012. "The role of regional knowledge spillovers on China's innovation," China Economic Review, Elsevier, vol. 23(4), pages 1164-1175.
    8. Yihua Yu & Li Zhang & Fanghua Li & Xinye Zheng, 2013. "Strategic interaction and the determinants of public health expenditures in China: a spatial panel perspective," The Annals of Regional Science, Springer, vol. 50(1), pages 203-221, February.
    9. Jin, Fei & Lee, Lung-fei, 2013. "Cox-type tests for competing spatial autoregressive models with spatial autoregressive disturbances," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 590-616.
    10. Adelar Fochezatto & Iván G. Peyré Tartaruga, 2014. "Estruturaprodutiva Potencialmente Inovadora E Desenvolvimento Local: Estudo Docaso Dos Municípios Do Rio Grande Do Sul Usando Econometria Espacial," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 161, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
    11. Atreya, Ajita & Ferreira, Susana, 2012. "Spatial Variation in Flood Risk Perception: A Spatial Econometric Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124863, Agricultural and Applied Economics Association.
    12. OA. Carboni & C. Detotto, 2013. "The economic consequences of crime in Italy," Working Paper CRENoS 201303, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    13. Jin, Fei & Lee, Lung-fei, 2012. "Approximated likelihood and root estimators for spatial interaction in spatial autoregressive models," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 446-458.
    14. Ward, Patrick S. & Pede, Valerien O., 2013. "Spatial Patterns of Technology Di usion: The Case of Hybrid Rice in Bangladesh," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150793, Agricultural and Applied Economics Association.
    15. Monkkonen, Paavo & Wong, Kelvin & Begley, Jaclene, 2012. "Economic restructuring, urban growth, and short-term trading: The spatial dynamics of the Hong Kong housing market, 1992–2008," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 396-406.
    16. Xu, Wan & Khachatryan, Hayk, 2013. "The Impact of Integrated Pest Management Practices on U.S. National Nursery Industry Annul Sales Revenue: An Application of Smooth Transition Spatial Autoregressive Models," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142961, Southern Agricultural Economics Association.

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