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Models for Dynamic Panels in Space and Time - an Application to Regional Unemployment in the EU

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  • J.Paul Elhorst

Abstract

One of the central research questions in modelling space-time data is the right econometric model. At least three problems must be tackled: (i) The observations on each spatial unit might be correlated over time, (ii) The observations at each point in time might be correlated over space, and (iii) The omission of time-invariant and/or spatial-invariant background variables could bias the regression coefficients in a typical cross-section or time-series model. As we have no a priori reasons to believe that one problem is more important than another, this paper presents a general model that encompasses a wide series of simpler models frequently used in the time-series econometrics, spatial econometrics and panel data econometrics literature. A framework is developed to determine which model is the most likely candidate to study space-time data.

Suggested Citation

  • J.Paul Elhorst, 2005. "Models for Dynamic Panels in Space and Time - an Application to Regional Unemployment in the EU," ERSA conference papers ersa05p81, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa05p81
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    References listed on IDEAS

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    2. Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach," China Economic Review, Elsevier, vol. 27(C), pages 264-276.
    3. Vicente Royuela & Gustavo Adolfo Garc�a, 2015. "Economic and Social Convergence in Colombia," Regional Studies, Taylor & Francis Journals, vol. 49(2), pages 219-239, February.
    4. Stefano Magrini, 2007. "Analysing Convergence through the Distribution Dynamics Approach: Why and how?," Working Papers 2007_13, Department of Economics, University of Venice "Ca' Foscari".
    5. Mark V. JANIKAS & Sergio J. REY, 2008. "On The Relationships Between Spatial Clustering, Inequality, And Economic Growth In The United States : 1969-2000," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 27, pages 13-34.
    6. Valentina Meliciani & Maria Savona, 2015. "The determinants of regional specialisation in business services: agglomeration economies, vertical linkages and innovation," Journal of Economic Geography, Oxford University Press, vol. 15(2), pages 387-416.
    7. Vassilis Tselios, 2011. "Is Inequality Good for Innovation?," International Regional Science Review, , vol. 34(1), pages 75-101, January.
    8. Zoltan Acs & Lawrence A. Plummer & Ryan Sutter, 2007. "Penetrating the Knowledge Filter in the Rust Belt," Jena Economics Research Papers 2007-058, Friedrich-Schiller-University Jena.

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