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Prediction Using Panel Data Regression with Spatial Random Effects

  • Bernard Fingleton

This paper considers some of the issues and difficulties relating to the use of spatial paneldata regression in prediction, illustrated by the effects of mass immigration on wages andincome levels in local authority areas of Great Britain. Motivated by contemporary urbaneconomics theory, and using recent advances in spatial econometrics, the panel regression haswages dependent on employment density and the efficiency of the labour force. There aretwo types of spatial interaction, a spatial lag of wages, and an autoregressive process for errorcomponents. The estimates suggest that increased employment densities will increase wagelevels, but wages may fall if migrants are under-qualified. This uncertainty highlights the factthat ex ante forecasting should be used with great caution as a basis for policy decisions.

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File URL: http://www.spatialeconomics.ac.uk/textonly/SERC/publications/download/sercdp0007.pdf
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Paper provided by Spatial Economics Research Centre, LSE in its series SERC Discussion Papers with number 0007.

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Date of creation: Sep 2008
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Handle: RePEc:cep:sercdp:0007
Contact details of provider: Web page: http://www.spatialeconomics.ac.uk/SERC/publications/default.asp

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  1. John M. Quigley, 1998. "Urban Diversity and Economic Growth," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 127-138, Spring.
  2. Luciano Gutierrez, 2003. "Panel Unit Roots Tests for Cross-Sectionally Correlated Panels: A Monte Carlo Comparison," Econometrics 0310004, EconWPA.
  3. Badi Baltagi & Dong Li, 2006. "Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 175-185.
  4. 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.
  5. Antonio Ciccone & Robert E. Hall, 1993. "Productivity and the Density of Economic Activity," NBER Working Papers 4313, National Bureau of Economic Research, Inc.
  6. Banerjee, Anindya, 1999. " Panel Data Unit Roots and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 607-29, Special I.
  7. Rivera-Batiz, Francisco L., 1988. "Increasing returns, monopolistic competition, and agglomeration economies in consumption and production," Regional Science and Urban Economics, Elsevier, vol. 18(1), pages 125-153, February.
  8. Anindya Banerjee & Massimiliano Marcellino & Chiara Osbat, 2005. "Testing for PPP: Should we use panel methods?," Empirical Economics, Springer, vol. 30(1), pages 77-91, January.
  9. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "The relative efficiencies of various predictors in spatial econometric models containing spatial lags," Regional Science and Urban Economics, Elsevier, vol. 37(3), pages 363-374, May.
  10. James P. LeSage & R. Kelley Pace, 2004. "Models for Spatially Dependent Missing Data," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 233-254, 09.
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