Prediction Using Panel Data Regression with Spatial Random Effects
AbstractThis 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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Bibliographic InfoPaper provided by Spatial Economics Research Centre, LSE in its series SERC Discussion Papers with number 0007.
Date of creation: Sep 2008
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Web page: http://www.spatialeconomics.ac.uk/SERC/publications/default.asp
panel data; spatially correlated error components; economic geography; spatialeconometrics;
Find related papers by JEL classification:
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General
- F02 - International Economics - - General - - - International Economic Order; Noneconomic International Organizations;; Economic Integration and Globalization: General
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