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Prediction Using Panel Data Regression with Spatial Random Effects

Bernard Fingleton ()

SERC Discussion Papers from Centre for Economic Performance, LSE

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

Keywords: panel data; spatially correlated error components; economic geography; spatial econometrics (search for similar items in EconPapers)
JEL-codes: C33 F02 O10 (search for similar items in EconPapers)
Date: 2008-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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http://cep.lse.ac.uk/pubs/download/sercdp0007.pdf (application/pdf)

Related works:
Journal Article: Prediction Using Panel Data Regression with Spatial Random Effects (2009) Downloads
Working Paper: Prediction using panel data regression with spatial random effects (2008) Downloads
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