Prediction using panel data regression with spatial random effects

B. Fingleton

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

This article 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 labor 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 underqualified. This uncertainty highlights the fact that ex ante forecasting should be used with great caution as a basis for policy decisions
Original languageEnglish
Pages (from-to)173-194
Number of pages21
JournalInternational Regional Science Review
Volume32
DOIs
Publication statusPublished - Apr 2009

Fingerprint

panel data
wage
wage level
regression
prediction
economic theory
labor force
immigration
migrant
uncertainty
income
efficiency
interaction
effect

Keywords

  • panel data
  • spatially correlated error components
  • economic geography
  • spatial econometrics

Cite this

@article{8d5fef66b91a4063986b587568d42fbd,
title = "Prediction using panel data regression with spatial random effects",
abstract = "This article 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 labor 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 underqualified. 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",
author = "B. Fingleton",
year = "2009",
month = "4",
doi = "10.1177/0160017609331608",
language = "English",
volume = "32",
pages = "173--194",
journal = "International Regional Science Review",
issn = "0160-0176",

}

Prediction using panel data regression with spatial random effects. / Fingleton, B.

In: International Regional Science Review, Vol. 32, 04.2009, p. 173-194.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Prediction using panel data regression with spatial random effects

AU - Fingleton, B.

PY - 2009/4

Y1 - 2009/4

N2 - This article 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 labor 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 underqualified. This uncertainty highlights the fact that ex ante forecasting should be used with great caution as a basis for policy decisions

AB - This article 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 labor 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 underqualified. This uncertainty highlights the fact that ex ante forecasting should be used with great caution as a basis for policy decisions

KW - panel data

KW - spatially correlated error components

KW - economic geography

KW - spatial econometrics

UR - http://irx.sagepub.com/

UR - http://dx.doi.org/10.1177/0160017609331608

U2 - 10.1177/0160017609331608

DO - 10.1177/0160017609331608

M3 - Article

VL - 32

SP - 173

EP - 194

JO - International Regional Science Review

JF - International Regional Science Review

SN - 0160-0176

ER -