"How industrial, occupational and racial structure contribute to spatial variation in unemployment in England and Wales"
"How industrial, occupational and racial structure contribute to spatial variation in unemployment in England and Wales"
This thesis looks at three factors of the labour market, namely industrial, occupational and racial structure, and analyses how they can influence the differing unemployment rates in local authorities across England and Wales. The first chapter studies the effects of racial segregation, which has been found to have significant effects in the US. However, there has been very little research on the subject using data from the United Kingdom, despite much of the ethnic minority population living in segregated areas. This chapter follows the approach used by Cutler and Glaeser (1997) and looks at the effects of segregation on unemployment in England and Wales in 1991 and 2001. We find that non-white residents suffer higher unemployment as segregation increases, whether segregation is measured compared to the racial structure of local authorities or counties. However, the nature of the relationship is different and the two segregation indices suggest policy should be aimed at different groups.
In chapter 2, a model of the labour market is presented that can explain why areas which have historically been dependent on industries that have suffered from a decline in employment experience higher unemployment in the future. This is done by extending the Pissarides (2000) model by introducing two sectors and making movement between the two costly. A numerical example is presented to show how this model can explain the difference between unemployment rates in the manufacturing and service industries in the UK in the 1980s, and also why low skilled workers have higher unemployment rates than more skilled colleagues.
The third chapter looks at how structural change can affect unemployment. This has been done many times in the past, but most measures devised have had problems associated with their formulation and use. This chapter provides new measures that show how changes in an area’s industrial and occupational structure can lead to changes above and beyond those associated with natural rate differences. We show that our measures have an important role to play in explaining the different unemployment rates across England and Wales.
University of Southampton
Redding, Stuart
5a730d25-7b2f-46dc-b528-0bd39a12fa23
2005
Redding, Stuart
5a730d25-7b2f-46dc-b528-0bd39a12fa23
Redding, Stuart
(2005)
"How industrial, occupational and racial structure contribute to spatial variation in unemployment in England and Wales".
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
This thesis looks at three factors of the labour market, namely industrial, occupational and racial structure, and analyses how they can influence the differing unemployment rates in local authorities across England and Wales. The first chapter studies the effects of racial segregation, which has been found to have significant effects in the US. However, there has been very little research on the subject using data from the United Kingdom, despite much of the ethnic minority population living in segregated areas. This chapter follows the approach used by Cutler and Glaeser (1997) and looks at the effects of segregation on unemployment in England and Wales in 1991 and 2001. We find that non-white residents suffer higher unemployment as segregation increases, whether segregation is measured compared to the racial structure of local authorities or counties. However, the nature of the relationship is different and the two segregation indices suggest policy should be aimed at different groups.
In chapter 2, a model of the labour market is presented that can explain why areas which have historically been dependent on industries that have suffered from a decline in employment experience higher unemployment in the future. This is done by extending the Pissarides (2000) model by introducing two sectors and making movement between the two costly. A numerical example is presented to show how this model can explain the difference between unemployment rates in the manufacturing and service industries in the UK in the 1980s, and also why low skilled workers have higher unemployment rates than more skilled colleagues.
The third chapter looks at how structural change can affect unemployment. This has been done many times in the past, but most measures devised have had problems associated with their formulation and use. This chapter provides new measures that show how changes in an area’s industrial and occupational structure can lead to changes above and beyond those associated with natural rate differences. We show that our measures have an important role to play in explaining the different unemployment rates across England and Wales.
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Published date: 2005
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Local EPrints ID: 465886
URI: http://eprints.soton.ac.uk/id/eprint/465886
PURE UUID: c4eb8ae0-13e1-4d16-b11d-51a0736ab6a4
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Date deposited: 05 Jul 2022 03:26
Last modified: 23 Jul 2022 01:14
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Author:
Stuart Redding
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