High-unemployment neighbourhoods in weak labour markets ”The socio-political challenges of medium-sized cities” 10 December 2010, Keele University Alex Fenton (aff28@cam.ac.uk) CCHPR, Department of Land Economy
Spatial disparities in unemployment - Two modes of analysis “Regional economics” “Neighbourhood geography” Primarily economics-based Variety of disciplines A puzzle for classical economics? Small spatial scale Large spatial scale Neighbourhoods, estates, districts Cities, regions Housing explanations Non-housing explanations Sorting by allocation & subsidy Agglomeration Sorting by stock & price Infrastructure Domestic and international migration Human capital Neighbourhood effects? Global competition
Background questions If there are inequalities, do they matter? Thresholds / non-linear effects of concentrated disadvantage “Cultures of worklessness”? “Equality” And if so, what should we do about it? Individual-level intervention (coercive / supportive) Broad redistribution Neighbourhood-level ABIs Sub-regional economic development
Three empirical studies of high-unemployment neighbourhoods 25-year estimates of neighbourhood unemployment rates in England & Wales Joseph Rowntree Foundation, “Communities in recession”, 2009 Modelling and cluster analysis of employment-deprived neighbourhoods in England Communities and Local Government, “Typologies of Place”, 2009-10 “Why do neighbourhoods stay poor?” - mixed methods study of Birmingham poverty neighbourhoods Supported by Barrow Cadbury Trust, 2008-10
Project 1: Neighbourhood unemployment rates 1985 - 2010 JSA claims data + GIS-derived population estimates For ~7,000 neighbourhoods in England & Wales, mean working age population ~4,500 Monthly values 1985 - mid-2009 - so short-term effects visible Linked socio-economic characteristics of n'hoods (housing, occupation etc) Research questions: “Vulnerability” to recession Persistence and change Inequality
Neighbourhood claimant rates 1985-2009, selected percentiles Chart with deciles! 50 (second bottom line) is the median average rate 75 is the rate for the worst-off 25% 95 is the rate for the worst-off 5%
What does it tell us? JSA rates have fallen overall Displacement onto incapacity benefits from early 1990s Problem for comparability Small number of areas have very high rates Gap between worst-off and average grows in absolute terms in recessions Long-term high-unemployment neighbourhoods suffer most More stark if considered as risk-per-person of becoming unemployed
Vulnerability to short-term shocks: Neighbourhood characteristics & rise in unemployment 2008-09 Industries & Workforce Long-term Unemployment Manufacturing Base claimant rate Construction Finance Orange bar = associated Region Real Estate with bigger rise in JSA London Public Sector North East Younger workers 16-30 NS: North West Older workers 50+ Yorks & H No qualifications East Mids High qualifications West Mids East Neighbourhood Green bar = associated South East Social rented with smaller rises South West NS: Private rented Wales Not White British No car
21 years and one-and-a-half recessions: long-term change? Use standardised rates for Starting point comparison over longer Claimant rate Q2 1986 periods Region Simple correlation of 1986 London North East rates with 2007 rates is .75 North West Yorks & Humb Of the 614 n'hoods which were (NS) East Mids in 1 st (worst-off) decile in 1985: West Mids East 400 were in the top decile again in South East 2005 South West Only 8 (1.9%) had below average Wales JSA rates in 2005
Cities and their high-unemployment neighbourhoods Some of the variation in rates is difference within cities and regions About 75% of overall variance is that between better-off and worse-off n'hoods within each town/city About 25% (by one measure) is the variation between cities and regions Difference between cities was: Highest in the late 1980s Lowest in the depths of the 1990s recession Has been gradually, though slightly, declining since 2000 Effects of the current recession not yet apparent
The trajectories of some small cities: Base neighbourhood JSA unemployment rate, relative to E&W
Project 2: Classifying high-unemployment neighbourhoods in 2008 Policy interest in use of spatial area classifications / typologies Allocation of resources Selection of suitable interventions Use in evaluation - identifying similar 'control' areas Statistical typologies have to be based on a selection of variables But what is 'relevant' to concentrated unemployment depends on perspective Regional or local causes? Housing, migration or people? Etc
Project 2: Classifying high-unemployment neighbourhoods in 2008 Model three dimensions of employment deprivation at neighbourhood level, for worst 20% areas on IMD Excess disability (IB/ESA claims) Claimant unemployment (JSA rates) Seasonal variation in unemployment (JSA flows) Consider three spatial levels Neighbourhood (LSOA): demographics, housing, labour force characteristics Housing market (LA): rents, migration, commuting Labour market (NUTS3): wages, productivity, labour demand Use results of models as basis for cluster analysis
The JSA model The variance is both between Spatial level % Variance and within labour markets Labour Market 24% (NUTS3) cf above: ~25% of variation is between regions Housing Market 14% Area and neighbourhood (LA) characteristics both useful Interactions: e.g. high rents + low Neighbourhood 62% (LSOA) entry-level wages + social housing What predicts JSA claim rates in most deprived 20% is not the same as in all n'hoods
A four-way classification Group Description A Highly deprived social housing neighbourhoods B Older workers in declining areas C High-churn neighbourhoods with younger workers D Ethnically mixed neighbourhoods in stronger labour markets (E) (Inner London)
A ten-way classification Description 4 Description 4 i Social housing n'hoods with A vi N'hoods with young population in C extreme multiple deprivation vulnerable employment B ii Multiply deprived social housing A vii High turnover, socially mixed C n'hoods n'hoods in self-contained labour B markets; much hospitality work iii Dormitory, declining n'hoods in very A weak economies; much ill-health B viii Mixed social housing n'hoods in D buoyant cities iv Stable n'hoods with older workers, B steady employment ix Young, socially and ethnically D mixed n'hoods in buoyant cities N'hoods with private housing in v C weaker self-contained labour x Inner London E B markets
The North of England i Soc hsg, extreme depr ii Soc hsg, multiple depr iii Declining areas, older, IB iv Older wrkrs, stable emp v Weak self-cont markets vi Young pop, vuln work vii High turnover, soc mix viii Soc hsg mix in buoyant ix Soc / eth mix in buoyant x Inner London - Not in most deprived
The Midlands and the South East i Soc hsg, extreme depr ii Soc hsg, multiple depr iii Declining areas, older, IB iv Older wrkrs, stable emp v Weak self-cont markets vi Young pop, vuln work vii High turnover, soc mix viii Soc hsg mix in buoyant ix Soc / eth mix in buoyant x Inner London - Not in most deprived
The South West
High-unemployment neighbourhoods in smaller cities Percent of neighbourhoods by classification England Hull Stoke Plymouth Bath 1 Extreme Deprived Soc Hsg 13 54 10 17 0 2 Multiple Deprived Soc Hsg 18 10 1 25 75 3 Declining, Ill Health 15 11 35 6 0 4 Older, Steady Work, Stable 17 0 27 23 0 5 Local Work, Private Hsg 11 6 22 2 0 6 Young, Vulnerable Work 7 6 4 10 25 7 Churn, Local Hospitality Work 5 13 0 15 0 8 Mixed Soc Hsg, Buoyant City 7 0 0 2 0 9 Young, Mixed, Buoyant City 5 0 0 0 0 * Inner London 2 0 0 0 0
Conclusions - neighbourhood unemployment High degree of unemployment persistence over ~25 years Cyclical unemployment effects strongly correlated with base unemployment Reserve pools of labour, not cultures of worklessness? Multiple spatial levels of analysis needed at once ~30-40% variance attributable to differences between labour markets Then - local demography / human capital / housing stock Interactions between neighbourhood housing tenure & wider area features Rented tenures, especially public housing, predominates Mechanisms are different for highest unemployment areas
What does it mean for smaller cities? Very different trajectories Smaller cities have distinctive types of high-unemployment n'hoods Varies by industrial history Varies by geographic features (self-containment) Varies by housing system (large estates? high-cost / low-cost Implications for policy interventions
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