High-unemployment neighbourhoods in weak labour markets The - PowerPoint PPT Presentation

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