Social Mix, Neighbourhood Outcomes and Housing Policy

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Social Mix, Neighbourhood Outcomes and Housing
Policy

• SG Firm Analytical Foundations Conference
• 22 April 2008
• Prof Glen Bramley

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Whats this paper about?

• Government policies and rhetoric have placed a
  new emphasis on social mix balance in
  neighbourhoods
• This raises questions about whether such policies
  are achieveable sustainable, as well as
  whether they are desirable
• This contribution focuses on aspects of
  desirability, in terms of social, economic and
  environmental outcomes
• It draws on evidence from a number of studies
• It discusses some of the analytical uncertainties
• And draws out some pointers for policy

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The Research Base

• ESRC Cities research in Edinburgh-Glasgow
  (Bramley Morgan, Housing Studies, 2003
  others)
• Treasury/NRU/Scot Exec Mainstream Services
  Neighbourhood Deprivation (Bramley, Evans, Noble
  2005)
• Scot Exec Educ Dept Home ownership and
  educational achievement(Bramley Karley,
  Housing Studies, 2007)
• Welsh Assembly Government Alternative Resource
  Allocation Methods for Local Government
  (outcome-based funding model for schools Bramley
  Watkins forthcoming)
• EPSRC CityForm Consortium, social
  sustainability urban form (Bramley Power,
  Environment Planning B, 2008 Bramley et al,
  Planning Research Conference, HWU 2007)
• J Rowntree Cleansweep study of neighbhourhood
  environmental services with Glasgow Univ
  (Bramley/Bailey/Hastings/Day/Watkins, EURA
  Conference, Glasgow, Sept 2005)

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How Social Mix Affects Outcomes

• Poor individuals will have poor outcomes anyway
  simple composition effect
• Housing market sorts poorest into intrinsically
  least desirable areas (selection effect)
• Behaviour by poor people (reflecting culture,
  expectations) worsens problems (e.g. rubbish,
  litter)
• Social interactions within neighbourhood
  reinforce negative patterns of behaviour (crime,
  ASB) low collective efficacy in resisting
• Social interactions and cultures within local
  institutions reinforce low outcomes (e.g.
  schools)
• Increased workload on local services not
  recognised by resource allocation so performance
  suffers
• Housing tenure may have some additional effects
  e.g.home ownership through stability commitment

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BACK TO BASICS the Cost of Clean Streets in
Different Physical and Social Circumstances

• Glen Bramley David WatkinsHeriot-Watt
  UniversityAnnette Hastings, Nick BaileyGlasgow
  UniversityRosie DayBirmingham Univ

Research supported by Joseph Rowntree Foundation
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Poor neighbourhoods and environmental problems

• Previous research suggests the risk factors
  associated with environmental problems
• Physical features open spaces, housing
  densities built form (alleys, wind tunnels)
  street scape (unfenced gardens, on street
  parking)
• Economic, social and demographic factors
  economic inactivity, high child density,
  overcrowding, concentrations of vulnerable people
• So can service provision predict and control for
  risk?

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S.H.S. Descriptive Analysis
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Initial Modelling Results (national)

• Worse environmental scores associated with
  poverty, social renting, older people, families
  (esp lone parent), high child density,
  overcrowding, terraced housing, London
• Better environmental scores in rural suburban
  areas, areas with more flats (?), where adequate
  parking, ethnic minorities, higher occupations
  growth areas
• Modest positive association with service
  expenditure (in England, not Scotland)

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Cleanliness outcomes by street deprivation
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Initial Findings from Case 1

• Deprived areas have a heavier workload (i.e. less
  resources) for routine sweeping, but attract more
  responsive resources
• Deprived areas have more problem-generating
  factors non-working population, density,
  overcrowding, flats child density
• Deprived areas have worse environmental outcomes
• Regression model confirms relationships of
  context with outcomes problems establishing
  relationship with resources
• Work to be extended and refined

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Urban Form and Social Sustainability planning
for happy, cohesive and vital communities?
Paper presented at EURA Vital City Conference,
Glasgow, September 2007

• Professor Glen Bramley
• With Dr Caroline Brown, Nicola Dempsey, Dr Sinéad
  Power David Watkins
• g.bramley_at_sbe.hw.ac.uk
• EPSRC GRANT NoGR/S20529/01www.city-form.com

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Measuring Social Sustainability

• 8 elements measured all based on responses to
  multiple questionse.g. social interaction based
  on 13 questions, such as whether they have
  friends in neighbourhood, see them frequently,
  know neighbours by name, look out for each other,
  chat, borrow, etc.
• Where possible, combined positives negatives
  scaled in natural way (100 would be neutral 0
  would be worst possible scores 200 best
  possible)
• Factor analysis generally confirmed groupings
• -Neighbourhood pride/attachment is best single
  representative measure- Closely related to
  environmental quality, home satisfaction,
  interaction

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CityForm Findings

• Most social sustainability outcomes (except
  service access collective participation) are
  worse in more deprived /social rented etc. areas
• Modelled effects of socio-economic variables also
  show this pattern, although sometimes muted after
  controlling for other factors, and sometimes
  non-linear/uneven
• Socio-economic effects tend to be bigger than
  urban form effects although both are important
  (also have to allow for demography,
  accessibility)
• National (S.E.H.) results consistent with
  5-city case study-based results

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Social Sustainability by Tenure Class
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Social Outcomes by Deprivation Ethnicity
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Some Simpl(istic) Simulations
Moving Households from Lowest Ownership Areas to
Middle Areas
Moving Households from Highest Deprivation Areas
to Middle Areas
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Comments on Simulations

• Even these simple examples suggest that there can
  be modest gains in average scores, simply from
  shuffling the pack
• Worst areas are eliminated former residents
  experience major improvement (Rawlsian
  principle)
• Some (probably) middling areas see some worsening
• However, this ignores (a) individual change
  effects e.g. individuals not only move area but
  some also change tenure, or get a job, etc.(b)
  interactive deprivation effect from
  deconcentration
• Therefore overall impact likely to be
  significantly positive

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Alternative Resource Allocation Models for Local
Education Services in Wales

• Research undertaken for Welsh Assembly Government
  by Glen Bramley and David Watkins(CRSIS/SBE,
  Heriot-Watt University, Edinburgh)2007g.bramley_at_
  sbe.hw.ac.uk

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Work on School Attainment

• Work grew out of interest in resource allocation
  for local services and Where does public
  spending go? as well as interest in
  neighbourhoods housing
• Enabled by major advances in data availability
  associated with PLASC/ScotXEd, SATS, LMS,
• Fairly standard modelling using data _at_ pupil,
  school, small larger neighbourhood levels
• Like other work, shows importance of poverty
  (FSM), special needs, parental educational
  background, etc.
• Draws particular attention to effects of
  clustering of poverty etc. at school (and assoc
  neighbourhood) level
• Explores particular role of home ownership

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Key Findings

• Poverty deprivation are key drivers of
  attainment, at both individual and school
  (/?neighbourhood) levels
• Other significant factors including LAC, SEN,
  parental qualifs, family background, mobility
  etc.
• Evidence that home ownership may have an
  additional effect, at individual and school
  levels- but closely correlated with poverty in
  some cases
• It is clearly better to go to a school with fewer
  poor kids, even if you are poor, and possibly to
  a school with more owner occupiers, even if
  parents are not owners.
• Search for non-linearities a bit inconclusive,
  but sensitivity appears greater in middle range

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What are we trying to achieve?

• Minimum standards approach - a floor level of
  attainment for all areas/schools
• A convergence approach a certain proportional
  reduction in the spread of attainment between
  most and least deprived areas/school
• Equal attainment for individual pupils with
  equivalent initial individual endowment/disadvanta
  ge (i.e. trying to neutralise the school or area
  effect of disadvantage)
• Equal entitlement to (lifetime) educational
  resources attainment is mainly relevant via
  progression, or later participation in adult,
  further or higher education
• Maximise percentage attaining (say) 5 A-C at
  KS4 across Wales implies allocating resources
  at margin where marginal productivity, in terms
  of this percentage, is highest social efficiency
  vs equity
• Incentives approach, whereby schools/LEAs get
  some bonus for attaining above a (need-related?)
  threshold level

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Outcome based funding model

• Analysis at school (virtual catchment) level
• Standardize school size for settlement size
• Standardize costs given size, spec needs, etc.
• Measure relative disadvantage due to social
  factors (in terms of attainment)
• Allocate enough extra money to bring predicted
  attainment x closer to mean
• Given minimum school allocation lowest
  observed, feasible x40 (primary)

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Outcome-based needs for primary schools
Note needs formula based on standardized costs
and compensating for 40 of social disadvantage
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Changing Schools Funding

• Wales model shows technical feasibility of
  outcome approach
• But suggests that full equalization could not be
  achieved in short run, even if political will
• Initial reaction to this report mixed LAs find
  it difficult to agree zero sum game
• Disparities between schools ( neighbourhoods)
  greater, but LEA formulae allocating to schools
  typically even less redistributive
• Small rural schools get most funding per pupil,
  and are of dubious educational value, but this
  issue is sensitive

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Reflections on Resource Allocation

• Poor areas tend to get poorer service outcomes,
  across quite diverse kinds of service
• Poverty/social deprivation makes the service
  provision task more difficult and potentially
  costly
• Poor areas get more resources of some kinds but
  less or the same of others
• They do not get enough extra resources to make a
  decisive difference to outcomes
• Therefore it may appear that there is a perverse
  negative relationship of resources with outcomes
• Local political resistance to re-allocation of
  resources likely to be formidable

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Other approaches to improving school outcomes

• Reduction in poverty thru e.g. tax/benefits,
  labour market, minimum wage, etc. (poverty the
  strongest predictor of poor outcomes)
• Reduction in concentrations of poverty, e.g.
  thru planning/regeneration including tenure
  diversification( Bramley Karley article in
  Housing Studies 2007 argues that owner occupation
  at indiv/nhood/school levels raises attainment)
• Focused use of special needs resources e.g.
  special units for disturbed pupils
• Close or amalgamate failing schools
• Earlier intervention, preschool/nursery after
  school clubs
• Changing curriculum (addressing motivation,
  engagement)

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Key analytical and policy challenges

• How far is it a zero-sum game, how far positive
  for all?
• This depends on significance of area effects,
  school effects, interaction effects, behavioural
  changes
• Do middle classes have to suffer some discomfort
  to achieve a more Rawlsian outcome for worst off?
• Non-linearities theoretically important,
  empirically elusive not necessarily convenient
• Possible to simulate both population change and
  system change (e.g. school reorganisation)

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More Reflections

• If cost of good services to poor areas is so
  high, maybe other approaches should be tried (as
  well as redistribution) prevention better than
  cure?
• Changing neighbourhoods social mix should help,
  particularly if there are additional adverse
  area concentration effects (as in the case of
  schools)
• Mechanisms include planning for affordable
  housing, mix in new build, tenure diversification
  in regeneration, use of LCHO, sales of vacant SR
  stock
• But this is only feasible in some areas in short
  term very long term policy
• Engagement, motivation, social capital also
  important