Urban deprivation, migration and the impact of regeneration

policy: a geodemographic perspective

Peter Batey, Peter Brown and Simon PembertonDepartment of Civic Design

University of Liverpool

civic design

1909

2009

Celebrating 100 years of planning education and research

Paper for presentation at the 47th European Regional Science Science CongressCergy-Pontoise, Paris 29 August – 2 September 2007

The ‘moving escalator’ problem(Cole et al, 2007)

• Regenerating a neighbourhood should make the area more attractive to existing residents. Fewer residents will want to leave the area and those who do will be replaced more rapidly. Community stability and cohesion will improve.

But …

• Improving life chances, through education, health promotion, training, job mentoring, etc may help job prospects and material circumstances of local residents. More may want, and be able, to leave the area. Out-movers may be replaced by more disadvantaged households. The neighbourhood will become more deprived ...

What evidence is there for this ‘moving escalator’ problem?

Structure of the presentation

1. Introduction: purpose of the research2. Urban deprivation, migration and

regeneration policy3. The research method4. Application: Merseyside Objective 1

Pathways Areas5. Conclusions

Research aim

• To develop and apply a method for assessing the degree to which regeneration activity has affected the level and characteristics of migration to, and from, deprived urban neighbourhoods.

Research objectives1. To examine available evidence about the relationship

between urban deprivation, migration and regeneration policy.

2. To explore the potential for combining geodemographics with small area census migration data as a novel approach to evaluating the impact of urban policy.

3. To demonstrate the utility of this approach in analysing how Objective 1 funding has affected the level and patterns of migration to and from particular targeted neighbourhoods, Pathways Areas on Merseyside.

4. To assess whether this case study evidence supports the notion of a ‘moving escalator’ in neighbourhood renewal, involving the ‘export’ of affluence and the ‘import’ of poverty.

Part of a sequence of 3 papers

‘The spatial targeting of urban policy initiatives: a geodemographic assessment tool’.

‘Methods for the spatial targeting of urban policy: a comparative analysis’.

‘Urban deprivation, migration and the impact of regeneration policy: a geodemographic perspective’.

Urban deprivation• Neighbourhood is the key spatial scale

for current regeneration policy in the UK.• This is because of the persistence and

worsening of geographical concentrations of poverty and disadvantage.

• Successive governments have re-affirmed the importance of area-based policies and programmes.

Spatial targeting of regeneration policy

• In the UK context, spatial targeting goes back to the late 1960s.

• Different urban policy initiatives give varying emphasis to ‘people’ and ‘place’.

• The current 39 New Deal for Communities (NDC) programmes and the National Strategy for Neighbourhood Renewal in England focus on addressing area characteristics / individual need.

Migration• There has been a limited research focus to date

on the relationship between urban deprivation, migration and the impact of regeneration policy.

• But the relationship between regeneration policy and ‘population churn’ is crucial to migration patterns and the relative impact of interventions.

• Diverse and complex motivations lie behind decisions to move into, within or out of an area (Beatty et al, 2005).

• Personal and economic ‘triggers’, especially for ‘frequent movers’ (Richardson and Corbishley, 1999) are framed within a neighbourhood-level and wider context for change.

Characteristics of movers in deprived areas: NDC evaluation 2002-04

• Out-movers are more likely to be white, young, employed with reasonable income, educated, owner-occupiers and in good health.

• In-movers are more likely to be younger still, belong to a (Black and Minority Ethnic) BME group, and live in private rented accommodation.

• Stayers are more likely to be white, older, in poor health and have fewer qualifications.

• This has implications for the nature and effectiveness of area-based regeneration policies and the degree to which they ‘export affluence’ and ‘import poverty’.

Bailey and Livingston Study (2007)

A comprehensive study, focusing on Stability, Connection and Area Change, concluded that:

• Deprived areas do not have a general problem of instability; turnover levels are only slightly above average.

• Deprived areas are not generally disconnected from the wider housing system; an average of around 50% migrants move to/from non-deprived areas each year.

• Deprived areas do not generally see significant net out-migration of less deprived individuals; there are flows in both directions and these are nearly in balance.

Research method

• A matched comparison method in which geodemographics is used to derive a set of neighbourhoods similar to the ones being assessed but without the specified policy intervention.

• Using this method it should be possible to isolate the impact of a particular regeneration initiative on both the level and characteristics of migration to an area.

• A four-way comparison: targeted areas; clones of these areas that have not been targeted; less affluent areas; more affluent areas.

Geodemographic classification systems

• In geodemographic systems, neighbourhoods throughout the country are classified according to demographic, social and economic characteristics as measured by the census.

• Geodemographic systems are created using cluster analysis.

• The resulting clusters, or neighbourhood types can be ranked according to affluence.

• Generally based on Output Areas, the finest level of census geography.

• Such systems are widely used in the public and private sectors for spatial targeting.

Analysing migration data• 2001 Census provides small area (Output Area)

migration data capturing changes of address in the period 2000-01.

• Inter-OA flows enable the identification of the area type at both origin and destination.

• Headline analysis of migration between these four types of area: are residents in targeted areas more or less likely to move than their counterparts elsewhere?

• Detailed analysis of migration between geodemographic area types: what evidence is there that targeted areas export population to more affluent areas and import population from less affluent areas?

Application: EU Merseyside Objective 1 Pathways Areas

• Pathways Areas are deprived neighbourhoods were set up for community-based economic development purposes at the start of the first Objective 1 programme (1994-99).

• In Merseyside, 38 Pathways Areas were identified, accounting for 35% of the population.

• Strong emphasis on improving the social and economic position of individuals and the areas in which they live.

Merseyside EU Objective 1Pathways Areas

EU Objective 1 Pathways Areas: progress• A recent report (Attwood, 2006) has tried to gauge the

‘success’ of Pathways Areas as a regeneration policy aimed at tackling deprived urban neighbourhoods.

• It found that the gap between Pathways Areas and non-Pathways Areas has widened on a number of indicators.

• Critical factors identified as hampering progress include:(i) the out-migration of Pathways Areas residents to “better areas” whose circumstances had improved as a result of Pathways Areas funding; and(ii) a lack of “replacement” leading to population decline and a persistent mis-targeting of those remaining (i.e. many beneficiaries were already employed)

• The approach developed here, linking geodemographics with migration analysis, should throw more light on these issues, given the lack of detail on the impact of migration

Analytical method1. Within Merseyside, identify the Output Areas that

together make up Pathways Areas.2. Examine these Output Areas as a notional cluster

in n-dimensional space and locate a cluster centroid. Progressively eliminate outlying Output Areas to develop a tighter cluster, at each stage re-computing the cluster centroid.

3. Once a ‘final’ definition of the cluster has been obtained, establish distance from the centroid of the nth percentile Output Area. This distance will serve as the selection criterion when it comes to defining ‘clones’ of the Pathways Areas (referred to as Pathways-like Areas)

Analytical method4. Extract a sample of Output Areas that satisfy the selection

criterion but are not designated as Pathways Areas (Pathways-like Areas). This sample is to be drawn from the group of local authorities that together contribute m% of the migration to and from Merseyside.

5. Extract a second sample of Output Areas (from the same set of local authorities) that fail to satisfy the selection criterion (other areas – distinguishing between less and more affluent areas).

6. Analyse the migration flows within and between these four types of areas: Pathways Areas; Pathways-like Areas; less affluent areas; and more affluent areas.

7. Undertake headline and detailed analyses, the latter examining migration between broad geodemographic area types.

P2 People and Places geodemographic typology

• Typology is based on cluster analysis applied to 84 variables from 2001 Census.

• Available at three levels of detail: 156 Leaves, 40 Branches and 13 Trees.

• Area types are presented in an affluence ranked sequence, e.g. Branches 1-40 [most to least]

• Typology built at Output Area level.• Developed jointly by University of Liverpool and

Beacon-Dodsworth.

Migration flows in the study area: working age population

ToFrom

Less affluent areas

Pathways areas

Pathways-like areas

More affluent areas

Total

Less affluent areas

7074 810 3483 1485 12852

Pathways areas 648 15927 3240 8937 28752

Pathways-like areas 3618 2352 24294 13473 43737

More affluent areas

1620 8505 11043 37935 59103

Total 12960 27594 42060 61830 144444

Types of residential move To From

Less affluent areas

Pathways areas

Pathways-like areas

More affluent areas

Less affluent areas

HorizontalUpward

1Upward

1 Upward

Pathways areas

Downward

4Horizontal

5Horizontal

5Upward

2Pathways-like areas

Downward

4Horizontal

5Horizontal

5Upward

2More

affluent areas

DownwardDownward

3Downward

3 Horizontal

Defining migration rates1. Upwardly-mobile in-migration rate: 1/x2. Upwardly-mobile out-migration rate: 2/x3. Downwardly-mobile in-migration rate: 3/x4. Downwardly-mobile out-migration rate: 4/x5. Horizontally-mobile migration rate: 5/x6. Gross turnover rate: (1+2+3+4+5)/x

where x is the population in 2001

all rates are expressed as per 10,000 population

Migration ratesper 10,000 population

Pathways areas

Pathways-like areas

Upwardly-mobile in-migration rate(1)

36 145

Upwardly-mobile out-migration rate(2)

394 560

Upwardly-mobile net-migration rate(1 - 2)

-358 -415

Downwardly-mobile in-migration rate (3)

375 459

Downwardly-mobile out-migration rate (4)

28 150

Downwardly-mobile net-migration rate (3 – 4)

347 309

Horizontally-mobileturnover rate (5)

1548 2117

Net-migration rate (1 - 2) + (3 - 4)

-9 -106

Gross turnover rate (1 + 2 + 3 + 4 + 5)

2381 3431

Less Affluent Neighbourhoods

Pathways Areas

More Affluent Neighbourhoods

2

1

3

4

Less Affluent Neighbourhoods

Pathways Areas

More Affluent Neighbourhoods

394 375

2836

Migration rates: commentary 1

For Pathways Areas• Overall, out-migration is almost exactly the

same as in-migration.• Those moving out are much more likely to

move to more affluent neighbourhoods than less affluent ones.

• Those moving into Pathways Areas are more likely to come from more affluent neighbourhoods than less affluent ones.

Less Affluent Neighbourhoods

Pathways-like Areas

More Affluent Neighbourhoods

145

560 459

150

Migration rates: commentary 2

For Pathways-like Areas• There is a greater propensity to move out

than in.• Those moving in are much more likely to

be from more affluent neighbourhoods than less affluent ones.

Migration rates: commentary 3Comparing Pathways & Pathways-like Areas• Population turnover is much lower in Pathways Areas,

suggesting that targeted Objective 1 resources are creating greater community stability and cohesion.

• Lower turnover is largely a function of less movement between Pathways Areas and more affluent Neighbourhoods.

• Gross turnover in the study area as a whole is 4039/10000• This is substantially more than for Pathways Areas (2381)

and Pathways-like Areas (3431).

ToFrom

Affluence1

[Br 1-20]

Level2

[Br 21-30]

Pathways Areas

Pathways-like

Areas

Affluence3

[Br 31-36]

Level4

[Br 37-40]

Total

1High

3240(12%)

5535(13%)

2Medium

5265(19%)

5508(13%)

Pathways Areas

4482(16%)

4455(15%)

15927(55/58%)

3240(11/8%)

648(2%)

0(0%)

28752(100%)

Pathways-like Areas

6669(15%)

6804(16%)

2352(5/9%)

24294(55/58%)

3537(8%)

81(0%)

43737(100%)

3Low

405(2%)

3078(7%)

4Very Low

405(2%)

405(1%)

Total 27594(100%)

42060(100%)

Pathways migration: highlighting the role of other neighbourhood types

Pathways migration: highlighting the role of other neighbourhood types

Commentary on table• The table shows migration flows to and from Pathways and

Pathways-like Areas using four neighbourhood types differentiated according to affluence level. These four types are based on aggregated blocks of affluence-ranked People and Places Branches (1-20, 21-30, 31-36, 37-40).

• Two thirds of migration takes place within Pathways Areas and Pathways-like Areas.

• The profile of neighbourhoods contributing migrants to Pathways and Pathways-like Areas is very similar.

• People migrating from Pathways Areas are more likely to move to neighbourhoods that are slightly more affluent than Pathways Areas. Those migrating from Pathways-like Areas move to a more diverse range of Neighbourhoods.

ToFrom

Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40]

Total

1High

24 12 37 18 91

2Medium

144 969 499 1159 2771

3Low

99 545 1215(8%)

1528(10%)

3387

4Very Low

234 1307 1771(11%)

6366(40%)

9678

Total 501 2833 3522 9071 15927(100%)

Gross migration within Pathways Areas

Migration within Pathways Areas: Commentary

• In Pathways Areas, the majority of migration (69%) occurs within and between the two least affluent groupings of neighbourhood types.

• Almost half of migrants (48%) in Pathways Areas remain within the same neighbourhood affluence category when they move.

• For those who do shift affluence category, there is a clear pattern of upward movement, from the less affluent Pathways neighbourhoods to Pathways Areas that are more affluent.

• A much less pronounced pattern is found in Pathways-like Areas.

ToFrom

Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40]

1High

2Medium

+132

3Low

+62 +46

4Very Low

+216 +148 +2434

Overall Net

+410 +62 +135 -607

Net migration within Pathways Areas

ToFrom

Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40]

1High

2Medium

3Low

-18

4Very Low

-108 +660

Overall Net

-126 +678 -552

Net migration within Pathways-like Areas

Conclusions 1

• The analysis of migration patterns is a crucial step in evaluating the effectiveness of any area-based regeneration policy.

• A geodemographic perspective helps to elucidate the ‘moving escalator’ problem.

• Evidence from the Pathways Areas study suggests that those moving out have ‘traded up’ and those moving in tend to be ‘trading down’.

• Population turnover is lower in Pathways Areas than in Pathways-like Areas suggesting that Objective 1 funding is contributing to greater community stability.

Conclusions 2• This implies that future targeting of

regeneration policy should emphasize both:(i) internal strategies focused on physical improvements to encourage individuals to stay in the area (for example, diversifying housing and employment opportunities); and(ii) internal strategies that are ‘people-based’, given the propensity for individuals to remain in situ, leading to lower levels of ‘drop out’ (from activities focused on up-skilling and improving employability)

Conclusions 3

• This is in line with the Regeneris (2003) mid-term evaluation of the Pathways programme which suggested that more emphasis needs to be placed on new ideas for physical improvements in Pathways Areas, along with a greater focus on improving entrepreneurship rates of local Pathways residents.

Conclusions 4Findings compared with those of Bailey and Livingston: B&L Study: Deprived areas do not have a general problem of instability;

turnover levels are only slightly above average. This study: Based on working age population, turnover rates appear to

be considerably lower in deprived areas, notably in Objective 1 Pathways areas.

B&L Study: Deprived areas are not generally disconnected from the wider housing system; an average of around 50% migrants move to/from non-deprived areas each year.

This study: In Pathways Areas and Pathways-like Areas migration is more self-contained than in the B&L Study (c. 66% compared with 50%).

B&L Study: Deprived areas do not generally see significant net out-migration of less deprived individuals; there are flows in both directions and these are nearly in balance.

This study: The evidence here confirms this finding for Pathways Areas and, to a lesser extent, for Pathways-like Areas.

ReferencesAttwood, R. (2006) Analysis of Change Over Time in Merseyside's Pathways

Areas, Powerpoint Presentation to EU Merseyside Objective 1 Strategy and Performance Sub-Committee, 13 September 2006.

Bailey, N. and Livingston, M. (2007) Population Turnover and Area Deprivation. Joseph Rowntree Foundation and Bristol: Policy Press.

Batey, P.W.J., Brown, P.J.B. and Pemberton, S. (in press) ‘The spatial targeting of urban policy initiatives: a geodemographic assessment tool’, Environment and Planning A, 38,

Batey, P.W.J., Brown, P.J.B. and Pemberton, S. (submitted) ‘Methods for the spatial targeting of urban policy: a comparative analysis’, Urban Geography,

Beatty, C., Cole, I., Grimsley, M., Hickman, P. and Wilson, I. (2005) New Deal for Communities (NDC) National Evaluation: Housing and the Physical Environment: Will residents stay and reap the benefits? Sheffield Hallam University: Centre for Regional Economic and Social Research.

Cole, I., Lawless, P., Manning, J. and Wilson, I. (2007) The Moving Escalator? Patterns of Residential Mobility in New Deal for Communities areas: Research Report 32. London: Department for Communities and Local Government.

Regeneris (2003) Mid Term Evaluation of the Objective 1 Programme for Merseyside 2000-2006. Altrincham: Regeneris Consulting Ltd.

Richardson, K. and Corbishley, P. (1999) The characteristics of frequent movers, Joseph Rowntree Foundation (JRF) Findings, No. 439, April 1999. York: JRF.

Department of Civic DesignUniversity of Liverpool

civic design

1909

2009

Celebrating 100 years of planning education and research