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Urban deprivation, migration and the impact of regeneration policy: a geodemographic perspective Peter Batey, Peter Brown and Simon Pemberton Department.

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Presentation on theme: "Urban deprivation, migration and the impact of regeneration policy: a geodemographic perspective Peter Batey, Peter Brown and Simon Pemberton Department."— Presentation transcript:

1 Urban deprivation, migration and the impact of regeneration policy: a geodemographic perspective Peter Batey, Peter Brown and Simon Pemberton Department of Civic Design University of Liverpool civic design 1909 2009 Celebrating 100 years of planning education and research Paper for presentation at the 47 th European Regional Science Science Congress Cergy-Pontoise, Paris 29 August – 2 September 2007

2 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?

3 Structure of the presentation 1.Introduction: purpose of the research 2.Urban deprivation, migration and regeneration policy 3.The research method 4.Application: Merseyside Objective 1 Pathways Areas 5.Conclusions

4 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.

5 Research objectives 1.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.

6 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’.

7 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.

8 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.

9 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.

10 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’.

11 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.

12 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.

13 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.

14 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?

15 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.

16 Merseyside EU Objective 1 Pathways Areas

17 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

18 Analytical method 1.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 n th 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)

19 Analytical method 4.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.

20 P 2 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.

21 Migration flows in the study area: working age population To From Less affluent areas Pathways areas Pathways- like areas More affluent areas Total Less affluent areas 70748103483148512852 Pathways areas 648159273240893728752 Pathways- like areas 36182352242941347343737 More affluent areas 16208505110433793559103 Total 12960275944206061830144444

22 Types of residential move To From Less affluent areas Pathways areas Pathways- like areas More affluent areas Less affluent areas Horizontal Upward 1 Upward 1 Upward Pathways areas Downward 4 Horizontal 5 Horizontal 5 Upward 2 Pathways- like areas Downward 4 Horizontal 5 Horizontal 5 Upward 2 More affluent areas Downward 3 Downward 3 Horizontal

23 Defining migration rates 1.Upwardly-mobile in-migration rate: 1/x 2.Upwardly-mobile out-migration rate: 2/x 3.Downwardly-mobile in-migration rate: 3/x 4.Downwardly-mobile out-migration rate: 4/x 5.Horizontally-mobile migration rate: 5/x 6.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

24 Migration rates per 10,000 population Pathways areas Pathways-like areas Upwardly-mobile in- migration rate(1) 36145 Upwardly-mobile out- migration rate(2) 394560 Upwardly-mobile net- migration rate(1 - 2) -358-415 Downwardly-mobile in- migration rate (3) 375459 Downwardly-mobile out- migration rate (4) 28150 Downwardly-mobile net- migration rate (3 – 4) 347309 Horizontally-mobile turnover rate (5) 15482117 Net-migration rate (1 - 2) + (3 - 4) -9-106 Gross turnover rate (1 + 2 + 3 + 4 + 5) 23813431

25 Less Affluent Neighbourhoods Pathways Areas More Affluent Neighbourhoods 2 1 3 4

26 Less Affluent Neighbourhoods Pathways Areas More Affluent Neighbourhoods 394 375 2836

27 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.

28 Less Affluent Neighbourhoods Pathways-like Areas More Affluent Neighbourhoods 145 560 459 150150

29 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.

30 Migration rates: commentary 3 Comparing 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).

31 To From Affluence 1 [Br 1-20] Level 2 [Br 21-30] Pathways Areas Pathways -like Areas Affluence 3 [Br 31-36] Level 4 [Br 37-40] Total 1 High 3240 (12%) 5535 (13%) 2 Medium 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%) 3 Low 405 (2%) 3078 (7%) 4 Very Low 405 (2%) 405 (1%) Total 27594 (100%) 42060 (100%) Pathways migration: highlighting the role of other neighbourhood types

32 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.

33 To From Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40] Total 1 High 2412371891 2 Medium 14496949911592771 3 Low 995451215 (8%) 1528 (10%) 3387 4 Very Low 23413071771 (11%) 6366 (40%) 9678 Total 50128333522907115927 (100%) Gross migration within Pathways Areas

34 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.

35 To From Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40] 1 High 2 Medium +132 3 Low +62+46 4 Very Low +216+148+2434 Overall Net +410+62+135-607 Net migration within Pathways Areas

36 To From Affluence Level 1 2 3 4 [Br 1-20] [Br 21-30] [Br 31-36] [Br 37-40] 1 High 2 Medium 3 Low -18 4 Very Low -108+660 Overall Net -126+678-552 Net migration within Pathways-like Areas

37 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.

38 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)

39 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.

40 Conclusions 4 Findings 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.

41 References Attwood, 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.

42 Department of Civic Design University of Liverpool civic design 1909 2009 Celebrating 100 years of planning education and research


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