Neighbourhood Effects and the Welfare State. Towards a European research agenda

Neighbourhood Effects and the Welfare State Towards a European research agenda? Roger Andersson Professor of Social & Economic Geography Institute for Housing & Urban Research Uppsala university, Sweden Contact: Roger.Andersson@ibf.uu.se Homepage: http://www.ibf.uu.se/PERSON/roger/roger.html Paper for the conference“Neighbourhood Effects Studies on the Basis of European Micro-data” at Humboldt University of Berlin on March 29 and 30, 2007 Draft version, please not quote Introduction Over the past couple of decades, studies on the impact of neighbourhood compositions on the life chances of individuals are slowly gaining interest and also slowly providing new insights (for some overviews see: Jencks & Mayer 1990, Briggs 1997, Ellen & Turner 1997, Leventhal & Brooks-Gunn 2000, Sampson et al 2002, Galster 2002, Friedrichs et al 2003) On both sides of the Atlantic, the interest is driven by academic and political debates about segregation, integration and social mix (see for example Friedrichs 1998, Atkinson & Kintrea 2001, Buck 2001, Andersson 2001, Ostendorf et al 2001, Farwick et al 2002, Kearns & Parkes 2003, Galster 2007, Musterd et al 2003, Brännström 2006, and Musterd & Andersson 2005, 2006) This paper takes its point of departure in one particular country, Sweden, a country that has pursued a social mix policy since the mid 1970s as an instrument to avoid further segregation One may doubt the efficiency and criticise the lack of strong commitment by planners and local politicians in relation to this general aim but the country is an interesting case for researching some of the underlying assumptions about neighbourhood compositions and social outcomes It is interesting from a policy perspective but also due to the existence of internationally unique types of data, which enable researchers to conduct large scale longitudinal studies on individuals (in fact the entire population) Empirically, this paper will make use of results from a series of published and yet unpublished papers using the Swedish data resources.1 The paper will address four broad questions indicated in figure 1 Is there really a strong relation between housing mix and social mix? This is a fundamental issue since planning for social mix is based on the assumption that the micro structures of the housing stock in terms of tenure, housing types, size and cost of dwellings etc are thought to strongly influence the population composition of neighbourhoods How does population composition of neighbourhoods affect residents’ social interaction and behaviour? Are social opportunities of individual residents related to their neighbourhood context? If there is such a relation, to what extent is this produced through local social interaction? The idea is that social opportunities might be directly or indirectly affected by residency Three equally important questions arise if one wants to study these relations: What population mix matters? What scale matters? What time matters? I will deal with these latter questions after having discussed figure more in detail Some readers might appreciate some contextual information on segregation patterns and processes in Sweden I have included an appendix that besides providing some relevant data also describes how these data are generated and can be used Andersson, R (2001), Andersson, R & Bråmå, Å (2004), Andersson, R & Musterd, S (2005, 2006), Musterd & Andersson (2005,2006, Andersson, R., Musterd, S., Galster, G & Kauppinen, T (2005), Musterd, S., Andersson, R., Galster, G & Kauppinen, T (2007), Galster, Kauppinen, Musterd & Andersson (fc) Figure A research programme on neighbourhood mix and neighbourhood effects up, but discussing innovative ways of research (What you’ll really then, is another Global, National and Urban Contexts question) The Micro Structure of the Housing Stock (neighbourhoods’ composition in terms of tenure and housing types) (1) Social and Ethnic composition of neighbourhoods (2) Social interaction Effects on attitudes and behaviour (3) Social opportunities (4) Housing mix and social mix Usually few legal opportunities exist that allow politicians to create social mixes directly – this would require almost totalitarian regimes that are able to intervene in individual choices with quite some rigor (Borevi 2002, chapter 6, who analyses Swedish housing mix policies since 1975) Therefore, politicians tend to use housing and planning policy tools instead to reach their goals In short, the idea is that housing mix (a mix of housing types and tenure types) will create social mix (a mix of households according to their socio-economic position) and that this will create better social opportunities for individuals In fact, these debates are based on two crucial assumptions The first is that social mix really enhances the individual opportunities (i.e relations and/or in figure are true) The second is that there is a strong relation between social mix and housing mix (relation is true) These issues are obviously firmly related to the actual plans and activities around the restructuring of certain areas in cities Today, at least in many European cities, a large share of urban restructuring plans is aimed at transforming large-scale post-war housing estates The areas in which these estates can be found tend to be rather homogeneous in terms of the type and tenure of the dwellings They are also often attracting households with a rather weak social position and many immigrants The dominant idea is that there is housing (type and tenure) homogeneity that creates social homogeneity (concentration of poor people) that reduces social opportunities for those who are living there So, the same set of assumptions applies for these estates and the people living in them It is worth noting that homogenous high-income areas are never considered to constitute problems for individuals or policy makers As Andersson (2000) shows in a countrywide analysis on housing segregation in Sweden, the geographical concentration of the rich is much stronger than that of the poor And in Sweden, as probably elsewhere, the majority of all homogenous areas are dominated by home ownership In the Stockholm region 288,000 people live in neighbourhoods having more than 90% of the population in home ownership As a contrast, only 52,000 live in neighbourhoods having a similarly strong dominance of rental dwellings If more mix as such is wanted, mixing the former seems to be an appropriate recommendation From the literature we know that assumptions regarding the relation between housing mix, social mix and social opportunities are insufficiently tested There will be post-war estates with a homogeneous population where individuals appear to be socially blocked; where social problems and sometimes criminality characterize the daily lives of their inhabitants and where, from time-to-time social tensions get too high, occasionally even resulting in urban riots These estates are well known locally and often also highly stigmatized Yet, this does not automatically imply that all post-war housing estates are associated with these problems; neither does it mean that all socially homogeneous (and poor) estates or areas are associated with problems (Musterd & Andersson 2005) In a paper on mixed housing policy, Musterd (2002, 140) argued that “…while social processes may become manifest in a certain residential stock in a neighborhood, as rising levels of social segregation or as local spatial concentrations of poverty, that does not necessarily imply that they are also caused by or being problems of the housing stock or of the neighborhood composition.” Musterd & Andersson (2005) find that relation (1) (see figure 1) is rather weak in Sweden as a whole Further study is needed, not least studies that analyse the relation more in detail for cities of different size One may hypothesize that although the relation is quite weak at the national level it might very well be much stronger in the larger cities (as indicated by the Stockholm example above) Social and ethnic mix and neighbourhood effects Many researchers make use of Charles Manski´s (2000) distinction between three types of neighbourhood effects: endogenous, contextual (exogenous) and correlated (See Galster, 2006) If we face endogenous interactions, the propensity of an agent to behave in some way varies with the behaviour of the group In contextual interactions, the propensity of an agent to behave in some way varies with exogenous characteristics of the group members Correlated effects concern situations when agents in the same group tend to behave similarly because they have similar individual characteristics or face similar institutional environments As concluded by Manski: “Endogenous and contextual interactions express distinct ways that agents might be influenced by their social environments, while correlated effects express a non-social phenomenon.” (Manski 2000, p 127) Numerous versions of endogenous effects have been forwarded, including effects related to socialization, social networks, local competition over finite resources, and relative deprivation Exogenous neighbourhood effects occur if the behaviours or attitudes of one neighbour depend on the exogenous (or predetermined, fixed) characteristics of the individual’s neighbours, such as ethnicity, religion, or race For my purpose the distinction between endogenous and exogenous effects are not of immediate importance Both sets of effects relate to the population composition of a neighbourhood and both relate to the fact that people interact locally and potentially have influence on each other (relation and in figure 1) Manski’s third type of possible effects, the correlated neighbourhood effect, is however interesting as it does not presuppose ideas about “contagion effects” or mechanisms related directly to the composition of households Correlated neighbourhood effects not vary by alterations in neighbourhood household composition, but rather are determined by larger structural forces in the metropolitan area, like locations of jobs and geographic dis-amenities and the structures of local government These external forces may impinge differentially on different neighbourhoods, but within any given neighbourhood they affect all residents roughly equally, producing thereby correlations in neighbours’ outcomes (Galster 2006, Andersson, et al 2005) Such aspects of peoples’ environment are not ‘non-social’ –and certainly not non-political– but they not stem from local human to human interaction Of course, the real effect of the external forces on individuals is depending on individual resources and dispositions What mix matters? In a Swedish-Dutch collaboration, Roger Andersson and Sako Musterd have produced a series of papers using the statistical database GeoSweden as the empirical foundation GeoSweden contains yearly demographic, socioeconomic, educational and geographical information on all people residing in Sweden 1990-2004 (later to be updated with information for 2005 and 2006) The first two papers (Musterd & Andersson 2005 and 2006 respectively) are based on the 1991 to 1999 period, and both attempts to analyse the existence and magnitude of neighbourhood effects on (un)employment careers Both these papers confirm the existence of such effects Figure gives an overview of the relation between the percentage of unemployed in the 500m by 500m neighbourhoods (entire country) and the percentage of all unemployed in 1991 who remain unemployed also in 1995 and 1999 The levels are different according to national origin but all categories experience a clear impact of the residential context (horizontal axis) The effects seem to be rather linear as unemployment increases from to about 15 percent In an enlarged collaboration, including also George Galster and Timo Kauppinen, Swedish data are used for examining several important issues in the neighbourhood effects discourse In Andersson, Musterd, Galster and Kauppinen (2005) the authors address the crucial question “What mix matters”? This paper explores the degree to which a wide variety of 1995 neighbourhood conditions in Sweden are statistically related to earnings for all adult metropolitan and non-metropolitan men and women during the 1996-1999 period, controlling for a wide variety of personal characteristics They find that the extremes of the neighbourhood income distribution, operationalised by the percentages of adult males with earnings in the lowest 30th and the highest 30th percentiles, hold greater explanatory power than domains of household mix related to education, ethnicity, or housing tenure Separating the effects of having substantial shares of low and high income neighbours, they find that it is the presence of the former that means most for metropolitan and non-metropolitan men and women, with the largest effects for metropolitan men According to research findings in a recently finished EU-funded project, Urban Governance, Inclusion and Sustainability (UGIS), both area-based policies and most mix policies are now partly driven by the fear of ethnic clustering (Andersson 2003, Beaumont et al 2003) Our findings not support the hypothesis that the ethnic dimension is the most crucial one in relation to employment and income prospects On the contrary, we find that the socioeconomic composition of neighbourhoods is the most important dimension, at least in terms of individuals’ incomes It is however important to note that although these results clearly point at the conclusion that mix of income groups is the most important aspect, this is not necessarily true for other types of social outcomes (educational achievements, crime, social cohesion etc.) percentag e remaining unemployed Figure Percentage unemployed staying unemployed in 1995 and 1999, per environment type, per country of birth Sweden Western Non-Western Total Eastern Europe 45 40 35 30 25 20 15 10 0 -5 40 -4 30 -3 20 -2 16 -1 14 -1 12 12 10 10 8- 6- 4- 2- 0- perc unemployed in the environment 1991 Source: Musterd, S & Andersson, R., 2006 A special aspect of the what mix matters issue relates to local concentration of immigrants A Musterd, Andersson, Galster and Kauppinen (fc) paper addresses the role of ethnic clusters in relation to immigrants’ income development Differences in immigrant economic trajectories have been attributed to a wide variety of factors One of these is the local spatial context where immigrants reside This spatial context assumes special salience in light of expanding public exposure to and scholarly interest in “ethnic enclaves” Does concentrating immigrants aid or retard their chances for improving their economic standing? In this paper the authors contribute clear statistical evidence relevant to answering this vital question They develop multiple measures of the spatial context in which immigrants reside and assess their contribution to average earnings of immigrant individuals in the three large Swedish metropolitan areas, controlling for individual and regional labour market characteristics They use unusually rich longitudinal information about Swedish immigrants during the 1995-2002 period They find no evidence (with one exception) that own-group ethnic enclaves in Sweden typically enhance the income prospects of its resident immigrants, unless individuals use the enclave for a short-term place from which to launch themselves quickly into different milieus What scale matters? In the wider literature on the relationship between man and environment some argue that the direct neighbourhood of individuals has lost significance, especially for life chances and social opportunities of the adult population Fischer (1982), for example, stated that people tend to become socially integrated through differentiated, looser networks at different scales Increased affluence, but also wider access to the rest of society or even the world, through higher levels of individual mobility and through the explosion of telecommunications and internet connections in particular, would have resulted in a diminishing role of the local environment in the daily lives of most people (Castells 1989) Blokland (2003), who applied in-depth interviews, found that the local environment had only minor impact on significant social interaction between different population categories However, others state that the local environment still plays a significant role Neighbourhoods tie people both socially and spatially, if only on functional grounds Janowitz (1974) and Suttles’ (1973) ‘community of limited liability’ clearly fits these ideas about the role of the local neighbourhood They state that (middle-class) neighbours come together, work together and become active and influence each other when they regard that as necessary; if not, they live a preferably silent and peaceful local life Bridge, Forrest and Holland (2004), who summarised the research evidences on neighbouring, state that “The evidence for the widely held perception that neighbourliness is declining is in fact mixed.” (p 39) Dietz (2002) observes that “neighbourhood definitions have typically not been formed by thoughtful theoretical considerations Rather neighbourhood delineation has been defined by the limitations of an available data set” (p541; see also Burgess et al 2001) The ‘what scale matters’ question is highly relevant to the more general ‘does neighbourhood matter’ question That is, if the ‘wrong scale’ is used in neighbourhood effect studies, we easily may arrive at wrong conclusions about neighbourhood effects; we may over- or underestimate them Then the question should be asked whether that conclusion holds when other scales are applied This ‘wrong scale’ argument may be applicable to a detailed Swedish neighbourhood effect study by Brännström (2006) He analysed neighbourhood effects on income and receipt of social assistance The empirical material (register data derived from the Stockholm Birth Cohort Study) provided a unique opportunity to analyse repeated information on both outcomes and place of residence for the cohort of Stockholmers born in 1953 during a 50-year period With the use of longitudinal multilevel modelling, this study explored the inter-dependence of the observations by partitioning the total variance into different components of variation due to various hierarchical levels in the data In the extensive longitudinal multilevel analyses the author worked simultaneously with two spatial levels (i.e census areas and parishes) These areas have different territorial scopes He concluded “the major message of this study is that it is people and time point of measurement, rather than place of residence, that matter Put simply, it matters more who you are than where you are At least where the outcomes addressed in this study are concerned, this may indicate that it is primarily people and their households that should be the focus of policy efforts to alleviate disproportions in social and economic opportunities.” (Brännström 2006, Introduction) However, both the census tracts and the parishes are socially very heterogeneous and also large-scale areas Social processes and relevant interactions between people may not occur at these levels, but at much smaller levels instead Ruth Lupton (2003) has reviewed part of the British and American studies on neighbourhood effects and discusses scale issues and the possibility of bringing qualitative and quantitative neighbourhood research closer together Concerning the quantitative studies, she states that “The geographical units of analysis used are often acknowledged to be too large to have any explanatory power.” (Lupton 2003, p 9) A study carried out by Johnston et al (2004) is very interesting from this perspective They focused on scale and neighbourhood effects on voting behaviour and applied the British Household Panel Study They created ‘bespoke’ neighbourhoods, local areas defined for each individual separately; these environments were built up with enumeration district data Two different types of bespoke neighbourhoods were created: by different numbers of nearest population around the respondent’s home (neighbourhoods with nearest 500 around the individual; neighbourhoods with nearest 1000 around the individual, etc); and by different distances from the respondent’s home (population within 250 m, population within 500m, etc.; see also Musterd, Ostendorf & De Vos 2003 and Musterd & Andersson 2006 in which similar types of bespoke neighbourhoods are used) Their arguments to so were based on the idea that separate mechanisms and processes may operate at different scales Among other things they found that there were simultaneous wide-area and highly local neighbourhood effects; labour voting was greater in more deprived areas, but especially so in pockets of extreme deprivation The authors conclude that: “there are many hypotheses regarding neighbourhood effects in geographical and related literatures, but their successful testing has been hampered by the absence of relevant data In particular, analysts have lacked data on both individuals and their neighbourhood milieus, which allow the interactions of different types of people in different kinds of local context to be explored Furthermore, most analyses of neighbourhood effects have been significantly constrained by the nature of the areas for which data are available In many cases these are relatively large and in almost all cases no data are available to explore variations in the nature and strength of the sought-for effects at different scales” (Johnston et al 2004, p 367) These statements were the drivers behind a recent Andersson & Musterd (2006) paper in which the question is raised: “to what extent individual social mobility of adults is influenced by individual and neighbourhood characteristics, with a special focus on various levels of scale and various definitions of area compositions.” It is reasonable to assume that if endogenous neighbourhood effects are in operation, such effects would be greater in the immediate surrounding of an individual and they would decrease as the size of the unit increases However, for correlated effects it is more difficult to hypothesize which level would be the most important and the spatiality can also be expected to vary according to which outcome we decide to study In our case, focusing on labour market-related outcomes, both the existence of spatial mismatch (no jobs available nearby, uneven public transportation services etc) and uneven support provided to people who are unemployed or in need of job information services can be expected to be more influential at the municipal and urban district levels than at the level of the immediate surrounding of individuals Or put the other way around: at higher levels of geographical scale we expect endogenous effects to be less strong than they are at the scale of peoples’ closest environment If correlated effects exist at higher levels (municipality, urban district) they would exist also at lower levels, adding up to more strong neighbourhood effects at the lowest geographical scale There is, however, one particular aspect of correlated effects that might operate primarily at lower geographical scales, namely spatial stigmatization Galster (2006) identifies stigmatization both as a type of endogenous effect and as a correlated effect: “Endogenous stigmatization of a place transpires when important institutional, governmental or market actors negatively stereotype all residents of a place and/or reduce the flows of resources flowing into the place because of its household composition This might occur as the percentage of households in some disadvantaged ethnic group in the neighbourhood exceeds the threshold of where they are perceived by these external actors as “dominant.” (… ) “External stigma: certain neighbourhoods may be stigmatized regardless of their current population because of their history, environmental or topographical dis-amenities, style, scale and type of dwellings, or condition of their commercial districts and public spaces.” (Galster 2006, p 8) It is highly plausible that both types of stigmatization occur at a relatively low geographical scale, such as neighbourhoods and maybe urban districts In this study we operationalized ‘neighbourhood’ at four spatial scales, running from the municipality, over an officially existing neighbourhood definition (SAMS) to coordinatebased bespoke neighbourhoods (environments constructed individual by individual on the basis of coordinate information; 500 meter and 100 meter around each individual, respectively) Using multivariate statistical techniques on employment and income development 1995-2002 for all inhabitants residing in Sweden’s three largest urban regions, controlling for a wide variety of personal and household characteristics, we were able to confirm our basic hypothesis that contextual effects on labour market performance are strongest at the very local level and non-existent or weak at the municipal level We were also able to show –indirectly– that stigmatization probably plays a significant role By analysing a subset of politically targeted poor neighbourhoods we found neighbourhood effects to be much stronger there compared to what we found for non-targeted (presumably much less stigmatized) neighbourhoods From a policy point of view this result indicates that mixing policies should aim at the micro neighbourhood level What time matters? There are several types of time issues that so far have not been subject to systematically designed empirical analyses First of all, some of the theories concerning neighbourhood effects suggest that we should expect instant effects for people residing in particular contexts Most of the correlated effects (spatial mis-match, external stigmatization etc) would have more or less instant impact on for example labour market performance The same apply for some of the endogenous effects (social networks, local competition over finite resources, and maybe also relative deprivation) Other effects would probably appear as a result of a longer period of exposure to certain environments (socialisation and other processes affecting behaviour and related to local social interaction) Secondly, effects might also last for shorter or longer periods, so that some would disappear if a person moves out of the specific context while other could last for years and maybe even decades regardless of later trajectories (certainly correlated effects on health due to bad environmental conditions, such as air pollution, water quality or nuclear-related radiation, but maybe also labour market careers as related to educational achievements in younger ages) Sweden is a welfare state with high ambitions to allocate resources according to needs I have hypothesized that neighbourhood effects in countries like Sweden are probably less pronounced compared to countries having less high ambitions in this regard (Andersson 2001) But there is also another aspect of urban Sweden that speaks in favour of this hypothesis In some countries, I get the impression that moving out of poor neighbourhoods is a difficult thing and that many are stuck in less resourceful environments for longer periods, maybe even for life and across generations This is certainly not the case in Sweden and I will end this paper by proving further evidence on the dynamic nature of Swedish neighbourhoods (see also Andersson & Bråmå 2004) I have chosen two adjacent neighbourhoods in the Stockholm region, located in the north-western part of the capital city (see appendix for a map of the area) One of these neighbourhoods is a quite typical middle-class area, comprising predominantly home owners in single housing having a medium to high level of income Consequently, few are unemployed This area, Spånga, has about 6,600 residents The adjacent area, Tensta, is one of Sweden´s most immigrant-dense housing estates, home for about 17,000 people Many are unemployed and rely on social allowances The average level of income is very low Tensta has been targeted by both state-funded and municipalityfunded restructuring programmes since many years In figure 2-4 I display results of a longitudinal study 1990-2004 of the 1990 cohort for respective area The figures show year by year and per age group who may remain in the area The very high mobility among younger people is a very distinct feature; half of the 20-29 years old have left after only about three years After 14 years, less than two out of ten remain Besides the 20-29 year old, out migration is at a higher level in the poor housing estate compared to the middle-class area While of 50 percent of the original cohort had left Spånga by the year 2000, 50 percent of the 1990 Tensta residents had left already in 1996 By the end of the period, 27 percent still live in Tensta, while 38 percent remain in Spånga Figure shows similar data for a number of specific one year age groups (age 5, 15, 25, 35, 45 and 55 in 1990) Figure Neighbourhood staying frequencies 1990-2004 for the 1990 population of Spånga in Stockholm city (area code 1800149; cohort size: N=6617 in 1990; 2537 in 2004) Source: GeoSweden 2004, Institute for Housing & Urban Research, Uppsala university 10 Appendix A Some basic features of Swedish residential segregation2 Data sources Without doubt, Swedish social scientists in general and segregation researchers in particular have access to internationally unique types of data I will briefly describe the basic features of these data Four characteristics are of key importance a) The general and frequent use of a personal ID code (personnummer), used in all official registers A similar code is used for firms b) Constantly updated addresses register (Register över totalbefolkningen, RTB); link to the ID code mentioned in (a) c) A geo-coded real estate and property register, linked to the address register (fastighetsregistren) d) Accessibility legislation By merging (1), (2), and (3) all residents in Sweden can be localised both in terms of housing and work places This allows for studying not only static distributions at any point in time but also events An individuals’ housing and working career can thus be studied both socially and geographically Obviously, both migration and commuting can be studied using complete populations If a person moves it will show up in the address register and due to the fact that all addresses refer to specific and geocoded buildings, the exact location will be known The individual-specific ID code comprises 10 digits and is given to everyone upon birth or immigration (permanent residents) This code is used by Statistics Sweden in all individual registers, such as the employment, income, population, education, and the event registers (birth, death, immigration, emigration), which makes it possible to (1) merge information from different sources, and (2) carry out longitudinal analyses based on the entire population The geocoding of all real estates took several decades to finish and this crucial part of the registers was not completed until about 1990 A final word on data accessibility: It is not difficult to realise that these data are “sensitive” and the use is of course restricted in several ways However, there is an important paragraph in the Swedish data security legislation saying that access to the registers should be generously provided to researchers Applications from researchers are scrutinised by a special committee at Statistics Sweden, and also by regional research ethics committees, who decides if permission could be given and if certain restrictions should apply Some restrictions are of a more general character, for instance that data on individuals or firms provided to researchers never contain the explicit ID code and that specific individuals should not be identifiable in publications Furthermore, the most detailed geocodes (coordinates) are seldom provided, and researchers normally have to settle with 100m by 100m coordinates (which of course still is a very detailed level) There are often also restrictions on handing out specific codes for the country of birth information, and researchers may have to settle with aggregates (world This appendix makes extensive use of a paper presented at the workshop “Ethnic Segregation in Germany and Europe: What we know about its extent and about links between residential segregation and integration?” Friday, 31 March 2006, Programme on Intercultural Conflicts and Societal Integration (AKI), Wissenschaftszentrum Berlin für Sozialforschung WZB will publish the paper in a reduced form 13 regions) However, I have myself been allowed to access specific country codes for all nationalities having more than 1000 persons in the country (about 70 specific codes) Neighbourhood division The country is divided into 21 counties, 289 municipalities, about 2,500 parishes and 9200 Sams units (Small Area Market Statistics) The Sams division was constructed in 1993 but older information can be located to the existing division by use of the more precise coordinates that all real estate property have in Sweden Local authorities in cooperation with Statistics Sweden delimit the Sams units The delimitation praxis is to construct fairly homogenous neighbourhoods in terms of housing types, date of construction, and tenure form However, praxis varies somewhat between municipalities (for example somewhat smaller areas exist in for instance Göteborg and Malmö compared to Stockholm) and it does not mean that areas comprising more than one tenure form by necessity is divided into two or several units The average population size of a Sams unit is about 1000 The Sams units have been used frequently in recent Swedish residential segregation studies (Andersson 2000, Andersson and Bråmå 2004, Bråmå 2006) with the argument that they constitute the most relevant formal division available The geocodes described above of course allow for researcher-specific divisions of urban space It is for instance possible, by using GIS or other techniques, to construct individualspecific environments (say contexts comprising everybody living within 200m or 500m from an individual) I will return to this later as some analyses of this kind have been carried out in the framework of the neighbourhood effects discourse Patterns of social class segregation There are many possible ways of describing residential segregation by class Obviously, urban housing markets are segmented over tenure forms where we find more well-off people in home ownership and less well-off residents in the rental segments If tenure forms were to be equally mixed across urban neighbourhoods this segmentation would not translate into residential segregation by income Although Swedish neighbourhoods are fairly well mixed (Musterd & Andersson 2005), this is not the case In much of the following I will use example from the Stockholm region Most of the basic featured described and analysed for Stockholm will be fairly representative for urban Sweden but one should of course not forget that scale matters, and that social distributions and the relative presence of foreign-born can be different in other cities (the share of foreign-born is about the same in Göteborg and somewhat higher in Malmö) Table shows the current segmentation over tenure forms in the Stockholm region with some key socioeconomic information The columns represent different degrees of tenure dominance (from almost complete dominance in the 1st column to complete absence of a particular tenure in the 7th column) for each one of four tenure forms: private rental, public rental, cooperative, home ownership Besides information concerning number of Sams areas and residents, and percentage for each neighbourhood type, the table also provides information regarding median gross income and employment rates It is clear that most mono-tenure neighbourhoods are of the home-ownership type Close to 300 out of 847 neighbourhoods are heavily dominated by this particular form and half of all neighbourhoods comprise more than 70 percent home ownership The three other tenure forms tend not to be very concentrated in space (except that they are not found in areas 14 dominated by home ownership) Furthermore, as expected, median income levels are higher in neighbourhoods dominated by home ownership, while rental-dominated neighbourhoods of both the private and public type are clearly below the median income in the region (204,000 SEK) Cooperative housing has a clear intermediate position Table Housing segmentation over tenure forms in Stockholm county, 2002.* Tenure form No of neighbourhoods in Stockholm with varying degree of dominance (no of neighbourhoods/perc of population) of four different tenure forms (median income/employment) Column Column Column Column Column Column Column Column > 90% 70-90% 50-70% 30-50% 10-30% LT 10% 0% Total Private rental (PrivR) 17 36 111 401 264 847 No of people residing in PrivR (1000s) 31 17 34 82 23 190 % of PrivR population 1,1 16,4 9,0 18,3 43,0 12,4 0,0 100,0 Median gross income (1000 SEK) 169 150 148 161 201 218 197 204 % employed 20-64 years 71,0 69,2 68,4 69,6 75,3 80,4 77,4 77,3 Public rental (PubR) No of people residing in PubR (1000s) % of PubR population Median gross income (1000 SEK) % employed 20-64 years 23 54 15,5 152 69,4 18 51 14,5 140 66,7 34 92 26,2 135 65,6 60 81 23,2 186 74,2 96 57 16,3 212 79,0 81 14 4,3 227 79,2 535 0,0 218 81,1 847 351 100,0 204 77,3 Cooperative (Coop) No of people residing in Coop (1000s) % of coop population Median gross income (1000 SEK) % employed 20-64 years 36 42 9,8 202 77,9 22 25 5,7 204 79,2 58 137 31,3 221 77,8 89 119 27,2 206 77,7 180 95 21,8 196 76,1 140 17 4,1 206 77,8 322 0,0 198 77,9 847 437 100,0 204 77,3 Home ownership (HO) No of people residing in HO (1000s) % of HO population Median gross income (1000 SEK) % employed 20-64 years 299 288 41,0 231 83,8 131 198 28,1 238 84,0 71 80 11,4 220 82,1 46 38 5,4 207 79,0 119 86 12,3 201 76,0 82 12 1,7 170 70,5 99 0,0 160 70,1 847 704 100,0 204 77,3 *Neighbourhoods according to the Sams division Source: GeoSweden 2002 Institute for Housing and Urban Research, Uppsala university The existence of many mono-tenure housing areas is part of the explanation of residential segregation by income and social class Figure shows tenure form by income deciles distribution in the Stockholm region Data refer to 1990 but this pattern is fairly stable over time Segregation and segmentation relate to each other in the sense that people having high incomes are predominantly found in home ownership while people with lower incomes are found in the rental segments Figure shows the mean income gradient over neighbourhoods in the city of Stockholm As indicated by the statistical trend line, the average income in rich neighbourhoods (excluding 3-4 out-layers) is about four times the average income in the poorest neighbourhoods This is, by international comparison, probably a quite compressed distribution but it is nevertheless enough powerful to produce rather distinct patterns of class segregation 15 Figure Forms of tenure and disposable income deciles 1990 in the Stockholm Labour market region Source: Database Geometro Institute for Housing and Urban Research, Uppsala University Figure Mean income in 1000 SEK per neighbourhood in Stockholm city in 2002 1000 900 800 700 600 500 400 300 200 100 Rich neighbourhoods Poor neighbourhoods Source: GeoSweden 2002 Institute for Housing and Urban Research, Uppsala University If we calculate an index of segregation (IS) for people belonging to the two highest and two lowest income deciles respectively, we can easily see that high income earners are spatially more concentrated than the poor in all three of Sweden’s largest cities (table 2) Those households that have economic resources to make a free choice tend to cluster more than those having more constrained opportunities These calculations are based on data on individuals and in many cases a male having a high income is married to a female having a low income If calculations are carried out by gender, it turns out the high-income females have the highest IS-values and low-income females have the lowest While a high-income female is often found in a household containing a high-income male person (thus forming a very resourceful household), a low income female is quite often living with a high-income husband Low-income females are thus simply more dispersed across different tenure forms and across urban space Table Index of segregation (IS) for low and high income earners in Stockholm, Göteborg and Malmö (1997) Statistical units are based on the Sams division City Stockholm Low income (bottom two deciles) 0.11 High income (top two deciles) 0.17 16 Göteborg Malmö 0.13 0.15 0.19 0.21 Source: Andersson 2000 Ethnic/racial segregation Understanding and explaining ethnic residential segregation are sometimes fairly easy, especially when residential patterns show distinct ethnic clusters However, in the absence of such clusters the relative spatial concentration of different immigrant categories could have complex demographic, socioeconomic and/or “ethnic” explanations In countries experiencing fairly recent waves of immigration, immigrants tend to have a younger age profile than that of the native population International migrants, like migrants in general, are often young adults (20-35) As households comprising young adults are overrepresented in rental housing we can expect to find many immigrants in rental housing, and also in less attractive rental housing since they will be over-represented in areas experiencing high turnover and vacancies This is the case also in Sweden Furthermore, as many immigrants face problems entering the labour market, they have substantially lower levels of income Low income means difficulties accessing cooperative and especially home ownership housing Demography as well as income could therefore be the factors explaining immigrants’ positions in the housing market These factors are important but cannot fully account for the present level of either segmentation or segregation It has been shown in many Swedish studies, most recently by Bråmå, Andersson & Solid (2006) that “the ethnic component” does play a significant role The authors present odds quota based on a multinominal regression analysis aiming at finding indications for what type of demographic, socioeconomic and origin-related attributes that account for differences with respect to home ownership and cooperative housing in the Stockholm region, using rental housing as the comparison group They find that after controlling for family type, employment status, disposable income, residence time in Sweden, and educational level, it is still five times more common for a native Swede to reside in home ownership compared to an individual born in Western Asia and Northern Africa How can this be explained? Before attempting to answer it is necessary to provide some further empirical data and a brief conceptual overview What is striking in the Swedish case is a) the distinct multi-ethnic character of all immigrant-dense neighbourhoods, and b) the pronounced ethnic/racial hierarchy that exists both on the labour market and in housing Let me start with the latter, using figure as an illustration Figure The ethnic hierarchy in the housing and labour markets* (Stockholm county, 2000) 17 * ID measures differences in residential distributions between people born in Sweden and different immigrant categories (based on the SAMS neighbourhood division) Value 1= “apartheid” LMP = Labour Market Participation Rate for people aged 20-64 (Value 1=100%) Source: GeoSweden 2002 Institute for Housing and Urban Research, Uppsala University With one noticeable exception, people born in Greece, all Western European nationalities show a fairly high level of labour market participation rate and low levels of residential segregation The Greek case is a bit special as the group comprises predominantly older labour migrants having high levels of pre-retirement and high unemployment Otherwise, those facing labour market integration problems and high levels of residential segregation are exclusively of a non-European or Muslim origin Although their housing location might be the result of preferences, their labour market position is certainly not Research carried out by Swedish economists and sociologists evidence that their position cannot be explained by reference to their human capital (education, training, language skills; for an overview, see Rapport Integration 2002 and 2003) Also second-generation immigrants from these countries –having passed the entire Swedish school system and also those having good marks in the Swedish language– have substantially lower employment rates compared to native descendants.(Rapport Integration 2002, 2003; SOU 2005:56) After a couple of decades of supply-oriented research, researchers are now focusing more on demand-related aspects, such as discrimination in recruitment processes As said before, the relation between integration and segregation may not be such that they immediately determine each other At the group level the relation appears to be strong, as indicated by figure 3, but it could of course be the case that discrimination explains both hierarchies and that labour market exclusion is not the result of residential segregation The reverse, however, is certainly highly probable since labour market exclusion will translate into limited freedom of choice in the housing market I will soon come back to this issue but let me first recapitulate some basic concepts concerning ethnic segregation and congregation If we distinguish between a majority and a minority group (see Knox & Pinch, 2000, ch 8), the literature offers a conceptual framework of relevance for discussing segregation 18 mechanisms relating to majority and minority behaviour The majority could react by accepting members of the minority or it could be reluctant to accept such residents In the latter case, this may trigger flight reactions (leaving neighbourhoods having experienced inmigration of minority households), avoidance (not moving into such neighbourhoods), and blocking strategies (acting to keep the minority out of majority-dense neighbourhoods; “isolated host communities” as they are labelled by Johnston, Forrest and Poulsen, 2002) Partly related to the behavioural response of the majority, the minority itself may either attempt to achieve spatial assimilation or to cluster In the latter case, the literature offers a set of reasons for why a minority would cluster: for defence, for mutual support, for reproduction of cultural behaviour, and for (offensive) struggle Knox and Pinch discuss three types of ethnic clusters, distinguished on the basis of longevity/permanence and the degree of free choice: colonies, enclaves, and ghettos While both the colony and the enclave is regarded to be a type of congregation (volunteer clustering), the ghetto is not The difference between the colony and the enclave is that the former is predominantly a first generation phenomenon (these clusters therefore decline and dissolve if immigration decreases or ends), while the latter reproduces over generations Neither ghettos nor enclaves exist in Sweden, albeit local pockets of the enclave type can be found in a few cases (such as the Assyrian-Syrian cluster in Södertälje, in the south-western part of the Stockholm region) Small colony-like clusters are quite common, and –as forecasted by the definition– they tend to depopulate when new immigration from the country of origin ends Table presents data on ethnic clustering in Stockholm County for a rather short period of time (1995-1999) These data have been calculated as follows For each individual living in the region in 1995, and in 1999, we have information concerning country of birth and each individual’s exact residence location (100m by 100m precision) This pair of coordinates has then been used to construct individual-specific environments, where an environment comprises all residents within a distance of 250m from the individual (creating 500m by 500m individual-specific areas centred on each person) By calculating the number (and percentage) of own-group presence in these environments we get the value that provides the basis for table This operation has been carried out for seven minority categories and for two points in time By adding time we get a sense of whether concentrations are increasing or decreasing Due to the fact that the dataset is longitudinal (panel data) it is also possible to study individual mobility in relation to these clusters Table gives one such example by cross tabulating the position of all people born in Turkey who have been residents in Stockholm in both these years (1995 and 1999) Ethnic clusters exist but are mostly small and scattered across many housing estates The percentage of each group who lives in own-group densities above percent is low for Ethiopians, Bosnians and Chileans (rapidly de-clustering), but high and increasing for Somalis and Iraqi and high but decreasing for Turks People born in Iran are increasing in numbers but show no increase in geographical clustering It is –with the noticeable exception of Bosnian immigrants– rather obvious that newly arrived immigrant categories tend to cluster during the expansion phase This has to not only with sheer mathematics (increasing numbers) but also with networks, i.e family reunions, chain migration and institutional policies 19 Table shows that of all 14,323 born in Turkey and who have remained in the Stockholm region 1995 to 1999, 8,184 have stayed in the plus 5% Turkish environments These concentrations have however lost about 450 Turkish residents during the period (from 9,272 to 8,829), so more Turks are leaving than are moving into the most Turkish-dense clusters It is still the case that a majority of the Turkey-born (who are certainly not ethnically homogenous but have different ethnic and religious affiliation) live surrounded by a noticeable share of fellow countrymen Table Own-group geographical concentration in Stockholm county 1995-1999 Source: GeoSweden database Institute for Housing and Urban Research, Uppsala University Table Own-group geographical concentration for Turks resident in Stockholm county 1995 and 1999 Crosstabulation Source: GeoSweden database Institute for Housing and Urban Research, Uppsala University The geographical patterns for a couple of minority categories are displayed in figure The Polish represents an immigrant category scoring low on the Dissimilarity index while the Turkish scores high This is easily visible in the two maps The Turkish-born population live fairly concentrated in the large housing estates built as part of the Million Program These estates are found along the main highways stretching southwest and northwest from the central parts of the region The Turks (which includes also Kurdish and Assyrian-Syrians) however live rather dispersed over many of these estates and they seldom exceed 10 percent of the population of a single estate They are most numerous (1,300) in Rinkeby (10 km north-west of Stockholm city) where they constitute percent of the population, and they constitute the largest share of the residents (15,5 percent) in Fittja (20 km south-west of 20 Stockholm city), where their numbers are just under one thousand In both cases we are talking about a few hundred households Figure Geographical distribution of Stockholm residents born in Poland (left) and Turkey (right) in 1998 Source: GeoSweden database Institute for Housing and Urban Research, Uppsala University In a recently produced but not yet published paper, Musterd, Andersson, Galster & Kauppinen (2005) have used Swedish data to address the question whether own-group clusters are beneficial or not for peoples’ labour market career The authors control for a range of key socioeconomic and demographic individual characteristics The results, derived from OLS regressions on longitudinal (1995-2002) data, are conclusive and show that people residing in own-group clusters in Sweden’s three largest city regions pay a rather severe penalty in terms of income development if the unemployment level in the close environment exceeds a few percentage points (which it almost always does) This hold true for both male and female immigrants of all seven groups listed in table –except for Somali females Similar findings were reported by Andersson in 1998(b) Swedish interpretations Partly due to the existence of good quality data Swedish segregation researchers have lately been stressing dynamic approaches, focusing on gross migration flows in relation to patterns of segregation (see for instance Bråmå 2006a) It has thereby been possible to better understand both the emergence and the reproduction of immigrant-dense neighbourhoods In one of her studies, Bråmå (2006b) addresses the flight and avoidance hypotheses by investigating migration flows during the 1990s to and from a series of neighbourhoods that became immigrant-dense during this period Although “white flight” could be confirmed, “white avoidance” was a much more appropriate label for what took place Figure shows the transition of the Husby housing estate (Stockholm) from a mixed Swedish-immigrant neighbourhood in 1990 to an immigrant-dense estate ten years later Table shows yearly gross migration flows to and from the estate according to origin The table clearly shows that differences in in-migration rates (avoidance) between Swedes and immigrants are much bigger than differences in out-migration rates (flight) Data for the year 2000 might indicate a shift but this is probably due to the construction of new student housing Figure Total number of residents and number of residents with Swedish and immigrant background in Husby, Stockholm 1990-2000 21 Source: Bråmå 2006b Table Annual out-migration and in-migration rates for residents with Swedish and immigrant background in Husby, Stockholm, 1991-2000 Out-migration rate Total In-migration rate With With Swedish immigrant background background Total With With Swedish immigrant background background 1991 12,8 14,0 11,5 12,5 7,7 17,0 1992 12,9 13,6 12,3 12,3 7,8 16,0 1993 13,7 14,3 13,2 13,7 6,9 18,3 1994 15,0 15,4 14,7 15,0 7,0 19,6 1995 12,5 12,8 12,3 12,9 6,7 16,0 1996 12,1 13,4 11,4 12,1 7,0 14,3 1997 11,9 13,1 11,3 11,8 8,9 12,9 1998 12,0 14,8 10,9 12,2 8,1 13,6 1999 11,4 11,8 11,2 11,8 8,8 12,7 2000 9,2 9,5 9,1 8,0 9,9 7,4 13,3 11,8 12,2 7,9 14,8 Mean 12,3 Source: Bråmå 2006b The dominating ethnic segregation discourse has changed over time in Sweden One might say that it has moved from initial propositions stating that the patterns were self-generated (the culturalist tradition3), via a structural understanding stating that socioeconomic subordination of minorities translates into housing segregation (the structuralist tradition), to a current discourse arguing that ethnic residential segregation has to be understood in the Typically, most studies arguing for the importance of self-segregation (congregation) are based on local casestudies Björklund (1980) studied Syrians in Södertälje, Andersson-Brolin (1984) Latin Americans in Tensta and Rinkeby, Pripp (1990) and Özukren and Magnusson (1997) Turks from the Kulu district in Fittja These studies find that people have chosen to live close to relatives but they also report that immigrants complain about the lack of native Swedes in the neighbourhoods These studies also recognise that living in ethnic clusters negatively affect integration opportunities (Urban 2005, p 101) According to the Swedish Board of Social Affairs (Socialstyrelsen, 1999) a majority of immigrants (from Chile, Iran, Poland and Turkey) residing in immigrant-dense areas want to live in more “Swedish” environments 22 context of racism, discrimination, and the role played by Swedish institutions and the majority in blocking immigrants from accessing more attractive parts of the housing market (the “postcolonialism” tradition) Discussions continue and none of these three interpretations are easily dismissed and neither of them can sufficiently explain current patterns and processes without bringing in elements from the other two.4 It is however quite unusual today to find strong advocates for the culturalist interpretation 23 Appendix Map of Tensta (northern part) and Spånga in Stockholm city Source: Kartex 24 References Andersson, R (1998) “Socio-spatial dynamics: Ethnic divisions of mobility and housing in Post-Palme Sweden”, Urban Studies 35: 397–428 Andersson, R (1998b) Segregering, segmentering och socio-ekonomisk polarisering Stockholmsregionen och sysselsättningskrisen 1990-95 Partnerskap för Multietnisk Integration, Rapport nr 2, Sociologiska 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Furthermore, most analyses of neighbourhood effects have been significantly constrained by the nature of the areas for which data are available In many cases these are relatively large and in almost... plans and activities around the restructuring of certain areas in cities Today, at least in many European cities, a large share of urban restructuring plans is aimed at transforming large-scale... both the census tracts and the parishes are socially very heterogeneous and also large-scale areas Social processes and relevant interactions between people may not occur at these levels, but at