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POPULATION, SPACE AND PLACE Popul. Space Place 2017; 23: e2013 Published online 24 January 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/psp.2013 Remaking Urban Segregation: Processes of Income Sorting and Neighbourhood Change 1, 2 2 Nick Bailey , Wouter P. C. van Gent and Sako Musterd Department of Urban Studies, University of Glasgow, Glasgow, UK AISSR: Urban Geography, University of Amsterdam, Amsterdam, The Netherlands ABSTRACT structured by historically specifictrends instate and housing market context. © 2016 The Authors. Segregation studies have mainly focused on Population, Space and Place. Published by John urban structures as a whole or have discussed Wiley & Sons, Ltd. specific (gentrifying or renewing) neighbourhoods. The literature suggests that changes in segregation occur primarily through Accepted 03 December 2015 selective migration. In this paper, we follow up Keywords: spatial segregation; income on recent work that has questioned these inequality; residential mobility; social mobility; orthodoxies, suggesting that in situ social neighbourhood change; gentrification mobility, and entries to and exits from the city population should be taken into account as well, and that dynamics in all neighbourhoods should be considered. The paper traces the INTRODUCTION processes by which segregation changes for the cities of Amsterdam and The Hague for patial segregation is one of the most basic 1999–2006, using a longitudinal individual- characteristics of cities. Much evidence sug- level database covering the entire population. S gests that segregation matters for individ- It extends previous work by looking at income ual welfare, economic growth, and broader rather than socio-economic status and by social cohesion. The neighbourhood effects litera- drilling down to the neighbourhood level. ture, while not conclusive, provides a range of Applying an existing measure of segregation studies tracing impacts of living in high-poverty (Delta) in a novel way, the analysis focuses on neighbourhoods on a range of welfare outcomes changes in the spatial distribution of (Ellen & Turner, 1997; Galster et al., 2010; van household income, measuring the relative Ham et al., 2012). Research on non-linear or thresh- contribution of a range of processes to changes old neighbourhood effects suggests that spatial in segregation. Results show that segregation patterning is more than a zero-sum game, with rises in both cities but that different processes negative aggregate impacts for economic efficiency drive changes in each case. Furthermore, the (Galster et al., 2015). It has also been suggested that aggregate change in segregation for each city segregation may affect social cohesion, for exam- masks a diversity of changes at the ple, by reducing awareness of inequality and a neighbourhood level, some of which tend to commitment to the solidaristic institutions of the increase segregation while others tend to reduce it. welfare state (Bailey et al., 2013). Mapping these changes and the individual The basic mechanisms underpinning economic processes contributing to them shows that they segregation are rather clear. On the one hand, seg- have a distinct geography, which seems to be regation emerges where individuals share prefer- ences in location with others from their group, *Correspondence to: Nick Bailey, Department of Urban including a preference to live close to others from Studies, University of Glasgow, 25–29 Bute Gdns, Glasgow that group (Schelling, 1971). On the other, market- G12 8RS, UK. E-mail: nick.bailey@glasgow.ac.uk dominated housing systems sort people by © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. 1 of 16 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduc- tion in any medium, provided the original work is properly cited. 2of 16 N. Bailey, W. P. C. van Gent and S. Musterd income or wealth into distinct areas (Reardon & and perhaps most importantly, the complete popu- Bischoff, 2011) although it is important to ac- lation coverage enables us to take the analysis knowledge that the relationship between social down to the level of individual neighbourhoods, inequality and socio-economic segregation is a to examine the variations in change between complex one. First, choices related to household neighbourhoods, and to explore the geography of type, cultural background, and lifestyle prefer- the processes in each city. ences can cut across those based on income. Sec- ond, market processes are altered by diverse LITERATURE REVIEW institutions of the welfare state (Musterd & Ostendorf, 1998; Maloutas & Fujita, 2012; Social-spatial patterns within a city can be attrib- Marcińczak et al., 2016). Both preferences and wel- uted to a range of processes. These include fare regimes vary between places and over time. individual-level features, such as the preference Rather less attention has been given to under- for certain dwellings and locations, and the extent standing the processes by which spatial segregation to which individuals have been able to attain changes. This is often assumed to occur entirely sufficient means to be able to realise these prefer- through selective residential mobility – an imbal- ences. Individuals also tend to have social-spatial ance in the characteristics of those moving into or preferences aimed at social homogeneity; many out of each neighbourhood (Dorling & Rees, 2003). people prefer to live close to other people who Cities tend to be viewed as closed systems, while in- are like themselves (McPherson et al., 2001; dividuals are seen as having fixed characteristics, so Musterd et al., 2015). This clearly is in line with the potential for inter-urban migration or in situ earlier work on the relationship between residen- social mobility (changes in status for people who tial preferences and segregation outcomes, do not move) to reshape segregation is ignored. starting with Schelling (1971). In his seminal Over recent years, however, some new perspectives paper, he suggested that even small differences have emerged. In their studies of the process of gen- between group preferences could result in major trification, Van Criekingen and Decroly (2003), segregation on aggregate. His ideas were empiri- Teernstra (2014), Hochstenbach and Van Gent cally tested and elaborated, for example by Clark (2015), Hochstenbach et al., (2015), and McKinnish (1991). Fossett (2006) speculated that sustained et al., (2010) showed the potential for in situ social segregation may have multiple causes, ‘not only mobility to drive change, challenging one of the discrimination, but also social distance and pref- three just-mentioned assumptions. Bailey (2012) erence dynamics’ (p. 185), while Clark and challenged all three. His research highlighted the Fossett (2008) argued ‘that there is now a rigorous levels of social mobility and provided evidence that mathematical basis for the Schelling model and in situ mobility may be as important in driving increasingly refined methods for simulating the change in segregation as selective migration. That impact of preferences and social distance dynam- work also highlights the scale of flows into and ics’ (p. 4114). These patterns are rendered more out of urban areas over the medium term. complex by the fact that they are not just socio- The study by Bailey was limited to a single economically driven but also reflect indepen- country (Scotland) and a single time period dent demographic and cultural dimensions (1991–2001), had restricted measures of socio- (Andersen, 2011). economic status (notably no income data), and Apart from individual-level conditions, struc- covered only a sample of the population (5%). tural conditions also play a role, and this has, The aim of this paper is to use the same analytical for a long time, been the dominant way through framework but to extend the analysis by using which urban change has been approached. The data from the Dutch System of Social Statistical character and position of the local urban economy Datasets (SSD), a longitudinal individual-level da- will have major implications. It drives growth or de- tabase covering the entire population in the period cline with crucial effects for employment demand, 1999–2006. First, the paper compares changes in and hence the social and professional characteristics segregation between two cities with rather differ- of the local population. Some urban economies are ent starting points: Amsterdam and The Hague. more unequal than others, and this is reflected in Second, it compares the processes by which house- space (Sassen, 1991). Walks (2001) has argued that hold income is redistributed across each city. Third, such a relationship may be very complex when © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 3of 16 brought down to the neighbourhood level: ‘the the characteristics of those moving in and out of social ecology of the post-Fordist/global city may neighbourhoods are seen as the main factors of be characterised by increasing social complexity change (Dorling & Rees, 2003). Inter-urban mi- and differentiation among, between and within gration and in situ social mobility tend to be ig- neighbourhoods’ (p. 440). nored – or are assumed to be important only as Historically grown structures of the housing a driver of selective residential mobility (Cheshire market will also have an influence. States with et al., 2003). In the current literature on urban so- a long tradition as social democratic welfare re- cial inequality, the description of social-spatial gimes will likely have larger social housing stocks processes has received a new impulse through a compared with more liberal welfare regimes. De- more analytical approach of the description of regulation generally results in higher levels of segregation. This literature makes efforts to ‘de- segregation (Musterd & Ostendorf, 1998; Reardon construct’ urban social processes, bringing them & Bischoff, 2011; Boterman & Van Gent, 2014; back to essential components that together pro- Marcińczak et al., 2015). Tenure structures and duce changes in social patterns (Bailey, 2012). So- house price structures may also be very different cial structures in neighbourhoods can be seen as between urban regions. Because the entire socio- the product of people moving within the city; economic character of the city will be related to their attributes may differ with impacts on social such urban histories, cities will show different spa- composition. In addition, however, those who do tial structures in these respects as well, which will, not move, and those who move in to or out of the again, eventually be reflected in the social-spatial city, produce change. Moreover, people die and patterns. thus ‘leave’ the neighbourhood or they ‘join’ the With regard to the impact of the type of welfare adult population through ageing, and both again regime, we must also consider aspects that do not may affect the characteristics of the place. relate directly to housing or to the spatial organisa- This literature is, however, still rather limited. tion of housing. As clarified by Esping-Andersen In the introduction, we already referred to the (1990), states may be more or less active in terms neighbourhood studies by Teernstra (2014) and of redistributing wealth, through the impact of Hochstenbach and Van Gent (2015), which were policy on the income distribution, prices, or able to show that much income gain in urban public services, such as schools or health services. neighbourhoods was in fact ‘produced’ by in situ They create the conditions for individual-level processes: by social mobility of individuals who differences in terms of social positions, and the op- remained in these neighbourhoods. In the US, portunities for changing such positions; and they McKinnish and colleagues (2010) suggested simi- create the conditions for structural differences in lar processes were driving gentrification pro- cities, which impact on residential mobility and cesses there. One of the interpretations was that migration processes (Hastings, 2009). Marcińczak stayers might ‘experience disproportionate in- et al. (2016, p. 378) concluded in their study on come gains’ (McKinnish et al., 2010, p. 189). This socio-economic segregation in European capital seems to be particularly a driver for change in cities that processes of globalisation are triggering neighbourhoods that have the proper set of condi- different levels of connectedness and international tions to enable marginal gentrification (Van migration of affluent and poorer sections of the Criekingen & Decroly, 2003; Van Criekingen, population in different cities; the restructuring of 2010; Hochstenbach et al., 2015). Marginal gentri- the economy and the labour market also impacts fiers have low incomes when they enter a differently in cities with different development ‘gentrifyable’ neighbourhood and then may stay paths; increasingly, neo-liberal politics and – in there for a longer period of time, likely experienc- some cities – declining investments in the social ing upward social mobility. In this study, we do rental housing sector are important processes as not intend to relate such processes to the gentrifica- well, which manifest themselves in different ways tion debate per se, because such processes may and with different rigour. Yet, all of these processes occur in all neighbourhoods and many of the can be regarded to impact upon segregation. changes will not just result in upwardly mobile Studies that have addressed neighbourhood processes either. What is important, however, is change often assumed that these would be to pay more attention to the various components mainly driven by selective residential mobility; of social change at the neighbourhood level. © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 4of 16 N. Bailey, W. P. C. van Gent and S. Musterd While we may benefit from efforts to under- gender, and household relationships for the pe- stand urban social segregation at the level as just riod 1999 to 2006. There is no data for unregis- sketched, and search for individual or structural tered immigrants, and some very limited explanations for variations in segregation, the is- numbers of foreign diplomatic and military per- sue of segregation is frequently approached with sonnel are removed from the data. Income and an ambition to better define and describe the pro- benefits data are derived from Dutch tax and cess at the level of the entire city. This, obviously, benefit registers. Individuals living in the started with the work of Duncan and Duncan Netherlands but receiving foreign benefits or (1955) on the dissimilarity index, soon followed paying income taxes abroad have missing or by others who designed additional measures that underestimated values on income but again focused on different aspects of segregation. Ini- with very minimal impact on this study. The tially, the measures focused on the comparison dataset is compiled from a range of registers, of two categories, but later on, the scope wid- merged by Statistics Netherlands on the basis ened. Massey and Denton (1988) brought the of unique personal identification codes but range of measures together in a system of mea- ‘anonymised’ before release to researchers. surement methods, including measures for levels The paper focuses on two cities defined in of unevenness (such as the index of dissimilarity, terms of their administrative boundaries: Gini index, and entropy index), exposure (includ- Amsterdam and The Hague. Amsterdam is the ing the index of isolation), and various measures largest and most diverse city in the Netherlands. of concentration, centralisation, and clustering. It is thecentreof finance and business, as well as All can be used to measure different aspects of of a rapidly growing set of creative industries. In segregation, although they sometimes overlap. terms of population, it grew slightly during the There has been much discussion about these period of research, with the total population ris- measures. Much debate relates to the size of the ing 2%, a result of an increase in the numbers be- spatial unit, which has an impact on the level of low 20 years (by 6%) and 20–65 years (by 3%), segregation. In addition, the form and location but a decline of those 65+ (down 8%). The of the area and its positioning relative to other Hague is the centre of (international) law and areas has received ample attention, as well as a government. While the city has long been range of other technical aspects. This resulted in known for its stability, over the research period, the development of more complex measures with it showed remarkable population dynamics. a spatial character (Wong, 2008). The most recent The total population increased by 8%, mainly efforts aim at using the rich information and caused by a strong increase in the numbers un- more detailed geographies that have become der 20 (up 12%) and 20–65 years (up 11%), while available in various contexts (Johnston et al., the elderly lost 10% (Statistics Netherlands 2008), yet none of these appear to focus on 2015). The Hague is known for its relatively high deconstructing the processes of segregation. All levels of segregation, and the city continues to of these factors may help to change or reorder show figures that are higher than those in the the positions of neighbourhoods, and this may other large Dutch cities, including Amsterdam happen when segregation is decreasing, increas- (Gijsbers & Dagevos, 2009). ing, or even staying stable for the system as a The comparisons between Amsterdam and whole. The Hague are made for the entire adult popula- tion (18+) present in either 1999 or 2006. This en- METHODS compasses everyone who could contribute to the income situation in the urban neighbourhoods at Data each period. Incomes in 1999 are adjusted so that This study uses data from the SSD, made avail- the total income for each city is the same in 1999 able by Statistics Netherlands. The SSD contains and 2006. This prevents inflation potentially individual-level register data on the entire popu- distorting the picture of change. lation of the Netherlands, including data on in- We initially use four measures of household in- come from work, benefits, student subsidies, comes: income from employment only (before and pensions, as well as other characteristics such taxes); income from employment and benefits as neighbourhood of residence, ethnicity, age, combined, before and after taxes; and total © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 5of 16 income including income from self-employment Segregation Measures or businesses (before taxes). In later analyses, Many measures of segregation have been we focus on the last of the four as providing the developed for use with categorical data (Massey & single most complete picture of income. In a very Denton 1988). It is these that were employed in pre- small number of cases, total incomes are negative vious work on processes of change in segregation; because businesses that those people own have Bailey (2012), for example, used dissimilarity and recorded a loss. Where such individuals have an isolation indices. We could have employed the income from employment and/or from benefits, same measures by collapsing our continuous mea- we take that figure instead. Otherwise, we record sures of income into binary categories, but this negative incomes to zero on the basis that house- throws away a great deal of information. We there- holds must have had some income in order to fore use two alternative measures, Gini and Delta. survive; the negative recorded income represents The Gini coefficient is widely used to measure a loss of wealth. Conversely, some individuals national or regional household income inequality, have extremely high incomes, which have the but it can also be applied at the neighbourhood potential to unduly influence the analysis of level. In this paper, we use it for both: household in- change, particularly when looking at individual come inequality for each city and neighbourhood neighbourhoods. We have experimented with a income inequality or segregation. In the latter case, range of thresholds for ‘trimming’ these ex- theGinicoefficient measures the extent to which in- tremes. This changes the details at the margin come is more or less equally shared between but does not affect the general structure of the neighbourhoods, taking account of the population results. In this paper, we report results based of each. on removing people with an income in the top The Gini coefficient is built from the cumula- 0.1% at either time period. tive income distribution, not from the characteris- tics of each neighbourhood. We cannot therefore Neighbourhood Units disaggregate the overall index to look at each neighbourhood’s contribution nor use it to under- This paper uses the neighbourhood units pro- stand how processes of change vary between vided by Statistics Netherlands. Although it is places. We can produce something that is closely widely recognised that the scale and nature of related to Gini, however, by adapting one of the neighbourhood boundaries may impact on mea- measures of concentration (Delta) discussed in sures of segregation (Östh et al., 2015), there is Massey and Denton’s (1988) review. They define no choice in this case. A predetermined set of concentration as the extent to which the physical units is the only option Statistics Netherlands of- area of the city is equally distributed across the pop- fers, in order to minimise disclosure risks on what ulation in each neighbourhood. We look instead at is relatively sensitive data. On the positive side, how the total income of the city is distributed across the units were determined in cooperation with lo- the population in each neighbourhood. For each cal municipalities and are generally socially and neighbourhood i,wecalculate Delta as the differ- physically homogeneous areas, which are clearly ence between the neighbourhood’sshare of city in- bounded by main roads, railways, or waterways. come and its share of city population: In a small number of cases, the neighbourhood boundaries altered between 1999 and 2006, or Delta ¼½ t =T – x =X i i i the neighbourhood only existed in 2006. These t - total income for neighbourhood i neighbourhoods are excluded, so the study is T -total incomeforcity based only on those with consistent boundaries over time. We can be confident therefore that, x - population of neighbourhood i for each neighbourhood, a change in characteris- X - total population of the city tics is not driven by boundary changes and, for For the city as a whole, Delta is given by each individual, a change of neighbourhood rep- resents a change in address. On this basis, Am- Delta ¼ ½∑½ t =T–x =X jj i i sterdam has 93 neighbourhoods with an average 18+ population of 5700, while The Hague has 91 Delta is analogous to the dissimilarity index. neighbourhoods with an average of 3500. Dissimilarity compares an area’s share of group © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 6of 16 N. Bailey, W. P. C. van Gent and S. Musterd x with its share of group y, whereas Delta com- pares the distribution of people with the distribu- tion of income. For an individual neighbourhood, arisein Delta indicates that the residents are be- coming more affluent (on average). Furthermore, there is a direct mathematical relationship between Delta and Gini as applied to income segregation, as both are derived from the same segregation curve; Duncan and Duncan (1955) established the rela- tionship in their discussion of dissimilarity and Gini. For the measurement of city-level income in- equality (using Gini), household relationships matter because the measures are based on total income for each household. These measures do not capture inequality in access to resources within each household, but they are affected by processes of household formation or dissolution. For the measurement of neighbourhood income segregation (using Gini and Delta), measures are based on total income for each neighbourhood. Figure 1. Processes of change in spatial segregation. Any inequality within the neighbourhood is correspondingly ignored, so they are unaffected by household formation or dissolution. with the ‘ageing in’ group or with the ‘moving in’ group. Here, we identify them as a separate stream. Analytical Approach To assess the effect that each individual pro- The paper aims to identify the processes by cess has on spatial segregation, we measure the which spatial segregation changes. The starting level of segregation ‘before’ that process has oc- point is the level of segregation of the population curred and again ‘after’. For example, with the 18 or over in 1999, and the end point is the level first process (deaths), we measure the segregation in 2006. Following Bailey (2012), three groups of level for the whole population present in 1999 processes contribute to the change: exits from and then again with the records for those who the adult population, change for adults present died before 2006 removed, but all other character- at both periods (referred to as the ‘core group’), istics unchanged. and entries to the adult population (Fig. 1). Exits occur where people present in 1999 are no longer FINDINGS recorded as part of the population of the city in 2006. Some exits occur through deaths between Scale of Flows 1999 and 2006; others occur when people move out of the city. For the core group, change in seg- Table 1 demonstrates the very open and fluid na- regation may occur where patterns of residential ture of the two urban systems – a feature often mobility are socially selective or where patterns underestimated in urban theorising and analysis. of social mobility for non-movers are spatially se- Almost one-third of the population in 1999 was lective; the latter termed in situ social mobility. Fi- no longer present in each city by 2006, and a sim- nally, change occurs through new entries to the ilar proportion of the 2006 population had not population over 18. Some young people present been present in 1999. Because the exit flow is in the city but under 18 in 1999 age into our pop- greater than the entry flow in each case, the net ulation of interest. Other people already over 18 effect is a slight decline in population (down 2% in 1999 but living elsewhere move into the city. and 6% for Amsterdam and The Hague, respec- A third group comprises those under 18 and not tively). These declines contrast with the growth in the city in 1999. These could be counted either in both cities’ populations noted in the preceding © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 7of 16 Table 1. Scale of flows for the two cities – 1999 to 2006. pensions are taken into account, inequality is markedly lower and becomes more so once the ef- Amsterdam The Hague fects of tax are factored in as well. Gross total in- Exits (%) 30 33 come is distributed slightly more equally than Deaths 8 11 gross income from work and benefits, implying Outmigration 22 23 that much of the income from self-employment Entries (%) 29 29 flows to people who have relatively few other in- Age in from city 6 7 come sources. Age in/move in 5 4 Income inequality is the same in the two cities In-migrants 18 18 if we look only at gross income from work, but, Net population change (%) 2 6 on the other three measures, it is slightly higher % of core group who 30 34 in Amsterdam in both periods. This implies that move (%) the tax and benefits system does less to reduce in- Source: System of Social Statistical Datasets. ‘Entries’ and ‘exits’ are equality there. This may reflect the presence in expressed as percentages of the population 18+ present in 1999 and Amsterdam of more people who are ineligible 2006, respectively. for welfare benefits (such as students) or the pres- ence in The Hague of more people for whom text. The difference is due to the exclusion here of benefits and pension transfers are more impor- both under-18s (growing rapidly in both cities) tant, perhaps reflecting the older population and the ‘new neighbourhoods’, which did not ex- profile of that city. ist in 1999, which, by definition, have seen popu- In both cities, income inequality at the house- lation growth. For the ‘core’ group (those present hold level rose between 1999 and 2006. There in the city at both time periods), the table also was little growth in the inequality of gross in- shows that about one-third moved between come from work but rather more in incomes that neighbourhoods. Exits are made up of deaths include benefits. This indicates that the value of and outmigration. Amsterdam’s lower exit rate benefits and other state transfers was being arises because of its lower death rate, indicating eroded over this period compared with the value a younger population profile. of income from work. Changing Income Inequality at the City Level Changing Spatial Segregation Before looking at spatial segregation, Table 2 Gini coefficients at the neighbourhood level are shows changes in income inequality at the house- much lower than those at the household level hold level. It reports the Gini coefficient for each (Table 3), as we would expect: as we move to city for the four income measures. Inequality ap- larger aggregations, inequality has to decline. pears greatest if we look at gross income from Therelativedifferences betweenthe measures work, as we would expect. Once state benefits are very similar to those for the household level. and other transfers such as state and private The coefficients are higher in The Hague, but Table 2. Household income inequality (Gini coefficient) in the two cities by type of income, 1999 and 2006. Work (gross) Work + benefits (gross) Work + benefits (net) Total (gross) Amsterdam 1999 66 45 40 43 2006 68 49 44 48 Change % +3 +9 +10 +10 The Hague 1999 66 42 38 42 2006 69 46 41 45 Change % +3 +8 +10 +9 Source: System of Social Statistical Datasets. People with an income in the top 0.1% at either period excluded. © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 8of 16 N. Bailey, W. P. C. van Gent and S. Musterd Table 3. Income segregation (Gini coefficient and Delta) in the two cities at the neighbourhood level, 1999 and 2006. Gini Delta Work + benefits Work + benefits Total Work + benefits Work + benefits Total (gross) (net) (gross) (gross) (net) (gross) Amsterdam 1999 10.1 7.8 10.9 7.4 5.7 7.9 2006 12.8 10.2 13.4 9.5 7.6 10.0 Change in +2.7 +2.4 +2.5 +2.1 +1.9 +2.1 points The Hague 1999 13.7 11.1 13.8 9.7 8.0 9.9 2006 16.9 14.1 17.1 12.0 10.0 12.4 Change in +3.2 +2.9 +3.3 +2.3 +2.0 +2.5 points Source: System of Social Statistical Datasets. People with an income in the top 0.1% at either period excluded. we should be wary of seeing this as an indication turning 18 in our research period (‘age in, from of greater segregation; neighbourhood units in outside’) offset this to some extent. In The Hague, The Hague are significantly smaller. In both cit- it is in-movers that dominate with no similar off- ies, we can say that spatial segregation increases setting effect. It is worth reinforcing here that the over time and by similar amounts. Table 3 also effects of any process occur in complex ways. For compares Gini coefficients with the Delta mea- example, residential mobility increases segrega- sure used in the neighbourhood analysis in the tion when richer people tend to leave poorer succeeding text. All the features noted with the neighbourhoods but also when poorer people Gini coefficient are repeated with Delta, which move away from more affluent neighbourhoods. is as expected given the mathematical connection Similarly, in-movers can widen segregation either between the two measures noted in the preced- by richer people moving into neighbourhoods ing text. with above-average incomes (provided their in- comes exceed the existing average) or by poorer people moving into poorer neighbourhoods (with Processes of Change in Segregation the same caveat). Table 4 shows how much each process contrib- utes to changes in segregation in each city, using A Typology of Neighbourhood Change the Delta measure of inequality applied to the total income measure; the results are very similar One advantage of Delta over Gini is that the contri- using other combinations of measures. Looking bution that each neighbourhood makes to the total at the three broad groups of processes (exits, index can be identified separately, so we can disag- entries, and change for the core group), we see gregate changes down to neighbourhood level. significant differences between the two cities. In This also allows us to see changes that are hidden Amsterdam, change in segregation is driven pri- when we only consider aggregate segregation for marily by the core population. Entry flows are the city as a whole. Segregation assesses whether also important, but exit flows play little role. In neighbourhoods are pulling apart or moving to- The Hague, however, change is dominated by gether, but, within these changes, we can also ob- entry flows with exit and core flows both impor- serve the reordering of neighbourhoods – the tant but clearly secondary. tendency for some poorer neighbourhood to be- Looking at the more detailed processes in come richer and vice versa. Figure 2 compares each Amsterdam, residential mobility is the reason neighbourhood’sincome shares in 1999 with its the core group contributes to increased segrega- change in income share between 1999 and 2006. tion, with in-movers having the next largest effect For both cities, there are neighbourhoods in all four although the entry moves of those who are also quadrants, giving four types. The two types top- © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 9of 16 Table 4. Changes in segregation by process – Amsterdam and The Hague. Amsterdam The Hague Delta in 1999 7.9 9.9 Changes due to: Exit 0.1 0.6 Death 0.1 0.2 Outmigration 0.1 0.3 Core 1.2 0.5 In situ social mobility 0.1 0.2 Residential mobility 1.2 0.2 Entry 0.6 1.5 Age in, in city 0.4 0.2 Age in, from outside 0.3 0.0 In-migration 0.6 1.2 Delta in 2006 10.0 12.4 Change 1999–2006 +2.1 +2.5 Source: System of Social Statistical Datasets. People with an income in the top 0.1% at either period excluded. Figure 2. Neighbourhood income share in 1999 versus change – Amsterdam and The Hague. right and bottom-left have changes that contribute (‘+/’). We might term these ‘reordering to increasing segregation – they start either with neighbourhoods’. above-average income shares and see these in- There is slightly more correlation between crease (labelled ‘+/+’), or they start with below- initial incomes levels and change in The Hague average incomes and see them decrease (‘/’). than in Amsterdam, but in both cities, the We term these ‘polarising neighbourhoods’.The proportion of the variance explained by the other two types contribute to reducing segregation starting position (as shown by the R )isrela- because they either had below-average shares of tively low. There is not just a pattern of rich income initially but saw these rise (‘/+’)or were neighbourhoods getting richer and poor getting above average initially but with incomes falling poorer but also considerable movement within © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 10 of 16 N. Bailey, W. P. C. van Gent and S. Musterd the overall structure. This is particularly so in decline due to newer suburban alternatives. Amsterdam where 36 out of 93 neighbourhoods There are of course some exceptions to the gen- are ‘reordering’, compared with 25 out of 91 in eral pattern. For example, there are some The Hague. centrally located neighbourhoods characterised by high shares of social housing, which show decreasing deltas. The Geography of Neighbourhood Types In The Hague, the initial picture in 1999 is Figures 3 and 4 map the four types of characterised by a marked income divide across a neighbourhood for each city. Differences are line running from north-east to south-west. To the mostly related to housing market characteristics north and west, the neighbourhoods almost all and state interventions (Teernstra & Van Gent, have above-average income, while to the south 2012). Looking at Amsterdam, the overall picture and east, they almost all have below average. The could be summarised as increasing income shares latter include some of the poorest neighbourhoods in the older, inner neighbourhoods. These include in the Netherlands (notably Transvaal and middle-class neighbourhoods like Middenmeer, Schildersbuurt). The pattern of change is rather dif- newly built Eastern Docklands or Rivierenbuurt, ferent, however, with rising income shares largely and highly affluent neighbourhoods such as the confined to neighbourhoods in the area north of Canal Belt and Oud-Zuid (‘Old South’). They the city centre but on both sides of this line. This also include poorer areas, which are gentrifica- includes more affluent areas with villas and tion neighbourhoods close to the historic city townhouses along with some poorer but centre (see also Hochstenbach & Van Gent, ‘reordering’ neighbourhoods, including areas that 2015). By contrast, outer areas with falling in- were undergoing urban renewal at the time, as come shares include poorer areas found in the well as several centrally located areas undergoing highly urbanised post-war areas in the western gentrification. Like Amsterdam, richer suburban and southern parts of town and north of the IJ neighbourhoods from the 1970s and 1908s to the estuaryaswellas richerpost-warsuburban south-west are experiencing relative housing mar- neighbourhoods, which were once relatively af- ket decline and falling income shares along with fluent but are now experiencing housing market poorer pre-war and post-war areas in the south. Figure 3. Four neighbourhood types – Amsterdam. © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 11 of 16 Figure 4. Four neighbourhood types – The Hague. Processes of Change at Neighbourhood Level cancelled out by the effects of exits (out-movers), while in situ social mobility plays a much greater Figure 5 shows how the processes driving change role. In particular, the poorer neighbourhoods vary between the four types of neighbourhood; that are becoming more affluent are benefitting entry and exit processes have been collapsed for from the upward mobility of existing residents simplicity. In Amsterdam, residential mobility is who choose to remain. the dominant influence in all four types. In the polarising neighbourhoods, its effects are rein- Figures 6 and 7 map the effects of residential forced by entries (in-movers). These two pro- mobility and social mobility in Amsterdam. They cesses were dominant in driving change in show that most of the inner areas have this ‘dou- segregation for the city as a whole (Table 4). In ble effect’ of income gains through both pro- the reordering neighbourhoods, however, the cesses. Discrepancies may be explained by effects of in-movers are either reduced or renewal (positive effect for residential mobility). Also, a few peripheral areas with suburban hous- ing built in the late 1980s and early 1990 still see an increase in income shares from in situ social mobility but a loss through residential mobility. Lastly, very affluent areas in Oud-Zuid see a neg- ative effect of in situ social mobility and a positive effect from residential mobility. This may be ex- plained by the older age structure in these areas as incomes tend to rise more rapidly in the early stages of a career while retirement generally comes with a drop in income. By contrast, in The Hague, entries (predomi- nantly in-movers to the city) are a strong influ- ence only in the polarising neighbourhoods where they act to increase segregation. In Table 4, Figure 5. Processes of change by neighbourhood type – Amsterdam and The Hague. we saw that residential mobility has very little © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 12 of 16 N. Bailey, W. P. C. van Gent and S. Musterd Figure 6. The effect of residential mobility on change in income share – Amsterdam. Figure 7. The effect of in situ social mobility on change in income share – Amsterdam. impact on segregation in The Hague and that is in income shares concentrated in neighbourhoods apparent here as well. In this city, its effect is con- north of the inner city. By contrast, residential fined to the reordering neighbourhoods. Figure 8 mobility is the key process in the reordering shows the effect of in-movers at neighbourhood neighbourhoods. In some cases, it seems to be level. The pattern reflects the overall picture of in- triggered by neighbourhood renewal going on come change from Figure 4, with the largest gains at the time (notably in south of Transvaal, on © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp Remaking Urban Segregation 13 of 16 Figure 8. The effect of in-migration on change in income share – The Hague. the coast, and in a few of the poorer southern left within the 7-year period and were replaced neighbourhoods). In contrast to Amsterdam, in by an equal number. These high levels of popula- situ social mobility plays only a marginal role in tion dynamics underpin segregation, in some The Hague (e.g. Valkenboskwartier and city cases contributing to change but mostly to sus- centre). taining existing patterns (Musterd et al., 2015). In- deed, given this level of change, one might argue CONCLUSIONS that the degree of continuity in segregation is the most notable feature. In this paper, we demonstrate a new approach to Nevertheless, we also show that segregation understanding how urban segregation gets re- changes and that the patterns and processes of made. Extending Bailey’s (2012) approach, we change vary between cities, even within the same show how household income is reallocated across country. Both our cities experienced increasing the neighbourhoods of two Dutch cities in the pe- income segregation at the household and riod 1999 to 2006, using longitudinal individual- neighbourhood levels, but The Hague saw level data for the whole population. We show sharper increases than Amsterdam. The sorting how much segregation changed in each city as processes underpinning this were rather differ- well as the processes that underpinned this. Go- ent. In Amsterdam, residential mobility within ing beyond earlier analyses, we examine varia- the city and in-migration were the dominant tions at the neighbourhood level, constructing a processes, while in The Hague, it was mainly typology of neighbourhoods based on these in-migration. These findings support insights changes, exploring the geography of this typol- gained from recent social-spatial research in which ogy and identifying the role of different processes – among other things – in situ social mobility in explaining neighbourhood trajectories. processes were brought forward as important This paper therefore makes a number of im- dynamics for understanding urban social change, portant contributions to our understanding of particularly in gentrifying neighbourhoods (Van how socio-spatial segregation changes over time. Criekingen & Decroly, 2003; Teernstra, 2014; First of all, it is clear that there is a very high de- Hochstenbach et al., 2015). gree of churn in urban populations, at least in The examination of change at the neighbourhood these two cities. In each, a third of the population scale reveals much greater fluidity than the © 2016 The Authors. Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp 14 of 16 N. Bailey, W. P. C. van Gent and S. Musterd aggregate, city-level picture suggests. Our typology the system of neighbourhoods. At the moment, distinguishes ‘polarising neighbourhoods’ from the ‘gentrifying’ older inner neighbourhoods are ‘reordering neighbourhoods’. The former contribute becoming less poor, but there may well come a to increased segregation, while the latter contribute point when their incomes rise above average and to reducing levels of segregation and to moves their continued change then acts to increase within the existing neighbourhood hierarchy. Not segregation. only did the balance in types vary between the In this paper, we were able to provide only ten- two cities, but also the processes that created the tative explanations as to why different processes types did too. In Amsterdam, for example, are operating in different neighbourhoods and cit- reordering neighbourhoods arose primarily from ies. The role of specific housing market contexts of in situ social mobility, but in The Hague, it was the two cities indicate that historically shaped mainly residential mobility that drove reordering, demand-side and supply-side factors appear to in large part due to renewal efforts. These processes be relevant for such understanding (cf. Brown & seem to be the outcome of contextually and histori- Chung, 2006). Nevertheless, even though more re- cally specific processes like gentrification and search is required, understanding the differenti- renewal. ated impact of various sorting processes arguably Mapping neighbourhood changes revealed provides substantial new input for ongoing discus- distinctive geographies, which, in both cities, re- sions on urban socio-spatial change and to the lated to readily recognisable housing market body of knowledge on segregation overall. structures. Amsterdam’s concentric structure emerges with more wealthy areas in the centre ACKNOWLEDGEMENTS and at the outmost periphery, as does The Hague’s North–South divide. Indeed, trends in The research was supported by funding from the segregation in Amsterdam are more pronounced UK’s Economic and Social Research Council under when a coarser scale is used (Boterman & Van the Applied Quantitative Methods Network (AQMeN) Gent, 2015). At the same time, variations at the II project (research grant ES/K006460/1) as well as neighbourhood level can often be explained by funding from the Centre for Urban Studies, Univer- government interventions (e.g. privatisation, re- sity of Amsterdam. The authors wish to acknowl- newal, or new development) or by the presence edge the contribution to the initial preparation of of particular types of housing for specific popula- the dataset made by Annalies Teernstra. tions (e.g. concentrations of student housing or elderly homes, and, with residualisation continu- NOTES ing, social housing). We know that using a finer scale of neighbourhood units increases measures (1) We should note that some of these neighbourhoods of segregation, and we may speculate that may contribute to increased segregation if the smaller units here would reveal more variance, change in Delta is very high, but such cases are rare and are ignored here. and more ‘polarising’ and ‘reordering’. Overall, this broader geography suggests that a specific kind of long-term urban change is REFERENCES underway. Central cities and already affluent suburbs are becoming richer, while outer areas Andersen HS. 2011. 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Population, Space and Place. Published by John Wiley & Sons, Ltd. Popul. Space Place 2017; 23: e2013 DOI: 10.1002/psp
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