Those who leave: Out-migration and decentralisation of welfare beneficiaries in gentrified Paris

Abstract

Chinese

In major metropolitan areas, gentrification, financialisation and welfare retrenchment contribute to a severe housing crisis. Over the past 20 years, home price inflation and affordable housing shrinkage have been particularly acute in Paris. Such issues have been linked to the displacement of lower-income Parisians and the suburbanisation of poverty on a regional scale. In this article, we match disaggregated data from the Family Benefits Fund (CAF) with information on local housing markets, to empirically document these expulsionary processes. Our methodology is twofold. First, we investigate out-migration factors using logistic regressions. Second, we compare households’ changes in access to the city centre and urban resources following a move. Data show that social vulnerability is associated with a greater risk of leaving Paris and that housing welfare is playing a crucial role in mitigating this risk. Also, the higher the pressure on local housing markets, the more social inequalities determine mobility behaviour. Finally, beyond the effects of family structure, patterns of decentralisation are related to income level: less affluent households go farther from the city centre, job opportunities and services than higher-income households.

Keywords

decentralisation displacement exclusion gentrification housing out-migration poverty

Introduction

From the 2000s onwards, housing costs have soared in Ile-de-France.¹ In Paris and most of the nearby suburbs, homeownership has become inaccessible to the majority of tenants living in the region (Allard et al., 2020). Meanwhile, the share of income that these tenants spend on rents has risen steadily, and the amount of substandard housing has intensified (Fondation Abbé Pierre, 2021). In 2021, a 16-year waiting period was theoretically required to access social housing in Paris.² Affordable housing shortage in the French capital is part of a global urban crisis that many scholars consider as inherent to contemporary forms of neoliberal capitalism (Sassen, 2014; Walks and Soederberg, 2021; Wetzstein, 2017). In metropolitan areas, the combined effects of expanding gentrification (Lees, 2008), financialisation (Aalbers, 2017) and housing welfare retrenchment (Doling and Ronald, 2010) constrain the residential careers of disadvantaged households, who are at higher risk of being displaced or of living in substandard housing (Wyly et al., 2010). When these households relocate, their residential choices may be limited to the less desirable segments of the housing stock in the central districts and many may be forced to move further away from the urban core and its resources to access decent affordable housing (Hochstenbach and Musterd, 2018).

The article focuses on the ‘expulsionary processes’ (Sassen, 2014; Watt, 2018) affecting less affluent dwellers in Paris. Out-migration and the suburbanisation of lower-income Parisians have been important topics in scholarly work (Clerval, 2020; Vermeersch et al., 2018). However, the quantitative analysis of these processes was mainly carried out through comparisons of successive snapshots, using spatially aggregated census data (Clerval, 2020; Préteceille, 2007). As Van Criekingen (2009: 827) previously pointed out, such an approach ‘says much on the extent and trajectories of neighbourhood change but conversely little on the socio-spatial and housing trajectories of [its] protagonists’. Few studies have closely tracked the residential mobility of Parisians (Delage and Miot, 2019; Le Roux et al., 2020), mainly because data sources for doing so have long been scarce. Yet, the opening of desegregated census or administrative data creates new opportunities for research (Easton et al., 2020). This article is based on the French Family Benefits Fund’s data (designated as CAF³ data), which cover about 40% of the Parisian population, with information on the standard of living, the occupational statuses, the family structure and the successive addresses of beneficiary households.

Our research is targeted at two related questions:

RQ1: In the context of central Paris’s affordability crisis, which categories of households are more likely to leave the capital?

RQ2: How far from the centre do Parisians go when moving out and how do social inequalities influence this distance?

Therefore, we tackle expulsionary processes both as discrete events (RQ1) and as continuous variations in distance (RQ2). First, we use logistic regressions to explain out-migrations. This method allows us to control for usual residential mobility factors, such as the life course (Clark and Huang, 2003), and to identify what specifically depends on social inequalities. As the CAF data include the type of housing benefit received by households, this approach also makes it possible to discuss the effects of welfare policies implementation or retrenchment (Watt, 2018). Using Parisian real estate’s detailed geodata, we finally explore the ways that the models respond to local housing market pressure. Second, we compare how households’ accessibility to the city centre changes after relocating. In that case, we assume that centrality can be measured both geographically (distance to the city centre) and functionally (distance to jobs and urban resources).

Literature review

Paris in the global housing affordability crisis

Rising housing costs are a global urban issue (Wetzstein, 2017). Drawing on examples in Berlin, Dublin and Toronto, Walks and Soederberg (2021: 572) describe the housing affordability crisis as ‘a reality of contemporary capitalism’, characterised by the expansion of financialisation, debt-driven growth and austerity. The crisis is particularly acute in global cities (Sassen, 1991), where land and housing are at the core of accumulation strategies undertaken by institutional financial actors (Aalbers, 2017). Initially targeting properties in the valuable central sectors, these strategies have gradually extended to the suburbs (August and Walks, 2018), and to the rental sector (Wijburg et al., 2018), including short-term rentals (Wachsmuth and Weisler, 2018) and social housing (Aalbers et al., 2017). Housing accumulation strategies by private and corporate landlords have also strongly contributed to the residential precariousness of poorer households in lower-valued areas (Desmond, 2016), especially when combined with the retrenchment of housing welfare (Watt, 2018). At both national and local levels, austerity-driven social and urban policies have indeed fostered the affordability crisis (Peck, 2012; Walks, 2014).

In this picture, France is a special case. Among the variegated housing and welfare regimes, the country has long been characterised by a generalist approach (Lévy-Vroëlant and Tutin, 2016; Tammaru et al., 2016), that is by the large scope of its redistributive schemes. In 2021, 15.6% of primary residences were social housing, with two thirds of the population eligible for it and the law requiring a 25% quota of public accommodation in urban municipalities. The same year, about 20% of the population received housing allowances, among whom were 50% of all renters.⁴ Overall, tenants are quite protected on the rental market and law-enforced evictions are relatively low. An enforceable right to housing (DALO) requires the State to provide adequate housing for households that have been on the social housing waiting list for an abnormally long period, or for those who are threatened with eviction. The State is also held responsible for homelessness, with an enforceable right to shelter (DAHO). Nonetheless, recent research reports that France now follows a path towards asset-based welfare (Benites-Gambirazio and Bonneval, 2022; Le Goix et al., 2021). Subsidies and zero-interest loans support lower-income households’ access to homeownership, and tax incentives bolster private investments in the rental market, with both policies leading to the expansion of households’ debts (Wijburg, 2019). Meanwhile, austerity measures trigger the residualisation of housing assistance. A 2021 reform specifically restricted access to housing allowances, with many households at the beginning of their working life losing their rights. Cutbacks in social landlords’ funding also contributed to a decline in social housing construction, which began in 2016 and was aggravated after the Covid-19 crisis (Fondation Abbé Pierre, 2021). Moreover, the law now encourages social housing sales, which is likely to further strain this sector (Gimat et al., 2023).

In the Paris region, access to affordable housing is especially difficult. Unlike many metropolises, the real estate market did not reverse in the wake of the global financial crisis of 2007–2008, but rather continued to bubble (Le Goix et al., 2021). Limited at first, residential financialisation recently unfolded, putting significant pressure on certain segments of the Parisian market (Le Corre, 2019). By developing rent-seeking strategies, investors and households also took advantage of short-term rental (STR) platforms such as Airbnb. The sector boomed from the early 2010s, with Paris becoming the world’s top Airbnb destination in 2015. Between 2011 and 2017, 2% of Paris’s housing stock was converted into secondary homes, vacant units or STR (Trouillard and Tillet, 2021). With prices topping three times the standard rental price, the STR industry creates new forms of rent gaps and contributes to the lack of affordable housing and price inflation (Wachsmuth and Weisler, 2018). Between 2000 and 2022, the price-to-income ratio increased by a factor of 2 in Ile-de-France, and by a factor of 2.8 in Paris, compared to a factor of 1.5 in the rest of the country (IGEDD, 2023). In the capital, most private-sector tenants receiving housing subsidies spent more than 40% of their income on rent in 2021.⁵ Thus, social housing is becoming the only affordable option. Although its share has increased over the last decade (22% of principal residences in 2021), the gap has also widened between the eligible population and actual beneficiaries. In 2021, only 11,000 social housing units were allocated in Paris for 170,000 pending applications.⁶ Ultimately, lower-income dwellers face a higher risk of substandard housing or housing-related cost burdens. In 2020, about 1.2 million people were living in inadequate accommodation or without personal housing in the Paris region (Fondation Abbé Pierre, 2021). An additional 2.9 million people were experiencing at least one severe housing-related difficulty, such as unpaid rent, overcrowding, energy precariousness or excessive financial effort. A third of the region’s population was therefore directly suffering from the affordable housing crisis. To reduce the pressure on lower-income households, the City of Paris implemented private rent control in 2019, and regulated STR in 2017 (requiring registration and a maximum rental of 120 days per year for non-professionals). Since then, both measures have been adopted by several nearby municipalities. Compliance has, however, remained incomplete: over 30% of the rental offer exceeded the maximum allowed rent in Paris in 2020 (Fondation Abbé Pierre, 2021) and a majority of seasonal rentals were still unregistered in Ile-de-France (Trouillard and Tillet, 2021).

Patterns of socio-spatial change: In the Paris region, the remaking of a long-standing northeast–southwest divide

Social polarisation, gentrification and the suburbanisation of poverty are the main patterns of socio-spatial change associated with the housing affordability crisis in major metropolitan areas (Hochstenbach and Musterd, 2021; Sassen, 2014; Walks and Soederberg, 2021). The social polarisation of urban cores has been much debated since Sassen (1991) linked it to the rise of global cities. While Butler et al. (2008) have, on the contrary, emphasised the ‘professionalisation’ (i.e. the growth of the middle class) of large metropolitan areas, studies favouring an income-based approach or a finer breakdown of occupational categories (Crankshaw, 2017; May et al., 2007) have tended to confirm Sassen’s findings. Growing social inequalities among city dwellers ultimately appear to be correlated with increasing socio-spatial segregation, although the extent of this relation varies according to local contexts and welfare regimes (Tammaru et al., 2016).

Rising segregation on a metropolitan scale often coexists with temporary increases in the social diversity of some neighbourhoods as a result of gentrification (Hochstenbach and Musterd, 2018; Ribardière, 2016). Three empirical criteria can serve to identify this process of class transformation (Van Criekingen, 2021): capital flows targeting areas that used to attract little – Smith (1979) once qualified gentrification as ‘a back to the city movement by capital, not people’– a residential and commercial market upgrading of these areas and the dispossession of place to the detriment of their ordinary dwellers or users. Over the years, the expansion of housing financialisation as well as entrepreneurial and austerity-led urban policies have bolstered the spread of gentrification beyond city centres (Walks and Soederberg, 2021). In the inner suburbs, urban renewal has been a particularly powerful driver of social change (Davidson and Lees, 2010). In addition, research has also documented processes of regentrification or ‘super gentrification’ in some central districts of global cities (Lees, 2003).

More recently, the study of the suburbanisation of poverty has gained in importance (Cooke and Denton, 2015; Hochstenbach and Musterd, 2018). This refers to a shift in the geography of metropolitan poverty, from the urban cores towards the suburban areas. Kneebone and Berube (2013) notably found that, in the USA during the 2000s, poverty increased five times faster in the suburbs than in the inner cities. However, Cooke and Denton (2015) later emphasised that the phenomenon is far from common to all US metropolises, and that it is important to consider the social and morphological diversity of the suburbs. Taking into account some ambiguities and inconsistencies in defining suburbia, Kavanagh et al. (2016) argued that research should rather focus on poverty decentralisation (change in distance to the centre). Drawing on the cases of Amsterdam and Utrecht, Hochstenbach and Musterd (2021: 2) ultimately stressed that the suburbanisation of poverty is ‘often the flip side of expanding gentrification as affordable centrally located neighbourhoods disappear’.

Polarisation, gentrification and the suburbanisation of poverty have all contributed to reshaping the singular social geography of the Paris region. Since the city’s first urban sprawl dynamics, this geography has been characterised by a divide between the bourgeois western parts and the working-class north-eastern parts (Clerval, 2020). The persistent presence of the upper classes in central Paris, despite intense suburbanisation throughout the 20th century, is also a distinctive feature of the metropolis. As a result, the relevance of gentrification to describe socio-spatial change in the capital has been called into question (Préteceille, 2007). Nevertheless, Clerval (2020) has shown how this process has spread from the Beaux quartiers to the outer arrondissements, which were once working class. Triggered by massive urban renewal schemes in the 1960s, gentrification intensified with rent deregulation and subsequent housing booms in the 1980s and 2000s. In recent years, the Parisian arrondissements were still among the municipalities with the sharpest rise in the upper classes and the sharpest fall in the working classes in Ile-de-France (Clerval and Delage, 2019), reflecting the extent of gentrification and regentrification processes in the capital. Meanwhile, several dynamics have coexisted in the inner suburbs. Segregation has intensified in more affluent communities, mainly in the west (Préteceille, 2007). Certain working-class municipalities have been further impoverished, notably in Seine-Saint-Denis (Ribardière, 2016), one of the most deprived départements in France, north of Paris. However, working-class districts have shrunk overall, as gentrification has spread to many pericentral areas. Entrepreneurial strategies of urban regeneration in the municipalities of the former ‘red belt’ have been instrumental in this dynamic (Albecker and Fol, 2013). In some inner suburbs, as in the northeast of Paris (18th–20th arrondissements), the effects of gentrification have been partly limited by the size of the social housing stock, leading the process to combine with social polarisation (Ribardière, 2016). In the outer départements of Ile-de-France, the middle classes are overrepresented (Préteceille, 2007), but the socio-spatial differentiation remains significant: as the distance from the centre increases, so does the share of low- and moderate-income households (Ribardière, 2016). Overall, the northeast–southwest discontinuity has not disappeared, but it is increasingly coupled with a centre–periphery gradient.

From places to people

Whether gentrification and the related decline in housing affordability cause the displacement of less privileged dwellers, which is compelled mobility (Marcuse, 1985), has been much debated (Easton et al., 2020). In line with professionalisation, Hamnett (2003) argued that in London, the working classes have been ‘replaced’ (retirement, death, departure from the metropolitan area or upward social mobility) rather than displaced. Subsequent research has called these findings into question, highlighting instead the reshaping of the working classes in the metropolitan economy (May et al. 2007). Others emphasised that out-migrations from a metropolitan area are not antonymic to displacement; on the contrary, they can reveal the spread of gentrification on a city scale (Van Criekingen, 2009; Watt, 2018). By downplaying the impact of gentrification on vulnerable households, the replacement approach ultimately risks ignoring the experience of these dwellers and the class conflicts at work in the process (Slater, 2009). Recent discussions between Clerval (2020) and Hamnett (2021) attest to the persistence of this controversy. Also, displacement is not the only way in which the lack of housing affordability can affect the residential trajectories of the less privileged households. In order to stay put or to move in affluent or gentrifying areas, these dwellers may adopt coping strategies involving cutbacks to daily expenses or deteriorating housing conditions (Wyly et al., 2010). In addition, expanding gentrification can exclude households with limited resources, that is prevent them from accessing certain places or housing (Marcuse, 1985).

Paradoxically, research addressing the migratory dimension of social change in cities has remained limited (Easton et al., 2020; Van Criekingen, 2009). Methodological challenges contribute to explaining why the literature on segregation dynamics has focused on places rather than people. Data enabling individual tracking of out-migration have long been sparse. Nonetheless, the recent opening of several types of longitudinal data (e.g. register or administrative) has eased the way (Easton et al., 2020). Using a longitudinal demographic sample, Amat et al. (2021) have shown that, since the 1960s, the gentrification of Paris and its inner suburbs as a whole has had more to do with the filtering of residential mobility than with natural changes or social mobility. At a finer geographical level, examples from New York (Wyly et al., 2010) and Brussels (Van Criekingen, 2009) have emphasised the value of individual mobility monitoring for assessing the impact of gentrification and the affordable housing crisis on vulnerable households. In the Netherlands, Hochstenbach and Musterd (2018, 2021) have also documented the way that gentrification and the suburbanisation of poverty are materially linked through the mobility of lower-income dwellers.

In line with these studies, this article aims to contribute to the empirical documentation of the expulsionary logics in Paris. We adopt the latest wording after Watt (2018) and following Sassen’s (2014) analysis of the ‘new logics of expulsion’ associated with contemporary neoliberalism. Housing expulsionary logics refer to a lower ability of disadvantaged populations to stay in a given dwelling, tenure or place. Such processes combine with housing exclusionary logics (the inability to access a given dwelling, tenure or place) in explaining the socio-spatial filtering of residential mobility. In the article, two expulsionary logics are specifically addressed: the uneven risk of leaving Paris, and the decentralisation of vulnerable households following a move. The study follows on from qualitative research that has investigated the way that less affluent dwellers may be forced to arbitrate between exclusionary and expulsionary logics in Paris. For poor households unable to access better segments of the housing stock, coping with substandard housing may be the only way to ‘resist exile’ from Paris (Dietrich-Ragon, 2014). Such arbitration also applies to the middle class, although in less acute forms. Vermeersch et al. (2018) contrasted two groups: those who chose to remain in the centre, even if it meant keeping accommodation that had become inadequate (mainly too small), and those they call ‘the displaced’, who moved to the surrounding suburbs in order to improve their housing conditions. These two studies ultimately reveal the special status of residential mobility across the périphérique⁷ for many Parisians. Despite its small size and recent policies fostering the integration of adjacent municipalities (Enright, 2016), the capital remains materially, functionally and symbolically quite separate from the rest of the metropolis.

Research design, data and methodology

Hypotheses

H1a. Given the extent of gentrification and the housing affordability crisis in Paris, we assume that more vulnerable households are at a greater risk of leaving the capital.

H1b. However, the social housing stock is substantial in Paris, and vulnerable households are likely to receive housing subsidies: we assume that housing assistance can play an important role in mitigating the risk of out-migration.

H1c. Moreover, the local residential context can produce ‘compensatory, contradictory or reinforcing effects’⁸ on social status (Cayouette-Remblière and Ichou, 2019: 387). We expect inequalities in residential mobility to be more pronounced in affluent or gentrifying neighbourhoods.

H2. Considering that centre–periphery logics are increasingly important in the Paris region, we expect less affluent Parisians to go further away from the city centre and urban resources when relocating.

Family benefits fund data

CAF data are a transactional type of administrative data (Woollard, 2014), that is information is collected to provide a public service, the disbursal of benefits. In addition to family allowances, the CAF provides other benefits, such as minimum income, housing allowances and disabled adult allowance. To assess benefit entitlements and amounts, CAF routinely collects detailed information on beneficiaries (age, nationality, marital status and occupational status) and the covered households (family structure, standards of living from the tax authorities and location). In case of housing allowances, CAF also gathers data on the accommodation: tenure, surface area, comfort standards and price.

The advantages associated with such administrative data are many:

- Data provide a considerable level of geographical and socio-economic detail. The beneficiaries’ places of residence are available at the address level. The depth of the database allows social vulnerability to be assessed beyond the sole question of income and to include family, professional, housing, administrative or disability-related aspects.

- These up-to-date data make it possible to follow up beneficiaries over time. In this article, we compare beneficiaries’ addresses, family and occupational status at the end of 2018 and the end of 2019. Thus, we can identify the occurrence of at least one move during the year, as well as family and professional events such as birth, separation, new job or loss of job.

- It offers a good coverage of the population, and especially of more vulnerable people and families. In December 2018, 41% of all Parisians, and almost 80% of people under 20 years old, lived in a household receiving CAF benefits (Table 1).

Table 1.

All households versus households with CAF benefits, in Paris in 2018.

	All households	Households with CAF benefits
Household population
All	2,175,601	887,252 (40.8%)
Under 20 years old	411,525	323,641 (78.6%)
Household size
Average size	1.87	2.10
Household composition
Single	51.7%	55.4%
Couple	19.4%	4.0%
Couple with children	16.8%	27.0%
Single-parent family	8.4%	11.9%
Other	3.8%	1.7%
Poverty
Households below poverty threshold	15.2%	32.9%

Sources: Insee RP 2018, Caf Ile-de-France FR6 31 December 2018, Insee-DGFiP-Cnaf-Cnav-Ccmsa FiLoSoFi 2018.

However, CAF data also come with some usual limitations (Woollard, 2014):

- Beneficiaries are not a representative subsample of the general population. CAF data over-represent families and lower-income households (Table 1), since these are more likely to be eligible for benefits. On the contrary, couples without children are strongly underrepresented. Some of the most disadvantaged inhabitants of the city are also missing from the database: people without legal status of residence, and people either unable or unwilling to access social benefits. The representativeness also varies spatially. In Paris, the coverage rate is higher in the outer arrondissements, where most CAF beneficiaries are located (Figure 1).

- Data collection may suffer from discontinuities. All households included in the study received benefits in Paris at the end of 2018, but some of them were no longer beneficiaries on 31 December 2019. In such cases, the last information update occurred at write-off time. We, however, include these households, as residential mobility is a frequent cause of entitlement closure.

- Reproducibility is challenging. CAF data are subject to statistical and professional confidentiality. They are only accessible through a secure server, with the agreement of the CAF. Although the database is particularly accurate and well structured, it is also difficult to manage due to the volume and specificity of the information.

Figure 1.

Population with CAF benefits in Paris, December 2018.

Housing market contextual data

To characterise local housing markets, we link two individual-level data sources. First, we use the open-access land registry database (DVF, Demande de valeurs foncières) to build an accurate spatial representation of transactions in 2018 (based on the method detailed in Le Goix et al., 2021). From this, we compute two indicators; one is the transaction density, the other is the estimated average price/sqm. For the aggregation, we use a 200 m grid that the French statistical agency distributes. Second, we draw on geolocated data from the ‘Inside Airbnb’ project to measure the local density of STR, using the same grid.

We rely on these indicators to classify the local housing markets in Paris. By means of a linear model, we first estimate the general relation between the density of property transaction (from DVF) and the density of Airbnb accommodation in each cell of the 200 m grid (bottom-right graph in Figure 2). In doing so, we elaborate on the hypothesis that STR can put significant pressure on local markets (Shabrina et al., 2021), and that they both reveal and fuel (re-)gentrification processes (Wachsmuth and Weisler, 2018). We assume that where the STR density is particularly high (positive residuals) compared with standard market activity (approximated by transaction density), an abnormal number of properties are used or converted to STR and withdrawn from ordinary residential use. We interpret such a situation as the local market being pressured by rent-driven strategies on the part of landlords. Then, we also split the price distribution into two categories (above or below the median average price per cell, bottom-left graph in Figure 2). Finally, we tabulate price levels with the STR pressure linear model’s residuals, to describe local housing market pressure with four distinct groups.

Figure 2.

Property prices and STR pressure on local markets in Paris, 2018.

The groups show well-defined spatial patterns (Figure 2). Higher prices–higher STR pressure covers central arrondissements 1–11, that is the historic centre with major amenities for tourism. This class also extends to the north, including the Montmartre neighbourhood (18th arrondissement). Higher prices–lower STR pressure overlaps predominantly residential areas: the bourgeois Beaux quartiers, west of Paris (16th and 17th) and in early gentrified southern neighbourhoods (parts of the 15th, 14th and 13th). The lower prices–higher STR pressure type is scarce, but its location requires attention. Across the boundaries of the 10th, 11th, 18th, 19th and 20th arrondissements, this category matches the front of advanced gentrification or re-gentrification (Clerval, 2020). Finally, outer arrondissements are mostly characterised by relatively lower prices and lower STR pressure. Gentrification in these districts is more recent and not omnipresent.

Estimating out-migration risk and measuring decentralisation

Mobility factors act in a systemic way, which is why scholarly work on residential behaviours considers logit as a standard method (Eluru et al., 2009; Wyly et al., 2010). This makes it possible to control the interactions between different variables and to isolate the specific effect of a parameter. We approximate the odds of leaving Paris using binomial logistic regressions. Based on research about life course and mobility (Clark and Huang, 2003), we first use a general explanatory model of out-migration (model 1) that includes as independent variables the age of the beneficiaries, their family and occupational status at the beginning of the year and the events that led to a change in these situations during the year. Housing tenure stands as another major driver of housing consumption but is available in CAF data only for the recipients of housing allowances. In 2018, 60% of CAF beneficiaries in Paris received housing allowances. Therefore, we add a variable that distinguishes beneficiaries without housing allowances, tenants in the private sector with housing allowances, tenants in the social sector with housing allowances, first-time homebuyers with housing allowances and people with other types of tenure (including student housing, health centres and shelters) receiving housing allowances. We also include the time elapsed since the last change of address (as of December 2018), to estimate the duration of stay in the accommodation and to control for this explanatory factor of mobility.

In addition to family and professional aspects such as single parenthood and unemployment, we introduce four more variables related to different forms of social vulnerability. First, we distinguish lower-income (below the poverty threshold,⁹ 33% of Parisian beneficiaries in December 2018), moderate-income (below 120% of the national median income, 26% of the beneficiaries) and higher-income households (17% of the beneficiaries). The income of the remaining 24% remains unknown, as CAF considers the information on their resources as insufficient (e.g. students receiving housing allowances only or people over 65 years of age). As a reminder, the thresholds are relative to the recipient population, a sample significantly less privileged than the Parisian population as a whole.¹⁰ We also consider capital income that we split into three categories (no capital income, under and over € 6000 per year). Then, as being a foreigner can impede access to employment and administrative procedures, and because of frequent discrimination in housing and employment markets (Pan Ké Shon, 2010), we consider nationality (French or foreign nationality) as another variable linked to social vulnerability. Disability is the last dimension we include, by distinguishing the beneficiaries of the disabled adult allowance from the others. This remains a superficial approach to disability, as previous studies have shown that its relationship with mobility depends on its nature and evolution (Speare et al., 1991), but it allows us to estimate a general effect of disability and to control for this parameter which is overrepresented among the CAF beneficiaries. Finally, to explore how mobility inequalities vary according to the local housing context, we reproduce this general model for each type of market tension (models 2a–2d).

Finally, we use georeferenced data on the recipients’ former and new addresses to estimate households’ decentralisation following a move within the Paris region limits (H2). The analysis is performed with different decentralisation indicators (see Supplemental Material for details and a reproducible code). First, we compute the change in Euclidian distance to the centre (arbitrarily, Paris City Hall). We then estimate the variation in functional centrality. This second approach aims to provide a better account of partially overlapping advantages associated with centrality. It allows us to go beyond symbolic aspects and to consider resources located in sub-centres. By doing so, we can observe how Parisians’ mobility contributes to inequalities in access to urban resources in the Paris region (Belton Chevallier et al., 2018; Korsu and Wenglenski, 2010). We use three indicators:

- The change in potentially accessible jobs. This is estimated using census data at a municipal aggregate level and Stewart’s (1941) potentials method of interpolation.

- The change in the average distance to upper-range services and facilities (e.g. high schools, hospitals and cinemas). We compute this with geolocation data available in the open-source Permanent database of facilities (Insee)

- The change in accessibility to public transportation. The score is based on bus stops and transit stations available within walking distance from home. Transport facilities geolocation derives from Ile-de-France Mobilités open-source data.

Results and discussion

The uneven risk of leaving Paris (H1a)

Table 2 presents the models’ results and metrics.¹¹ Model 1 shows that leaving Paris is a behaviour that correlates with life course and family status, like other types of residential mobility (Clark and Huang, 2003). The likelihood of leaving the capital city decreases with age and duration of stay in the current accommodation. In contrast, the odds increase substantially if a family event occurs, whether the household gets smaller (i.e. separation, children leaving home or a death) or increases in size (i.e. pairing, birth or adoption). Yet, data show some singular configurations regarding the family structure: childless couples are more likely to stay in Paris compared to couples with children, although this category is often found to be the least mobile in other studies (Eluru et al., 2009). This can be explained by a specific combination of constraints and preferences, including the shortage and unaffordability of large dwellings in Paris and families’ desire for single homeownership.

Table 2.

Leave Paris, model results and metrics.

	1. Leave Paris	2a. From lower prices–lower pressure areas	2b. From lower prices–higher pressure areas	2c. From higher prices–lower pressure areas	2d. From higher prices–higher pressure areas
(Intercept)	0.397***	0.490***	0.411***	0.389***	0.280***
Age (decade)	0.585***	0.581***	0.583***	0.563***	0.606***
Foreign nationality	1.026	1.053**	0.984	0.945	1.020
Disability	0.585***	0.527***	0.591***	0.610***	0.725***
Family composition	Reference: single
Couple	0.613***	0.652***	0.648***	0.591***	0.521***
Single-parent family	0.814***	0.852***	0.887	0.753***	0.706***
Couple with children	0.918***	0.927**	1.022	0.849**	0.881**
Pairing	2.977***	3.185***	2.735***	2.885***	2.632***
Newborn or adoption	1.540***	1.399***	1.586***	1.630***	1.935***
Decrease in hh. size	7.851***	7.078***	7.214***	9.059***	9.532***
Income	Reference: higher income
Moderate	1.244***	1.045	1.336***	1.409***	1.453***
Lower	1.186***	1.015	1.255**	1.293***	1.386***
Capital income	Reference: no capital income
Under €6000 per year	0.879***	0.925**	0.896	0.886***	0.804***
Over €6000 per year	0.549***	0.645***	0.580**	0.529***	0.534***
Activity	Reference: employed beneficiary
Unemployed	1.118***	1.018	1.206**	1.195***	1.295***
Student	1.163***	1.117***	1.109	1.257***	1.184***
Inactive	1.026	1.000	1.037	1.078	1.075**
Professional event	Reference: no professional change
Became employed	1.026	1.046	0.930	0.980	1.028
Became unemployed	1.740***	1.572***	1.493***	2.240***	1.983***
Became student	1.514***	1.393***	1.719**	1.719***	1.497***
Became inactive	1.434***	1.378***	0.934	1.857***	1.561***
Tenure (housing allowance recipients)	Reference: no housing allowances
Private rental	0.991	1.045**	1.002	1.006	0.891***
Social rental	0.202***	0.216***	0.205***	0.149***	0.166***
Access to ownership	0.707**	0.599**	1.061	1.579	0.369**
Other	1.095**	1.149***	0.817	1.180	1.009
Minimal duration of stay	Reference: from 3 to 10 years of residence
Less than a year	1.293***	1.304***	1.260***	1.212***	1.360***
From 1 to 3 years	1.297***	1.292***	1.114	1.332***	1.363***
Over 10 years	0.428***	0.435***	0.421***	0.393***	0.443***
Metrics
N	307,728	162,199	26,411	52,112	67,006
Events	20,370	10,643	1716	3496	4515
McKelvey Zavoina pseudo-r²	0.35	0.37	0.36	0.35	0.31
Nagelkerke pseudo-r²	0.17	0.18	0.16	0.15	0.15

Scope: Beneficiary households living in Paris on 31 December 2018, excluding unknown income, unknown professional activity and ‘other’ family composition.

Sources: Caf Ile-de-France FR6 31 December 2018 and 2019, DVF Etalab 2017, Inside Airbnb 2018. Made with R packages stats 4.2.1 and DescTools 0.99.45.

Note: Odds ratios are indicated. *p < 0.1. **p < 0.05. ***p < 0.01.

Results also confirm the hypothesis that more vulnerable households are more likely to leave Paris. Compared with higher-income recipients, lower- and moderate-income beneficiaries’ out-migration is 19% and 25% more probable. Differences are greater with respect to capital income, as earning more than € 6000 in annual capital income yields 80% more chance of staying in Paris than without capital income. Employed beneficiaries are also more likely to stay in the capital than unemployed and student ones. Eventually, becoming unemployed is the occupational change that most strongly correlates with out-migration. In contrast, there is no significant difference between recipients who started a job during the year and those whose situation remained stable.

Nevertheless, the effects of vulnerability factors are not homogeneous. For instance, single-parent families are less likely to leave Paris than couples with children. Several reasons can explain this. Individual housing in the suburbs is mostly unaffordable for single-parent families. They may prioritise central locations with better accessibility and resources. We also found no significant effect for beneficiaries with foreign nationality. Finally, households receiving the disabled adult allowance are much more likely to stay in Paris than other recipients. This can relate to the more difficult mobility of this category of household but also to the greater density of disability-orientated services in the capital. Overall, our results emphasise the need for studies specifically addressing these different types of vulnerability.

The mitigating effect of social housing (H1b)

Housing tenure has a significant effect on the likelihood of leaving Paris. Social housing tenants with housing allowances are five times less likely to leave the capital than beneficiaries without housing allowances (mostly private renters and owners). An important finding is therefore that social housing mitigates the effect of social vulnerability and constitutes a refuge option for lower-income households. First-time homebuyers with housing allowances are also less likely to leave, which is consistent with the greater residential stability that we usually observe for owners (Eluru et al., 2009). In contrast, tenants in private rentals with housing allowances do not show any significant difference from recipients without housing allowances.

The differentiated effects of social inequalities across market types (H1c)

Comparing models 2a to 2d (Table 2), we find a recurring pattern: social inequalities are linked to greater inequalities in mobility in neighbourhoods with higher market pressure. Whereas lower and moderate income show no significant differences with higher income in lower price–lower STR pressure areas, differences between these groups are greater in expensive areas than in the general model. Capital income also improves stability to a greater extent in these places. For the same price category, STR pressure reinforces the gaps associated with income. In addition, those who became unemployed in 2019 contrast more strongly with beneficiaries whose situation remained stable in higher price neighbourhoods. Eventually, most of the effects associated with family structure and events do increase with prices and STR pressure. In short, the more expensive or under pressure the market, the more difficult it is for vulnerable households to settle durably in a dwelling that matches their budget, their family situation and future changes in comparison to other beneficiaries living in the same type of neighbourhood. When they ultimately move, it is harder for them to relocate within Paris. The stabilisation effect of social housing is also relatively stronger in more expensive neighbourhoods.

The decentralisation of less affluent households (H2)

Our analysis above shows that family structure is a preeminent factor in explaining mobility. Consequently, we tabulate decentralisation metrics according to the households’ family structure¹² and income level (Figure 3). The results show that beneficiaries all tend to go farther from Paris, job centres, facilities and transit corridors when they move within the urban region’s limits. This was expected, since all moves analysed originate from the centre. It is also consistent with a trend towards urban sprawl in the Paris region (Delage and Miot, 2019). However, distance matters: geographical decentralisation and changes in access to urban resources vary greatly with income level and family composition.

Figure 3.

Decentralisation of moving beneficiaries, by income level, in 2019: (a) Change in distance from Paris City Hall (km), (b) mean distance from City Hall before and after moving, by income level, (c) potential accessible jobs loss (k), (d) change in average distance to upper-range services (m) and (e) loss in access to public transportation (pts).

In terms of Euclidian distance (Figure 3a), the decentralisation of higher-income households following a move is lower than that for other income categories, regardless of family structure. The differences between moderate and lower incomes depend on the family composition. Moderate-income singles and couples with children move slightly further away than lower-income ones. The opposite holds true for single-parent families. Overall, couples with children are the ones that tend to move the farthest away and single-parent families the least far. The combination of families’ search for larger accommodation, social housing’s more central location and the centre–periphery variation in real estate prices probably best explains these differences. Overall, the expulsionary process that less affluent households experience becomes clear when analysing dwellings’ average position before and after a move (Figure 3b).

Figures 3c–e show how this expulsionary process correlates with a loss of accessibility to urban resources, emphasising the social justice issues at stake. The results for the variations in accessible jobs (Figure 3c) and distance to upper-range services (Figure 3d) are consistent with Figure 3a: higher-income households suffer less from a loss in accessibility, and within each income group, couples with children are the ones who move the farthest away from the resources. Access to public transportation, however, gives a different perspective (Figure 3e), as family structure yields prevailing effects. For couples with children, moving to larger dwellings implies a big loss of accessibility to public transportation, regardless of income differences. However, we can assume that the consequences are far from the same for all couples with children, since higher-income ones rely much less on public transportation (Belton Chevallier et al., 2018). By contrast, income remains a prevailing factor of discrimination between single-parent families: again, we can assume that keeping a good level of accessibility is of greater importance to them. Whatever the index, lower-income single parents are systematically in the worst situation. By the end of 2018, 94% of these households were headed by women, showing that gender is an additional dimension of vulnerability.

Conclusions

Elaborating from the literature on the affordable housing crisis and gentrification in Paris (Clerval, 2020; Vermeersch et al., 2018), we assumed that more vulnerable households face expulsionary processes in the capital. To track residential mobility at the individual level and take account of different local housing market configurations, we linked data on Parisian beneficiaries of the Family Benefits Fund with information about the property market and STR. We investigated the occurrence of expulsionary processes in two ways: we first compared the odds of beneficiaries leaving Paris and then measured their geographic and functional decentralisation following a move.

Our hypotheses are mainly verified. Among the social vulnerability dimensions considered, lower income, no capital income and unemployment are associated with higher risks of leaving Paris. Differences between social categories are also stronger in high priced and high STR market pressure neighbourhoods. As remediation to inequalities, social housing plays an important role: it greatly increases the chances of staying in Paris, especially where the local market is under higher pressure. This finding underlines the way that housing welfare programmes can help reduce households’ housing constraints and mitigate income inequality’s spatial patterns. However, we can assume that this effect is double-edged, as it may also be a symptom of the crisis. As the price gap widens between the private and social sectors, it becomes more difficult to exit social housing, which in turn reduces the rotation within this sector. In the end, many tenants might be locked in their residential careers (Driant, 2015).

Subsequently, we found that less affluent households go farther away from the city centre when they move. Euclidian distance from the centre turns out to be a good proxy for access to resources, as these inequalities are reproduced with respect to access to employment and facilities. Most of the differences also apply to access to transportation, but couples with children stand out in this case, as the effect of income is low among them. Whereas poverty is particularly discriminating for single-parent families, for the other family configurations, beneficiaries with moderate income (i.e. the lower middle class within the general population) are often the ones who go the farthest away. They also have the highest risk of leaving Paris. Thus, our findings also point to the social polarisation of the centre of the Paris region. They are consistent with previous research that emphasised the greater suburbanisation of moderate-income homebuyers (Delage and Miot, 2019; Gobillon et al., 2022).

Out-migration from Paris is a symbolic and much-debated case (Vermeersch et al., 2018), but expulsionary processes are also likely to occur within Paris or on a regional scale. Complementary analyses should especially consider the sectoral dimension of mobility filtering in order to clarify the way that it contributes to the social fragmentation of the metropolis (Ribardière, 2016). In addition, most of our interpretative assumptions point to the need for surveys investigating households’ reasons for moving. These are particularly necessary to identify displacement (Watt, 2018), which is compelled mobility, and to estimate its contribution to expulsionary processes.

Supplemental Material

sj-docx-1-usj-10.1177_00420980231224640 – Supplemental material for Those who leave: Out-migration and decentralisation of welfare beneficiaries in gentrified Paris

Supplemental material, sj-docx-1-usj-10.1177_00420980231224640 for Those who leave: Out-migration and decentralisation of welfare beneficiaries in gentrified Paris by Luc Guibard and Renaud Le Goix in Urban Studies

Footnotes

Acknowledgements

The CAF Beneficiaries database is subject to statistical and professional confidentiality. It was made available by CTRAD (Cellule Technique de Réflexion et d’Aide á la Décision des Caisses d’allocations familiales d’Ile-de-France), under a research MOU with Université Paris Cité.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article was prepared under the ANR WIsDHoM project Wealth Inequalities and the Dynamics of Housing Markets (ANR-18-CE41-0004). Additional funding is from Fondation Palladio, Bourses Palladio 2021 and Institut Universitaire de France, Senior Grant, 2019–2024.

ORCID iDs

Luc Guibard

Renaud Le Goix

Supplemental material

Supplemental material for this article is available online.

Notes

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