# Residential Relocations and Housing Changes Among Immigrants and Their Descendants: An Analysis of Longitudinal Register Data From France

Joseph Harrison, Isaure Delaporte, Ariane Pailhé, Hill Kulu

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Joseph Harrison, Isaure Delaporte, Ariane Pailhé, Hill Kulu. Residential Relocations and Housing Changes Among Immigrants and Their Descendants: An Analysis of Longitudinal Register Data From France. Population, Space and Place, 2025, 32 (1 (January 2026)), pp.1-15. 10.1002/psp.70163. hal-05391414

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RESEARCH ARTICLE

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# Residential Relocations and Housing Changes Among Immigrants and Their Descendants: An Analysis of Longitudinal Register Data From France

Joseph Harrison<fnref n="1" />,² ID | Isaure Delaporte³ | Ariane Pailhé⁴ | Hill Kulu<fnref n="1" />

**Correspondence:** Joseph Harrison (jh383@st-andrews.ac.uk)

**Received:** 18 June 2025 | **Revised:** 20 October 2025 | **Accepted:** 10 November 2025

**Funding:** This paper is part of the MigrantLife project that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 834103).

**Keywords:** descendants of immigrants | discrete-time logistic models | family | france | housing | immigrants | life-course events | residential mobility

## ABSTRACT

This paper investigates residential mobility and housing changes among immigrants, their descendants, and the native population, alongside the association between family and household characteristics and residential mobility. We apply discrete-time event history analysis to rich French administrative panel data covering the period 2012–2019. The results show distinct patterns of residential moves among migrant groups and generations. Immigrants from North Africa and Sub-Saharan Africa are less likely to move to homeownership and more likely to move to social renting compared to the native French population. By contrast, immigrants from Southeast Asia, Turkey, and Europe have a similar likelihood of moving to homeownership as the native population. We find little differences in the probability of moving to homeownership across migrant generations; however, the second generation appears less residentially mobile than the immigrant generation. The descendants of immigrants from North Africa and Sub-Saharan Africa are the least likely to move to homeownership and the most likely to move to social renting. This suggests that either structural barriers or cultural norms shape the mobility patterns of immigrants and their descendants in the same way. Finally, we observe similarities in the association between household characteristics and residential mobility for migrants, their descendants, and the native population. This suggests that life course events play a similar role in residential mobility across all population groups. For migrants and their descendants, those with low socioeconomic resources move less, suggesting that a lack of resources is a determinant of low mobility.

## 1 | Introduction

Patterns of residential mobility and housing changes provide important information on the integration of immigrants and ethnic minorities (Alba and Logan 1992; Bonvalet et al. 1995; Borjas 2002; Catney and Finney 2016). The classical theory of *assimilation* suggests that residential mobility and housing patterns of immigrants and natives will differ, but over time

they will become increasingly similar and indistinguishable between natives and the descendants of immigrants (Alba and Logan 1992; Myers and Lee 1998). In contrast, the *stratification* theory argues that the disparities in residential mobility and homeownership rates will persist between immigrants, their descendants, and the native population (Acolin 2019; Davidov and Weick 2011; Gobillon and Solignac 2020; McAvay 2018).

<footnote n="1">¹School of Geography and Sustainable Development, University of St Andrews, St Andrews, UK | ²School of Health and Society, University of Salford, Salford, UK | ³International Labour Organisation, Geneva, Switzerland | ⁴Institut national d'études démographiques (INED), Paris, France</footnote>

<footnote>This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.</footnote>
Research on residential mobility and housing in Europe finds that immigrants have higher mobility rates compared to natives, but that this difference disappears when socioeconomic characteristics are considered (Andersson 1996; Clark and Drever 2000; Rephann and Vencatasawmy 2000). Moreover, immigrants are less likely to own a home and more likely to be in rental accommodation (Acolin 2019; Davidov and Weick 2011; Drever and Clark 2002; Gobillon and Solignac 2020). Their housing quality is also poorer than that of the native population (Gobillon and Solignac 2020). Less is known about residential mobility and the housing conditions of immigrants' descendants. Studies show that differences in mobility and housing patterns between immigrants' descendants and natives are reduced, but ethnic minorities still have lower homeownership levels than the majority population (Acolin 2019; McAvay 2018).

Residential relocation and housing changes are often driven by changes in other life domains, particularly family changes and changes in socioeconomic circumstances (Dewilde 2008; Diaz-Serrano 2005; Feijten and Mulder 2005; Mikolai et al. 2020; Mikolai and Kulu 2018; Smits and Mulder 2008; Thomas and Mulder 2016). Previous research has reported differences in transitions to adulthood (de Valk and Billari 2007; Ferrari and Pailhé 2017; McAvay and Pailhé 2022), employment (Algan et al. 2010; Dustmann et al. 2010) and family patterns (Delaporte and Kulu 2022; Harrison et al. 2023; Liu and Kulu 2023; Mikolai and Kulu 2022; Pailhé 2015, 2017) of immigrants, their descendants, and the native population. Therefore, we can expect that their mobility and housing behaviour may respond differently to life events (Finney 2011; Geist and McManus 2008; Lacroix et al. 2024; Mulder and Wagner 1993). Immigrants and their descendants also face limited financial resources and exposure to job insecurity (Algan et al. 2010; Meurs et al. 2006), alongside discrimination in access to housing (Pan Ké Shon and Scodellaro 2016). Thus, understanding immigrants and their descendants' residential mobility and housing patterns, and their relationship to other life course domains will provide critical information on the economic and cultural integration of immigrant and ethnic minority populations.

In this paper, first, we investigate residential and housing changes among immigrants and their descendants by origin group. Second, we examine how household characteristics, namely the presence of children and disposable income, shape residential mobility and housing changes in different migrant groups. Finally, we analyse housing tenure trajectories for migrants and descendant groups. We use a large-scale panel data set from France known as the *Permanent Demographic Sample*. This data contains information on individuals' residential mobility as well as information on family changes and socioeconomic factors, allowing us to study their interactions. The analysis covers the period of 2012–2019, characterised by a sharp rise in house prices. We apply a series of discrete-time event history models, first, calculating the likelihood of experiencing a residential move each year by migrant generation and origin group. We then determine how the risk of a move varies by the number of children in the household and the equivalised household income. Finally, we estimate the probability of a move to and from different housing tenures. This

allows us to determine possible disparities in access to homeownership.

We develop previous research in the following ways. First, we distinguish between immigrants and their descendants. Distinguishing migrant generations is important to understand long-term trends, and most housing research focuses either on immigrants alone or ethnic minorities (without distinguishing migrant generations). Second, we investigate how residential mobility among immigrants and their descendants is related to other life course characteristics. Third, we use longitudinal register data from France, one of the main immigrant destination countries in Europe. Most research on Western Europe uses survey data, which suffer from small numbers of migrants and their descendants and attrition.

## 2 | Literature Review

### 2.1 | Residential Mobility and Housing

Previous literature has found that there is considerable heterogeneity in residential mobility rates across migrant groups and between migrant and native populations (Bonvalet et al. 1995; Clark and Drever 2000; Schündeln 2014). Some studies show that migrants and their descendants are more mobile than the natives due to housing precarity and disadvantage (Finney and Harries 2015). Other studies report lower mobility, which is explained by socioeconomic constraints and the disadvantage that migrants face regarding barriers to accessing the housing market. Conversely, experiences of immobility can represent stability and satisfaction with the local vicinity and material conditions (Fischer and Malmberg 2001). Understanding the relationship between socioeconomic and demographic status and residential outcomes for migrant groups is therefore important to unpicking the meaning of residential relocation for different population groups.

Many previous studies use housing tenure, particularly homeownership, to measure the housing position of immigrants and minority groups. Homeownership signals economic success and wealth accumulation and therefore represents material well-being. Becoming a homeowner can thus be considered an important step in the process of migrant integration (Alba and Logan 1992; Borjas 2002; Constant et al. 2009; Flippen 2001; Myers and Lee 1998). Previous research shows that immigrants are less likely to own their residences than the majority population. This has been found across many high-income high-immigration contexts (Davidov and Weick 2011; Gabriel and Rosenthal 2005; Gobillon and Solignac 2020; Haan 2007; Magnusson Turner and Hedman 2014; McAvay 2018; Shankley and Finney 2020; Zorlu and Mulder 2008). Some studies have also examined the use of social housing by immigrants (Andersen 2016; Fougère et al. 2013; Lévy-Vroelant 2014; Verdugo 2011, 2016). Housing conditions have also been examined, such as overcrowding, dwelling type, dwelling quality (Drever and Clark 2002; Gobillon and Solignac 2020; Verdugo 2016), and neighbourhood characteristics such as ethnic density (Bolt and van Kempen 2010; McAvay 2018). There are notable differences in homeownership and social
renting rates across migrant groups (Acolin 2019; Davidov and Weick 2011; Gobillon and Solignac 2020; Magnusson Turner and Hedman 2014; McAvay 2018). In France, immigrants of Sub-Saharan African origin display the lowest homeownership rates and the highest concentration in public housing (McAvay 2018). Immigrants from North Africa also have high rates of public housing and low rates of homeownership relative to other groups. In contrast, half of immigrants from Asia and Europe are homeowners, and their presence in public housing is small. Immigrants from Turkey hold an intermediate position, with a somewhat higher proportion of public housing tenants than homeowners. Similar findings also exist in Sweden, where Western European immigrants have homeownership levels similar to the natives, while immigrants from North Africa, Western Asia, and Sub-Saharan Africa have lower homeownership rates (Bråmå and Andersson 2010).

Differences between migrants and natives are expected to be reduced across migrant generations. With the descendants of immigrants expected to display mobility patterns that are similar to those of the native population (Alba and Nee 2003). While some studies support these expectations for certain origin groups, differential residential paths have been found by race and ethnicity (Alba and Logan 1993; South et al. 2005). This means that differences in residential mobility and homeownership rates persist between the descendants of immigrants and natives (Acolin 2019; Davidov and Weick 2011; Gobillon and Solignac 2020; McAvay 2018).

## 2.2 | Family Structure and Residential Mobility

Residential relocations and housing experiences are strongly linked with family dynamics: partnership changes and child-bearing (Holland 2012; Lauster and Fransson 2006; Mikolai et al. 2020; Smits and Mulder 2008; Wagner and Mulder 2015). Most literature on residential relocation and family dynamics has focused on the majority population; seldom have differences in residential mobility across immigrant generations looked at this relationship. Transitions to adulthood and leaving the parental home are life course events which often incorporate a residential relocation and often a union formation, previous research has shown differences between children of immigrants and natives in these processes (de Valk and Billari 2007; Ferrari and Pailhé 2017). In France, the children of immigrants stay significantly longer in the parental home. This is partly explained by sociocultural factors relating to family ties, but also difficulties in becoming economically self-sufficient (Ferrari and Pailhé 2017). There are differences across origin groups: while the entry into adulthood for children of immigrants from North Africa, especially women, is slower and less marked by union formation, children of immigrants from Southern Europe behave similarly to French natives (Ferrari and Pailhé 2017). In the Netherlands, the relationship between union formation and residential relocation is much weaker for Moroccan, Antillean, and especially Turkish young adults than for the Surinamese and the Dutch (de Valk and Billari 2007). Other studies examine differences between migrant and native populations in the triggering effect of family events on internal migration. Findings show that immigrants are less residentially mobile at the time of childbirth, compared to natives, in

Switzerland (Lacroix et al. 2020), which could be related to immigrants and minorities being socioeconomically disadvantaged and facing barriers to housing access.

## 2.3 | Socioeconomics and Residential Mobility

The lowest-income population generally displays higher rates of residential relocation, as they are more likely to live in unstable tenures. Those with higher incomes are also more likely to be homeowners – homeowners have a higher attachment to their place of residence, which decreases propensity and desire to move. Additionally, homeowners are discouraged from moving due to housing market volatility and associated costs of selling and buying housing (Helderman et al. 2004). Those in rented accommodation will (typically) have to move to enter homeownership if their income allows, which can explain some of the disparities across income lines. Relocation can be driven by education and employment transitions (Baron and Rapp 2019; Böheim and Taylor 2002; Boman 2011; Bonvalet and Brun 2002; Warner and Sharp 2016). Relatedly, experiencing job loss often leads to a move into housing of lower quality (Böheim and Taylor 2002). Moreover, it can lead to economic precarity, which creates a need to sell assets and, therefore, a move to a different tenure type, for example, from homeowner to rental. However, some studies suggest that unemployment periods decrease the propensity to move due to the financial barriers to moving that long-term unemployment can produce (Warner and Sharp 2016). Those with a higher income are likely to be the most satisfied with their working life and thus less likely to pursue relocation for new employment opportunities, which can lead to lower mobility in this group (Nowok et al. 2018).

Immigrants may have a different relationship between socioeconomic success and residential relocation. Due to the structural barriers in the housing and labour market, they may experience fewer employment changes which require moving. Moreover, moving may be less desired, even with socioeconomic success due to cultural norms and preferences to stay in certain areas. Alternatively, the structural barriers and discrimination in the labour market may necessitate more residential relocations to find opportunities. Some studies suggest that residential relocations are more often related to economic factors and employment for migrants than for natives (Gurak and Kritz 2000; Schündeln 2014). Natives also seem to more often opt for long-distance commuting, whereas immigrants are more likely to change residence (Fischer et al. 2000; Viry et al. 2010) – which could be associated with the higher likelihood of the native population to be homeowners and thus less inclined to relocate.

## 2.4 | The French Context

In France, there have been major developments in residential mobility over time (Bonvalet and Brun 2002). An increase in mobility was observed between 1954 and 1975 due to population growth and an active home ownership assistance policy. Due to a decline in new construction and less favourable economic conditions, between 1975 and 1999 mobility decreased at all geographical scales. Since then, residential mobility has
continued to further decline. Between 2009 and 2013, 27% of households living in France had changed housing, compared to 33% between 1997 and 2001. During the 2010s, the French population experienced a significant housing crisis, characterised by a marked increase in housing prices. Between 2010 and 2020, the cost of buying a house in France rose by 17%, far beyond the growth of salaries; rental costs in major urban areas such as Paris increased even more (IGEDD 2025). This period saw increasing housing inequalities, with those possessing the lowest incomes and lacking familial support encountering significant challenges in accessing adequate housing (Bugeja-Bloch et al. 2021). Compared to other European countries, France displays mobility rates that are lower than the Nordic countries and the United Kingdom, and higher than Germany, Southern Europe, and most Eastern European countries (Causa and Pichelmann 2020).

The housing system in France comprises three main tenure groups: owner occupiers, private renters, and social renters; the latter category being considered as a crucial element of housing supply in France (Lévy-Vroelant 2014). In 2021, the majority of households were in owner-occupied dwellings (58%), the remaining households were either private renters (25%) or social renters (18%) (Ministere de la Transition Ecologique et de la Cohesion des territoires 2022). The stock of owner-occupied housing grew in the 2000s driven by the construction of individual houses, it has since slowed down in the recent decade. By contrast, the share of private renters decreased significantly between 1985 and 2012. The share of social renting has also been steadily declining since a peak reached in 1997.

Homeowners and social and private renters differ in socio-demographic characteristics. The owner-occupiers are generally older, and their household is usually larger. Private renter households are relatively young and smaller in size than both homeowners and social renters (Bonvalet and Brun 2002; Ministere de la Transition Ecologique et de la Cohesion des territoires 2022). In France, access to social housing is subject to criteria related to income, family composition, and the presence of people with a disability (Fougère et al. 2013). Therefore, social housing is occupied by more socioeconomically deprived households.

France has a long history of immigration, beginning in the mid-19th century. Post-WWII, immigration was encouraged to aid in economic reconstruction, peaking between 1960 and 1974 with male labour migration. In 1974, France stopped most immigration, except for family reunification, but many immigrants stayed and were joined by their families. Despite restrictive policies, immigration continued, with the immigrant population reaching 11% of the population by 2021. Since immigration started a long time ago, the descendants of immigrants also represent a significant share of the adult population: 11% in 2021 (INSEE 2024). Immigrant origins shifted over time, from Southern Europe to North and Sub-Saharan Africa, Southeast Asia, and, more recently, other EU countries. Housing patterns differ according to origin (Dietrich-Ragon et al. 2023). Immigrants and their descendants from Sub-Saharan Africa and the Maghreb generally live in more modest housing conditions and are disproportionately represented in public housing compared to the majority population (Verdugo 2011). On average, they

have lower social and economic status, with lower incomes that push them towards more affordable housing. Migrants from Southern Europe and Southeast Asia have adopted a strategy of home ownership.

## 2.5 | Hypotheses

Based on previous research, we develop the following hypotheses. First, we expect, once controlled for socioeconomic characteristics, a lower likelihood of residential mobility for immigrants, followed by descendants of immigrants and then by the native population (H1). We expect that the presence of any children in a household will be associated with a higher risk of a move for natives and immigrants' descendants compared to immigrants (H2). Compared to natives and immigrants' descendants, immigrants experience more barriers to moving due to limited access to the housing market. Thus, we expect those with the highest equivalised disposable income to be the most mobile (H3a). However, we may also observe that lower socioeconomic resources are associated with precarity, which leads to higher spatial mobility compared to natives (H3b).

Regarding tenure, we expect immigrants to be less likely to move into owner-occupied dwellings and more likely to move into social or private renting compared to immigrants' descendants and natives (H4). Nevertheless, we expect to find some differences across origin groups (H5). Specifically, in line with prior research, we expect immigrants from North Africa and Sub-Saharan Africa and their descendants to exhibit the highest probability of moving to social renting and the lowest probability of moving to homeownership. Whilst immigrants from Southeast Asia and Europe, as well as their descendants, would have similar tenure moves to natives, with a lower probability of becoming social renters and a higher probability of becoming homeowners.

## 2.6 | Data

We use the *Permanent Demographic Sample* – or *Echantillon Démographique Permanent* (EDP)– which was developed by France's Institut National de la Statistique et des Etudes Economiques (INSEE). This longitudinal administrative database comprises information for all people born between the 2nd and 5th of January and in the first 4 days of April, July, and October taken from the civil records since 1968, along with exhaustive census information from 1968, 1975, 1982, 1990, and 1999. In addition, it contains information from annual fiscal reports from 2011 to 2019. In this study, we use information provided by the annual fiscal reports and from census records. The fiscal records contain yearly information on individual, household, and dwelling characteristics.

For the period 2011 to 2019, from the fiscal reports, we have yearly information on the municipality and neighbourhood (IRIS), commune, department, and region of residence, as well as information on the characteristics of the dwellings and whether it is owned or rented. Residential moves, which are the
outcome variable, can be identified as a change in the identification code of the dwelling or a change in the IRIS, municipality, department and/or region of residence between two consecutive years.

Our main independent variable is the migrant status of individuals. This is determined using information available in the census on the country of birth and citizenship at birth. We define immigrants (G1) as those born outside of France without French citizenship at birth.¹ We create the following categories representing the largest origin groups in France: North Africans, Sub-Saharan Africans, Southeast Asians, Turkish immigrants, Southern Europeans, Eastern Europeans, West Europeans, and others. We define the descendants of immigrants (G2) as individuals who were born in France but who have at least one parent identified as a migrant. This approach means that migrants who entered France as children are included in the G1 category; this was necessary as not all foreign-born sample members have information on year of arrival. Parental information is only recorded in the EDP if parents are also members. However, identifying more second-generation individuals in the EDP can be done by observing members as children in households in past censuses (McAvay 2018). We classify the descendants of immigrants into similar origin groups as their parents. If individuals have two foreign-born parents, we assign the origin of the mother. Finally, the native population is individuals born in France with French citizenship whose parents were also born in France with French citizenship.

Our sample is EDP members aged between 15 and 59 between the years 2012 and 2019. We analyse men and women together since most moves occur at the household level and thus affect both men and women equally; sex-stratified results yield similar patterns. Our final sample comprises 309,822 immigrants, 76,562 immigrants' descendants, and 1,518,066 French natives. The share of the second generation is lower than the share in the total population, which is partly explained by the younger age structure, which means fewer G2 are fiscal independents. Yet, we acknowledge there could be some misclassification. The census questions link children only to a household head; therefore, if their immigrant parent is not the reference person, they would not be captured. Additionally, some immigrant parents may declare being French at birth or born in France, as they were born in colonised parts of North Africa. Sensitivity analyses where the upper age limit is reduced to limit the impact of these issues did not alter results.

## 2.7 | Methodology

We apply discrete-time event-history analysis with clustered standard errors. Our first dependent variable is any residential move. Individuals started being 'at risk' of changing residence from 2012 and remained so until the end of 2019. Those who enter the panel in later years are 'at risk' from the year of their first completed fiscal report until the end of 2019. Once individuals have experienced a change in residence, they are at risk of experiencing a move the following year once again. All individuals are being observed from 2011² (or from their first fiscal year) to 2019, from the age of 15 to 59. Our baseline is age.

Censoring occurs when no tax record is found, which we can assume means emigration or death.

We estimate a series of models to investigate our hypotheses. First, we fit a discrete-time logistic regression (Allison 1982) to estimate the hazard of any residential move by origin group (Model 1). The model can be written as follows:

$$ \log\left(\frac{h_{it}}{1 - h_{it}}\right) = \alpha(t) + \beta'x_{it} + u_i, \quad (1) $$

where the subscript t stands for time (or calendar year); $h_t$ is the hazard of a move for individual i; $\alpha(t)$ is the baseline hazard fitted as a linear function of age elapsed since 2012 (or later) until 2019; and $x_t$ is a vector of time-constant and time-varying covariates measured at t. These variables include time-constant migrant origin (the main independent variable) and sex. Additionally, we control for age group, 15-24, 25-29, 30-34, 35-39, 40-49, and 50-59. We also include several time-varying variables. First, whether children are in the household with categories 'no children', '1 child', and '2+ children'; second, partnership status with categories: 'single', 'partnered'³ and 'separated/widowed'; third, initial housing tenure 'homeowner', 'social renter', 'private renter' and 'unknown'; fourth, we control for the area size that an individual currently resides in either 'rural', '2000-100,000', '100,000-2 million', and the 'Paris agglomerate region'; last, we control for the household's socioeconomic tercile in that year. This tercile is the equivalised disposable income of the household. It is derived by INSEE as the income of the household divided by the consumer units, such that it considers not only income but also household composition (INSEE 2021).

Using the same approach as Model 1, we further estimate models which predict the likelihood of experiencing a residential move, but add an interaction between the presence of children in the household and origin background (Model 2), and disposable income tercile and origin background (Model 3). Both Model 2 and 3 include all covariates previously mentioned. The final model (Model 4) uses a multinomial logistic model to identify which of the competing tenure options an individual moves to. This model is stratified by the original tenure to better identify transitions to different tenure states by different groups. This model includes the same covariates as Models 1-3. For this model, we exclude person-years from and to unknown tenure states, which account for fewer than 5% of residential relocations.

## 3 | Results

In total, 1,407,964 moves are observed between 2012 and 2019 (Table 1). Almost half of these moves were into the 'Private renter' tenure state, followed by homeownership, which is about one-third of moves, and the remainder moved into a social rented property. We present the results of the main explanatory variable, migrant origin and its interactions, in the main text. However, results from the full models, including all covariate coefficients, are in Tables S1 and S2. Coefficients follow expected patterns of moving being more prevalent in
<table><caption>TABLE 1 | Number and proportion of person-years and residential moves by categories of variables.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Person-years</th><th colspan="2">Moves</th></tr><tr><th>Number</th><th>%</th><th>Number</th><th>%</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td><td></td><td></td></tr><tr><td>Men</td><td>5,844,990</td><td>50.1</td><td>691,713</td><td>49.1</td></tr><tr><td>Women</td><td>5,815,889</td><td>49.9</td><td>716,251</td><td>50.9</td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td></tr><tr><td>15-24</td><td>1,419,659</td><td>12.2</td><td>215,683</td><td>15.3</td></tr><tr><td>25-29</td><td>1,438,618</td><td>12.3</td><td>259,563</td><td>18.4</td></tr><tr><td>30-34</td><td>1,456,270</td><td>12.5</td><td>188,589</td><td>13.4</td></tr><tr><td>35-39</td><td>3,075,945</td><td>26.4</td><td>262,202</td><td>18.6</td></tr><tr><td>40-49</td><td>2,945,354</td><td>25.3</td><td>163,694</td><td>11.6</td></tr><tr><td>50-59</td><td>1,419,659</td><td>12.2</td><td>215,683</td><td>15.3</td></tr><tr><td>Initial housing tenure</td><td></td><td></td><td></td><td></td></tr><tr><td>Homeowner</td><td>5,973,004</td><td>51.2</td><td>442,213</td><td>31.4</td></tr><tr><td>Social renter</td><td>1,463,336</td><td>12.5</td><td>196,241</td><td>13.9</td></tr><tr><td>Private renter</td><td>2,903,888</td><td>24.9</td><td>703,271</td><td>49.9</td></tr><tr><td>Unknown</td><td>1,320,651</td><td>11.3</td><td>66,239</td><td>4.7</td></tr><tr><td>Destination tenure</td><td></td><td></td><td></td><td></td></tr><tr><td>No move</td><td>10,252,915</td><td>87.9</td><td></td><td></td></tr><tr><td>Homeowner</td><td>473,527</td><td>4.1</td><td>473,527</td><td>33.6</td></tr><tr><td>Social renter</td><td>182,744</td><td>1.6</td><td>182,744</td><td>13.0</td></tr><tr><td>Private renter</td><td>692,117</td><td>5.9</td><td>692,117</td><td>49.2</td></tr><tr><td>Unknown</td><td>59,576</td><td>0.5</td><td>59,576</td><td>4.2</td></tr><tr><td>Partnership status</td><td></td><td></td><td></td><td></td></tr><tr><td>Single</td><td>5,053,920</td><td>43.3</td><td>766,993</td><td>54.5</td></tr><tr><td>Partnered</td><td>5,692,938</td><td>48.8</td><td>517,181</td><td>36.7</td></tr><tr><td>Separated</td><td>914,021</td><td>7.8</td><td>123,790</td><td>8.8</td></tr><tr><td>Children in household</td><td></td><td></td><td></td><td></td></tr><tr><td>No children</td><td>6,590,279</td><td>56.5</td><td>826,142</td><td>58.7</td></tr><tr><td>1 child</td><td>2,163,187</td><td>18.6</td><td>279,995</td><td>19.9</td></tr><tr><td>2+ children</td><td>2,907,413</td><td>24.9</td><td>301,827</td><td>21.4</td></tr><tr><td>Origin group</td><td></td><td></td><td></td><td></td></tr><tr><td>Native</td><td>9,484,007</td><td>81.3</td><td>1,167,830</td><td>82.9</td></tr><tr><td>G1 North Africa</td><td>541,847</td><td>4.6</td><td>59,348</td><td>4.2</td></tr><tr><td>G1 Sub-Saharan Africa</td><td>303,034</td><td>2.6</td><td>33,928</td><td>2.4</td></tr><tr><td>G1 Southeast Asia</td><td>50,156</td><td>0.4</td><td>4,163</td><td>0.3</td></tr><tr><td>G1 Turkey</td><td>114,420</td><td>1.0</td><td>10,227</td><td>0.7</td></tr><tr><td>G1 Southern Europe</td><td>189,944</td><td>1.6</td><td>17,455</td><td>1.2</td></tr><tr><td>G1 East Europe</td><td>121,043</td><td>1.0</td><td>13,297</td><td>0.9</td></tr><tr><td>G1 West Europe</td><td>122,235</td><td>1.0</td><td>11,393</td><td>0.8</td></tr><tr><td>G1 Other</td><td>258,426</td><td>2.2</td><td>27,692</td><td>2.0</td></tr><tr><td>G2 North Africa</td><td>215,858</td><td>1.9</td><td>28,786</td><td>2.0</td></tr><tr><td>G2 Sub-Saharan Africa</td><td>39,377</td><td>0.3</td><td>5201</td><td>0.4</td></tr><tr><td>G2 Southeast Asia</td><td>17,340</td><td>0.1</td><td>2370</td><td>0.2</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 | (Continued)</caption><thead><tr><th rowspan="2"></th><th colspan="2">Person-years</th><th colspan="2">Moves</th></tr><tr><th>Number</th><th>%</th><th>Number</th><th>%</th></tr></thead><tbody><tr><td>G2 Turkey</td><td>16,367</td><td>0.1</td><td>1807</td><td>0.1</td></tr><tr><td>G2 Southern Europe</td><td>119,314</td><td>1.0</td><td>15,395</td><td>1.1</td></tr><tr><td>G2 East Europe</td><td>13,028</td><td>0.1</td><td>1512</td><td>0.1</td></tr><tr><td>G2 West Europe</td><td>31,617</td><td>0.3</td><td>4670</td><td>0.3</td></tr><tr><td>G2 Other</td><td>22,866</td><td>0.2</td><td>2890</td><td>0.2</td></tr><tr><td>Disposable income tercile</td><td></td><td></td><td></td><td></td></tr><tr><td>Low</td><td>3,383,951</td><td>29.0</td><td>462,323</td><td>32.8</td></tr><tr><td>Medium</td><td>3,755,827</td><td>32.2</td><td>469,802</td><td>33.4</td></tr><tr><td>High</td><td>3,762,622</td><td>32.3</td><td>410,372</td><td>29.1</td></tr><tr><td>Unknown</td><td>758,479</td><td>6.5</td><td>65,467</td><td>4.6</td></tr><tr><td>Area size</td><td></td><td></td><td></td><td></td></tr><tr><td>Rural</td><td>2,463,959</td><td>21.1</td><td>245,476</td><td>17.4</td></tr><tr><td>2000–100,000 inhabitants</td><td>3,299,886</td><td>28.3</td><td>434,882</td><td>30.9</td></tr><tr><td>100,000–2 million inhabitants</td><td>3,276,137</td><td>28.1</td><td>452,886</td><td>32.2</td></tr><tr><td>Paris</td><td>1,906,764</td><td>16.4</td><td>215,158</td><td>15.3</td></tr><tr><td>Unknown</td><td>714,133</td><td>6.1</td><td>59,562</td><td>4.2</td></tr><tr><td>Total</td><td>11,660,879</td><td>100</td><td>1,407,964</td><td>100</td></tr></tbody></table>

Source: Permanent Demographic Sample, authors' own calculations.

early adulthood, slightly more common for women than men, more likely for those who are single, and least likely for those already in homeownership.

We present the results of the discrete-time event history models using predicted annual probabilities. These results can be interpreted as the annual probability of experiencing any residential move, all else being equal. Figure 1 presents the probability of a residential move by origin. Overall, the differences in magnitude between immigrants and natives may not appear to be of a substantive nature. However, over longer periods of time, the accumulation of these yearly differences in mobility between natives and the other groups will widen further and could become substantively significant. Among natives, the annual probability of a residential move is approximately 9.6%, which is significantly higher than all other groups except the G2 of Western European origin. Among immigrants, those born in Turkey have the lowest risk of moving over two percentage points lower than that of French natives. Other immigrant groups have a relatively similar risk of residential relocation to each other, with 8% and 9% chance each year. G2 Turkish and Sub-Saharan African individuals have a significantly lower risk of moving compared to G1 immigrants of the same background. The Western and Southern European G2 have a greater probability of residential relocation than their respective G1. North Africa, Southeast Asia, and Eastern European groups have non-significant differences between G1 and G2.

Our second model in Figure 2 shows differences in the probability of a residential move by the number of children in the household and origin. Among the native population and the first generation, we see evidence of a trend where no children

and one child are associated with a greater likelihood of moving compared to two or more children. All G1 groups, except Southeast Asians, who live in households with two or more children, have a significantly lower probability of moving compared to natives. They also experience larger gaps than natives in the likelihood of moving compared to those of the same origin with fewer children in the household. Generally, the moving rates for no children and one child are similar. Exceptions to this are immigrants from Southeast Asia, where there is no difference in the propensity for housing changes based on the number of children in the household, and also among Turkish G1 immigrants, who display a clear gradient of lower propensity for housing changes as the number of children in the household increases.

The G2 patterns are less similar to those of the natives. In G2 groups, we see more propensity for elevated mobility when exactly one child is present in the household. This is particularly clear for North African, Sub-Saharan African, Southeast Asian and South European G2, but can also be seen with less significance in other G2 groups. The exception is the G2 of Western European background, for whom there are no differences in the likelihood of moving by the number of children present in the household. Childless natives have a significantly higher probability of moving compared to other childless groups, the exception being Sub-Saharan African immigrants and the Western European G2. The G2 Turkish have especially low mobility, under 7%, regardless of the number of children in the household, far below all other G2 groups.

Next, we examine the association between household disposable income and residential relocation. We find a clear gradient
<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | Predicted annual probabilities of a residential move by origin group. The predicted probabilities are computed at the mean values of other covariables. Whiskers indicate 95% confidence intervals. Odds ratios for all covariates are presented in Table S1. Source: Permanent Demographic Sample, authors' own calculations.</figcaption></figure>

across most groups where those with higher incomes are associated with an increased probability of moving (Figure 3). One of the exceptions to this gradient is among natives for whom the lowest tercile is associated with a higher probability of moving compared to the middle; this pattern also holds for the G1 Southern European and G2 Southeast Asian. For G1 immigrants from North Africa, Sub-Saharan Africa, Turkey, Eastern Europe, and ‘Other’ origins, the gradient is very clear with large within-group differences between the richest and poorest. Those born in North Africa and Sub-Saharan Africa in the highest income tercile have a probability of moving that is even beyond that of the natives in that tercile. Similar patterns of high mobility amongst the richest are found among the second generation.

Much like the immigrant generation, North African, Sub-Saharan African, and Turkish G2 groups all show wide disparities in the probability of experiencing a residential move, with the highest rate amongst those with the highest socioeconomic success. Moreover, G2 North Africans and Turkish have a significantly higher probability of moving compared to the native population in the most prosperous tercile. Most G2 groups show a significantly lower likelihood of relocation compared to natives amongst the poorest tercile. This is particularly noticeable for G2 Sub-Saharan Africans and Southern Europeans, who, if in the poorest income tercile, have a less than 6.5% probability of

moving annually compared to close to 9.5% for the similar native population. Western European immigrants and their descendants, along with G1 Southern Europeans, are an exception to the norm with little variation between income terciles.

The final model investigates the tenure that individuals move to by origin group; the results are presented in Figure 4 (detailed results, including coefficients for covariates, are available on request). To identify moves which result in changes in tenure and moves between the same tenure type, the analysis is stratified. The horizontal panels refer to the tenure type before the move, with the coloured point and error bar showing the annual probability of moving to a given tenure type given that origin. For all groups, when in homeownership or private rental tenure, lateral moves to the same type of tenure are the most common, and moving into social housing is the rarest; this is expected given the relative scarcity of social housing. When in social housing, the most common move tends to be one that results in private rental tenure; however, this is not the case for North African, Sub-Saharan African and Turkish immigrants, who are significantly more likely to move from one social rental property to another. Compared to natives, North Africans and Sub-Saharan African immigrants have a higher probability of moving into a social rental property, regardless of whether the original tenure is social or private rental. For Turkish immigrants, their low overall mobility means that they have a lower
<figure><img src="image_4.png" /><figcaption>**FIGURE 2** | Predicted annual probabilities of a residential move by origin group and number of children. The predicted probabilities are computed at the mean values of other covariables. Whiskers indicate 95% confidence intervals. Natives are included in each panel for ease of comparison. Odds ratios for all covariates are presented in Table S2. Source: Permanent Demographic Sample, authors' own calculations.</figcaption></figure>

probability of moving from one social rental to another compared to the native population.

Amongst G1 immigrants from Europe, there is more similarity to the native population compared to immigrants from Africa. However, these groups have a lower probability of moving to homeownership from the rental sector compared to natives. This is unlike the G1 Southeast Asian group, who have a similar probability to the native population of moving to a homeownership from a private rental. Southeast Asian immigrants also have the highest probability of moving from social renting to homeownership, although this is an uncommon transition in general. Lateral moves in the private rental sector do not differ for immigrants from European and Southeast Asian origins compared to the native population, and moves within the social rental sector are also comparable.

The patterns described are similar between G1 and G2. North and sub-Saharan African G2s are more likely to move to the social renting sector and to move laterally within that sector. However, there is some generational convergence towards the native rate. Similarly, there are less pronounced differences in the transition to homeownership from private rentals; the probability is still lower for second-generation Africans compared to natives, but the gap is smaller. For the descendants of Turkish origin, we again observe a very low probability of moving laterally within the private rental sector. European and Southeast Asian G2 groups show very similar patterns to natives across all combinations of origin and destination tenure. Southern European and Southeast Asian G2s actually show a higher probability of transitioning into homeownership from the private rental sector compared to natives.
<figure><img src="image_5.png" /><figcaption>**FIGURE 3** | Predicted annual probabilities of a residential move by origin group and equivalised disposable income tercile. The predicted probabilities are computed at the mean values of other covariables. Whiskers indicate 95% confidence intervals. Natives are included in each panel for ease of comparison. Odds ratios for all covariates are presented in Table S2. Source: Permanent Demographic Sample, authors' own calculations.</figcaption></figure>

4 | Conclusion

In this paper, we examined residential mobility among immi-
grants, their descendants, and the native French population.
While most previous literature focuses on mobility and housing
with regard to factors such as location and segregation
(McAvay 2018), we instead studied residential mobility and
tenure changes. We also go beyond previous studies in France,
which have focussed on specific geographic areas (such as
Paris) or were conducted in a time when the age structure of
immigrants was younger, and their total number lower
(Bonvalet et al. 1995; Bonvalet and Brun 2002). Using rich
longitudinal register data from France, we followed individuals
over an 8-year period and analysed housing changes by differ-
ent characteristics, namely the presence of children in the
household and equivalised household income. We found that

differences between migrant origin groups and across genera-
tions exist in both housing tenure and mobility patterns.

Our results indicate first that the probability of experiencing a
residential move differs between migrant and native popula-
tions (Hypothesis 1). All G1 groups were less mobile than the
native population. Some migrant groups, such as those born in
North Africa, Sub-Saharan Africa, and Southeast Asia, were
closer to native levels of residential mobility compared to those
born in Turkey, who exhibited very low mobility. We find that
many G2 groups have lower mobility than immigrants and thus
even lower than the native population – this is a partial rejec-
tion of Hypothesis 1. An explanation for this could be delayed
patterns in leaving the parental home (Ferrari and Pailhé 2017;
McAvay and Pailhé 2022). Therefore, we observe more resi-
dential relocations for the native population in younger adult
<figure><img src="image_6.png" /><figcaption>**FIGURE 4** | Predicted annual probabilities of a residential move to different housing tenure types by origin group. The predicted probabilities are computed at the mean values of other covariables. Whiskers indicate 95% confidence intervals. We do not present the most common outcome, which is 'no move'. Natives are presented in both panels for ease of comparison. Source: Permanent Demographic Sample, authors' own calculations.</figcaption></figure>

ages, whereas many G2 groups are delaying this transition and therefore appearing less mobile. However, when we conducted sensitivity analyses which excluded younger ages (thereby lessening the influence of home leaving as an explanation) these patterns remain, indicating that these differences in mobility for the G2 may come from structural constraints or differences in preferences.

The analysis showed that moving was most prominent when individuals had no children or exactly one child. Our expectation was that the presence of children would lead to a higher likelihood of moving for natives and immigrants' descendants compared to immigrants (Hypothesis 2). This was partly supported: natives with children in the household had a higher risk of moving than similar immigrants; however, when comparing between generations, the probability of moving was even higher for G2 with two or more children present compared to the G1. However, for some G2 groups having no children saw lower propensities to move. This may be partly related to the period approach applied in this analysis. The second generation is more likely to be observed during life course stages where family formation, partner change and childbearing are most common. Thus, the elevated mobility for G2 with children in the household is a reaction to more pressing spatial needs and potential future intentions to grow their family (Kulu and

Steele 2013). Conversely, the immigrant generation is more likely to have completed their family formation and fertility and thus moves less. Controlling for age group should have lessened this potential explanation; therefore, it does not exclude the possibility of structural issues and barriers that are preventing relocation even when it is desired to meet spatial needs. The location of immigrant groups in dense urban areas with high rents, combined with less access to information on housing markets, discrimination in the housing market (Acolin 2019; Acolin et al. 2016) and in credit access (L'Horty et al. 2019) may also reduce mobility.

When analysing the differences between socioeconomic terciles and mobility, we found a clear gradient that higher mobility is associated with higher levels of income. This finding confirmed Hypothesis 3a. This gradient was consistent across nearly all immigrant groups, countering the idea of Hypothesis 3b that precarity amongst immigrants and descendants is a driver of higher mobility (Finney and Harries 2015). This is not to say that precarity is not a factor for those with low socioeconomic standing, but that it does not create mobility to the same degree as those in the highest tercile for immigrants. This trend helps us conclude that socioeconomic considerations are relevant for all groups when it comes to residential relocation. The widest within-group disparity between high and low socioeconomic
positions was found amongst North and Sub-Saharan African
groups, where the highest earners had a higher probability of
moving than even the natives in a similar position. This sug-
gests that the lower mobility found for these groups is driven by
socioeconomic constraints that the group faces, with a larger
proportion being in the poorer terciles (Algan et al. 2010; Meurs
et al. 2006). The few exceptions to the gradient are found
amongst natives, the Southeast Asian groups and Southern
European immigrants, where there is less heterogeneity
between different terciles and the lowest tercile has a higher
probability of moving than the middle tercile. Given that the
results in general do not suggest that precarity is driving a
disproportionate number of moves amongst the poorest, we
speculate that this finding reflects cultural capital and better
knowledge of housing practices that enable natives to overcome
socioeconomic barriers and move despite lacking resources. For
European and Southeast Asian groups in particular many of
the second generation have one French parent (Safi 2010).
Consequently, the aforementioned barriers are not affecting
them to the same extent as socioeconomically deprived immi-
grants and second generation in groups such as North Africans,
Sub-Saharan Africans and Turks, as they have advantages due
to their greater knowledge and experience less discrimination
than those from Africa or Turkey (Brinbaum et al. 2018).

Our expectations regarding the housing tenure that individuals
move to were largely met – we observed a lower probability of
moving into homeownership for immigrants (H4) and found dif-
ferences across origin groups regarding their tenure trajectories
(H5). High levels of social renting were observed for North and
Sub-Saharan African immigrants; this finding is in line with what
previous studies have documented (Gobillon and Solignac 2020;
Lévy-Vroelant 2014; McAvay 2018; Verdugo 2016). This persists to
their descendants and could be evidence of increasing place
stratification for these groups (Alba and Logan 1992, 1993; Pan Ké
Shon and Scodellaro 2016). By contrast, immigrants from South-
east Asia, Turkey, and Europe, as well as their descendants, have a
probability of becoming social renters like that of the native pop-
ulation and similar trajectories for being homeowners. These dif-
ferences may be explained by differences in cultural preferences,
which are often transmitted across generations of immigrants
(Huber and Schmidt 2022). These preferences may stem from
different values towards homeownership (Huber and
Schmidt 2022), which may stem from return intentions and
commitments to family in the country of origin (Owusu 1998).
Preferences could also be relevant to neighbourhood choice, which
might have specific tenure types within. For example, North
African and Sub-Saharan African G1 and G2 having a higher
likelihood of becoming social renters might be an option that
allows them to remain in, or move to, preferred neighbourhoods.
These neighbourhoods may be those with available cultural
amenities, community support systems, and proximity to co-
ethnics, which fosters a sense of belonging. The solidarity they can
find in these neighbourhoods, combined with the fewer resources
and constraints they face in accessing property or private housing,
may also contribute to the lower overall mobility amongst these
groups, as social housing scarcity will limit residential relocation,
as there is no available property to move to. Future research
should consider the geographic distribution of social housing to
assess how availability (or lack of) might influence housing
changes for different population groups.

The research here benefits from the richness of the EDP and
large sample sizes. However, some limitations exist. First, using
annual tax records as a source of information means we lose the
ability to look in detail at the ordering of events such as
childbearing on moving. We can only speculate on the antici-
pation of having further children or response to spatial pres-
sures as being the motivators of moving; the annual data means
this cannot be tested accurately. We implore further exploration
of data that can better identify triggers of residential relocation
and whether they differ across migrant groups and
generations. Second, annual data means that multiple moves in
a single year are not captured. This may represent a bias that
those in the most precarious of housing situations are con-
tributing less moves to the analysis than reality. Future research
should investigate alternative data to see if this affects a par-
ticular group of immigrants or descendants. Last, we rely on a
normative assumption that homeownership is the ideal state of
tenure; without more nuanced information about individual
preferences, we can only suggest that moving to and within the
social and private rental sectors is a sign of disadvantage for
some immigrant groups compared to the native population.

Nevertheless, our study has shown clearly that there are large
differences in the propensity to move between immigrant groups.
These differences are also sustained in the G2, particularly among
North African and Sub-Saharan African communities. Turkish
immigrants and their descendants also display unique patterns of
very low mobility. Factors of childbearing and socioeconomic
status influence all groups similarly. Barriers to residential relo-
cation among the most deprived are more apparent among those
from North and Sub-Saharan African backgrounds, especially
compared to the native population and those with a European
background. Our study of tenure highlights that access to
homeownership is more difficult to achieve for all immigrant
groups, who rely more on the rental sector. For African immi-
grants and their descendants, there is a higher likelihood of
moving into social rental properties compared to the native
population and other immigrant groups. We believe this reflects
the structural disadvantage that these groups face; however, dif-
ferent cultural values placed on homeownership may also have an
influence. Further research should unpick these nuances and
differences by analysing how residential mobility and tenure
trajectories correspond to desires and intentions.

Acknowledgements

We thank Dr. Haley McAvay for providing the codes to identify second-
generation immigrants. This paper is part of the MigrantLife project
that has received funding from the European Research Council (ERC)
under the European Union_s Horizon 2020 research and innovation
programme (Grant agreement No. 834103).

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data used in this study is provided by the Institut national de la
statistique et des études économiques (INSEE). Access to the Perma-
nent Demographic Sample is done via Centre d'Accès Sécurisé aux
Données (CASD).
Endnotes

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<footnote n="1">¹We exclude those born abroad with French citizenship. This category represents only 0.2% of the sample.</footnote>

<footnote n="2">²Individuals have been observed since 2011, but since there is no year prior to compare, the risk period can only begin in 2012.</footnote>

<footnote n="3">³The category 'partnered' includes individuals who are married, in a civil partnership, or cohabiting with someone with whom they file a joint tax record. It includes both first and higher order unions.</footnote>
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## Supporting Information

Additional supporting information can be found online in the Supporting Information section.

**Supplementary Table 2:** Odds Ratios of models predicting residential relocation with interactions of children in the household (Model A) and equivalised disposable income (Model B).