Housing tenure and subjective poverty among young European adults: The role of rent regulation

Abstract

Poverty has spread in Europe over the last decade, becoming a central issue in the political debate. Alongside objective measures of poverty, assessing the level of subjective poverty, especially among young adults, is important because of the consequences that feeling poor can have on household fertility decisions, consumption, and investment in human capital. Objective and subjective poverty do not fully overlap, and the sense of insecurity can lead to a feeling of not being able to make ends meet. For renters and mortgaged homeowners, housing costs can be a significant burden, and the risk of not being able to pay the rent or mortgage installments can affect young adults’ wellbeing and feeling of poverty. Our study investigates the relationship between tenure status and subjective poverty for households of young independent adults aged 18-34 living in 24 European countries, assessing whether rent regulation plays a role in influencing this association. Using micro-level data from EU-SILC and macro-level data on rent regulation, we estimate multilevel linear regression models with a three-level random effects specification: young household respondents (Level 1) are nested in country waves (Level 2), which in turn are nested within countries (Level 3). Controlling for income level and housing costs, we found that being a tenant or a mortgaged homeowner increases the probability of economic hardship compared to being an outright homeowner. By offering affordable options, rental housing policies can also reduce subjective poverty among young people who are not direct beneficiaries of these policies.

Keywords

tenure status subjective poverty youth rent regulation housing Europe

Introduction

The political debate of the last few decades has recognized the spread of poverty as a serious problem, and young people are at the most risk of poverty throughout Europe. Most poverty studies focus on objective measures of income or wealth poverty to identify situations of economic disadvantage. However, the subjective perception of financial hardship can be equally important in identifying the target population of anti-poverty policies (Hagenaars and De Vos 1988; Ravallion 2014).

Subjective poverty entails feeling that the economic resources needed to maintain a minimum standard of living are lacking and is often defined as the inability to meet monthly expenses in the days leading up to the payment of a salary, pension, or allowance, which has been called the “fourth week syndrome.”

Objective and subjective poverty do not always fully overlap. Many studies have shown that some households feel poor even though they are not, while other households do not feel poor despite being classified as such (Anand et al., 2021; Diener et al., 1993; Strengmann-Kuhn 2000).

The subjective dimension of poverty is overlooked in research (Chevalier 2023). This is a serious shortcoming because subjective poverty is linked to individuals’ wellbeing and negatively affects several aspects of life, from consumption to social participation, and from health care to fertility choices. Subjective poverty, rather that the objective measure of poverty and material deprivation, affects people’s ability to imagine their future and thus their ability to make choices for their lives (Papuchon and Duvoux 2019). For this reason, when examining young adults, analysing the causes of their feelings of poverty is even more pertinent than considering their actual levels of income and consumption, because young people are more likely to feel poor, especially during times of economic crisis (Chzhen 2017). Therefore, social policies should be concerned with this phenomenon and the mechanisms that influence the feeling of being poor in general and for younger households in particular.

Previous research has shown the relevance of insecurity in determining subjective poverty: people employed on a fixed-term contract or, more generally, those who face unstable earnings tend to feel poorer than those with an equal but stable income (Filandri et al., 2020). Looking at the housing market, previous literature on the relationship between tenure status and perception of poverty has shown that European homeowners are less likely than tenants to perceive themselves as living in poverty (Watson and Webb 2009). The mechanism is again related to both the sense of security and life satisfaction. On the one hand, perceptional security refers to the sense of security that people have over their housing such that, for example, they may feel insecure if they are concerned about their tenancy not being renewed even if this does not eventuate (Hulse and Haffner 2014; Hulse and Milligan 2014). On the other hand, not only do homeowners have a stronger sense of ontological security than tenants, and a greater sense of order and continuity in their life experiences, also due to their residential stability (Acolin 2022), but homeownership is also seen as a form of economic security for the future, a way to accumulate assets. This reduces the feeling of poverty, buffering potential financial risks and improving the financial outlook. Homeowners’ greater life satisfaction also reduces the risk of suffering from subjective poverty (Deidda 2015; Elsinga and Hoekstra 2005; Peng et al., 2020; Watson and Webb 2009).

However, the relationship between homeownership and subjective poverty may also be the reverse, especially for young owners with a mortgage. The first few years of a mortgage payment can be a heavy burden for young households, as a high mortgage payment can directly affect the level of consumption, forcing them to reduce spending on other goods and services to maintain regular mortgage payments and thus avoid losing their home. A recent study showed that mortgage-holding owners are significantly less satisfied with their income than renters, highlighting that the negative effects of the mortgage may cancel out the positive effects of homeownership (Will and Renz 2023). Since housing costs represent the most important and direct impact of housing on poverty, only homeowners without a mortgage can be protected from the increase in housing costs resulting from rising rents and mortgage interest rates (Tunstall et al., 2013). Both renters and mortgaged owners thus suffer from housing insecurity, which in turn might affect their subjective poverty¹ with consequences for the attainment of housing independence and for the fragmentation and reversibility of their housing outcomes and living arrangements (McKee, 2012).

Rental housing policy can contribute to addressing subjective poverty through more restrictive rent regulation measures (DeLuca and Rosen 2022). On the one hand, rent control is a restrictive measure for regulating the housing market to protect tenants from rising rents, which can have a major impact on the population’s purchasing power (Kholodilin and Kohl 2023). On the other hand, social housing, even though it is an increasingly residual policy, can provide the poorest households with an affordable alternative to the private market. It should be noted that the demand for private rental housing has risen among all young people, not just those on low incomes. Between 2008 and 2017, the proportion of young Europeans aged 18-24 and 25-34 living in private rentals increased from 60% to 69% and from 32% to 42%, respectively². Renting is not only an option for the transition to homeownership, but also one of the few available for those who either seek to meet their mobility or employment aspirations, or experience material deprivation and social exclusion (Filandri and Bertolini 2016).

This study investigates the relationship between tenure status and subjective poverty among young adults in European countries, assessing whether and how rent regulation policies play a role in influencing this association. Our hypothesis is that rent regulation directly affects tenants’ subjective poverty, as they are aware of the protection provided by the policy. However, these measures may also indirectly give mortgaged homeowners the feeling that they have an affordable way out if they lose their home because they are unable to meet their mortgage payments. This highlights the importance and symbolic value of policies for household wellbeing, as the value assigned to a measure targeting a limited group of people has a wider range of consequences.

Our analyses are based on pooled cross-sectional microdata from the European Union Statistics on Income and Living Conditions (EU-SILC, 2009-2013-2017) on households of independent young people aged 18-34, as well as on institutional data on housing and policies.

Our study contributes to the scant literature on young adults’ subjective poverty by investigating differences between European countries and institutional settings (Chevalier 2023). First, it provides empirical evidence of the role of housing tenure for young people’s subjective poverty at individual and country levels. Second, by focusing on young people’s ability to make ends meet, it sheds light on the importance of evaluating the effect of policies on subjective dimensions. While housing rental policies influence housing costs and wealth accumulation, their impact on subjective perceptions of economic hardship can affect households’ well-being more comprehensively.

Theoretical framework and previous research

Subjective poverty, tenure status, and young adults

Poverty has mainly been investigated using objective monetary indicators. Studies on subjective poverty that investigate individuals’ perceptions of their own situation in relation to poverty are less common (Kuivalainen 2014).

Subjective poverty is defined as the feeling of not having enough money and is assessed using individuals’ evaluation of having “sufficient” or “insufficient” income. This evaluation is clearly related to the ability to “make ends meet,” which typically includes monetary aspects (Hagenaars and De Vos 1988). Subjective poverty is thus a measure of self-assessed economic strain (Nolan and Whelan 2000)³ that entails a subjective perception of what constitutes necessary expenditure. This necessary expenditure may vary depending on individual and household characteristics, as well as the socio-economic context in which the household lives (Buttler, 2013; Strengmann-Kuhn, 2000; Van Praag et al., 1980).

Subjective poverty has several negative consequences. It is detrimental to several dimensions of individuals’ well-being and can reduce consumption levels regardless of actual household income level (Filandri et al., 2020; Guagnano et al., 2016; Ravallion 2014). In addition, the experience of poverty can lead to psychological stress, depression and loneliness, which reduce individuals’ happiness, quality of life and health, hindering individuals’ social participation and integration, and jeopardizing future expectations and life satisfaction (Achdut et al., 2021; Chang et al., 2020). Subjective poverty also reduce political participation, social interaction and fertility, increases marital conflict and instable relations and lead to intimate partner violence (French and Vigne 2019; Vignoli et al., 2020). These consequences of subjective poverty are critical for the entire population, but particularly for young people (Achdut et al., 2021; Chevalier 2023).

The causes of subjective poverty have not been investigated in depth. One of the main determinants is clearly the level of income (Buttler 2013). However, not all low-income households perceive their economic situation as problematic, just as some households may feel poor despite having an income above the objective poverty line.

Insecurity is a factor that can lead to subjective poverty. The concept of insecurity is very broad and can be linked to various dimensions⁴. Financial vulnerability resulting from income instability—often associated with the spread of temporary work—has been shown to affect subjective poverty even for households above the poverty line (Filandri et al., 2020). Another significant dimension of uncertainty is related to housing tenure. Indeed, position in the housing market is considered central to household economic security (Arundel and Ronald 2021). Homeownership is in general seen as a secure and stable housing arrangement, while renting is perceived as inherently more precarious (Clair et al., 2019). Security of renting is linked to the tenants’ ability to afford the rent, both initially and as their tenancy progresses (Hulse and Milligan 2014). Moreover, homeownership is generally associated with better living conditions, a greater ability to accumulate wealth, and higher subjective wellbeing and satisfaction than renting (Deidda 2015; Elsinga and Hoekstra 2005; Peng et al., 2020; Watson and Webb 2009; Will and Renz 2023). Mortgaged homeowners benefit only partially from housing security, as they have to accumulate savings to secure mortgage repayments against a loss of income (Lersch and Dewilde 2018). Tenants are also at risk in the event of income loss, but may have more flexibility in adjusting their housing costs (Lersch and Dewilde 2018). A distinction on the perceived security of rented households is needed. If anyone can have access to the private rental market social housing has limited access. In the literature, private renting is considered less secure when assessed in terms of lease arrangements and rent regulation, although the literature on social housing has assisted in developing a more nuanced understanding of different types of rental systems (Hulse and Haffner 2014, 573). It is also important to note that young adults entering social housing can face ongoing precarity. The introduction of short- and fixed-term tenancies in social housing limits duration for those who can gain access undermining security (Fitzpatrick and Pawson 2014).

Housing tenure has a slightly different meaning for young people. First of all, the expectations generally associated with living independently are linked to a sense of wellbeing (Gaiser 1999). This is true regardless of tenure status, which may not correspond to having one’s own sufficient income. Residential independence does not rule out financial strain, and it is often difficult to identify young adult’s wellbeing by considering only their housing arrangements (e.g. Chevalier 2023; Dewilde and Flynn 2021; McKee 2012).

First, homeownership is perceived as a desirable and stable housing option, but it is unaffordable for many young adults: more so than for the population as a whole. Outright homeownership is mainly the result of inheritance or gift, and only in such cases does it provide security of tenure and a protection against increasing housing costs. Second, for young homeowners with a mortgage, debt has a more pronounced negative effect than for the overall population because of labor market instability and low wages (Lersch and Dewilde 2015). It has been shown that young homeowners with a mortgage are aware that there is a considerable risk of losing the home if installments are not paid (Fuster et al., 2019). In addition, there is a strong belief among young people that homeownership is a financial investment. This compounds their frustrations, as they perceive renting as boosting their landlord’s investment rather than investing in their own property (Hoolachan et al., 2017). The expression “mortgaged homeownership is like mortgaging your life” (Fuster et al., 2019) sums up the experience of some young people who feel it can reduce their quality of life (forcing them to work long hours, and sometimes moonlighting) as well as bringing risks relating to variable interest rates (Fuster et al., 2019).

Third, living in rented accommodation is often the result of constraints on access to housing. For low-income young adults, renting appears to be the only affordable option for living independently. However, young adults’ access to the rental market might also be a lifestyle choice in line with their preferences for freedom, professional careers and mobility (Filandri and Bertolini 2016).

The value of tenure status—both in material terms of protection from feeling poor and in intangible terms of wellbeing—varies among young people. These differences are predictable across contexts and reflect the historically complex economic and social processes that have led to the current configuration of housing markets. In a society where aspirations for homeownership remain strong, renting is often seen as a secondary choice. Many young renters feel a lack of control created a sense of flux and uncertainty, destabilizing their living situation, and challenging their ability to feel safe, secure and settled (McKee et al., 2020). In a country where outright homeownership is prevalent, mortgage homeownership is presented as dangerous, imbued with a risk of losing one’s house. Renting is seen as a cautious choice, largely due to the flexibility it offers, which is crucial for adapting to the unstable life prospects faced by young people (Fuster et al., 2019). Finally, in societies where homeownership is less widespread, ownership is seen as a ‘bourgeois’ conception of life that would not match young people’ ideals. Typical for the German situation, homeownership was perceived by many younger adults as inflexible and requiring a commitment which would restrict future choices in terms of residential locations, occupational careers and family life (Lennartz and Helbrecht 2018).

The scant literature on the relationship between tenure and subjective poverty has shown the protective role of homeownership from feeling poor (Watson and Webb 2009). To the best of our knowledge, only a few previous studies have distinguished between outright and mortgaged homeowners and considered financial satisfaction rather than subjective poverty. Most of them are single-country cases (for the United States, Germany, and Australia) and all find a negative effect of mortgage debt on income satisfaction (Ong ViforJ et al., 2023; Tharp et al., 2020; Will and Renz 2023). None, however, focus specifically on young people, nor do they consider the effect of housing policies.

The role of housing policy

Though often considered the wobbly pillar under the welfare state (Torgersen 1987), housing policies have a key role among social protection instruments and in promoting household wellbeing, as well as in the economic and social regulation of the housing market. They can be defined as the set of all measures applied by a government to affect housing market outcomes in order to provide housing security (DeLuca and Rosen 2022; Kholodilin 2020), resulting in better overall housing quality at lower cost.

Rent control⁵ is one of the more effective ways of intervening in the housing market and consists in protecting tenants from rent increases. While economists tend to label more strict rent regulation as inefficient when it comes to profitability for landlords, stricter regulation is clearly effective in terms of improving access to decent and affordable housing (Dewilde 2022), in particular by lowering rents and rental expenditure (Kholodilin and Kohl 2023).

When housing becomes scarce, rents rise quickly. As rent is one of the most important components of household expenditure, increases in rent have a strong impact on the population’s purchasing power (Kholodilin 2020). Rent control policy can specify the level of rents in general for both new and existing rental contracts, or it can define exceptions where regulation cannot be applied (Kettunen and Ruonavaara 2021).

Rent regulations have been classified into three categories of rent control, or generations (Kholodilin 2020). First-generation rent controls were introduced during World War I and remained in force until 1970. These rules involved hard control through rent freezes, which meant that rents were fixed at a certain level. Second-generation rent control is a more relaxed form of regulation. It allows for controlled rent increases, usually distinguishing between new and existing contracts. In addition, it is often combined with a set of additional regulations concerning tenant security, housing quality, landlord-tenant relations, and conversions, improvements, and maintenance of premises. Third-generation rent control limits rent increases during a tenancy but allow unrestricted rent increases between tenancies. In other words, it sets a market rent at the beginning of a new tenancy, taking the potential impact of in-tenancy controls into account, but limits increase during the tenancy.

Rent control has both advantages and disadvantages (Kholodilin 2020). On the positive side, rent control makes rental housing more affordable for tenants and has some anti-inflationary effects. It also promotes the social integration of disadvantaged renters and discourages renters’ residential mobility: tenants remain in the same accommodation for longer, increasing their tenure security and satisfaction⁶. On the debit side, rent control can be considered to have adverse effects on the housing market. In the event of a positive demand shock, rent control delays the transition to a new equilibrium. In addition, restrictions on rent levels and increases might have a negative impact on rental returns, making the real estate sector less attractive for property owners. Instead of investing in housing, they may turn to commercial property or equities. But if less money is invested in housing, both the quantity and quality of housing will decline. Another consequence is that landlords might carry out repairs less frequently to reduce costs and increase the return on their housing investment. Lastly, restrictions on rent increases not only decrease landlords’ income, but also reduce tax revenues for the government.

An additional form of intervention in the housing market is social housing, which is seen as a stimulating policy that aims to make housing more affordable by increasing the overall supply (Kholodilin 2020). In Europe, the most common definition of social housing focuses on the social rental sector, which includes subsidized housing rented at below-market rates and allocated administratively (Poggio and Whitehead 2017). It typically targets specific groups, such as low-income and vulnerable households (Scanlon et al., 2014). However, there are significant differences between countries in how supply and demand subsidies are managed within national housing systems (Pittini 2019).

First, the residualisation of social rented housing, that is the reduction of expenditure in public housing, targeted especially at the most economically vulnerable groups, is particularly significant across Europe, although it varies from country to country. As suggested in previous studies (Angel 2023), Austria, France and Switzerland report the lowest degree of residualisation. At the same time, in the UK, “de-residualisation” has increased over the last decades. Tunstall (2023) suggests a distinction between two definitions of residualisation: the processual and the static. Indeed, the process of residualisation can be moderate and public housing systems can remain heterogeneous, non-exclusive and non-targeted, following a more generalist approach to social housing allocation.

Second, there is a tradeoff between targeted allocation and maintaining a social mix in the sector. The more targeted the allocation of social rented housing, the more difficult it becomes to maintain a certain level of social diversity in social housing estates.

Third, public policy has increasingly supported forms of social rented housing midway between traditional social housing and the private rental market, especially for young adults, rather than only subsidizing the construction of new social rented housing.

Research questions and hypotheses

The study focuses on young households in European countries. The comparative perspective casts light on whether similar patterns in the relationship between tenure status and subjective poverty exist in different contexts, taking the varying impact of rent regulation policies into account.

Two main research questions are addressed: (a) what is the relationship between tenure status and subjective poverty among young adults in European countries? (b) does rent regulation influence the association between housing tenure status and subjective poverty?

Regarding the first question, we expect that in all European countries outright homeownership is negatively associated with subjective poverty compared to mortgaged homeownership and rented accommodation. For mortgaged homeowners and renters, we expect that—when controlling for income level and housing cost burden—the difference disappears, as they both feel they are in an insecure tenure status.

Regarding the second research question, our hypothesis is that rent regulation affects the ability of tenants to make ends meet, as they feel protected by state intervention. Furthermore, we expect that rent regulation policy will give young mortgaged householders the feeling of having an affordable way out should they lose their home because they are unable to meet their mortgage payments. Indeed, uncertainty may affect subjective poverty beyond the actual economic situation (Filandri et al., 2020).

Data, variables, and method

Micro-level data

The analyses are based on European Survey on Income and Living Conditions (EU-SILC) data. EU-SILC provides detailed and comparable information on income, social exclusion, housing conditions and living conditions of individuals and households. We pool data from three waves (2009-2013-2017) for 28 European countries including Norway, Switzerland, Iceland, and United Kingdom, according to the availability of data for the macro-level variables.⁷ The three survey waves were chosen in view of the EU-SILC’s rotating design, where a quarter of the sample is replaced each wave, and each household is interviewed for up to 4 years. Hence, no households in our sample were surveyed more than once (Dewilde 2022).

We select young-independent households, that is, households whose reference person is the highest earner aged between 18 and 34.⁸ The final sample consists of 28 countries, 84 country-waves and 60,390 households (see Table A1 in Appendix for details).

The main dependent variable is subjective poverty, measured using an indicator of the ability to make ends meet. We treat the variable as continuous on a six-point scale ranging from 0 (households that make ends meet “very easily” to 5 (those that make ends meet “with great difficulty”).⁹ The key independent variable is housing tenure status classified into three categories: outright homeowners, mortgaged homeowners, and renters. The category of renters includes those paying rents at prevailing or market rates (private) and those paying at reduced rates (social). As suggested in previous studies (e.g. Dewilde 2022), renters in the private segment (as coded by EU-SILC) might include renters who receive housing allowances or pay rent at reduced prices. This is particularly relevant in countries such as Denmark, Netherlands and Sweden that historically have a strictly regulated rental market (Angel 2023), where there is no clear distinction between private and social renters and all are thus classified in the social renting category¹⁰.

We consider several control variables at the household- and reference person-level: household income quintiles,¹¹ housing affordability problems,¹² household composition (couple vs single), number of dependent children (none, one child, two children, three or more children), age, employment status (employed, unemployed, inactive, student), and educational level (low, medium, high). The descriptive statistics for the individual- and household-level variables are presented in Table A2 in the Appendix.

Macro-level data

The main independent variable at country-level is the indicator of rental market control, measured as the level of protection from rent increases provided to renters. The indicator for rent control is a composite index based on the average of six binary items relating to specific policies¹³ (Kholodilin 2020): real rent freeze, nominal rent freeze, rent level control, intertenancy decontrol, specific rent decontrol, and other specific rent recontrol. It is treated as a numerical variable ranging between 0 and 1, with 0 denoting the absence of rent control and 1 corresponding to stricter rent control.

In addition, we use one indicator that reflects at the macro-level the housing context influencing the availability and affordability of housing options for young people: percentage of households in social renting (Dewilde 2022). This is an indicator of affordable social housing provided by the state to low-income households, measured on the share of total households paying rents at reduced prices¹⁴ computed from the EU-SILC dataset. As Angel (2023) and Dewilde (2022) suggest, here we consider all renters in Denmark, Netherlands, and Sweden as social renters.

To consider both variables simultaneously we construct a third measure which is a composite index related to the overall extent of rental market regulation based on the combination of the two indicators discussed above.¹⁵

Three contextual-level variables are included as control variables: inequality measured by the Gini coefficient computed on the equivalized disposable income, level of economic development measured by GDP per capita, and the outright homeownership rate. The latter is used as an indicator of housing commodification, which can be related to the reduction of state involvement in housing provision and, at the same time, to the level of private market participation in determining housing outcomes. Given our hierarchical data structure, all contextual indicators measured at country-wave level have been standardized.¹⁶

Empirical strategy

Given the hierarchical structure of the data, several multilevel linear regression models with a three-level random effects specification were estimated. Young-household respondents (Level 1) are nested in country-waves (Level 2), which in turn are nested within countries (Level 3). This nesting structure, where countries are observed at several points in time (i.e., time series cross-sectional data), involves both a cross-sectional and a longitudinal association between time-varying macro-level variables (housing policies/market characteristics) and outcome (subjective poverty). To estimate the random effects for both country-waves and country, an appropriate multilevel modeling technique is required to reduce standard error underestimation (Schmidt-Catran and Fairbrother 2016).

Accordingly, we define the between- and within-components of the macro-variables that differentiate the societal contextual effects. The first component represents the country-average of a macro-level variable over all waves, which captures between-country differences (B). The second component measures the difference between the variable and the country-average for each wave, which captures within-country variations (W). Hence, all contextual-level variables are included in the models in two forms, according to the components we have just described. In addition, we included two survey-wave fixed-effects dummies to account for potential and simultaneous time trends (see Table A3 in the Appendix for details on data structure).

We conduct the analyses in three steps. In the first step, we explored how subjective poverty is associated with housing tenure status controlling for socio-demographic and contextual variables (Models 1-2 in Table 2). In the second step, we examine the influence of housing policies and housing market characteristics on subjective poverty among renters, outright and mortgaged homeowners (Models 3-5 in Table 2). In the third step, we test whether country housing policies and market characteristics affect the association between housing tenure status and subjective poverty through cross-level interactions (Models 6-8 in Table 2). The random slopes for housing tenure status are included at Level 2 and 3 so that the effect on subjective poverty of being either a renter or a homeowner could vary across country and waves net of other controls. Given the complexity of the data structure, the models are presented using the stepwise approach, keeping the number of macro-level variables as small as possible. Full models are available in Section C in the Appendix (Tables C1-C2). In the Appendix, we also present several robustness checks and sensitivity analyses (for details, see Section D).

Results

Descriptive analysis

Table 1 shows the descriptive statistics of young independent households in Europe, by country and by household income quintile. Comparing European countries reveals a highly heterogeneous picture. Average subjective poverty among young people is widespread in some countries (e.g., Greece and Hungary), while it is less common in others (e.g., Netherlands and Sweden).

Table 1.

Subjective poverty, housing tenure, rent control, and social renting in Europe by country and household income quintiles.

	Subjective poverty	Young adults’ homeownership (%)	Young adults’ mortgaged-homeownership (%)	Young adults’ renting (%)	Rent control indicator	Households in social renting (%)	N. of young independent households
Country
Austria	2.2	26.7	17.1	73.3	0.16	9.9	2176
Belgium	2.4	47.6	43.4	52.4	0.16	7.4	2332
Czech Republic	2.9	60.1	28.3	39.9	0.07	7.2	2341
Denmark	1.9	38.4	32.4	61.3	0.77	37.5	1843
Estonia	2.6	71.8	32.2	28.2	0.51	3.2	1468
Finland	1.9	39.5	36.4	60.5	0.16	15.0	4923
France	2.7	33.8	30.2	66.2	0.27	15.4	3984
Germany	1.8	15.8	8.1	84.2	0.38	5.6	3539
Greece	3.8	33.2	7.5	66.8	0.01	0.4	2239
Hungary	3.6	74.4	29.0	25.5	0.00	3.4	1870
Iceland	2.3	55.8	52.6	44.1	0.00	8.5	1265
Ireland	3.1	35.8	31.4	64.2	0.33	12.5	1499
Italy	3.2	54.2	25.2	45.8	0.16	4.9	3086
Latvia	3.2	71.4	20.1	28.6	0.16	4.4	1327
Lithuania	3.0	86.4	25.2	13.6	0.16	1.7	646
Luxembourg	2.0	51.7	48.8	48.3	0.66	3.7	1526
Malta	2.9	84.9	59.5	15.0	0.35	14.6	873
Netherlands	1.5	50.7	48.2	49.3	0.66	33.9	3604
Norway	1.8	58.3	52.2	41.7	0.16	4.2	2745
Poland	2.7	72.8	18.9	27.2	0.33	1.5	2193
Portugal	3.2	56.5	42.9	43.5	0.27	5.9	1060
Romania	3.2	87.9	3.1	12.1	0.33	1.0	1096
Slovakia	3.0	74.6	29.0	25.4	0.16	0.4	979
Slovenia	2.9	73.9	24.2	26.0	0.00	3.4	978
Spain	3.0	60.3	48.7	39.7	0.33	3.0	2475
Sweden	1.6	45.5	41.5	54.5	0.71	34.7	2955
Switzerland	1.8	8.9	5.8	91.1	0.33	4.7	2629
United Kingdom	2.7	40.8	38.0	59.2	0.16	16.0	2739
Income quintiles
I	2.9	26.9	12.6	73.0	-	-	-
II	2.7	42.2	27.6	57.7	-	-	-
III	2.4	52.9	36.0	47.0	-	-	-
IV	2.1	60.6	42.5	39.3	-	-	-
V	1.9	68.9	47.8	31.0	-	-	-
Total	2.5	48.0	31.3	51.9	0.28	11.2	60,390

Note: Averages of the three waves. Subjective poverty is computed as average value of six-point scale indicator of the ability to make ends meet. The indicator for rent control is a composite index ranging between 0 and 1 based on the average of six binary items relating to specific rental policies (for details, see Data and Method). Source: EU-SILC cross-sectional data (2009-2013-2017) and https://rpubs.com/Konstantin_Xo/RHMR.

However, subjective economic strain among young people cannot be regarded as a limited phenomenon. The distribution of tenure status also varies, partly reflecting the overall distribution of tenure status in the population. Home ownership is particularly widespread in Southern and Eastern European countries, which are typically considered to be homeowner societies. In addition, in Western Europe, where the deregulation of mortgage markets has facilitated access to debt for various social groups, it may have exposed them to the risk of payment insolvency. Moreover, countries where the culture of intergenerational transmission of outright home ownership and stricter regulation of mortgage markets prevail report higher rates of renting. The exception is Greece, one of the countries most affected by the economic crisis in recent decades.

Table 1 also illustrates the overall degree of rental market regulation through the different distribution of rent control and social rented households. Looking at the household income quintiles, a negative association between objective economic resources and subjective poverty emerges: the intensity of subjective poverty decreases as household income increases. The distribution of subjective economic wellbeing shows that a non-negligible proportion of young households feel poor.

Multilevel analysis

The multilevel analysis shows the relationship between tenure and subjective poverty and the role of rent control policies in affecting this relationship.¹⁷ Contextual variables are included following the decomposition approach mentioned earlier to capture the between-countries and within-country differences over time. Table 2 presents the results of the three-level linear regression models (Models 1-8) in which the dependent variable is the intensity of subjective poverty suffered by the young household

Table 2.

Multilevel regression analyses of subjective poverty: household- and contextual-level results and cross-level interactions.

	Model 0	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8
Household-level variables
Housing tenure (ref: Outright homeowners)
Mortgaged homeowners		0.151^*** (0.019)	0.150^*** (0.019)	0.150^*** (0.019)	0.150^*** (0.019)	0.150^*** (0.019)	0.135^*** (0.019)	0.154^*** (0.020)	0.141^*** (0.020)
Renters		0.166^***(0.018)	0.170^*** (0.018)	0.170^*** (0.018)	0.170^*** (0.018)	0.170^*** (0.018)	0.155^*** (0.019)	0.176^*** (0.019)	0.161^*** (0.019)
Household-level control variables - not reported		Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Contextual-level variables
Rental regulation (B)				−0.165^** (0.061)			−0.130^* (0.064)
% Of households in social renting (B)					−0.094 (0.079)			−0.122 (0.082)
Rental index (B)						−0.079^* (0.037)			−0.073⁺ (0.038)
Contextual-level variables (W) - not reported			Yes	Yes	Yes	Yes	Yes	Yes	Yes
Contextual-level control variables (B) and (W) - not reported			Yes	Yes	Yes	Yes	Yes	Yes	Yes
Cross-level interactions with housing tenure
Rental regulation (B)* mortgaged homeowners							−0.065^** (0.021)
Rental regulation (B)* renters							−0.036⁺ (0.020)
% Of households in social renting (B)* mortgaged homeowners								−0.006 (0.022)
% Of households in social renting (B)* renters								0.030 (0.021)
Rental index (B)* mortgaged homeowners									−0.024^* (0.012)
Rental index (B)* renters									−0.004 (0.011)
Cross-level interactions with housing tenure (W) - not reported							Yes	Yes	Yes
Wave dummies		Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Constant	2.607^*** (0.115)	2.466^*** (0.130)	2.316^*** (0.077)	2.319^*** (0.072)	2.317^*** (0.076)	2.316^*** (0.073)	2.333*** (0.072)	2.311*** (0.076)	2.324***(0.074)
Random effects (Variances)
Intercept variance household-level	1.344^*** (0.008)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)	1.034^*** (0.006)
Intercept variance country-wave level	0.038^*** (0.008)	0.020^*** (0.005)	0.015^*** (0.004)	0.015^*** (0.004)	0.015^***(0.004)	0.015^*** (0.004)	0.015^*** (0.004)	0.015^*** (0.004)	0.015^*** (0.004)
Intercept country-level	0.355^*** (0.099)	0.383^*** (0.105)	0.066^*** (0.019)	0.080^*** (0.020)	0.072^*** (0.021)	0.072^*** (0.021)	0.067^*** (0.020)	0.081^*** (0.023)	0.072^*** (0.021)
Slope variance housing tenure-country-wave level		0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)	0.001^*** (0.000)
Slope variance housing tenure country level		0.003^** (0.001)	0.003^*** (0.001)	0.003^*** (0.001)	0.003^*** (0.001)	0.003^*** (0.001)	0.003^*** (0.000)	0.003^*** (0.000)	0.003^*** (0.000)
Aic	189584.67	173824.70	173780.57	173777.22	173783.29	173779.74	173773.33	173788.64	173782.71
BIC	189620.71	174067.93	174077.85	174092.52	174098.59	174095.04	174124.66	174139.98	174134.05
Log likelihood	−94788.34	−86885.35	−86857.29	−86853.61	−86856.64	−86854.87	−86847.66	−86855.32	−86852.36
ICC Country-wave	0.226	0.280	0.087	0.072	0.084	0.077	0.073	0.084	0.077
ICC Country	0.204	0.266	0.073	0.059	0.070	0.064	0.059	0.071	0.064
N	60,390	60,390	60,390	60,390	60,390	60,390	60,390	60,390	60,390

Note: Number of country-years = 84, number of countries = 28. (B) and (W) corresponds to between and within components respectively. For full model and details on components, household- and contextual-level controls, see Tables C1-C2 in the Appendix. Standard errors in parentheses, covariance unstructured. + p < .10, *p < .05, *p < .01, **p < .001. Source: EU-SILC cross-sectional data (2009-2013-2017). Authors’ calculations.

A first assessment of the proportion of variability in subjective poverty that occurs between country-waves and country factors is estimated through an empty model (Model 0). The ICC shows that 20.4% of the total variance¹⁸ is due to between-countries variance while 22.6% is due to between-waves within-country variance.

Thus, Model 1 includes only the main predictors at micro level, namely, housing tenure status and household-level control variables. The slope related to tenure status is random both at country and country-wave levels, representing the country- and country-wave association between tenure status and intensity of subjective poverty. The results show that being a tenant or a mortgaged homeowner is associated, on average, to a higher intensity of subjective poverty compared to outright homeownership (+0.16 and +0.15 in the scores respectively). In other words, as we hypothesized, only the young outright owners are protected from suffering subjective poverty, and this is also true after controlling for income and housing cost burden. This is a significant fact of the extent of inequality in Europe.

In Model 2 we added the macro level control variables. Even though our empirical strategy relates to the decomposition of contextual-macro variables, we present only the between component that captures between-country differences. The results indicate that between-country differences in outright homeownership rate and income inequality are positively associated with subjective poverty, while GDP per capita is negatively associated but not statistically significant.

Models 3, 4, and 5 show the effect of rental housing policies using a stepwise approach for each selected macro-contextual indicator. Results show that two out of three indicators are negatively associated with subjective poverty. One standard deviation increase in rental control produces a negative variation of 0.16 points in the intensity of subjective poverty (Model 3), whereas one standard deviation increase in rental index leads to an 0.08 point reduction in subjective poverty (Model 5). By contrast, the coefficient related to the percentage of households in social housing (Model 4) is not statistically significant. Therefore, the models’ results are partially consistent with our hypotheses: in countries with higher rent regulation, subjective poverty is less intense.

In our hypotheses, we also argued that rental housing policies could affect the relationship between housing tenure status and subjective poverty. In this perspective, cross-level interactions between macro-contextual variables and housing tenure status are estimated. Table 2 also shows the results of these latter multilevel regression models (Models 6-8).

The interaction effects between tenure status and rental housing policies are all negative, except for the interaction between housing tenure status and the percentage of households in social housing (Model 7), as well as the coefficient related to the interaction between the rental index and renters’ households (Model 8), which are not statistically significant. This means that as rental regulation and availability of social housing increase, the differences in the intensity of subjective poverty between outright homeowners and renters decrease. Model 6 indicates that while tenant households’ subjective poverty intensity is higher by 0.15 scores than outright homeowners when rent control is at the mean level, one standard deviation increase in macro-level rent regulation reduces this gap by almost 0.03 scores. This is also true when comparing mortgaged homeowners and outright homeowners: one standard deviation increase in rent control reduces the gap by 0.06. Figure 1 shows that the average subjective poverty gap between renters, outright and mortgaged homeowners tends to narrow as rent control increases.

Our hypothesis posits that regulating rent increases may also offer security to mortgaged homeowners who see renting as an affordable housing alternative should they be unable to meet their mortgage payments. This hypothesis seems to be confirmed by the data. Lastly, we also observe the effect of the composite rental index (Model 8): one standard deviation increase in macro-level rental index reduces the gap between outright and mortgaged homeowners by 0.02 scores.

Discussion and conclusion

The article contributes to the literature on the relationship between housing and wellbeing, particularly subjective poverty, an underinvestigated dimension (Arundel and Ronald 2021; Chevalier, 2023; Dewilde 2022), and sheds light on the micro- and macro-level effect of housing tenure. Our findings show that subjective poverty is widespread among young people in Europe, and that being a tenant or mortgaged homeowner rather than an outright homeowner is positively associated with the feeling of living in economic hardship, even when controlling for the level of income and housing cost burden. It can thus be argued that housing tenures are associated with a specific level of insecurity among young adults. However, we also found that at macro level, rental housing policies can reduce young people’s subjective poverty and the gap in feeling poor between renters and homeowners with and without mortgages.

Our findings are consistent with other studies reporting that housing policies oriented towards rental options not only affect the level of households’ expenditures, making the rental sector more affordable, but also influence the housing market as a whole, reducing its rigidities and making it more accessible to young people entering the market (DeLuca and Rosen 2022; Dewilde 2022; Kholodilin and Kohl 2023). A higher level of state intervention in the housing sector, with stricter regulation and more affordable social housing, could benefit all young adults, especially those with low incomes. At the same time, the entire housing market would benefit as a result of easier access to decent, affordable housing (Dewilde 2022).

Further discussion is needed, since we found that rent control seems to be more effective than social housing. The latter is marginal in several countries (Pittini 2019). For this reason, young households do not consider it a viable option, and this is probably why it does not show a significant effect on their subjective poverty.

Nevertheless, social housing can play an important role especially for the poorest households: on the one hand, controlled rents may still be too high for them, and on the other hand, landlords who are forced to charge overly low rents because of control policies may decide to let their properties remain vacant, reducing the supply of houses in the market (Scanlon et al., 2014).

In terms of subjective wellbeing, the lower likelihood in the feeling of poverty among mortgaged homeowners points to the symbolic value of public policies. Strong state intervention, in fact, can be perceived as a way of protecting citizens from rising prices in the free market (Fuster et al., 2019). Thus, the effect of housing policies may not be limited to the decision to leave the parental home. It may also affect other dimensions, such as young adults’ consumption and reproductive choices, mitigating the current polarization of socioeconomic conditions between (outright) homeowners and renters.

Our study has certain limitations resulting from the lack of comparable data for European countries. We cannot, in fact, control for the role of family background on young adults’ outcomes. Parents’ support through social and economic resources plays a significant role in determining adult children’s living conditions and independence process (Tucci 2024), but its impact varies across European countries. Being able to rely on tangible and intangible family transfers can influence young adults’ perception of economic difficulties and outcomes in the housing market, with different implications for the reproduction of social inequality (Filandri and Bertolini 2016). Future work will investigate the impact of social origin on young Europeans’ housing conditions to gain an understanding of how the importance of family background changes in relation to different levels of rent regulation.

Within this framework, various research lines are possible. Regarding the housing market, a detailed analysis of the differences between private and social renting is desirable. Additionally, adopting a longitudinal perspective may reveal differences between tenants and mortgaged homeowners, as ownership can represent a significant source of household wealth and provide greater security. Also, regarding the labour market, it would be suitable to investigate how temporary and non-temporary contracts contributes to this sense of insecurity.

Supplemental Material

Supplemental Material - Housing tenure and subjective poverty among young European adults: The role of rent regulation

Supplemental Material for Housing tenure and subjective poverty among young European adults: The role of rent regulation by Marianna Filandri, Silvia Pasqua and Violetta Tucci in Journal of European Social Policy.

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Violetta Tucci

Supplemental Material

Supplemental material for this article is available online.

Notes

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