2. Is the housing market an obstacle to inclusive growth? For whom?

Housing is a key dimension of inclusive growth, but some groups face bigger obstacles in the housing market than others.1 This section explores the housing challenges of low-income households, children, youth, seniors, and the homeless, for whom reduced housing opportunities and poorer housing outcomes threaten to deepen inequalities across people, space and time.

The housing sector in many OECD countries is changing on several fronts, with important implications for low-income and other vulnerable households. First, even though home ownership remains the dominant form of tenure for the majority of OECD households (Figure 2.1), this is changing in many countries. On average, in 2018 nearly 70% of households across the OECD either owned their dwelling outright or with a mortgage, while 28% rented a dwelling, either in the private rental market or as subsidised rental housing. As will be discussed below, the policy preference for home ownership in many OECD countries has contributed in part to the dominance of owner-occupied housing. However, the share of owner-occupied dwellings in the total housing stock has declined or stabilised in nearly all OECD countries since 2000 – thus before the global crisis, and especially for young people (Scanlon and Whitehead, 2004[1]; Arundel and Doling, 2017[2]; Whitehead and Williams, 2017[3]).

Second, the private rental sector is expanding and the age of renters is diversifying (Hulse, Parkinson and Martin, 2018[4]). In some countries, tenants are staying longer in private rental housing, underscoring its decline as a transitional tenure for young adults on their path towards home ownership, as well as a trend in older households remaining in or re-entering the rental market. In most OECD countries, private rental housing was the only tenure type that saw a consistent increase across all age groups since 2010 (with the exception of seniors over 65). The diversification of tenants in the private rental sector can in part be attributed to rising house prices that put home ownership out of reach for some households, as well as growing pressures on the social (subsidised) rental sector.

Third, as discussed in Section 1, housing is on average, across all income groups, the single-largest expenditure of households in the OECD (Figure 1.1, Panel A). The weight of housing in household budgets affects households’ ability to spend or invest in other areas that matter for inclusive growth, such as education or health. Part of the reason lower-income households spend more on housing on average, relative to other income groups, is that housing is a necessary good and one of the first expenses that households need to cover. For some people, higher housing costs may not be an impediment to achieving greater satisfaction, but rather a means to achieving it: some households are willing to spend more to live in areas with better-performing schools or better air quality, which are key to improving outcomes for households and especially for children.

Fourth, estimates of consumption data suggest that people are spending more of their household budget on housing than they used to (Figure 1.1, Panel B).2 On average across OECD countries for which estimates are available3, the share of housing in household budgets – which covers housing costs (e.g. rent), regular maintenance and repairs, and utilities – rose by nearly 5 percentage points between 2005 and 2015. Over the past decade, the share of household budgets also increased for other key consumption items such as transport, health and education, yet to a lesser extent (a less than 1 percentage-point increase). Going back twenty years in time (1995-2015), albeit for a smaller subset of countries4, the share of household spending on housing increased even further. Households were estimated to have spent almost 6 percentage points more of their budget on housing in 2015 relative to 1995, compared to just over 2 percentage points more on health, the budget item for which the next largest jump in spending was recorded.5

Further, housing prices have increased over the past two decades, especially for renters. This can at least partly explain increased household spending on housing. On average, real house prices increased in 31 OECD countries between 2005 and 2019, with Colombia, Canada, Sweden and Israel recording the largest increases (over 80%) over this period (Figure 2.2 – Panel A). Seven OECD countries recorded a drop in real house prices over this period, most significantly in Greece, Italy and Spain. The evolution of rent prices across the OECD over this period features more uniform trends, with rent prices increasing in all but two OECD countries between 2005 and 2019 (Figure 2.2 – Panel B). Turkey, Lithuania, Iceland and Estonia recorded the largest increases (e.g. over 100%) over this period. Japan and Greece were the only two countries that saw a drop in real rent prices since 2005; however, in Greece, the drop in rent prices was nonetheless much smaller than that of real house prices (10% vs. 33% drop). High and rising rent prices also make it harder for tenants to save up for a down payment to purchase a home.

Box 2.1 provides a summary of indicators of housing quality and affordability that are used in this report. These may provide a useful starting point for policy makers to assess the extent of housing market exclusion for different groups and regions in their country.

On average across the OECD, low-income households spend the biggest share of their household budget on housing, much more so than middle- and upper-income households (Figure 1.1). As a result, they have fewer resources to invest in better housing or in other areas that could improve their life chances, such as education. Moreover, there is a large share of low-income households spending more than 40% on housing costs. The housing overburden rate, defined as the share of households spending more than 40% of their disposable income on housing costs6, varies depending on whether households are renting a home or paying off a mortgage (Figure 2.3). In ten OECD countries, more than two out of five low-income renters in the private market spent over 40% of their disposable income on housing in 2018. The same share was reached for low-income owners with a mortgage in four OECD countries. In New Zealand and the United States, at least two out of five low-income people (regardless of tenure) spent over 40% of disposable income on rent or a mortgage in 2018. And while they tend to fare better than renters in the private market, at least three out of ten low-income renters in subsidised rental housing faced a housing cost overburden in Hungary, Finland and the United Kingdom (OECD, 2019[6]).

Moreover, while the share of spending on housing has increased for all households over the past decade, estimates of household consumption data suggest that low-income households have seen the most significant rise (Figure 2.4). On average across OECD countries for which estimates are available,7 the share of housing costs in household budgets among the bottom quintile increased by more than 9 percentage points between 2005-2015, compared to an increase of around 5 percentage points for middle-income households and 3 percentage points for high-income households. Going back further in time for a smaller subset of countries8, the weight of housing in household budgets increased by an estimated 13 percentage points for the bottom quintile between 1995 and 2015. This suggests that low-income households were seeing a larger share of their budgets go towards housing even well before the Global financial crisis (drawing on analysis prepared for OECD (2019[6])).

On average, low-income households have lower housing quality and are more likely to live in overcrowded conditions relative to those with higher incomes. Rates of overcrowding vary widely across countries, but in nearly all countries, households in the bottom quintile have a higher rate of overcrowding than those in the middle- or top-income quintile (Figure 2.5). In Mexico, Poland, Latvia and the Slovak Republic, more than 30% of low-income households are considered overcrowded. Overcrowding is also more likely to occur among renters, yet some countries also show high rates of overcrowding in owner-occupied homes (OECD, 2019[8]). The COVID-19 pandemic renewed concerns over overcrowding and other deficiencies in housing and neighbourhood quality, which can have adverse health effects (Box 2.2).

Housing has important implications for wealth. On the one hand, real estate assets overall tend to be more concentrated at the top of the income distribution, since higher-income households are more likely to own more expensive primary residences as well as invest in secondary residences. On the other hand, however, housing constitutes the largest source of wealth and the biggest financial liability among low-wealth households. Real-estate wealth makes up the biggest share of wealth among households in the bottom quintile, outweighing financial and other non-financial wealth in most OECD countries. The biggest shares of housing-related wealth among low-wealth households are found in the Netherlands, Denmark, Norway and Ireland (Figure 2.6). However, property liabilities (e.g. mortgages) among low-wealth households are larger, on average, than the level of housing assets, contributing to negative average net worth among low-wealth households in many OECD countries (Balestra and Tonkin, 2018[26]). Real estate tends to be the most important means to build wealth for low- and middle-wealth households; at the same time, however, this creates risks, as such households may be less able to draw on their wealth to absorb shocks in incomes, because real estate is not as easy to liquidate compared to other forms of wealth (Clarke, Fernandez and Königs, forthcoming[27]).

Mortgage debt can be both an opportunity and a risk for low-wealth households. On the one hand, it allows (particularly younger and lower-income) households to accumulate wealth, but, on the other hand, it also exposes them to financial risks. Lower-wealth households tend to be at a higher risk, whether measured in terms of solvency (their ability to pay back their mortgage) or liquidity (households’ vulnerability to face difficulty in reimbursing mortgage debt in case of an economic shock). For instance, on average across the OECD, indebted households in the bottom quintile of the net wealth distribution record loan-to-value ratios (a solvency risk indicator) that exceed the conventional at-risk threshold value of 75% (Causa and Woloszko, 2019[28]). For all households, real-estate makes up the largest share of liabilities, on average, in most OECD countries (Figure 2.7).

High levels of real estate debt are not necessarily a problem, since they usually coincide with even higher housing wealth. However, over-indebtedness can pose risks to individuals and to the economy at large. High levels of debt relative to household income or to household assets can put households at risk of financial instability or default should asset (e.g. real estate) prices, interest rates or personal circumstances change. The Global Financial crisis contributed to over 9 million homeowners in the United States going through a foreclosure, surrendered their home to a lender or sold their home via a distress sale between 2006 and 2014 (Kusisto, 2015[29]). Too much debt can also create vulnerabilities for the economy as a whole, as was experienced during the global crisis (Balestra and Tonkin, 2018[26]), and weigh on long-term economic performance (Cournède, Denk and Hoeller, 2015[30]). Indeed, mortgage distress and defaults in the housing market were at the origins of the 2008 global financial crisis with lasting impacts on the housing market. Evidence from the United States suggests that the Global Financial crisis also resulted in unequal impacts across different types of households. Minority households, such as African-American and Hispanic households, suffered the most severe equity losses and experienced the sharpest increases in default as well as the biggest drops in home ownership rates in the aftermath of the Global Financial crisis (Gould Ellen and Dastrup, 2012[31]).

Housing and neighbourhood quality matters, especially when children are young. Indeed, poor housing quality is a critical dimension of child poverty and represents one of the most common forms of material deprivation among children, compared to other dimensions, such as nutrition or clothing (Thévenon, 2018[32]). Research on intergenerational mobility from the United States finds that low-income children are most likely to succeed when they grow up in counties with less concentrated poverty, less income inequality, better schools, a larger share of two-parent families and lower crime rates (Chetty and Hendren, 2018[33]). Children who spend more of their early childhood years in higher-opportunity neighbourhoods9 also earn more as adults.

For children, poor housing and neighbourhood quality can have an adverse impact on health and the home learning environment (Coley et al., 2013[34]; Evans, Saltzman and Cooperman, 2001[35]; Marcal and Fowler, 2015[36]). In OECD countries for which data are available, on average nearly 11% of children live in households with self-reported problems of crime, violence or vandalism in the local area; the share is higher among households with a low education level (15%) and among households in the lowest tertile of the income distribution (13%) (OECD, 2019[37]). Although it can be difficult to disentangle the neighbourhood from the socio-economic effect, the impact of one’s childhood neighbourhood can be long lasting. Evidence from the United States and the United Kingdom finds that life expectancy can vary by decades across neighbourhoods, based on the neighbourhood’s proximity to environmental and health hazards, the concentration of poverty and the level of racial segregation (OECD, 2016[38]).

The neighbourhood in which housing is situated shapes children’s access to (quality) schools and educational opportunities. The quality of neighbourhood communities – in terms of peers, colleagues, and local authorities – and facilities can have a direct impact on early childhood outcomes (OECD, 2017[39]). The broader learning environment encompasses a child’s home, neighbourhood and early childhood education and care services. Households tend to geographically cluster based on their incomes (see discussion of spatial segregation below) (OECD, 2018[40]), and the socio-economic segregation of neighbourhoods can reproduce itself in schools: OECD (2012[41]) reports that wealthier parents tend to avoid schools with a significant number of disadvantaged students. A study that followed individuals in England (United Kingdom) over time, at least part of the reason why poorer children fell behind their richer peers could be attributed to attending different secondary schools (Crawford, Macmillan and Vignoles, 2017[42]). Wealthier parents are more likely to exercise school choice and can enrol their children in good quality schools, compared to more disadvantaged parents who tend to exercise choice less and send their children to their local neighbourhood schools (OECD, 2012[41]). Research suggests the existence of peer effects, and that pupils from a low socio-economic background gain from attending a school with students from a more advantaged socio-economic background (Causa and Chapuis, 2009[43]).

The challenges associated with poor neighbourhood quality and limited access to opportunity are especially salient, given that income segregation and spatial inequality are high and on the rise in many OECD countries. Residential segregation occurs when individuals with shared characteristics, such as income level, race or ethnicity, are concentrated in a geographic space. While some level of residential segregation is natural, it becomes problematic when it results in the concentration of disadvantage in space – that is, in neighbourhoods with poor access to quality jobs and services – as this can affect individual outcomes much later in life, weighing on future generations and limiting social mobility (OECD, 2016[38]; OECD, 2018[44]). A comparison of segregation by income levels in twelve countries10 yields considerable differences in spatial patterns within and across countries (OECD, 2018[44]). For instance, the most income-segregated cities in the Netherlands and France are at comparable levels with the least income-segregated cities in the United States (OECD, 2016[38]). OECD (2018[44]) found that income segregation tends to be higher in bigger, richer and more productive metropolitan areas. Segregation by income level has increased in recent decades in Europe and the United States (van Ham et al., 2016[45]; Massey, Rothwell and Domina, 2009[46]). These findings have particular importance for households with children, and suggest that interventions that focus on (young) children can have important generational effects.

On average, more than 1 in 5 children between 0-17 years old live in an overcrowded household in European OECD countries, with considerable variation across countries (Figure 2.8). Over half of all children live in overcrowded households in Hungary, Latvia and Poland, compared to less than 8% in Ireland, the United Kingdom, the Netherlands, Norway and Finland. In all countries for which data are available, children in low-income households are much more likely than those in high-income households to face overcrowded conditions.

Even children who do not live in income-poor households can suffer from housing-related deprivation that relates either to the quality of the dwelling or the broader neighbourhood environment (such as noise or crime). For instance, one in five children in non-income poor households in France and Spain, and one in four non-income poor children in the United Kingdom, are faced with “multiple housing problems”, a composite measure of housing quality that includes adequate lighting, quality of roof, presence of humidity or mould, ability to keep the dwelling adequately warm (Thévenon, 2018[32]).

The rising cost of housing means that young families with children – even those with median income levels – are finding it increasingly difficult to afford quality housing, including purchasing a home. Based on price data from capital cities across the OECD, OECD (2019[7]) finds that a median-income couple with two children must spend significantly more to purchase a modest-sized flat today than they would have 30 years ago, putting increasing pressures on household budgets and making home ownership less accessible to young families relative to previous generations (Figure 2.9). Real interest rates have fallen considerably since 1985, moderating somewhat the impact of house price increases on housing costs.

Housing is one of several dimensions of well-being – along with employment opportunities – that have become more challenging for young adults in recent years, and threatens to deepen inter- and intra-generational inequalities. Frequently, today’s youth have access to fewer quality, affordable housing opportunities than previous generations and they increasingly struggle to become homeowners, which limits their ability to build wealth. Low-income youth face even greater challenges than their higher-income peers in securing good quality housing, because they are not able to rely on family resources for support.

In a context of rising rents and house prices, several features of youth living arrangements are worth noting:

  • Young adults aged 20-29 (e.g. those out of upper secondary schooling) are, on average across the OECD, most commonly living with their parents, though there is wide variation across countries (Figure 2.10). The biggest shares of youth living with their parents were recorded in Italy (75% in 2017), the Slovak Republic (74%) and Greece (74%), followed by Slovenia, Spain and Portugal (each around 70%). The Nordic countries are a notable exception, as only 10-20% of youth in Norway, Finland and Sweden live with their parents; they are more likely to be living with a partner or living alone.

  • The trend in youth living with their parents appears to be on the rise in some OECD countries. For instance, between 2007 and 2014, there was a 12.5 percentage-point rise in the share of youth aged 15-29 living with their parents in France; the share also increased by nearly 9 percentage points in Hungary, nearly 6 percentage points in Italy, and almost 5 in Greece (OECD, 2016[48]; Lennartz, Arundel and Ronald, 2016[49]).

  • Nearly 30% of youth (aged 20-29) live in a private rental dwelling; no other age group includes as large a share of renters. Just over two-thirds of youth (20-29) in the OECD live in owner-occupied homes (OECD, 2019[6]).

  • Youth tend to move to urban areas, where housing costs have soared in recent decades. While urban areas in the OECD are attracting more new residents overall compared to rural areas, youth make up a large share of new urban dwellers. In Latvia, Estonia, Japan, Israel, Korea, Spain, Sweden, the Slovak Republic, Australia, the United Kingdom, the Czech Republic and Norway, more than 90% of young internal net migrants11 moved to regions with a predominantly urban population in 2016 (OECD, 2018[50]).

In some countries, both low- and middle-income young households are finding home ownership increasingly out of reach. For instance, in the United Kingdom, home ownership rates among youth have dropped overall, and most significantly for those in the middle-income bracket: 65% of middle-income youth were homeowners in 1995-96, compared to just 27% two decades later (Cribb, Hood and Hoyle, 2018[51]). Clarke et al (forthcoming[27]) find that, relative to their peers in the past, younger people accumulate wealth less quickly, which may result from the rising age at labour market entry, less stable labour market prospects and slower earnings growth in the aftermath of the economic crisis.

Several factors have contributed to the decline in home ownership among young households, including high house prices, high transaction costs, insecure employment and low income levels (Whitehead and Williams, 2017[3]). On the one hand, rising house prices have made ownership increasingly unaffordable for young households, particularly relative to their income. For instance, in 2015-16, the average regional house price was four times the income of almost nine out of ten young adults in the United Kingdom; two decades earlier, this was true for less than half of young adults (Cribb, Hood and Hoyle, 2018[51]). On the other hand, notably in the aftermath of the Global Financial crisis, access to mortgages has become more difficult (particularly due to lower loan-to-value caps), while greater insecurity in economic and job conditions for youth are additional barriers to buying a home. Whitehead and Williams (2017[3]) suggest that the latter appears to have had a greater effect on home ownership rates among youth than the former. Arundel and Doling (2017[2]) argue that the decline in home ownership is not a temporary consequence of the global crisis, but given the increasing insecurity in the labour market (which especially affects youth) declining home ownership rates represent a more structural and sustained change in housing tenure arrangements.

In some OECD countries, young households increasingly rely on financial support from their families to purchase a home, which can in turn exacerbate intra-generational inequalities. In France, there is a growing gap in access to home ownership among affluent and low-income young households (aged 25 to 44): 32% of low-income young households were homeowners in 1973, compared to just 16% four decades later (Bonnet, Garbinti and Grobon, 2019[52]). This is in part driven by affluent young households increasingly benefitting from personal family financial support in the 2000s, which contributed to their capacity to purchase a home, while low-income households did not have similar levels of family support. Family support to buy a home also increased significantly in the United Kingdom: in 2014-15, three times as many buyers relied on support from inheritance relative to 1994-95 (Social Mobility Commission, 2016[53]). In Australia, around half of first-time buyers need financial support from their parents (Whitehead and Williams, 2017[3]).

It is not surprising, then, that access to quality affordable housing is a chief concern of young people. According to the 2018 OECD Risks That Matter survey, which asked over 22 000 people in 21 OECD countries about their social and economic risks12, housing concerns were highest among younger people. On average, around a third of respondents aged 20 to 34 reported that securing or maintaining adequate housing was among their top three short-term concerns, with the share peaking at 40% among 25 to 29 year olds (Figure 2.11) (OECD, 2019[54]). In all countries but one (Norway), the share of youth identifying housing as a top short-term concern was higher than the share of the overall population. Israel, Lithuania, Estonia, Slovenia and Portugal recorded a more than 20-percentage point difference between youth and the overall population. These countries, in addition to Chile, Austria, Finland and Canada, registered the largest share of youth (e.g. over 40%) identifying housing as a top short-term concern.

Higher levels of vulnerability and instability among youth in the labour market have important implications for housing. When labour market instability is accompanied by lower wages or greater wage volatility, people face challenges to secure affordable housing in the rental housing market, where prices have continued to rise. Youth (aged 15-29), who were hit disproportionately hard by the Global Financial crisis, are more likely to work in temporary and atypical contracts that are easier to terminate (OECD, 2016[48]). Aurand et al. (2019[55]) reported that a minimum-wage worker would have to have three full-time minimum-wage jobs to afford paying rent for a two-bedroom apartment anywhere in the United States in 2019. Longer term employment instability can in turn weigh on opportunities for home ownership. Arundel and Doling (2017[2]) suggest that the decline in well-paid jobs with secure contracts – particularly among young adults – is reducing youth’s access to home ownership. One reason is that secure job contracts are most appropriate for taking out housing loans. A study of six European countries finds that higher levels of employment insecurity reduce the chances of holding a mortgage in all countries (Dotti Sani Collegio Carlo Alberto et al., 2018[56]). Prospective homeowners are not the only ones made more vulnerable by increasingly flexible employment contracts, as landlords often require employment stability from prospective tenants.

Looking ahead, increased instability in housing, employment and other aspects of life for youth not only risks changing the structure of home ownership patterns in the future, but also exacerbating inter-generational inequality. On the one hand, Arundel and Doling (2017[2]) report that the cumulated trends of “delayed labour market entry, increased educational indebtedness, and a lack of well-paid and stable job opportunities” have created obstacles for youth to make traditional transitions into adulthood, including for housing. As a result, youth are struggling to get on a stable, quality housing ladder – including, but not limited to, home ownership. This can result in delayed household and family formation, and can also affect their access to quality schools (for their children), employment opportunities and wealth-building opportunities through home ownership. On the other hand, while rising house prices create challenges for young generations, older home-owning households tend to reap the benefits, which may ultimately exacerbate inter-generational disparities (Meen, 2018[57]).

At first glance, housing is, for many seniors in the OECD, a source of economic stability and an important asset in old age. Yet, for the more than a third of seniors in the OECD who do not own their home outright, housing can represent a major source of vulnerability. Across the OECD, on average, 14% of seniors live in owner-occupied dwellings with a mortgage, with another 14% in rental housing in the private market, 5% in subsidised (social) housing, and 5% in some type of institutionalised or communal housing. However, there is significant cross-country variation (Figure 2.12). More than one in ten seniors who do not live in homes that are owned outright13 are overburdened by housing costs. In some countries, the share of seniors paying over 40% of their disposable income on housing can be much larger, reaching around 20% of all seniors in Australia, Belgium, Chile, Greece, Japan, Sweden and the United States, and 18% in the United Kingdom. There are important cross-country differences (see Table B.1 in Annex B). Seniors living in private rental housing are especially sensitive to increases in rental prices, as their income from pensions tends to increase more slowly than rent.

Because the majority of seniors own their home outright, they tend to be overrepresented among the “income-poor but asset-rich” households, and are more likely to be able to rely on their real estate assets in old age, even if their income does not continue to increase (Clarke, Fernandez and Königs, forthcoming[27]). This is a big difference compared to seniors who are both income- and asset-poor and are likely to suffer from old-age poverty because they cannot compensate their low incomes by drawing on wealth; this group may also find it harder to pay for caring expenditures (Clarke, Fernandez and Königs, forthcoming[27]). Heightened housing and economic vulnerability among seniors can have significant consequences, and in the most extreme cases, can lead to homelessness (see discussion below).

There are large inequalities in access to health and transport services for elderly populations in the OECD, with considerable regional variation across countries (OECD, 2017[58]). For instance, OECD (2017[58]) found that the regional distribution of hospital beds and doctors does not match the localities where older people live in most OECD countries, and that physical proximity to the nearest hospital also varied widely across regions and is especially a challenge in more rural areas. In terms of access to public transport, which can facilitate the integration of older people into society as well as their ability to access health care and social and other services, there are important disparities in the share of the elderly population who can access public transport services within walking distance (OECD, 2017[58]).

As populations across the OECD age (OECD, 2019[47]), the current housing stock appears ill adapted to the evolving needs of an ageing society. While housing quality and accessibility are important for all households, senior households have particular needs that may evolve over time. For elderly or disabled residents, the physical aspects of a dwelling can facilitate or hinder their daily activities. Well-adapted housing can enable ageing households to remain independently housed for longer, thereby reducing the need to transition to more costly supportive or institutionalised care (Slaug et al., 2017[59]). Adaptations to the dwelling can include eliminating stairs, widening doorways to allow for wheelchairs, ensuring that walls can withstand grab rails and providing an entrance-level toilet. Accessibility investments can have important health benefits, and do not necessarily imply significant net costs.14

Yet while data are far from comprehensive, much of the housing stock in the OECD is not equipped to allow seniors, to age in place (that is, to continue to live in their own homes) for as long as feasible, which is their preferred housing arrangement (OECD, 2017[58]). The Canada Mortgage Housing Corporation found that only one-quarter of all households and one-third of senior households had an accessible entrance (Canada Mortgage Housing Corporation, 2017[60]). Adapting dwellings or moving to a more suitable housing arrangement that meets the needs of seniors will be more difficult among ageing households who are poor.

Moving forward, housing for the elderly will be an increasingly pressing policy priority, given the current affordability pressures combined with ageing and inequality trends. Across the OECD, the risks of increasing inequality among the elderly have been building up, as demographic change and fiscal constraints are changing life prospects in old age (OECD, 2017[58]). In the OECD, on average one in seven people over the age of 76 is poor, and in many countries the over-76s are the age group most at risk of living in poverty (OECD, 2017[58]).

The drivers of homelessness are multiple and complex, resulting from structural factors, institutional and systemic failures, individual circumstances – or a combination of these.

  • Structural factors include tight housing market conditions, labour market changes, poverty, a shrinking social safety net, increased migration and, in particular, reductions in housing allowances. Research has identified a correlation between homelessness and rising housing costs; other studies have pointed to a link between homelessness levels and increasing rates of poverty and evictions.

  • Institutional and systemic failures refer to the higher risk of homelessness and housing instability among people transitioning out of institutional settings, such as foster care, the criminal justice system, the military, or hospitals and mental health facilities. In France, for instance, around one in four homeless adults born in the country was previously in foster care or known to child welfare services.

  • Individual circumstances, including traumatic events, such an eviction or job loss, a personal crisis (family break-up or domestic violence), child poverty, and health issues (mental health or addiction challenges) are also correlated with homelessness.

Homelessness is the most extreme form of housing and social exclusion. Homelessness has emerged as a pressing challenge across the OECD, in view of the increasing number of homeless people in many – but not all – OECD countries. According to the latest national statistics, there are roughly 1.9 million homeless people across 35 countries for which data are available, representing less than 1% of the total population in each country.15 Due to methodological challenges and definitional differences across countries16, this figure is likely an underestimate. In recent years, homelessness has risen in around one-third of OECD countries, and fallen or remained stable in a quarter of OECD countries. In many OECD countries, homelessness is concentrated in big cities. For instance, Dublin accounted for around 66% of the national homeless population in Ireland in 2019, even though it only represents about a quarter of the country’s total population.

National trends in homelessness can also mask different developments across regions and cities within a country. For instance, a number of large metro areas have seen their homeless populations swell, even as national averages record more modest changes. In England (United Kingdom), despite a levelling off of rough sleepers nationally, their number has been increasing in London, Birmingham and Manchester. In Canada, homelessness rose in Toronto by 24% between 2008 and 2014, whilst decreasing in Calgary and Metro Vancouver by 62% and 39%, respectively. In the United States, homelessness increased by 57% in Los Angeles County and by 31% in New York City between 2012 and 2017, even as national trends were much more subdued (OECD, 2020[61]; 2019[6]).

Policy makers must also keep in mind that people experience homelessness in different ways. A smaller, but more visible, share of the homeless population experiences prolonged periods of homelessness, or may transition in and out of homelessness over the course of several weeks, months or years (typically known as the “chronically homeless”). A larger share of the homeless population in most countries is “transitionally” or “temporarily” homeless, in that they are homeless for only a short period before finding a more stable housing solution.

In addition, the faces of the homeless are becoming increasingly diverse. Traditionally, single men have been more likely to be homeless. Although data on homelessness are hard to come by and difficult to compare across countries, homelessness among youth, families with children, and seniors has increased in some countries for which data are available. Further, in Australia, Canada, New Zealand and the United States, Indigenous populations are overrepresented among the homeless. Migrants make up a significant share of the homeless, but data are scarce.

Homelessness among families with children has risen – in some cases, significantly – in several OECD countries that monitor family homelessness. Homelessness among families with children almost quadrupled in Ireland between 2014 and 2018, from 407 to over 1 600 households (OECD, 2019[6]). Family homelessness in New Zealand increased by 44% between 2006 and 2013, representing nearly 21 800 individuals in 2013 (OECD, 2019[6]). Family homelessness in England (United Kingdom) increased by 42% between 2010 and 2017, representing over 44 000 households in 2017 (OECD, 2019[6]). In the United States, families with children represented one-third of the homeless population in 2018 (over 180 000 people in more than 56 300 families). Moreover, some U.S. states saw a significant rise in family homelessness: between 2007 and 2018, Massachusetts and Washington, D.C., experienced an increase in homelessness among families with children of more than 90%, while New York saw a rise of 51% over that period (US Department of Housing and Urban Development (HUD), 2018[62]). By contrast, family homelessness declined in Denmark and Finland in recent years (OECD, 2019[6]).

Children in homeless families are much more likely to suffer from negative impacts to their physical and mental health, and have a higher likelihood of poor educational outcomes (OECD, 2019[63]). Further, housing insecurity (which can take the form of housing unaffordability, frequent moves and homelessness) can contribute to child maltreatment, independent from poverty and economic hardships (Warren, 2015[64]). Lack of access to affordable and adequate housing compromises parents’ ability to meet children’s basic needs through material deprivation (OECD, 2019[63]).

Youth homelessness (among youth aged 15-29, unless otherwise indicated) is a growing concern in a number of OECD countries. However, in New Zealand, homeless youth represented around 1.1% of the total youth population in 2013 (11 076 homeless youth). In Australia, the share of homeless youth represented 0.77% of all youth in 2016 (38 277 homeless youth); 0.49% of the total youth population in Canada in 2016 (34 209 homeless youth); roughly 0.21% of all youth in Denmark in 2019 (1 928 homeless youth aged 18-29); and less than 0.15% of all youth in Finland and Ireland in 2018.

Further, among countries for which government data are available over time, youth homelessness has increased in Australia, Ireland and New Zealand, among others (OECD, 2019[6]). Ireland reported the largest increase, with a jump of 82% over just a four-year period, from 2014 to 2018. Denmark experienced an increase in youth homelessness (aged 18-29) of 43% between 2011 and 2017, but it has since declined between 2017 and 2019 (VIVE - Knowledge of Welfare The National Center for Welfare Research and Analysis, 2019[65]). Youth homelessness grew by 20% between 2011 and 2016 in Australia and by 23% between 2006 and 2013 in New Zealand (OECD, 2019[6]). In each of these countries except Ireland, youth homelessness grew faster than the growth in the overall homeless population. In some countries, youth ageing out of the state care system (such as foster care), for lack of transitional solutions upon becoming adults, end up homeless: in France, for instance, around one in four homeless adults born in the country was previously in foster care or known to child welfare services (Fondation Abbé Pierre, 2019[66]). Meanwhile, homelessness dropped among youth in Canada (by 17% between 2011 and 2016), Finland (by 25% between 2019 and 2018), and England (United Kingdom) (by 20% among 16-24 year olds between 2010 and 2017) (OECD, 2019[6]).

While cross-national data are scarce, homelessness among seniors has risen in several OECD countries. In Canada, while seniors make up only a small share of users of homeless shelters, the number of seniors using emergency shelters increased by about 50% from 2005 to 2016 (Government of Canada, 2019[67]). England (United Kingdom) recorded a ten-year high of homeless people over the age of 60 in 2018, with the share of homeless seniors more than doubling in eight years (Bulman, 2018[68]). In New York City, homelessness among seniors has more than tripled over the past decade, with the waiting list for affordable senior housing reaching up to seven years in some cases (CBS New York, 2019[69]).

References

[17] Ahrentzen, S., J. Erickson and E. Fonseca (2016), “Thermal and health outcomes of energy efficiency retrofits of homes of older adults”, Indoor Air, Vol. 26/4, pp. 582-593, http://dx.doi.org/10.1111/ina.12239.

[2] Arundel, R. and J. Doling (2017), “The end of mass homeownership? Changes in labour markets and housing tenure opportunities across Europe”, Journal of Housing and the Built Environment, Vol. 32/4, pp. 649-672, http://dx.doi.org/10.1007/s10901-017-9551-8.

[55] Aurand, A. et al. (2019), Out of Reach 2019, National Low Income Housing Coalition, http://www.nlihc.org/oor (accessed on 20 June 2019).

[16] Babisch, W. (2012), Exposure to environmental noise: risks for health and the environment. Workshop on “Sound level of motor vehicles”, http://www.europarl.europa.eu/document/activities/cont/201205/20120524ATT45762/20120524ATT45762EN.pdf (accessed on 19 September 2019).

[14] Baker, M. et al. (2008), “Tuberculosis associated with household crowding in a developed country”, Journal of Epidemiology Community Health, Vol. 62/8, pp. 715-721, https://jech.bmj.com/content/jech/62/8/715.full.pdf (accessed on 19 September 2019).

[26] Balestra, C. and R. Tonkin (2018), “Inequalities in household wealth across OECD countries: Evidence from the OECD Wealth Distribution Database”, OECD Statistics Working Papers, No. 2018/01, OECD Publishing, Paris, https://dx.doi.org/10.1787/7e1bf673-en.

[9] Bonnefoy, X. (2007), Nos. 3/4, 2007 ’Inadequate housing and health: an overview, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.462.6443&rep=rep1&type=pdf (accessed on 17 June 2019).

[52] Bonnet, C., B. Garbinti and S. Grobon (2019), Rising inequalities in access to home ownership among young households in France, 1973-2013, https://publications.banque-france.fr/sites/default/files/medias/documents/wp711.pdf (accessed on 5 July 2019).

[68] Bulman, M. (2018), Number of homeless pensioners in England hits 10-year high, figures show, The Independent, https://www.independent.co.uk/news/uk/home-news/homeless-pensioners-elderly-single-parent-household-housing-shelter-figures-a8419241.html (accessed on 4 July 2019).

[60] Canada Mortgage Housing Corporation (2017), Research Insight: Accessibility of Canadian Seniors’ Homes, http://peterkubiczekteam.com/wp-content/uploads/69126.pdf (accessed on 4 July 2019).

[43] Causa, O. and C. Chapuis (2009), “Equity in Student Achievement Across OECD Countries: An Investigation of the Role of Policies”, OECD Economics Department Working Papers, No. 708, OECD Publishing, Paris, https://dx.doi.org/10.1787/223056645650.

[28] Causa, O. and N. Woloszko (2019), “Housing, wealth accumulation and wealth distribution: evidence and stylized facts”, Economics Department - Economic Policy Committee, Working Party No. 1 on Macroeconomic and Structural Policy Analysis, http://dx.doi.org/ECO/CPE/WP1(2019)1.

[69] CBS New York (2019), Finding Affordable Housing In NYC Is Hard, It’s Almost Impossible If You’re A Senior – CBS New York, CBS New York, https://newyork.cbslocal.com/2019/06/12/affordable-housing-nyc-seniors/ (accessed on 4 July 2019).

[18] Centers for Disease Control and Prevention (United States) (2018), Childhood Lead Poisoning, https://ephtracking.cdc.gov/showCommunityDesignAddLinkChildhoodLeadPoisoning.action (accessed on 12 March 2020).

[23] Cha, O. (2013), La santé des sans-abri - Health of the homeless, Bulletin de l’Académie Nationale de Médecine.

[71] Chetty, R. et al. (2015), The Impacts of Neighborhoods on Intergenerational Mobility: Childhood Exposure Effects and County-Level Estimates*, https://scholar.harvard.edu/files/hendren/files/nbhds_paper.pdf (accessed on 17 June 2019).

[33] Chetty, R. and N. Hendren (2018), “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects*”, The Quarterly Journal of Economics, Vol. 133/3, pp. 1107-1162, http://dx.doi.org/10.1093/qje/qjy007.

[27] Clarke, R., R. Fernandez and S. Königs (forthcoming), Inequalities in household wealth: Drivers and policy implications, OECD Publising, Paris.

[34] Coley, R. et al. (2013), “Relations between housing characteristics and the well-being of low-income children and adolescents.”, Developmental Psychology, Vol. 49/9, pp. 1775-1789, http://dx.doi.org/10.1037/a0031033.

[30] Cournède, B., O. Denk and P. Hoeller (2015), “Finance and Inclusive Growth”, OECD Economic Policy Papers, No. 14, OECD Publishing, Paris, https://dx.doi.org/10.1787/5js06pbhf28s-en.

[42] Crawford, C., L. Macmillan and A. Vignoles (2017), “When and why do initially high-achieving poor children fall behind?”, Oxford Review of Education, Vol. 43/1, pp. 88-108, http://dx.doi.org/10.1080/03054985.2016.1240672.

[51] Cribb, J., A. Hood and J. Hoyle (2018), The decline of homeownership among young adults, The Institute for Fiscal Studies, https://www.ifs.org.uk/uploads/publications/bns/BN224.pdf (accessed on 5 July 2019).

[56] Dotti Sani Collegio Carlo Alberto, G. et al. (2018), “Two hearts and a loan? Mortgages, employment insecurity and earnings among young couples in six European countries”, Urban Studies Journal Limited, Vol. 55/11, pp. 2451-2469, http://dx.doi.org/10.1177/0042098017717211.

[70] Eriksen, M., N. Greenhalgh-Stanley and G. Engelhardt (2015), “Home safety, accessibility, and elderly health: Evidence from falls”, Journal of Urban Economics, Vol. 87, pp. 14-24, http://dx.doi.org/10.1016/J.JUE.2015.02.003.

[35] Evans, G., H. Saltzman and J. Cooperman (2001), “Housing Quality and Children’s Socioemotional Health”, Environment and Behavior, Vol. 33/3, pp. 389-399, http://dx.doi.org/10.1177/00139160121973043.

[15] Fisk, W., Q. Lei-Gomez and M. Mendell (2007), “Meta-analyses of the associations of respiratory health effects with dampness and mold in homes”, Indoor Air, Vol. 17/4, pp. 284-296, http://dx.doi.org/10.1111/j.1600-0668.2007.00475.x.

[66] Fondation Abbé Pierre (2019), L’état du mal-logement en France 2019 : Rapport annuel #24, https://www.fondation-abbe-pierre.fr/documents/pdf/rapport_complet_etat_du_mal_logement_2019_def_web.pdf (accessed on 14 May 2019).

[11] Fuller-Thomson, E., J. Hulchanski and S. Hwang (2000), “The housing/health relationship: What do we know?”, Reviews on environmental health, Vol. 15/1-2, pp. 109-33, http://www.ncbi.nlm.nih.gov/pubmed/10939088 (accessed on 17 June 2019).

[31] Gould Ellen, I. and S. Dastrup (2012), Housing and the Great Recession, The Russel Sage Foundation and the Stanford Center on Poverty and Inequality.

[67] Government of Canada (2019), Highlights of the National Shelter Study 2005 to 2016 - Canada.ca, https://www.canada.ca/en/employment-social-development/programs/homelessness/reports-shelter-2016.html#h4 (accessed on 17 December 2019).

[4] Hulse, K., S. Parkinson and C. Martin (2018), “Inquiry into the future of the private rental sector”, AHURI Final Report 303, http://dx.doi.org/10.18408/ahuri-5112001.

[25] Ivers, J. et al. (2019), “Five-year standardised mortality ratios in a cohort of homeless people in Dublin.”, BMJ open, Vol. 9/1, p. e023010, http://dx.doi.org/10.1136/bmjopen-2018-023010.

[22] Jelleyman, T. and N. Spencer (2008), “Residential mobility in childhood and health outcomes: a systematic review”, J Epidemiol Community Health, Vol. 62, pp. 584-592, http://dx.doi.org/10.1136/jech.2007.060103.

[29] Kusisto, L. (2015), Many Who Lost Homes to Foreclosure in Last Decade Won’t Return — NAR, https://www.wsj.com/articles/many-who-lost-homes-to-foreclosure-in-last-decade-wont-return-nar-1429548640.

[49] Lennartz, C., R. Arundel and R. Ronald (2016), “Younger Adults and Homeownership in Europe Through the Global Financial Crisis”, Population, Space and Place, Vol. 22/8, pp. 823-835, http://dx.doi.org/10.1002/psp.1961.

[12] Mackenbach, J. and P. Howden-Chapman (2002), “Houses, neighbourhoods and health”, European Journal of Public Health, Vol. 12, https://academic.oup.com/eurpub/article-abstract/12/3/161/497840 (accessed on 17 June 2019).

[36] Marcal, K. and P. Fowler (2015), Housing and Child Well-Being, Center for Social Development, George Warren Brown School of Social Work, https://openscholarship.wustl.edu/cgi/viewcontent.cgi?article=1805&context=csd_research (accessed on 15 July 2019).

[46] Massey, D., J. Rothwell and T. Domina (2009), “The Changing Bases of Segregation in the United States”, Annals of the American Academy of Political and Social Science 626, p. 1, http://dx.doi.org/10.1177/0002716209343558.

[57] Meen, G. (2018), How should housing affordability be measured?, UK Collaborative Centre for Housing Evidence, http://housingevidence.ac.uk/wp-content/uploads/2018/09/R2018_02_01_How_to_measure_affordability.pdf (accessed on 22 July 2019).

[61] OECD (2020), Better data and policies to fight homelessness in the OECD. Policy Brief on Affordable Housing, OECD Publishing, Paris, http://oe.cd/homelessness-2020. (accessed on 16 March 2020).

[8] OECD (2019), Affordable Housing Database - OECD, http://www.oecd.org/social/affordable-housing-database.htm (accessed on 4 December 2018).

[63] OECD (2019), Changing the Odds for Vulnerable Children: Building Opportunities and Resilience, OECD Publishing, Paris, https://dx.doi.org/10.1787/a2e8796c-en.

[6] OECD (2019), OECD Affordable Housing Database, http://www.oecd.org/social/affordable-housing-database/.

[37] OECD (2019), OECD Child Well-Being Data Portal, http://www.oecd.org/els/family/child-well-being/data/ (accessed on 14 May 2019).

[54] OECD (2019), Risks that Matter, https://www.oecd.org/els/soc/Risks-That-Matter-2018-Main-Findings.pdf (accessed on 2 May 2019).

[47] OECD (2019), Society at a Glance 2019: OECD Social Indicators, https://doi.org/10.1787/soc_glance-2019-en (accessed on 12 June 2019).

[7] OECD (2019), Under Pressure: The Squeezed Middle Class, OECD Publishing, Paris, https://dx.doi.org/10.1787/689afed1-en.

[40] OECD (2018), A Broken Social Elevator? How to Promote Social Mobility, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264301085-en.

[44] OECD (2018), Divided Cities: Understanding Intra-urban Inequalities, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264300385-en.

[19] OECD (2018), Inclusive Growth in Seoul, Korea, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264290198-en.

[50] OECD (2018), OECD Regions and Cities at a Glance 2018, OECD Publishing, Paris, https://dx.doi.org/10.1787/reg_cit_glance-2018-en.

[39] OECD (2017), Educational Opportunity for All: Overcoming Inequality throughout the Life Course, Educational Research and Innovation, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264287457-en.

[58] OECD (2017), Preventing Ageing Unequally, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264279087-en.

[38] OECD (2016), Making Cities Work for All: Data and Actions for Inclusive Growth, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264263260-en.

[48] OECD (2016), Society at a Glance 2016: OECD Social Indicators, https://doi.org/10.1787/9789264261488-en (accessed on 20 June 2019).

[20] OECD (2016), The Economic Consequences of Outdoor Air Pollution, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264257474-en.

[41] OECD (2012), Equity and Quality in Education: Supporting Disadvantaged Students and Schools, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264130852-en.

[5] OECD et al. (2013), Handbook on Residential Property Prices Indices (RPPIs), http://publications.europa.eu/others/agents/index_en.htm (accessed on 16 March 2020).

[24] Romaszko, J. et al. (2017), “Mortality among the homeless: Causes and meteorological relationships.”, PloS one, Vol. 12/12, p. e0189938, http://dx.doi.org/10.1371/journal.pone.0189938.

[1] Scanlon, K. and C. Whitehead (2004), International trends in housing tenure and mortgage finance, Council of Mortgage Lenders, http://www.urbancenter.utoronto.ca/pdfs/elibrary/CML_Inter-Trends-Housing-Te.pdf (accessed on 8 July 2019).

[59] Slaug, B. et al. (2017), “Improved Housing Accessibility for Older People in Sweden and Germany: Short Term Costs and Long-Term Gains”, International Journal of Environmental Research and Public Health, Vol. 14/964, http://dx.doi.org/10.3390/ijerph14090964.

[53] Social Mobility Commission (2016), State of the Nation 2016: Social Mobility in Great Britain, http://www.gov.uk/government/publications (accessed on 5 July 2019).

[32] Thévenon, O. (2018), “Child poverty in the OECD: Trends, determinants and policies to tackle it”, OECD Social, Employment and Migration Working Papers 218, https://doi.org/10.1787/c69de229-en.

[62] US Department of Housing and Urban Development (HUD) (2018), The 2018 Annual Homeless Assessment Report (AHAR) to Congress, Part 1: Point-in-Time Estimates of Homelessness, https://files.hudexchange.info/resources/documents/2018-AHAR-Part-1.pdf (accessed on 21 June 2019).

[45] van Ham, M. et al. (2016), “Spatial Segregation and Socio-Economic Mobility in European Cities”, IZA Discussion Paper No. 10277, https://www.oecd.org/regional/makingcities-work-for-all-9789264263260-en.htm (accessed on 18 June 2019).

[65] VIVE - Knowledge of Welfare The National Center for Welfare Research and Analysis (2019), Homelessness in Denmark 2019: National mapping.

[13] Wanyeki, I. et al. (2006), “Dwellings, crowding, and tuberculosis in Montreal”, Social Science & Medicine, Vol. 63/2, pp. 501-511, http://dx.doi.org/10.1016/J.SOCSCIMED.2005.12.015.

[64] Warren, E. (2015), “Housing Insecurity, Maternal Stress, and Child Maltreatment: An Application of the Family Stress Model”, Social Service Review, Vol. 89/1, https://www.journals.uchicago.edu/doi/full/10.1086/680043.

[3] Whitehead, C. and P. Williams (2017), “Changes in the regulation and control of mortgage markets and access to owner-occupation among younger households”, OECD Social, Employment and Migration Working Papers, No. 196, OECD Publishing, Paris, https://dx.doi.org/10.1787/e16ab00e-en.

[21] World Health Organisation (WHO) (2018), Global Status Report on Road Safety, WHO, https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/ (accessed on 5 September 2019).

[10] World Health Organization (WHO) (2018), WHO Housing and Health Guidelines, https://www.who.int/sustainable-development/publications/housing-health-guidelines/en/ (accessed on 17 June 2019).

Notes

← 1.  Governments identify groups at risk of housing exclusion differently. For instance, in the United States, some groups (determined by colour, disability, familial status, national origin, race or ethnicity, religion or gender) are legally protected from housing discrimination, as defined in the Fair Housing Act. Other countries identify specific target groups to be supported by housing policies: female head of households, people who have been displaced or lost their homes due to natural disasters (Brazil); people with disabilities, seniors, victims of domestic violence, indigenous communities (Canada); people living in extreme poverty, people who have been displaced, including by national disasters, people living in areas at risk (Colombia); victims of gender violence or victims of terrorism (Spain); low-income households, the homeless, seniors, and households with children (Germany); young families (Lithuania); people with disabilities, seniors, the homeless (Luxembourg); victims of natural disasters, low-income households, seniors, people with disabilities, people caring for others, among others (Latvia); low- and moderate-income households (Poland); low-income households, young people, seniors, victims of domestic violence, the homeless (Portugal) (based on country responses to the 2019 OECD Questionnaire on Affordable and Social Housing, QuASH)).

← 2. Please refer to (OECD, 2019[7]) for further details on the consumption estimates cited in this report.

← 3. Austria, Belgium, the Czech Republic, Finland, Germany, Greece, Hungary, Ireland, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden and Turkey.

← 4. Austria, Belgium, Finland, Germany, Greece, Ireland, Luxembourg, the Netherlands, Portugal and Sweden.

← 5. There are significant cross-national differences in housing spending trends among households. Since 2005, the share of household spending on housing has increased in all OECD countries for which estimates are available, yet the pace of the increase varies considerably across countries. This points to differences in how the global economic crisis affected housing consumption in different countries, and that national policies make a difference. It is also important to note that country averages hide huge within-country differences in levels of household spending on housing, as well as in their evolution over time, which have significant effects on the impact of housing on inequality. More research is needed to understand the drivers of these differences across and within countries.

← 6. Housing costs can refer to: i) a narrow definition based on rent and mortgage costs (principal repayment and mortgage interest); or ii) a wider definition that also includes costs of mandatory services and charges, regular maintenance and repair, taxes and utilities, also referred to as “total housing costs.”

← 7. Austria, Belgium, the Czech Republic, Finland, Germany, Greece, Hungary, Ireland, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden and Turkey.

← 8. Austria, Belgium, Finland, Germany, Greece, Ireland, Luxembourg, the Netherlands, Portugal and Sweden.

← 9. The authors define higher opportunity neighbourhoods as a commuting zone or county in which the children whose families are already living in the neighbourhood (e.g. sitting residents) have higher average incomes as adults (Chetty et al., 2015[71]).

← 10. Australia, Brazil, Canada, Denmark, France, Ireland, Mexico, the Netherlands, New Zealand, South Africa, the United Kingdom, the United States.

← 11. The net migration rate is the difference between the number of immigrants and the number of emigrants (people leaving an area).

← 12. The survey, conducted for the first time in two waves in the spring and autumn of 2018, draws on a representative sample of 22 000 people aged 18 to 70 years old in 21 OECD countries: Austria, Belgium, Canada, Chile, Denmark, Estonia, Finland, France, Germany, Greece, Israel, Ireland, Italy, Lithuania, Mexico, the Netherlands, Norway, Poland, Portugal, Slovenia and the United States. Respondents are asked about their social and economic concerns, how well they think government responds to their needs and expectations, and what policies they would like to see in the future.

← 13. This estimate excludes individuals living in homes that are owned outright (i.e. there is no longer a mortgage to pay off) in order to better assess the share of individuals who, among those who have something to pay for housing, pay more than 40% of their disposable income.

← 14. One study from the United States found that the presence of safety and accessibility features reduced the likelihood of a serious fall among the elderly by 20 percentage points; in addition, estimates suggested that investments in home safety and accessibility features in housing were largely offset by a nearly equal reduction in medical costs (Eriksen, Greenhalgh-Stanley and Engelhardt, 2015[70]).

← 15. The OECD Affordable Housing Database (indicators HC3.1 and HC3.2) and the OECD Policy Brief, “Better data and policies to fight homelessness in the OECD” (OECD, 2020[61]) document recent cross-national trends in homelessness and discuss the data and definitional constraints in measuring homelessness across countries.

← 16. There is no internationally agreed upon definition of homelessness, and countries do not define or count the homeless in the same way. Authorities may use administrative data (such as registries from shelters and local authorities), point-in-time estimates (such as street counts, which are often conducted annually at a given time of year), or a combination of both. Both methods provide only a partial picture of homelessness, and neither effectively captures the “hidden homeless” – people who may not be visibly homeless or appear in official statistics, either because they do not seek formal support or they seek shelter with family or friends, or live in their car. Definitional differences drive some of the variation in the reported incidence of homelessness across countries; these differences hamper international comparison and an understanding of the differences in homelessness rates and risks across countries. There are also a number of challenges in the scope, frequency, consistency and methods of data collection that might affect measuring the full extent of homelessness. For further details, refer to indicators HC3.1 and HC3.2 in (OECD, 2019[6]) and (OECD, 2020[61]).

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