Housing features prominently not only in household expenditure budgets but also in their balance sheets as it accounts for the lion’s share of household assets and liabilities. This chapter delivers new evidence on the link between homeownership and wealth inequality. It assesses the socio-economic drivers for the different housing tenures and discusses the policy implications.
Brick by Brick
Building Better Housing Policies
5. Measuring the Role of Housing in the Distribution of Wealth
Abstract
Main lessons
Housing is a fundamental driver of the accumulation and the distribution of assets, liabilities and wealth over the lifecycle and across generations.1 The contribution of housing to wealth inequality varies significantly across countries, yet the following facts stand out from the data:
Wealth inequality is much higher than income inequality, in part reflecting lifecycle effects as wealth accumulates over time.
There is a strong negative cross-country association between homeownership and wealth inequality. Low homeownership countries exhibit high wealth inequality, even when income inequality is low.
Housing tends to equalise the distribution of wealth because it is the most important asset in household balance sheets and it is more equally distributed than other assets like financial assets: housing represents in relative terms a much higher source of wealth in the middle than at the top of the distribution.
Access to mortgage markets allows credit-constrained households a better chance of owning their own home, but it entails risks:
Housing-related debt is the most important liability in households’ portfolios, particularly for young homeowners and homeowners at the bottom of the distribution. OECD countries exhibit stark variation in the extent to which households hold mortgage debt, ranging from almost half to less than a tenth.
Mortgage debt is both an opportunity and a risk. While it allows households, especially those with little initial assets, to accumulate wealth it can expose households, especially those at the bottom of the distribution, to economic and social vulnerabilities.
Housing wealth: Trends, drivers and policies
Quantify the importance of housing wealth in household balance sheets
Housing represents the largest asset in household portfolios
Housing and wealth distribution warrants attention for several reasons. Housing is the largest asset in household portfolios. It is therefore a fundamental driver of the accumulation and the distribution of assets and net wealth over the lifecycle and across generations, hence contributing to wealth inequality. Assessing housing from a wealth distribution perspective is all the more important in a context where income inequality has been rising in a number of countries, where the capital share of income has increased relative to that of labour, and where wealth inequality is much higher than income inequality (Figure 5.1) – even though the latter partly reflects lifecycle effects as wealth accumulates over time.2
Figure 5.1. Wealth inequality is much higher than income inequality
Top 10% shares, 2015 or latest available year
Note: This chart shows the top 10% of households in wealth distribution, and the top 10% of individuals in the income distribution. Available wealth inequality measures harmonised across countries do not include occupational or public pensions (see Box 5.1). Including net pension wealth can substantially change wealth inequality measures. See a publication from the Ministry of Economic Affairs and the Interior (2018[1]) for a quantification in the case of Denmark.
Source: OECD Wealth Distribution Database (oe.cd/wealth), OECD Income Distribution database (https://stats.oecd.org/Index.aspx?DatasetCode=IDD).
Housing debt is the largest liability in household portfolios
Housing is also the largest liability in household balance sheets, because most homeowners borrow to finance the purchase of their homes. Housing-related debt allows households with low income and little assets, for example young households, to accumulate wealth. The benefits of leverage need to be balanced against its risks, and that is one major lesson from the Global Financial Crisis. Assessing housing from a wealth distribution perspective requires looking at housing assets and liabilities, with particular attention to the bottom of the income and wealth distributions (Box 5.1).
Box 5.1. Data sources to analyse housing and wealth distribution
The OECD relies on a dedicated statistical database, the OECD Wealth Distribution Database (WDD), to monitor and compare wealth inequality across countries. This database is based on national sources (household surveys and administrative records) and on common definitions, classifications and data-treatments. Estimates referring to the most recent year (around 2015) are currently available for 28 OECD countries, while estimates referring to more than one year are available for 19 countries. All the indicators available through this database are based on the concept of “household net wealth” as defined in the OECD Guidelines for Micro Statistics on Household Wealth (OECD, 2013[2]), i.e. the value of financial and non-financial assets net of the value of liabilities held by private households resident in the country, with no adjustment made to reflect differences in household size. The method of data collection used for the OECD WDD aims to maximise international comparability as well as inter-temporal consistency of data. This is achieved by a common set of protocols and statistical conventions (e.g. on wealth concepts and components) to derive comparable estimates. Public and occupational pension plans are not included in financial assets and thus neither in household net wealth. International guidelines on micro statistics on household wealth require to maintain consistency with the definition of financial assets in the system of national accounts (SNA), which reflects the view that reliable estimates of pension entitlement in social security schemes may not be readily available. For more information, see http://www.oecd.org/sdd/OECD-wealth-distribution-database-metadata.pdf and Balestra and Tonkin (2018[3]).
The use of the semi-aggregated data from WDD is complemented with micro data. One main source for this paper is the Household Finance and Consumption Survey (HFCS) database from the European Central Bank, second wave (2014). This dataset provides individual and household data collected in a harmonised way in euro area countries as well as Hungary and Poland. The main aim of the HFCS is to gather micro-level structural information on euro area households' assets and liabilities e.g. real assets and their financing, liabilities/credit constraints, private businesses, financial assets, intergenerational transfers and gifts, and consumption and saving. The survey also collects other distributional-relevant information in particular gross income, labour market status, education and demographic characteristics. The data allow to analyse the joint distribution of housing wealth, net wealth and income, while taking into account socio-demographic effects. The HFCS-based microdata analysis is complemented with the Luxembourg Wealth Study (LWS) for a number of non-euro area countries (Australia, Canada, Norway, the United Kingdom and the United States).
Analyse the link between housing and wealth inequality
There is a strong negative association between homeownership and wealth inequality (Figure 5.2). High (low) homeownership countries tend to display low (high) wealth inequality, because housing wealth is much more equally distributed than non-housing wealth. This can be seen by comparing inequality in net total wealth, which includes all households’ assets and liabilities, and inequality in net housing wealth, which includes only housing assets (defined here primary residence) and liabilities. Top 10% households receive on average across countries around 55% of total net wealth, against around 35% of total net housing wealth (Figure 5.3). This is because non-housing sources of wealth, such as financial wealth, are more unequally distributed and more important at the top of the distribution.
Housing equalises the net wealth distribution. Indeed, excluding housing from net wealth equalises the wealth distribution across countries. It implies a significant increase in measured wealth inequality, around one-quarter on average across countries (Causa, Woloszko and Leite, 2019[4]).
Figure 5.2. High-homeownership countries tend to exhibit low wealth inequality
Source: OECD Wealth Distribution Database (oe.cd/wealth). Available wealth inequality measures harmonised across countries do not include occupational or public pensions (see Box 5.1).
Figure 5.3. Housing wealth is much more equally distributed than non-housing wealth
Inequality in net housing wealth and in net total wealth, top 10% shares
Note: Households are ranked by net wealth. Available wealth inequality measures harmonised across countries do not include occupational or public pensions (see Box 5.1).
Source: OECD Wealth Distribution Database (oe.cd/wealth).
Housing tenure varies largely across countries
OECD countries exhibit great variation in the housing tenure mix (i.e. in homeownership rates and in the relative proportion between outright owners and owners with a mortgage) (see OECD Affordable Housing Database). Homeownership rates are highest in the Slovak Republic, Hungary and Spain and lowest in Germany, Denmark and Austria (Figure 5.4). Such cross-country differences reflect historical legacies, exceptionally high homeownership rates in Eastern European countries as a result of mass privatisation at submarket prices to sitting tenants. Another part reflects differences in households’ socio-demographic characteristics, notably the structure of households in terms of age and size. In the vast majority of countries, households composed of retirement age members and larger households are more likely to be owners.
In contrast, households composed of younger members and single-person households are more likely to be renters. Among owners, households composed of retirement age members are more likely to be outright owners relative to younger households (Causa, Woloszko and Leite (2019[4]). Moreover, countries where the average homeownership rate is high exhibit a low difference in homeownership between low and high-income households, while the reverse tends to apply in countries where the average homeownership rate is low (Figure 5.4).
Figure 5.4. Homeownership is more equally distributed across income groups in high-homeownership countries
Homeownership across the income distribution
Source: OECD Wealth Distribution Database (oe.cd/wealth). Household Economic Survey database for New Zealand.
Housing features prominently in household balance sheets
Housing is the highest ranked asset in households’ portfolios (Figure 5.5). It accounts on average for around one-half of total assets, ranging from around 70% in the Slovak Republic to around 25% in Germany. The share of the value of secondary residences (“other real estate”) in total assets tends to be relatively high, for instance higher than that of financial assets in a number of countries, further highlighting the importance of real estate for household wealth. Also, housing is the chief asset of the “middle class”, or households in the middle three quintiles of the income or wealth distribution, amounting to over 60% of assets in the majority of OECD countries. Moreover, housing is a relatively less important asset at the very top of the distribution. On average, it represents around one-quarter of total assets among households at the top 1% of the net wealth distribution. Average figures mask substantive cross-country differences, part of which may reflect policy factors, e.g. concessionary tax treatment of housing relative to other assets and their effects on developments in house prices relative to prices of other assets.
Figure 5.5. Housing is the chief asset of the middle class
Panel A. Asset decomposition of households’ portfolio
Note: In this chart due to data availability income refers to gross income, that is, disposable income less income taxes.
Source: Data from HFCS and LWS.
Weigh opportunities and risks of housing debt
Mortgage debt is the largest component of household debt portfolios (Figure 5.6). From an economic resilience perspective, monitoring household debt and housing market developments requires a careful focus on mortgage debt, as discussed in Chapter 3. From a distributional perspective, mortgage debt entails opportunities but also risks, particularly for vulnerable households, as witnessed during the financial crisis (Mian and Sufi, 2011[5]).
Figure 5.6. Mortgage debt is the largest part of household debt
Note: How to read this figure: in France, total mortgage debt represents 55% of total household debt; among households with mortgage debt, the latter represents on average 87% of the household’s total total debt. The numbers refer to principal residence debt only.
Source: OECD Wealth Distribution Database (oe.cd/wealth), HFCS database.
The proportion of households that hold a mortgage varies significantly across OECD countries (Figure 5.7). On average, around 25% of households have mortgage debt, ranging from around 10% in Slovenia and Italy to between 40 and 50% in the United States and the Netherlands. Mortgage debt shares increase with household income (Figure 5.7), as mortgage markets are regulated and bank lending is conditional on household repayment capacity, measured primarily by their level of income. Yet, the link between household income and mortgage debt is somewhat steeper in some countries than in others, reflecting a variety of country-specific considerations, including differences in housing finance, not least prudential regulations, house prices, and social preferences.
Figure 5.7. Participation in mortgage markets increases with household income
Proportion of households with mortgage debt across OECD countries and in bottom and top income quintiles
Note: The numbers refer to principal residence debt only.
Source: OECD Wealth Distribution Database (oe.cd/wealth).
Access to mortgage debt is a key driver of homeownership
Access to mortgage debt for young household is likely to be one key driver of homeownership for this group, given their relatively low current wealth and income. Indeed, across OECD countries, the higher the participation in mortgage markets among young households, the lower is the difference in homeownership between the young and the rest of the population (i.e. the homeownership age spread) (Figure 5.8). Young households are relatively more sensitive than other groups to policy settings affecting homeownership, in particular mortgage market regulations (Andrews, Caldera Sánchez and Johansson, 2011[6]). Cross-country differences in homeownership between young people and the rest of the population are also likely to reflect differences in housing affordability.
Figure 5.8. Access to mortgage finance is particularly important for young cohorts
Note: The numbers refer to principal residence debt only.
Source: OECD Wealth Distribution Database (oe.cd/wealth).
High housing debt exposes households to financial vulnerabilities
From a household perspective, mortgage debt is both an opportunity and a risk. On the one hand, it allows households, especially young households and those with little initial assets to accumulate wealth. On the other hand, it can expose households, especially those at the bottom of the distribution, to financial risks in the event of income losses, of house price declines as well as interest rates increases. Indeed, the expansion in mortgages over the last decades, in particular prior to the Global Financial Crisis, led to an increase in the debt-to-income ratios for households with mortgage debt. This ratio is well above 100% in most OECD countries and it exceeds 200% in some of them such as Portugal, Spain and the Netherlands (Figure 5.9). This is likely to partly reflect, at least for the Netherlands, the prevalence of interest-only and contractual savings mortgages, which delay repayment of the principal (ECB, 2009[7]). Households at the bottom of the income distribution are particularly vulnerable, with debt-to-income ratios exceeding the conventional at-risk threshold value of 300%. Associated risks seems to be particularly significant in some countries, including Australia and Canada, reflecting the strong increase in house prices over the last decade, especially in Canada.
At the current juncture, the COVID‑19 crisis is creating mortgage-related financial vulnerability among households, in particular due to falling income as a result of job or earnings loss. Liquidity constraints prevent households, at least temporarily, from paying back their debt. Low- income homeowners are likely to be particularly vulnerable. To address this issue and prevent social hardship, some OECD countries including Italy, Portugal, Spain and the United Kingdom temporarily suspended mortgage payments (see Box 1.7 in Chapter 1).
Figure 5.9. Mortgage debt can make low-income households financially vulnerable
Debt-to-income ratio among borrowers, median
Note: The numbers refer to principal residence debt only. These ratios are calculated only for households with principal residence mortgages. The calculation is done only in cases where the number of observations exceeds 50, which is why some data is not shown for bottom income and wealth households. In this chart due to data availability income refers to gross income, that is, disposable income less income taxes.
Source: HFCS database, LWS database.
Mortgage-related policies need to strike the right balance between allowing access to mortgage debt as an opportunity to accumulate wealth, and preventing the building up of excessive leverage with potential large economic and social risks. Indeed, borrower-based prudential regulations involve a trade-off between stability and distributional concerns as borrowers with high loan-to-value ratios are concentrated at the bottom of the wealth distribution, and borrowers with high loan-to-income ratios at the bottom of the income distribution. Subsequently, caps on loan-to-value and debt-to-income may exclude low-income and low-wealth households from the mortgage market. The down-payment constraint resulting from more restrictive caps will be particularly binding for first-time buyers and liquidity-constrained households such as younger and low-income households.
Excessive expansions of mortgage credit can trigger higher house price increases, which reduce housing affordability, and thus price out low-income households from the market. By curbing the joint increase of credit volume and house prices during leverage cycle booms, prudential caps may enhance housing affordability. This can enhance microeconomic resilience, especially for those households most vulnerable to price and income shocks. As a result, from both a macroeconomic and a distributional perspective, long-term positive gains from borrower-based prudential policies are likely to outweigh short-term costs.
References
[6] Andrews, D., A. Caldera Sánchez and Å. Johansson (2011), “Housing Markets and Structural Policies in OECD Countries”, OECD Economics Department Working Papers, No. 836, OECD Publishing, Paris, https://dx.doi.org/10.1787/5kgk8t2k9vf3-en.
[3] Balestra and Tonkin (2018), Inequalities in household wealth across OECD countries: Evidence from the OECD Wealth Distribution Database.
[4] Causa, O., N. Woloszko and D. Leite (2019), “Housing, Wealth Accumulation and Wealth Distribution: Evidence and Stylized Facts”, OECD Economics Department Working Papers, No. 1588.
[7] ECB (2009), Housing Finance in the euro area, European Central bank, http://www.ecb.europa.eu.
[5] Mian, A. and A. Sufi (2011), “House Prices, Home Equity–Based Borrowing, and the US Household Leverage Crisis”, American Economic Review, Vol. 101/5, pp. 2132-2156, http://dx.doi.org/10.1257/aer.101.5.2132.
[1] Ministry of Economic Affair (2018), Distribution and Incentives (Fordeling og incitamenter).
[2] OECD (2013), OECD Guidelines for Micro Statistics on Household Wealth.