Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 2 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 3 https://isni.org/isni/0000000404811396, International Monetary Fund

Annex 1. Selected Sources of Data on Rental Costs

Eurostat EU Statistics on Income and Living Conditions

The EU Statistics on Income and Living Conditions (EU-SILC) is the reference source for comparative statistics on income distribution and social inclusion in the European Union (EU). EU-SILC was launched in 2003 on the basis of an informal agreement between Eurostat and six Member States (Austria, Belgium, Denmark, Greece, Ireland, and Luxembourg) and Norway. It was formally launched in 2004 in 15 countries and expanded in 2005 to cover all of the then EU-25 Member States, together with Norway and Iceland. Bulgaria launched EU-SILC in 2006 while Romania, Switzerland, and Turkey introduced the survey in 2007. Germany is included in EU-SILC but is excluded from the analysis in this paper due lack of access to the microdata administered by the German Federal Statistical Office.

EU-SILC provides two types of annual data:

  • Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion, and other living conditions

  • Longitudinal data pertaining to individual-level changes over time, observed periodically over a four-year period

EU-SILC focuses mainly on income. Detailed data are collected on income components, mostly on personal income, although a few household income components are included. Information on social exclusion, housing conditions, labor, education, and health information is also obtained.

The reference population in includes all private households and their current members residing in the territory of the countries at the time of data collection. Persons living in collective households and in institutions are generally excluded from the target population. Some small parts of the national territory amounting to no more than 2 percent of the national population, and the national territories may be excluded. All household members are surveyed, but only those aged 16 years and older are interviewed.

As it is usual in empirical studies based on microdata, for this paper some observations were removed at the outset following a number of criteria. For example, households with negative or zero gross disposable income were ignored. Further details are available upon request. While most of the analysis relies on data at the household level, some of these data were matched with personal-level information (for instance, on age and citizenship).

To assess rental affordability, unless otherwise mentioned, this paper focuses on households’ equivalized disposable income—that is, the total income (including housing allowances) after tax and other deductions that is available for spending or saving, divided by the number of household members converted into equalized adults. A similar adjustment for household size and non-response factors is also applied to the variable that captures rental costs.1

For the EU-SILC-based figures in Chapters 2 and 3, a minimum threshold of 100 observations is used to report the results. Related to this threshold, countries may be excluded from figures if they report insufficient granular data for a relevant category of analysis; for example, in figures depicting results for the first, third, and fifth income quintiles, countries are included only if data are available for at least two of these three income quintiles (whereas if data are only available for one of the income quintiles, then a country is simply dropped from the figure).

For additional information, see: https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions

EARS: Estate Agency Rent Surveys

These surveys are carried out in collaboration among Eurostat, the International Service for Remunerations and Pensions (ISRP) at the OECD, and the National Statistical Offices. They are part of wider work conducted to compare the relative cost of living of international civil servants between their place of employment and that of Brussels.

EARS rely on rental surveys carried out annually, around mid-year, through face-to-face interviews with real estate agencies. Eurostat and ISRP are the overall coordinators of surveys, aiming to ensure a consistent approach across cities and years. The sample sizes are undisclosed, but a valid and representative sample is ensured across all cities.

The data reflect transaction-based monthly rental prices, excluding charges and utilities, for an unfurnished property. The frequency is annual, and the data start in 2003. It covers up to 54 cities (35 of them in advanced economies, as per the WEO 2019 classification).

Annex Figure 1.1.
Annex Figure 1.1.

Advanced Europe, Cities: Annual Real Rental Price Growth

(Percent)

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EARS (two-bedroom apartments); IMF, World Economic Outlook database; and IMF staff calculations based on selected cities.

EARS include rental price data for 1-, 2- and 3-bedroom apartments, nondetached houses, and detached houses. Annex Figure 1.1 depicts the rental price-growth dispersion from 2004 to 2013 across 24 cities in advanced Europe, based on 2-bedroom apartments. (Though not shown, the median price growth in 2019 was slightly higher than in 2018.) In general, the analysis in this paper focuses on 2-bedroom apartments, assumed as the most representative dwelling, but the results based on the other types of dwelling were often robust. The quality of the dwellings included in EARS is “good to very good, but not luxurious,” and their general characteristics are narrowly defined. Although these characteristics are reviewed annually, at least some of them (such as size) have remained stable over time.

The neighborhoods surveyed for EARS are residential areas of good quality, favored by expatriates and professional workers such as international civil servants, university staff, doctors, managers, etc., who pay their rent themselves (that is, not paid by their employers). These neighborhoods are reviewed annually, but the selection has remained stable over time.

For the analysis in this paper, one important caveat is in order. Since EARS focus on a specific subset of the rental market, as described above, at least for some cities the data may not necessarily provide an accurate representation of the overall rental market or its low-income segment. Related to this limitation, there could be discrepancies with other data sources on city-level rental prices. Illustratively, for the case of London, the EARS data shown in Chapter 3 point to a decline in real rental prices from 2013 to 2018; whereas, by contrast, data from the UK Office for National Statistics (Experimental Index of Private Housing Rental Prices) point to a moderate increase in such prices over the same period.

For additional information, see: https://ec.europa.eu/eurostat/web/civil-servants-remuneration/estate-agency-rent-surveys

OECD Analytical House Price Indicators

Rental prices in this OECD database are based on consumer price indices for actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another is chosen—usually, the CPI aggregate for housing including actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and maintenance and repair of the dwelling (COICOP 04.3). The data are originally in quarterly frequency (seasonally adjusted), and are averaged to convert to annual frequency. The data cover OECD countries and, where available, start in 1959.

Arguably, these CPIs imperfectly reflect ongoing market rental prices, not least because the data also capture subsidized prices and slow-moving prices from multiyear contracts.

Annex 2. The Macroeconomic Role of Rental Markets

Rental markets can address multiple social needs. Whether temporarily or permanently, renting is a valuable choice for individuals and families who face liquidity constraints. To the extent that homeownership may constitute a final objective as a preferable form of savings and wealth accumulation, renting can be conceived as a vehicle allowing households to make informed decisions about where and when to buy, while helping build savings necessary for home purchase in the transition. The rental market lends itself naturally to urban policies aimed at improving the social mix of neighborhoods and promoting inclusion.1

Beyond enhancing social inclusion directly, key macroeconomic benefits from rental housing arise mainly from two channels. First, rental housing promotes labor mobility, including by allowing people with matching skills to move to areas where jobs are available, thereby lowering structural unemployment and enhancing productivity and potential growth (see, for example, Hsieh and Moretti 2017, Czerniak and Rubaszek 2018). Second, compared to housing markets, rental markets tend to be less susceptive to the asset-price boom-bust cycle and can thereby contribute to financial stability and a smoother business cycle (Gallin 2008, Ambrose, Eichholtz, and Lindenthal 2013). Such a stabilization “side benefit” would arise mainly when the policies primarily aimed at financial stability, such as macroprudential and supervisory measures, are not fully effective.

A sizable supply of rental housing across locations fosters labor mobility, which in turn might reduce structural unemployment.2 Transitional labor markets warrant flexible accommodation to optimize resource allocation across regions and skills, in particular in the transition from education to employment for the low-skilled and young individuals. Absent language and other barriers, matching of skills across regions and countries and, more generally, employment opportunities, are also improved if families are not locked into ownership. Indeed, an ad-hoc EU-SILC survey conducted in 2012, which surveyed if households had moved during the past five years, shows that countries with a larger share of rental housing appear to have had a higher residential mobility (Annex Figure 2.1, panel 1). Plotting the share of households moved and unemployment rates shows that countries with larger residential mobility tended to have lower unemployment rates (Annex Figure 2.1, panel 2). This finding mirrors “the Oswald hypothesis” (Oswald 1996, 1999), that high rates of homeownership can lead to lower employment, higher unemployment, and lower wages.

Annex Figure 2.1.
Annex Figure 2.1.

Rental Market, Internal Mobility Rates, and Unemployment1

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: Eurostat; EU-SILC; and IMF staff calculations.1The x-axis for panel 1 and the y-axis for panel 2 refer to the share of households that moved during 2008–12. Rental dwelling as share of total dwellings is as of 2012.

Higher labor mobility can in principle also raise potential output. When affordable rental housing allows workers (youth, in particular) to move to the areas where high-skilled jobs are created, investment is stimulated, employment levels and labor productivity levels rise (Hsieh and Moretti, 2017). Indeed, the long-term average of total factor productivity (TFP) growth rates in advanced European economies tends to be higher in countries with larger rental markets (Annex Figure 2.2).

Sizable rental housing could help dampen the effect of real estate bubbles. Some studies (Gallin 2008, Ambrose, Eichholtz, and Lindenthal 2013) indicate that rental prices were less volatile than housing prices. Developed rental housing markets—such as the ones in Austria and Germany—attenuated price fluctuations in the overall housing sector (Czerniak and Rubaszek 2018). Based on EARS and Haver Analytics data, it is possible to show that in nearly all advanced European economies, the volatility of housing prices was higher than of rental prices during 2008–18 (Annex Figure 2.3, panel 1).3 Thus, while macroprudential policies are the targeted policy tool to lessen real estate price cycles, sizeable rental may have the added benefit of providing security against short-term price volatility and their macroeconomic implications. Indeed, the data show that countries with a larger rental housing share seem to have experienced lower real GDP growth volatility among advanced European economies (although the relationship is weak) (Annex Figure 2.3, panel 2). The evidence also shows that countries with larger rental housing experienced a smaller decline in growth during the global financial crisis (Annex Figure 2.3, panel 3).4 This perhaps reflects that higher labor mobility can smooth the business cycle as lower frictions (or greater flexibility) promote a faster return to the steady state and less pronounced increase in unemployment (Annex Figure 2.3, panel 4). Hence, a well-functioning affordable rental market can be an important catalyst for the economic recovery from the COVID-19 pandemic, which will likely require some relocation of resources as economies shift to more digital and greener activities.

Annex Figure 2.2.
Annex Figure 2.2.

Total Factor Productivity Growth and Rental Market Size

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; The Conference Board Total Economy Database™ (Adjusted version), April 2019; and IMF staff calculations.
Annex Figure 2.3.
Annex Figure 2.3.

Growth and Rental Market Size

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EARS; Eurostat; EU-SILC; Haver Analytics; and IMF staff calculations.Note: Panel 3 excludes Greece. Growth volatility is calculated as the standard deviation divided by the historical mean.

The interaction between sizeable rental housing markets and inequality is complex and depends on the equality measure. Higher labor mobility and lower unemployment, associated with sizeable supply of rentals across locations, would generally help improve overall social inclusion. The availability of housing accommodation in particular allows people to move to more prosperous locations (Bayoumi and Barkema 2019), possibly helping reduce income inequality. Indeed, advanced European economies with larger rental housing markets tend to have lower market-income inequality, once controlling for key factors determining income inequality—that is, per capita GDP, unemployment rate, old-age dependency ratio, the share of tertiary education, trade openness, and marginal tax rate (Annex Figure 2.4, panel 1). However, the literature (for example, Causa, Woloszko, and Leite 2019) also finds that countries with larger rental housing markets tend to have higher wealth inequality as homeownership is an efficient way to build wealth and governments also tend to provide incentives for homeownership. This finding is illustrated for advanced Europe in the scatter plot in Annex Figure 2.4, panel 2.

Annex Figure 2.4.
Annex Figure 2.4.

Inequality and Rental Housing Markets

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; and IMF staff calculations.1“Gini (after controlling for key factors)” are the country fixed effects extracted from regressing the disposable income Gini with factors that commonly explain inequality (that is, per capita income, old age dependency ratio, tax wedge, unemployment rate, education attainment, and trade openness).

Annex 3. Background Charts on Tenure Structure and Rental Affordability

Annex Figure 3.1.
Annex Figure 3.1.

Tenure Structure for the Bottom Income Quintile1

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; and IMF staff calculations.Note: In panel 1, 2017 data for Ireland, Slovakia, and the United Kingdom; 2016 data for Iceland. In panel 2, latest data point is 2018 except for: 2017 data for Ireland, Slovakia, and the United Kingdom; 2016 data for Iceland; earliest data point is 2010, except for: 2011 data for Greece, Iceland, and Italy. Data for Czech Republic reflects the rent deregulation law aimed at equalizing the rent of formerly regulated apartments with the market rate ones.1For Denmark, Netherlands, and Sweden, EU-SILC does not accurately capture the share of tenants in subsidized rental housing (see OECD 2020c). For Denmark and Netherlands, all renters at market-rate and social rental accommodations are put in the market-rate category. In Sweden, very few respondents to EU-SILC select the subsidized housing option (Salvi del Pero and others 2016).
Annex Figure 3.2.
Annex Figure 3.2.

Selected Results Based on 30-Percent Threshold to Define Overburdened Tenants

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; and IMF staff calculations.Note: For both panels in the figure, tenants are considered overburdened if they devote 30 percent or more of their household disposable income to rental payments. The baseline results of the paper use a 40 percent threshold (see Figure 9, panel 1, and Figure 1, panel 2). On the left chart, “latest year” is 2018, except for Ireland and the United Kingdom (2017), and Iceland (2016). Figure uses International Organization for Standardization (ISO) country codes.
Annex Figure 3.3.
Annex Figure 3.3.

Development of Housing Costs for Renters and Homeowners across Income Groups

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; and IMF staff calculations.Note: Solid lines represent medians. Shaded areas: lower bound = median for the bottom quintile; upper bound = median for the top quintile. Housing costs are based on a narrow definition: for homeowners it includes principal repayments and mortgage interest payments, while for renters it includes rental payments. Sample includes Austria, Belgium, Denmark, Finland, France, Greece, Italy, Luxembourg, Netherlands, Norway, Portugal, Slovenia, Spain, Sweden, and Switzerland.
Annex Figure 3.4.
Annex Figure 3.4.

Developments in Incomes and Rental Costs in the Youngest Cohort

Citation: Departmental Papers 2021, 013; 10.5089/9781513570204.087.A999

Sources: EU-SILC; and IMF staff calculations.Note: Sample includes Austria, Belgium, Denmark, Finland, France, Greece, Italy, Luxembourg, Netherlands, Norway, Portugal, Slovenia, Spain, and Switzerland.

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1

For example, the OECD’s “Framework for Policy Action on Inclusive Growth” (2018) advises that policies to enable greater equality of opportunities should also include measures that provide access to affordable housing.

2

For the United States, Albouy, Ehrlich, and Liu (2016) show that that increased pressure on housing affordability is a long-term trend. They report that the share of income spent by renters and homeowners has been on an upward trend rise since the 1970s with a sharper increase for renters. Their analysis suggests that rising rents appear to be the primary driver of the rising income share spent on rental housing..

3

Germany is not covered in the analysis in those parts of the paper that use EU-SILC data due lack of access to the microdata administered by the German Federal Statistical Office.

4

See, for example, Arregui and others (2020) who argue that carbon tax revenues could be directed toward targeted assistance to combat energy poverty, including in the housing sector.

1

See Annex 2 for a discussion and analysis of the role that rental markets play for the macroeconomy. In particular, rental markets can contribute positively to economic and financial stability as well as labor market mobility and efficient resource allocation. The impact on wealth and income inequality is ambiguous, however.

2

Fischer and Gervais (2011) look at the reasons for a decline in young home ownership between 1980 and 2000 in the United States. They find that a trend toward marrying later mechanically lowered young home ownership after 1980. They also show that the large rise in earnings risk that occurred after 1980 probably accounts for the remaining decline in young home ownership. On the decline of home ownership, see also The Economist (2020).

3

The analysis is based on EU-SILC data for the most recent year available at the time of writing, which for many countries is 2018. Choosing 2013 as the comparator year allows to largely abstract from the earlier boom-and-bust-housing cycle that many countries experienced around the global financial crisis. For the remainder of this chapter, the analysis excludes Lithuania because only about 1 percent of its population are tenants renting at market prices, and data are volatile.

1

Unless otherwise stated, to assess affordability this paper focuses on equivalized disposable income including housing allowances (see Annex 1). Annex Figure 3.2 shows a few results based on the use of a 30 percent threshold to define overburdened tenants, for a simple comparison with the baseline results. Relevant literature on housing affordability indicators includes Quigley and Raphael (2004), Stone, Burke, and Ralston (2011), Metcalf (2018), Ben-Shahar, Gabriel, and Golan (2019), and Ezennia and Hoskara (2019).

2

For the remainder of this chapter, the analysis excludes the Czech Republic and Slovakia due to methodological issues related to the variable that captures rental payments in the EU-SILC data. For drawing attention to these problems, the authors are grateful to Marissa Plouin and her colleagues in charge of the OECD Affordable Housing Database.

3

The latter three countries are not included in Figure 8 as the data do not meet the minimum threshold of 100 observations applied in Chapters 2 and 3 to report EU-SILC-based results. For more details, see Annex 1.

4

López-Rodríguez and Matea (2019) and Salas (2020) have analyzed recent trends in rental prices and affordability in Spain, where the rental market has expanded since the 2009 housing bubble burst.

5

See Box 2 for the relationship between rents and housing prices. The comparison should ideally be between renters and recent homebuyers with a mortgage. However, such a comparison is not feasible due to data constraints. Instead, focusing on housing costs for the prime age cohort (30–49) as a proxy—as households tend to buy homes during these ages—confirms the findings that housing cost has been lower and declining for homeowners.

6

The empirical evidence from unconventional monetary policies on inequality appears to be still inconclusive (see for example, Amaral 2017). Some studies suggest that quantitative easing has benefited lower-income households via the employment channel while the wealth channel has been small (for example, Lenza and Slacalek 2018).

7

Using EU-SILC data for all tenants (including those renting at subsidized rates) shows very similar increases as for renters at market rates, with Portugal’s gap being the largest with stronger cost rises for those renting at subsidized rates. Using OECD rental price data (see footnote 10 in this chapter) gives somewhat different magnitudes and country rankings but confirms the broad story of real rent prices rises across about half the countries with great dispersion.

8

The analysis uses data from the Estate Agency Rent Surveys (EARS). Two key advantages of EARS are (1) its surveys reflect transaction prices, and (2) it is a rare example of a publicly available data set on rental prices that harmonizes the data across locations and years. However, EARS focus on a specific subset of the rental market, so the data may not necessarily give an accurate representation of the overall rental market or its low-income segment. See Annex 1.

9

National consumer price indices (CPIs) were used to compute real rental prices. Where available, however, city-level CPIs (and in a few cases, CPIs excluding housing-cost components) were used for robustness checks, and the results were broadly similar.

10

The country-level data come from the OECD house price database, based primarily on the rental-housing component of CPIs. These data imperfectly reflect ongoing market prices because they also capture subsidized prices and slow-moving prices from multiyear contracts. On the indexation of rental prices in some European countries, see Roma (2019). Given these characteristics of the CPI-based data on rental prices, it is unsurprising that some studies relying on related metrics of house price-to-rental ratio and rental price-to-income ratio find relatively muted increases of rental prices and limited affordability problems for tenants (see, for example, Le Roux and Roma (2018) for an analysis of the euro area).

11

Related to such differences, other studies have focused on house prices, especially in the United States, and documented persistent divergences in average price changes across locations within countries as well as within metropolitan areas, labeling those locations with persistent high price growth as “superstars” (Gyourko, Mayer, and Sinai 2013).

12

This category includes occupations such as cleaners and helpers, food preparation workers, as well as laborers in manufacturing, transport, and construction.

13

Brussevich, Dabla-Norris, and Khalid (2020) show that workers in the food and accommodation and wholesale and retail trade are the hardest hit from COVID-19 for having the least “teleworkable” jobs. Young workers, those with lower education levels, women, part-time workers, and those employed in small and medium enterprises are particularly vulnerable. Espinoza and Reznikova (2020) document that the likelihood for teleworking decreases for workers without tertiary education and with lower levels of numeracy and literacy skills. Using a teleworking index and model-based analysis, Palomino, Rodríguez, and Sebastián (2020) demonstrate that wage inequality in Europe is set to rise from the lockdown and social distancing impacts of the COVID-19 pandemic. Furceri, Loungani, and Ostry (2020) document the adverse distributional impacts of past pandemics.

14

For example, for Barcelona and Madrid new rental prices are reported to have dropped by about 12–13 and 8 percent, respectively, in November 2020 compared to pre-COVID (according to the real estate portals Idealista and Fotocasa) while for Spain as a whole rental prices still exceeded those in 2019. In Dublin average rents fell by 1 percent in the third quarter of 2020 (year over year) while for Ireland as a whole average rents were 1.4 percent higher compared to 2019, which is still a significant moderation from a 6 percent increase in 2019 (Residential Tenancies Board). In the city center of Rome rents dropped by 10.3 percent in 2020 compared to 2019 but they rose in other parts of the city (according to Idealista). In Zürich the rental price index increased marginally (by 0.1 percent) in 2020 compared to a 0.9 percent increase on average in Switzerland (Schweizer Bundesamt für Statistik, Stadt Zürich). In London the average rental price increase remained broadly unchanged at 0.7 percent in 2020 compared to 1.1 percent in 2019 (Office for National Statistics, United Kingdom). Some caution is warranted with interpreting these data since differences in methodologies and sample size limit their comparability across countries.

15

Ramani and Bloom (2021) document a significant drop in rents in centers of “expensive” cities and an increase in rents, though less intense, in their suburbs. They attribute this “donut effect” in shifting housing demand to the rise in working from home as the likely key driver.

16

Several studies also find a negative association between homeownership and labor mobility in Europe (for example, Barceló 2006, Fidrmuc and Huber 2007). It should be noted that higher residential mobility also entails individual and social costs, such as the weakening of “social capital.”

1

For similar approaches and related literature, see for example Girouard and others (2006), Belke and Keil (2018), Egner and Gabrietz (2018), among others.

2

However, even this level of disaggregation may be insufficient to prevent this from happening if, for example, regions contain very large cities as well as sizeable surrounding areas.

3

The exact number of observations depends on the individual specification as some variables are not available for all time periods and/or regions.

4

To the extent that the increased rental cost burden is not driven by shifting preferences toward higher-value housing (that is, homothetic preferences).

5

Saiz (2003) presents further evidence that the relationship between immigration inflows and housing rents is indeed causal, that is, not driven by omitted variables or reverse causality.

6

For neighborhoods in the top decile of Airbnb activity distribution, rents are estimated to have increased by 7 percent, while increases in transaction (posted) prices are estimated at 19 percent (14 percent).

8

In the absence of a supply response, the inflow of high-income households to cities would initially induce an increase in rents. While some of the cost impact for low-skilled and low-income residents could be offset by rising local incomes via the employment or wage channel, in reality the cost effect has generally outweighed the income effect as shown in this paper’s empirical analysis.

9

Using the equivalized disposable household income.

10

Household characteristics that may determine the rental burden are one example. Overall, shocks to households, to the degree that they are idiosyncratic, are independent of aggregate variation. Hence, they do not exert an omitted variable concern for the structural estimation of the impact of aggregate factors (for example GDP, tourism intensity, etc.).

11

Generally, including a lagged dependent variable may cause the fixed-effects estimator to be inconsistent as these variables are necessarily correlated with the error term in the fixed-effects specification (Nickell 1981, Baltagi 2001). However, this concern is not directly relevant to the paper’s baseline specification, which uses country (not household) fixed effects, while the regression is estimated at the household level. In addition, this Nickell bias diminishes at a rate 1/T and has its direct effect mainly on estimates of the autocorrelation coefficient.

12

The decline in agricultural activities could increase the supply of land available for construction and zoning, which could lower rental costs. However, this decline in agriculture is more likely, as suggested by our results, to be driven by a structural transformation of economic activity toward manufacturing and services alongside urbanization. This process puts upward pressure on housing cost as a share of income, a characteristic of homothetic preferences.

13

How the monetary policy rate affects rental markets is another key question that would require identification of ECB and national central banks’ surprise actions, which lies beyond the scope of this paper’s analysis.

14

High-growth firms are firms with turnover growth rates of 10 percent or more. Its share is calculated as the number of high-growth enterprises divided by the total number of active enterprises.

15

For a discussion on the roles of fiscal, structural, and labor market policies that enhance equality of opportunities and incomes see OECD (2018), IMF (2017), Chen and others (2018), Georgieva (2020), Bozio and others (2020).

1

See López-Rodríguez and Matea (2020) for a recent comprehensive review of policies for the rental housing market. See also OECD (2020b); Andrews, Caldera Sánchez, and Johansson (2011); Salvi del Pero and others (2016); and Inchauste and others (2018) who focus on housing policies more broadly.

2

The 1948 Universal Declaration of Human Rights (UDHR) and subsequent bills (The 1966 International Covenant on Economic, Social and Cultural Rights, ICESCR and The International Covenant on Civil and Political Rights, ICCPR) recognize adequate housing as a component of the human right to an adequate standard of living. More than 50 constitutions, including those of Belgium, France, Portugal, and Spain include the right to adequate housing or outline the State’s general responsibility to ensure adequate housing and living conditions for all (Report to the 58th Commission on Human Rights, E/CN.4/2002/59, § 2, 1 March 2002).

3

Under the 2019 Basic Housing Law the Portuguese government becomes responsible for ensuring adequate housing for all citizens as guarantor of the right to housing. The law emphasizes the social function of housing, with the explicit goals of eradicating homelessness, prioritizing the use of public real estate for affordable housing, and prohibiting tenant evictions under specific circumstances.

4

The October 2020 IMF Fiscal Monitor reports that per $1 million invested in energy-efficient new buildings, such as schools and hospitals, 2–13 jobs are created based on studies by IEA (2020) and Popp and others (2020).

5

In the case of the United States, the Section 8 program was administered as a project-based assistance program between 1974 and the mid-1980s when it was replaced by housing vouchers.

6

Blanchflower and Oswald (2013), for instance, find that rises in the home-ownership rate in a US state are a precursor to eventual sharp rises in unemployment in that state and lead to lower levels of labor mobility, greater commuting times, and fewer new businesses. Lui and Suen (2011) describe the lock-in effects caused by public housing following from the fact that the subsidy received is tied to specific housing units.

7

Contrary to recent studies, Susin (2002) found that housing vouchers pushed up the rent paid by unsubsidized poor households in the average United States metropolitan area by 16 percent in the early 1990s, which more than offset the value of the total voucher program spent on the subsidized poor.

8

One exception to that evidence is perhaps Favilukis, Mabille, and Van Nieuwerburgh (2019). Using a model calibrated for the New York metropolitan statistical area, they show that rent controls can be part of a toolkit with redistributive effects to tackle rental housing affordability problems. At the same time, they point out that, compared to other housing policies, rent controls also create more housing and labor supply distortions and more housing misallocation.

10

Full liberalization in Spain in 1985 resulted in a period of volatility and uncertainty so that soft controls had to be reintroduced (Urban Tenancy Act 1994).

11

Cuerpo, Kalantaryan, and Pontuch (2014) and Inchauste and others (2018) offer evidence on rental market regulations in Europe, including indicators of rent controls and tenant-landlord relations.

12

The court’s procedures in Washington, DC, have been found to burden tenants and favor landlords as opportunity costs associated with court compliance pressures tenants into waiving rights and resources and not showing up in court (Fleming-Klink 2019).

13

In Belgium evictions were suspended in Brussels and in the Flemish and the Walloon regions. Ireland also increased the notice period for tenancies of less than six months from 28 to 90 days.

14

As in the federal Section 8 voucher program, the subsidy is paid directly to the landlord.

15

The estimates for Brussels range between 15,000 and 30,000 units in 2018 (article). In Italy, a 2016 census in the city of Rome revealed 161 vacant buildings, half of which were owned publicly and 260 abandoned buildings in Milan. Dublin’s vacant sites register includes 26 properties required to pay a levy in 2019 introduced by the Urban Regeneration and Housing Act of 2015, with a further 260 sites being considered as eligible for the tax. The Irish government has a national strategy for the use of vacant housing for 2018–21 (strategy).

16

In 2017, Australia adopted a vacancy fee on foreign owners of residential real estate where the property is not occupied or available on the rental market for at least six months of the year. No detailed impact assessment is yet available.

17

The Netherlands employed another financial incentive to offer rental housing by exempting rent paid to landlords from income tax (De Boer and Bitetti 2014). Disadvantages are its fiscal costs and, similar to mortgage relief, the creation of a bias toward one form of tenure status.

18

The entity bears the rental risk and maintains the property while the landlord receives a below-market rent with some tax benefits.

19

Measures that are not targeted at increasing supply but enhance access to credit and fuel demand for a given housing stock, risk pushing up prices up and worsen affordability. For example, Andrle and Plašil (2019) show that house prices in Canada responded rapidly to the households’ ability to borrow.

20

According to anecdotal evidence, while rental housing availability in Vancouver has increased, affordability has not improved as the new units are offered at market rent values. Arvai (2018) analyzes affordability in some Canadian regions.

21

Washington, DC, recently passed a land value tax with the hope of fostering rehabilitation and greater use of abandoned land. However, the tax was said to merely have brought substantial revenue to the city, because property values are increasing and owners have preferred to either pay the tax or ask for an exemption rather than implement changes to the property (ACT 21–556, The Council of D.C., December 2016).

22

OECD (2020c) defines social housing “as residential rental accommodation provided at sub-market prices that is targeted and allocated according to specific rules, such as identified need or waiting lists.”

23

For a recent overview on social housing see OECD (2020c), which notes that different definitions of social housing and data limitations make cross-country comparisons difficult. For the period from 2010 to about 2018, they observe a decrease in the stock of social housing in some advanced European economies (Denmark, Finland, Germany, Norway, United Kingdom) and a slight rise in three countries in which the stock was already high (Austria, France, Netherlands).

24

This distortion can be addressed by introducing fixed-term tenancies with review of eligibility after a certain number of years, already adopted in some countries for new contracts.

25

For a comprehensive review of studies examining the empirical relationship among regulations, house prices, and construction with US data, see Gyourko and Molloy (2015). Evidence of spillover of demand to other localities, which reduces price increases in the regulated locality, was found by Lin and Wachter (2020).

26

See Ortalo-Magné and Prat (2014) on political economy considerations.

27

A literature review by Higgins and Kanaroglou (2016) on the effect on increased transportation access on land prices in the United States suggests that the results are heterogenous, which may be explained by omitted variables across studies.

1

Deducting housing allowances from disposable income and rental costs does not significantly affect key findings reported in Chapter 3. However, this robustness exercise points to milder affordability problems than in the baseline results for some countries, including Nordic ones such as Finland and Denmark.

1

Gabriel and Painter (2020) discuss societal consequences of the deterioration in rental housing affordability, with a focus on the United States.

2

See, for example, Caldera Sánchez and Andrews (2011), Andrews, Caldera Sánchez, and Johansson (2011), Blanchflower and Oswald (2013), and Czerniak and Rubaszek (2018).

3

Based on 355 years of data in Amsterdam, Ambrose, Eichholtz, and Lindenthal (2013) find that market correction of the mispricing occurs mainly through housing prices, not rents.

4

These findings are consistent with the analysis by Cournède, Sakha, and Ziemann (2019) who show that countries with sharper declines in residential investment in the aftermath of the global financial crisis, in several countries driven by the burst of a housing price bubble mostly for owner-occupied housing, generally needed more time to recover from the crisis and regain the precrisis level of real GDP.

Affordable Rental Housing: Making It Part of Europe’s Recovery
Author: Khalid ElFayoumi, Ms. Izabela Karpowicz, Ms. Jenny Lee, Ms. Marina Marinkov, Ms. Aiko Mineshima, Jorge Salas, Andreas Tudyka, and Ms. Andrea Schaechter