While promoting residential mobility is not an end in itself, it is an important policy challenge, especially in countries with large spatial disparities and labour market skills mismatches. Policies that remove disincentives to move are likely to bring efficiency and equity gains by lifting productivity growth and social mobility. Removing policy obstacles to residential mobility can do much to facilitate labour market adjustment during the recovery from the COVID 19 crisis.
Brick by Brick
Building Better Housing Policies
6. Lifting Obstacles to Residential Mobility
Abstract
Main policy lessons
OECD countries exhibit substantive differences in residential mobility, which tends to be relatively high in Australia, the United States and the Nordic countries, while it is much lower in Eastern and Southern European countries.1 In all countries, homeowners are much less mobile than renters.
Housing conditions and policies influence people’s decisions and possibilities to move:
Residential mobility is higher where housing supply is more responsive to changes in demand. Reforming poorly designed land-use and planning policies, may facilitate mobility by reducing house price differences across locations.
Social cash and in-kind spending on housing are positively correlated with residential mobility. Social housing can be designed to avoid lock-in effects, for example, by waiving residency or queuing requirements in the case of unemployed workers taking up a job in the region.
Stricter rental market regulations, both rent control and greater security of tenure, are associated with lower residential mobility, particularly for renters, low-educated and low-income households. Rental regulations need to strike a balance between tenants’ and landlords’ interests, create security of tenure and encourage the supply of affordable rental housing.
Higher transaction costs in buying and selling a home, in particular from transaction taxes such as stamp duties and notary fees, are associated with lower residential mobility, especially among younger households, which are more likely to be first-time buyers.
Tax reforms shifting housing taxation from non-recurrent (e.g. transaction) to recurrent taxes would help reduce barriers to mobility. However, this may entail a trade-off with resilience as transfer taxes can curb excessing house price volatility and speculative behaviour.
Social and labour market policies also affect mobility. In particular, higher levels of cash income support to low-wage job seekers and minimum income schemes embedded in social transfers are associated with greater residential mobility.
Housing mobility: Trends, drivers and policies
Do not hinder residential mobility
Residential mobility matters. The ease of moving residence geographically has efficiency implications, because it affects the job-matching process. Low rates of residential mobility can be an obstacle to labour adjustment, making labour markets less efficient, with adverse effects on overall economic performance (Oswald, 1996[1]; Caldera Sánchez and Andrews, 2011[2]; Blanchflower et al., 2013[3]; World Bank, 2018[4]).The ease of moving residence geographically has resilience implications. Indeed, it affects the speed of adjustment to shocks by determining the capacity of workers to move from high to low unemployment areas.
The ease of moving residence geographically also has well-being and equity implications, because it affects individual and family opportunities to climb the socio-economic ladder through various channels (Judge, 2019[5]); for instance, by facilitating access to better paying jobs in more prosperous areas, through better education and training opportunities and also to better neighbourhoods, especially for children and young people coming from disadvantaged backgrounds. Evidence from the US Moving to Opportunity (MTO) project shows that the young children from families that were randomly selected to receive housing vouchers allowing them to relocate from high to low-poverty areas later in their lives had improved rates of college attendance, higher earnings and lower incidence of single parenthood (Chetty, Hendren and Katz, 2016[6]). These findings underscore the benefits of combatting segregation and reducing spatial income and wealth sorting. They also show that benefits from mobility are strongest for children as they can kick-start towards better lifetime opportunities. Moving, however, is not always beneficial. Evictions, for instance, force people to move which is neither suitable for the affected individuals nor for the economy and society as a whole. Indeed, excessive residential mobility may have adverse implications for social stability within neighbourhoods by depreciating local social capital or for the educational performance of children if they are forced to change school too often (OECD, 2020[7]).
To complement this work, future OECD work in the area of housing and mobility will deliver new granular evidence on inter-regional mobility, on the extent to which people move in responsive to local economic shocks including unemployment shocks, and on how policies can shape such responsiveness (Causa, Abendschein, Cavalleri, 2021; Cavalleri, Luu, Causa 2021). By doing this, the work will discuss the need to implement packages of structural and place-based policies that strike the right balance between encouraging people to move towards better opportunities if they wish so, and policies that create opportunities and foster local development in places lagging behind.
Housing matters for mobility and homeowners are much less mobile than renters
Empirical analysis shows that residential mobility is closely tied to housing market conditions and policies (Box 6.1). Household surveys show that the main reasons for re-locating are related to housing preferences and needs, including the desire to change tenure status, to have a new or better dwelling, or to move to a better neighbourhood (Figure 6.1). The degree to which households relocate varies widely across OECD countries: residential mobility is highest in Australia and in the United States, where more than 40% of individuals move over five years, while it is low in Southern and Eastern European countries, where less than 10% of individuals move over five years (Figure 6.2).
Box 6.1. Household-level data and empirical approach to study residential mobility
The analysis in Causa and Pichelmann (2020[8]) draws on household-level survey data for OECD EU countries, the United States and Australia. The advantage of these datasets is that they are based on a representative random sampling of the population and include information on residential moves, i.e. change of dwellings, and household socio-economic characteristics, including housing tenure status, income, household composition and size, labour market information, education, as well as urbanisation of the area of residence and region. This allows for a comprehensive analysis of individual and household drivers of mobility. Household data for the EU comes from the European Union Statistics on Income and Living Conditions (EU-SILC) household database. The analysis focuses on the 2012 cross-section, which in that year contained a specific module on household housing conditions, including information on change of dwelling and the reasons for doing so. The data for European countries is complemented with household data for the United States and Australia. The Australian data come from the Household, Income and Labour Dynamics in Australia (HILDA) survey, a household panel survey collecting information about economic and subjective wellbeing, labour market dynamics and family dynamics of Australian households. The American data is collected from the American Housing Survey (AHS), which collects data on housing and household characteristics, as well as recent movers.
To investigate the factors influencing residential mobility in OECD countries, a two-step approach is adopted. First, the effects of household and individual characteristics, such as housing tenure, income and age, on residential mobility are estimated for each country. This key step allows for comparing the effects across countries of household’s attributes on mobility and for assessing the effect of individual housing tenure status on mobility while filtering out the confounding effects of other individual drivers of mobility such as age and education. In a second step, the empirical approach exploits cross-country variation in policies and institutions to assess the role of policy settings in explaining residential mobility. Policies included in the analysis cover housing policies such as rental market regulations and housing transaction costs as well as other policies that may influence mobility such as social and job protection. Policy effects are also estimated by socio-economic groups (e.g. by housing tenure status, education, age) to identify differential effects across groups, which underscores the distributional effects of these policy levers.
Figure 6.1. Housing is the most important reason for moving
Note: Households that have recently moved are asked their main reason for having moved among housing, family, financial, education, and other (see Causa and Pichelmann (2020[8]) for details). This charts provides the breakdown of such reasons across households, for each country.
Source: OECD Calculations based on 2012 EU SILC Data for EU countries, AHS 2013 for the United States, HILDA 2012 for Australia.
Figure 6.2. Selected OECD countries display wide variation in residential mobility
Note: Light blue refers to a mobility rate ranging from 5% to 20%, medium blue to a mobility rate in-between 20% and 35% and dark blue to a mobility rate of above 35%.
Source: OECD Calculations based on 2012 EU SILC Data for EU countries, AHS 2013 for the United States, HILDA 2012 for Australia.
While there are large differences in mobility rates across countries, homeowners are systematically less mobile than renters (Figure 6.3), implying a negative cross-country correlation between homeownership and residential mobility (Figure 6.4). Mobility differences between housing tenure status persist after taking into account a wide array of individual and household drivers of mobility such as age, education, incomes (Causa and Pichelmann, 2020[8]).
Mobility is the highest among tenants renting at market price and the lowest among outright owners. Social or subsidised tenants tend to be less mobile than private tenants.
Mobility differences by tenure status are very large in all countries: for instance on average across OECD EU countries, private renters are around 5.6 times more mobile than outright owners. In The United States, displaying among the highest mobility rate in this study, the gap across housing tenure status is also very large, as private renters are around 3 times more mobile than outright owners.
Figure 6.3. Homeowners are much less mobile than renters
Residential mobility by housing tenure status
Source: OECD Calculations based on 2012 EU SILC Data for EU countries, AHS for the United States, HILDA for Australia.
Figure 6.4. High-homeownership countries tend to have low residential mobility
Source: OECD Calculations based on 2012 EU SILC Data for EU countries; AHS 2013 for the United States; HILDA 2012 for Australia. Homeownership rates from the OECD Affordable Housing Database.
Embrace policies that favour residential mobility
Reduce housing transaction costs
Reducing policy-driven housing transactions costs encourages residential mobility. Housing-related transfer taxes, which are non-recurrent taxes due when buying or selling a property, discourage residential mobility, especially among young households, because these levies are likely to be more binding for first-time buyer. Notary fees associated with housing transactions, which are also due in certain countries when buying or selling a property, also discourage residential mobility. As a result, shifting housing taxation from non-recurrent to recurrent taxes, such as annual taxes on immovable property, can do much to enhance residential mobility.
Indeed, policy simulations suggest that shifting housing taxation away from non-recurrent levies would increase residential mobility (Figure 6.5). Reforms to reduce housing transaction levies have been recently implemented in a few countries (Box 6.2).
Figure 6.5. The probability to move depends on taxes, transaction costs and housing supply
Note: OECD calculations based on estimates reported in Causa and Pichelmann (2020[8]). The dot is the average estimated probability to move evaluated at average policy and household characteristics. The distance between the Min/Max and the average is the change in the estimated probability associated with a policy change.
Box 6.2. Recent reforms to reduce housing transaction costs
In 2017, the United Kingdom abolished the Stamp Duty (transfer tax) for first-time homebuyers in England and Wales for home purchases up to GBP 300 000.
In 2011, Ireland reduced its stamp duty from 9% to 1% on the value of a property up to EUR 1 million, and 2% on the value exceeding the EUR 1 million. Simultaneously, all existing reliefs and exemptions for stamp duty on residential property were abolished. In 2013, the government completed these reforms by deciding to impose a recurrent property tax: 0.18% on all residential properties worth up to EUR 1 million and 0.25% for properties worth more than EUR 1 million.
Australia shifted from non-recurrent to recurrent housing taxation as part of a 2014 reform as the Capital Territory reduced transfer duties on conveyances and abolished insurance taxes while increasing land taxes.
The Netherlands reduced the housing transaction tax from 6% to 2% in 2012. The reform was financed by abolishing the tax exemption for work-related travel allowances, including the tax exemption for private travel in company cars.
Remove bottlenecks to responsive housing supply
Residential mobility is higher where housing supply is more responsive to changes in demand. The responsiveness of housing supply depends on geographical characteristics and also on policies, in particular on land-use regulations which influence the allocation of land and housing among different uses (see Chapter 2). For instance, restrictive regulations typically give rise to large house price differentials across regions and prevent households from moving from lower-priced areas to higher-priced areas, where jobs and training opportunities tend to be better. This situation has the potential to undermine both allocation of resources and social mobility.
Simulations indeed show that policy reforms that enhance housing supply responsiveness can do much to boost residential mobility (Figure 6.5). Such reforms have recently been implemented in a number of OECD countries. For example, in 2018 the Netherlands simplified the approval procedure and removed constraints for housing corporations which seek to rent on the private market and is progressively allowing municipalities to have more control over zoning and the planning of the private rental market. Steps in this direction were also taken by Sweden in 2016, where the government presented legislative measures to make the planning system more efficient and introduced support to municipalities based on the number of dwellings permitted.
In addition, housing supply conditions can affect the economic incentives to inter-regional migration and, consequently, the spatial allocation of workers within countries (Causa, Cavalleri and Luu, 2021[9]; Causa, Abendschein and Cavalleri, 2021[10]). A flexible housing supply enhances the responsiveness of people to both local GDP per capita and regional unemployment, thus potentially contributing to an efficient matching between workers and jobs, a reduction of local imbalances and more flexibility in case of local shocks. Reducing policy-driven barriers to a responsive housing supply, for example by reforming the governance of land-use, may also improve inclusiveness as it supports people’s access to better jobs and limit the risks that people are trapped in less-advantaged areas. In fact, in the United States, rising cross-regional divides in house prices have been found to create barriers especially to the mobility of low-skilled workers towards metropolitan areas (Causa, Cavalleri and Luu, 2021[9]; Bayoumi and Barkema, 2019[11]). Overall, the lack of opportunities for regional mobility for some socioeconomic groups can have adverse consequences in terms of growth and inclusiveness (Hsieh and Moretti, 2019[12]).
Box 6.3. The role of housing in inter-regional migration
Inter-regional migration has been declining in several OECD countries over the past decades. The decline has been attributed to a reduction in the economic returns to migration due to, among other factors, rising housing costs (Bayoumi and Barkema, 2019[11]). The expected income gains from moving no longer compensate for the rising costs of housing, especially for workers at the bottom of the wage and skill distribution.
Recent OECD research (Causa, Abendschein and Cavalleri, 2021[10]; Causa, Cavalleri and Luu, 2021[9]), exploiting both cross-country and country-specific regression analyses, show that economic and housing-related factors affect the direction and intensity of inter-regional migration flows. High GDP per capita and low regional unemployment rates are found to attract migrants, while high regional house prices discourage mobility. High or rising regional house prices reduce the economic attractiveness of a region. For example, a 10% rise in house prices in a region deter inward migration by on average 3%.
At the same time, high house prices in the region of residence could induce outward migration because of affordability concerns. Some people – especially among disadvantaged social groups – may leave an area because they cannot afford stable or adequate quality housing. In some European countries, rising outward migration from large metropolitan areas, often of young families, has occurred in parallel with a rise in inter-regional commuting. This trend is sustained by the improvement of transport infrastructure and the increase in housing costs and congestion in major metropolitan areas. Indeed, migration outflows are stronger from regions where house prices grow comparatively faster: on average, a 10% rise in house prices is associated with a rise of outflow migration by 1.5%. Overall, the negative effect of house prices on inward migration is comparably larger in magnitude than the positive effect on migration outflow, implying that rising house prices in a region could result in a sustained loss of population over time.
The significance and magnitude of the effect of house prices on inward and outward migration vary across countries (Figure 6.6). House prices have a stronger impact on internal migration where they have increased more sharply (such as Sweden, Switzerland, Australia and Canada), or where cross-regional differences in housing costs are more pronounced (e.g. the United States and the United Kingdom).
Housing-related policies can affect the evolution of regional house prices and hence have a direct impact on inter-regional migration. However, they can also have an indirect impact because they affect the responsiveness of migration to other economic factors. For example, where housing supply is more flexible, inter-regional migration is more responsive to local economic conditions, such as GDP per capita and unemployment. On the contrary, stricter rental regulations, both rent control and greater security of tenure, are associated with lower responsiveness of inter-regional migration to local labour market conditions.
Figure 6.6. Estimated regional migration elasticities to local house prices at origin and destination
Note The charts show the estimated elasticity of inter-regional migration to real regional house prices by destination and origin region. The estimates have been derived from country-specific gravity models of inter-regional migration. The size of the bar represents how much, in percentage points, migration towards or out of a region would change following a 1% increase in the house prices in that region. Countries are ranked in ascending order by the elasticity in the destination region.
Source: Causa, Cavalleri and Luu (2021).
Reform excessively rigid rental market regulations
Residential mobility is lower where rental market regulations, both rent control and tenant-landlord regulation, are stricter. Tenants in rent-controlled dwellings may be reluctant to move and give up their below-market rents. Also, rent control and tenant protection measures affect disproportionately low-income households as well as low- and middle-educated ones. These social groups are the least mobile to start with, which implies that too restrictive rental market regulations may unintendedly constitute an additional barrier to the mobility of the least mobile groups. Moreover, where rents are out of line with housing market conditions, landlords are discouraged from letting their property, which reduces the size of rental markets (see Chapter 3), with potentially negative repercussions for affordability. Also, excessive protection of tenants puts vulnerable workers, such as those with non-standard contracts, including young people, at a particular disadvantage.
Policy simulations suggest that adopting more balanced regulations between landlord and tenants and reducing rent control have the potential of facilitating residential mobility (Figure 6.7). The majority of OECD countries have made landlord-tenant regulations more landlord-friendly over the last decade, in particular Austria and Finland, even though rent control has often increased at the same time, with few exceptions such as the Czech Republic, the United Kingdom and the United States, where rent control has actually been eased.
While reducing excessively rigid rental market regulations is found to encourage mobility, reforms in this area can raise trade-offs. Too stringent rental regulations can discourage new construction and maintenance by capping the price of rentals. Regulations are motivated by the legitimate goal of counteracting the asymmetric bargaining power between landlords and tenants. This is particularly salient at the current juncture where countries’ need to avoid evictions of financially distressed households.2 As a response to the COVID‑19 crisis, several countries have temporarily increased the stringency of rental market regulations, most often by temporarily suspending evictions and also, less often, by reducing or postponing rent payments for disadvantaged tenants (see Box 1.6 in Chapter 1).
Figure 6.7. Rental market regulations and social housing also affect the probability to move
Note: OECD calculations based on estimates reported in Causa and Pichelmann (2020[8]). The dot is the average estimated probability to move evaluated at average policy and household characteristics. The distance between the Min/Max and the average is the change in the estimated probability associated with a policy change.
Invest in social housing
Residential mobility is affected by the level and design of cash and in-kind housing transfers, especially among renters and low-income groups. Both housing allowances (i.e. housing-related cash transfers) and the provision of social housing are associated with higher mobility. However, social housing tenants are less mobile than private renters (Figure 6.3), because of limited portability of entitlements, which creates lock-in effects.
Based on policy simulations, increasing social spending on housing, including cash (e.g. housing allowances) and in-kind transfers (e.g. social housing), would foster residential mobility (Figure 6.7). As developed in Chapter 2, social spending on housing, which is primarily motivated by affordability and inclusiveness concerns, has declined over time in many countries. Countries such as Belgium, Canada, Luxembourg and New Zealand have nevertheless taken steps to increase the supply or renovate their social housing stock. Provided eligibility rules are designed to avoid lock-in effects, such reforms may address housing affordability issues and at the same time make it easier to relocate for disadvantaged households.
References
[11] Bayoumi, T. and J. Barkema (2019), “Stranded! How Rising Inequality Suppressed US Migration and Hurt Those Left Behind”, Vol. 19/122.
[3] Blanchflower, D. et al. (2013), Does High Home-Ownership Impair the Labor Market?, http://www.nber.org/papers/w19079.ack.
[2] Caldera Sánchez, A. and D. Andrews (2011), “Residential Mobility and Public Policy in OECD Countries”, OECD Journal: Economic Studies, Vol. 2011, http://dx.doi.org/10.1787/19952856.
[10] Causa, O., M. Abendschein and M. Cavalleri (2021), The laws of attraction: economic drivers of inter-regional migration,housing costs and the role of policies, OECD, Economics Department Working Papers, forthcoming.
[9] Causa, O., M. Cavalleri and N. Luu (2021), Migration, housing and regional disparities: a gravity model of inter-regional migration with an application to selected OECD countries, OECD, Economics Department Working Papers, forthcoming.
[8] Causa, O. and J. Pichelmann (2020), “Should I stay or should I go? Housing and residential mobility across OECD countries”, OECD Economics Department Working Papers, No. 1626, OECD Publishing, Paris, https://dx.doi.org/10.1787/d91329c2-en.
[6] Chetty, R., N. Hendren and L. Katz (2016), The effects of exposure to better neighborhoods on children: New evidence from the moving to opportunity experiment, American Economic Association, http://dx.doi.org/10.1257/aer.20150572.
[12] Hsieh, C. and E. Moretti (2019), “Housing Constraints and Spatial Misallocation”, American Economic Journal: Macroeconomics, Vol. 11/2, pp. 1-39, http://dx.doi.org/10.1257/mac.20170388.
[5] Judge, L. (2019), BRIEFING info@resolutionfoundation.org +44 (0)203 372 2960 @resfoundation resolutionfoundation, http://www.nuffieldfoundation.org.
[7] OECD (2020), Housing and Inclusive Growth, OECD Publishing, https://www.oecd.org/fr/social/housing-and-inclusive-growth-6ef36f4b-en.htm.
[1] Oswald, A. (1996), “A Conjecture on the Explanation for High Unemployment in the Industrialized Nations: Part 1”, University of Warwick Economic Research Paper No. 2068-2018-901.
[4] World Bank (2018), Living and Leaving: housing, mobility and welfare in the European union, World Bank.
Notes
← 1. This chapter presents new evidence on housing and residential mobility across OECD countries and on the role of housing-related and other policies in influencing mobility based on Causa and Pichelmann (2020[8]).
← 2. New OECD data in the Housing Affordable Database show that at least 3 million formal eviction procedures we initiated in 18 OECD countries for which data are available. See Affordable Housing Database - OECD.