3. Enhancing Resilience

Housing markets provide a sizeable contribution to economic activity. Fluctuations in house prices and residential investment can also be large, affecting the business cycle and amplifying shocks through balance sheet effects on households and lenders (Figure 3.1).1 In the boom phase, strong labour markets, economic growth and abundant credit supply feed strong demand, which pushes up real house prices. House price increases raise households’ collateral values and their net worth, which can, in turn, boost their consumption. Higher real house prices may lead to second-round effects as they may also create expectations of further price increases, feeding back into higher demand. Relaxation of lending standards and innovations in mortgage markets may further fuel house prices, a feedback loop that was at the centre of the global financial crisis.

Housing market busts are characterised by the opposite developments. First, house price drops lower collateral values, which in turn increase the losses that lenders face in the event of a default with implications for financial stability. Second, household wealth and the prospects of the construction sector are negatively affected, which tends to decrease spending. This reduces overall economic activity, leading to deteriorating macroeconomic conditions and a weakening of the economic outlook and fiscal balances. Housing downturns seem to have particularly damaging effects for inclusion and productivity because of the role of homes as collateral in loans to small and new firms. Housing downturns are, therefore, often associated with severe recessions (Figure 3.2).

Many factors affect housing demand. These include demography, including migration, changes in disposable income, house prices, interest rates or credit conditions. Demand shocks can stem from domestic factors but also international ones such as shifts in global capital flows, which can have large effects on some housing markets (Barcelona, Converse and Wong, 2020[3]). When housing demand changes, housing supply rigidities lead to either an increase in vacant homes (negative demand shock) or scarcity (positive demand shock), which result in housing investment and house price adjustments to clear housing markets. The extent to which the housing demand shock affects prices depends on the financial cycle (e.g. initial over or under-valuation of house prices, credit conditions), policies (inelastic supply due to zoning regulations, rent control, etc.) and cyclical or structural variables (e.g. construction costs, infrastructure).

Changes in house prices influence housing demand directly, but they also have indirect effects through the financial system. Movements in house prices have a strong impact on household balance sheets. Changes in household balance sheets affect, for instance, the number of non-performing loans and loan-to-value ratios. Changes in house prices also affect consumption depending on the size and institutional set-up of mortgage markets, such as the ease with which households can borrow against the value of their home.

Housing and the broader economy interact through various channels and policy interactions that affect the build-up of vulnerabilities, the severity of crises and the economy’s capacity to recover from them (Figure 3.3). An important distinction is between ex-ante (vulnerability to shocks) and ex-post (recovery from shocks) resilience.

Both types of resilience can be gauged using a variety of indicators. For example, ex-ante resilience can be assessed by crisis probability, defined as the frequency of large downward deviations from trend, and GDP-at-risk, which measures the performance of the economy in bad times (i.e. GDP changes in the worst 5% periods). Ex-post resilience, on the other hand, can be gauged through measures of the severity of downturns (peak-to-trough changes in activity), the duration of business cycle downturns and the time needed to recover, that is, regain the pre-crisis level of output. On the basis of these indicators, cross-country evidence indeed suggests that where crisis probabilities are high, business cycle fluctuations are also high, and so is the strength of post-crisis recoveries (Figure 3.4).

The main objective of macro-prudential policy is to prevent financial threats to economic stability, by restraining the build-up of systemic risks by moderating credit and asset price cycles, while ensuring the presence of sufficient buffers in the financial system. A key advantage of macro-prudential regulation is that it can be tailored to risks of specific sectors, such as housing, or loan portfolios, such as mortgages. In contrast to interest rate hikes, macro-prudential tightening need not entail a generalised reduction of economic activity, limiting the potential costs of policy intervention.

The most common macro-prudential tools include:

  • Loan-to-value (LTV) caps, which limit the amount of loans below a share of the dwelling price (Figure 3.5). The experience of OECD countries shows that countries that apply tighter LTV caps face lower crisis risks (Box 1.8). However, more restrictive LTVs imply less vigorous recoveries. Besides, tightening LTV caps could in the short term involve a trade-off between financial stability and social-inclusion objectives, by making it more difficult for young households with low savings to purchase a home. In the medium-to-long term, however, lower house prices preserve the housing purchasing power of all households, including the young ones.

  • Debt-service-to-income ratios (DSTIs), which require households to pay no more than a certain proportion of their income to service their housing loans. In some countries, DSTIs are based on total rather than only housing debt servicing costs.

  • Loan-to-income ratios (LTIs), which limit the amount of debt to a certain fixed multiple of income, are less commonly used. They are equivalent to DSTIs for a given interest rate and repayment period but have the advantage of not becoming looser in times of booms when interest rates are low and banks offer more accommodative credit conditions.

  • Risk-weighted capital requirements, which set the minimum ratio of capital that banks must hold for housing loans depending on their riskiness. The strength of this requirement is determined by the combination of minimum capital ratios and risk weights. Regulatory frameworks that require banks to hold more capital against mortgage loans are linked with a reduced crisis probability and stronger recoveries from crises.

Macro-prudential policies have been used more intensively since the global financial crisis. In the aftermath of the crisis, both capital requirements and LTV caps have been mostly tightened. Since 2012, the balance is more uneven for LTV caps, as many countries loosened regulation following the euro area sovereign debt crisis. In the face of the COVID-19 crisis, countries took measures to support mortgage borrowers and lenders (Box 1.7 and OECD (2020[5])). Furthermore, policies that keep mortgage borrowing in check are unlikely to entail costs in terms of foregone housing supply: from the high levels observed in OECD countries, further housing loan expansion seems to boost prices rather than construction (Kohl, 2020[6]).

Rent controls and landlord-tenant rules have been devised for a variety of social and economic reasons, such as to provide affordable accommodation by limiting rent increases, and to balance the landlord-tenant bargaining power. However, excessively tight regulations can discourage investment in new dwellings and maintenance of the existing rental housing stock, and hamper the development of the rental market. This can lead to housing shortages, exacerbate speculative housing price bubbles and increase household debt, which poses significant vulnerabilities for macroeconomic stability and economic growth (Caldera and Johansson, 2013[7]; Cavalleri, Cournède and Özsöğüt, 2019[8]; Hermansen and Röhn, 2017[2]).

The tightness of rental market regulations varies considerably within the OECD area (Figure 3.6). Evidence suggests that tighter rental market regulations are associated with higher crisis risk and deeper business cycle downturns (Box 3.1), because they distort the adjustment of housing supply to demand, which can exacerbate the accumulation of imbalances. GDP fluctuations (measured by GDP at risk) however tend to be milder in countries with strong tenant protection as a result of the protection that such regulations provide to vulnerable tenants against the consequences of income shocks.

Housing markets are affected differently by different tax instruments. For example, stamp duties can slow down house price rises by reducing the expected returns on speculative house purchases. Higher stamp duties therefore reduce housing transaction volumes, but they also raise housing transaction costs and can lead to a lock-in effect, which poses an obstacle to reallocation in the labour market (see Chapter 6). By contrast, recurring taxes on property are broadly neutral with respect to the cyclical behaviour of housing markets and economic resilience. Their main effect is to reduce the size of the housing market, by making housing more expensive. As a result, it is important to gauge the combined effect of all tax instruments, rather than that of individual instruments, through marginal effective tax rates (METR) on owner-occupied and rental housing (Figure 3.6).

METRs are derived as the difference between the pre and post-tax rates of return of a marginal investment divided by the cost of capital of that investment where the post-tax real rate is the minimum rate of return necessary to make the investment worthwhile (OECD, 2018[11]). Overall property taxation (measured by the METRs) generally smooths business cycles: higher METRs are associated with a reduced severity of downturns (Box 3.1).

The responsiveness of housing supply to changes in demand is influenced by policies, such as rental market regulations and land-use, which influence the dynamics of housing cycles. Indeed, countries where housing supply responds more strongly to demand have higher volatility of homebuilding (Cavalleri, Cournède and Özsöğüt, 2019[8]).

References

[3] Barcelona, W., N. Converse and A. Wong (2020), US Housing as a Global Safe Asset: Evidence from China Shocks, https://www.banque-france.fr/sites/default/files/session1_c_presentation_converse.pdf.

[9] Brys, B. et al. (2021), Effective Taxation of Residential Property, forthcoming.

[7] Caldera, A. and Å. Johansson (2013), “The price responsiveness of housing supply in OECD countries”, Journal of Housing Economics, Vol. 22/3, pp. 231-249, http://dx.doi.org/10.1016/J.JHE.2013.05.002.

[8] Cavalleri, M., B. Cournède and E. Özsöğüt (2019), “How responsive are housing markets in the OECD? National level estimates”, OECD Economics Department Working Papers, No. 1589, OECD Publishing, Paris, https://dx.doi.org/10.1787/4777e29a-en.

[10] Cournède, B., F. De Pace and V. Ziemann (2020), The Future of Housing: Policy Scenarios.

[1] Cournède, B., S. Sakha and V. Ziemann (2019), “Empirical links between housing markets and economic resilience”, OECD Economics Department Working Papers, No. 1562, OECD Publishing, Paris, https://dx.doi.org/10.1787/aa029083-en.

[4] Harding, D. and A. Pagan (2002), “Dissecting the cycle: a methodological investigation”, Journal of Monetary Economics, Vol. 49/2, pp. 365-381, http://dx.doi.org/10.1016/S0304-3932(01)00108-8.

[2] Hermansen, M. and O. Röhn (2017), “Economic resilience: The usefulness of early warning indicators in OECD countries”, OECD Journal: Economic Studies, Vol. 2016/1, https://www.oecd-ilibrary.org/docserver/eco_studies-2016-5jg2ppjrd6r3.pdf?expires=1547983022&id=id&accname=ocid84004878&checksum=3A3C6140FEC597236FBC3673C21D5C42.

[6] Kohl, S. (2020), “Too much mortgage debt? The effect of housing financialization on housing supply and residential capital formation”, Socio-Economic Review, http://dx.doi.org/10.1093/ser/mwaa030.

[5] OECD (2020), Housing Amid COVID-19: Policy Responses and Challenges, https://www.oecd.org/coronavirus/policy-responses/housing-amid-covid-19-policy-responses-and-challenges-cfdc08a8/.

[11] OECD (2018), Taxation of Household Savings, OECD Tax Policy Studies, No. 25, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264289536-en.

Note

← 1. This chapter provides policy insights on the effect of housing on economic stability based on two background papers, which also provide detailed bibliographic references (Cournède, Sakha and Ziemann, 2019[43]; Cavalleri, Cournède and Ziemann, 2019[2]).

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