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Are there ways to protect economies against potential future housing busts?

by Boris Cournède, Maria Chiara Cavalleri, Volker Ziemann, OECD

Housing, a large and volatile sector, is often at the centre of economic crises, as a trigger or amplifier. The current situation, which is characterised by house prices approaching or exceeding pre-crisis levels in many countries, raises questions as to whether these price levels may be indicative of a possible impending correction and what can be done to reduce housing-related macroeconomic risks.

Figure 1. House price developments since the global financial crisis

The OECD has been developing models that allow assessing to which extent economic trends associated with housing booms, such as steep house price increases or strong debt expansion, can fuel the risk of a severe economic downturn (Turner, Chalaux and Morgavi, 2018). About half of the countries covered by the models are estimated to face real yet limited risks (above 20% but below 30%) of experiencing a severe downturn over the medium term, with housing trends playing a significant role.” Model results suggest that housing booms can fuel crisis risk domestically but also across borders as a consequence of international financial links (Cavalleri, Cournède and Ziemann, 2019).

Countries can reduce housing-related risks in particular by:

  • Capping the size of loans relative to house prices. New evidence suggests that such caps are capable of containing house prices and mortgage lending incurring limited economic cost (Figure 2): housing investment is only marginally reduced and there is very little effect on consumption. Tighter loan-to-value ratios are also linked with a lower risk of severe downturns.
  • Limiting the size of loans relative to income. This measure holds promising potential but has been seldom used so far, which means there is little scope yet to evaluate it ex post.
  • Tightening bank capital requirements for riskier housing loans. Measures of this nature are linked to more moderate output fluctuations and stronger recoveries after downturns.
  • Reducing the tax advantages given to housing assets. Higher effective taxation of housing assets (which can come from higher property taxes or lower income tax breaks for housing) favours smoother housing cycles.

Figure 2. Effect of tightening LTV caps

References:

Cavalleri, M. C., B. Cournède and V. Ziemann (2019), “Housing Markets and Macroeconomic Risks“, OECD Economics Department Working Papers, No. 1555, OECD Publishing, Paris.
Turner, D., T. Chalaux and H. Morgavi (2018), “Fan Charts around GDP Projections Based on Probit Models of Downturn Risk”, OECD Economics Department Working Papers, No. 1521, OECD Publishing, Paris.




The output cost of the global financial crisis

By David Turner and Patrice Ollivaud, OECD Economics Department

Assessing the damage from the Global Financial Crisis (GFC) is not straightforward, even with the benefit of hindsight provided by ten years of history, because the counter-factual of what might have happened in its absence is unknowable. However, a simplistic, but commonly adopted approach, of comparing the post-crisis path of GDP with the pre-crisis trend exaggerates the cost and can lead to misleading policy conclusions. Such an approach is akin to treating the GFC as a meteorite from outer space which is completely unrelated or ‘exogenous’ to preceding macroeconomic developments. This is implausible because the pre-crisis trend in GDP involved unsustainable trends in asset prices, most obviously house prices, driven by a long period of rapid excessive credit growth across most of the advanced economies. Similarly ageing has started to progressively reduce the contribution from labour in many economies, so reducing their growth capacity. Hence, the counter-factual represented by the extrapolation of the past trends in GDP was never realistically attainable. A more plausible basis for a counter-factual is an extrapolation of pre-crisis trends of potential output, where potential output is an estimate of a sustainable measure of GDP [1]. The difference between these two approaches is first illustrated by considering the OECD countries as a group and using aggregated measures of potential output that are regularly published in the OECD Economic Outlook. A simple-minded extrapolation of OECD-wide GDP per capita implies an ever-widening loss, which is currently more than 10% of GDP, whereas compared to a pre-crisis extrapolation of potential output per capita implies a smaller loss of around 2-3 percentage points of GDP (Figure 1).

eoturnerdec2018

However, the estimated cost of 3% of GDP for the OECD as a whole hides large variations across countries. Among the 19 OECD countries that experienced a banking crisis, following the same approach, the median loss in output is more than double that, at around 6%.

The estimates of potential output also provide an estimate of how the loss was incurred and some clues as to some policy lessons that might be drawn. Perhaps surprisingly, in nearly all OECD countries, aggregate employment rates have recovered and are close to, or have even surpassed, the pre-crisis levels, although some groups (for example young workers) have suffered more permanent losses than these aggregate calculations suggest.  A notable exception is the United States, where the aggregate employment rate is still more than 3% below the pre-crisis level, which may be partly explained by the effects of opioid addiction [2].

Instead, the main lasting macroeconomic damage from the GFC is accounted for by lost productivity. OECD estimates suggest that for a majority of OECD countries experiencing a banking crisis, most of this lost productivity is accounted for by lower growth in capital per worker, rather than lower total factor productivity (tfp) (Figure 2). The loss in capital per worker illustrates how a severe adverse demand shock can be transformed into an adverse supply shock via an accelerator effect on investment that then reduces the capital stock [3]. In addition, increasing evidence, including from firm level studies, suggests that many countries where interest rates were particularly low in the pre-crisis period, especially in Southern Europe, experienced a substantial misallocation of capital. These countries are also among those that experienced a more abrupt post-crisis adjustment in capital stock growth. The fall in capital stock growth was also exacerbated in some countries by cutbacks in public investment after the crisis.

eoturnerdec2018fig2

Conversely, much of the loss in tfp can be traced back to weakening trend tfp growth that pre-dates the Global Financial Crisis. This in turn would suggest that policy may be better directed to addressing more long-standing causes, such as the increasing divergence between productivity performance of frontier and laggard firms, which may be symptomatic of rising entry barriers and reduced contestability [4].

References:

[1]  The approach described here represents an update of the calculations presented in:

Ollivaud, P., and D. Turner (2015),”The effect of the global financial crisis on OECD potential output“, OECD Journal: Economic Studies, OECD Publishing, vol. 2014(1), pages 41-60.

[2]  A more in-depth analysis of post-crisis trends in employment and labour force participation in the United States, including the effect of the opioid crisis, is provided by:

OECD (2018), OECD Economic Surveys: United States 2018, OECD Publishing, Paris, https://doi.org/10.1787/eco_surveys-usa-2018-en.

[3]  A more detailed analysis of the effect of the crisis on productivity in OECD countries, in terms of its effects on capital per worker and tfp, is provided by:

Ollivaud, P., Y. Guillemette and D. Turner (2018), “Investment as a transmission mechanism from weak demand to weak supply and the post-crisis productivity slowdown“, OECD Economics Department Working Papers, No. 1466, OECD Publishing, Paris, https://doi.org/10.1787/0c62cc26-en.

[4]  Evidence on the difference between the productivity performance of firms at the global frontier and laggard firms, as well as possible causes and policy responses, is provided by:

Andrews, D., C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy“, OECD Productivity Working Papers, No. 5, OECD Publishing, Paris, https://doi.org/10.1787/63629cc9-en.