International Evidence on Housing Booms

by Ken Gibb

This post authored by Alex Marsh and Ken Gibb

A recent NIESR paper by Armstrong and Davis (November 2014) compares the last two booms and busts in major OECD country housing markets. The authors present a thoughtful macroeconomic analysis of national housing markets and from there conduct panel data analysis of the determinants of house prices focusing on financial, debt and related variables.

The authors argue that comparison of the two most recent housing market cycles (1985-94 and 2002-11) can test the hypothesis that there was something unique about the most recent boom and its aftermath. They state that the housing market is widely considered to be the main cause of the global financial crisis (quoting such authorities as the IMF). However, the authors come away from overall reading of the data for the two cycles unconvinced. In their view the two cycles are sufficiently similar that it difficult to draw the conclusion that the most recent cycle is different in meaningful ways: it is certainly not unique. The implications is that if the received wisdom is incorrect and other factors were important in causing the crisis then macro-prudential policies in countries like the UK may be incorrectly targeted at the control of house prices and mortgage lending.


We are interested in this broad area for several reasons: why did economists miss the bubble nature of the housing market and its departure form fundamentals? Why did they miss the downturn in national housing markets? How plausible are the microfoundations of the models being used to analyze the housing market and explain what is actually going on? What do these analytical weaknesses tell us about the health or otherwise of economics and its capacity to evolve and learn for future challenges?

On reading the Armstrong and Davis paper we were struck by several points that we felt warranted comment. First, is there something of a straw man at the heart of this paper – do we really consider the house price boom to be the source of the GFC? Second, while the descriptive analysis is valuable and the technique is sound and well-derived from the literature, might it have been done differently? Third, does the principal policy inference, regarding the greater regulation of house prices and mortgage lending, stand up on the basis of this analysis?

Do analysts really generally view the housing market boom as the cause of the GFC? It is surely more that the sub-prime securitization and its exposure in the market for US mortgages in 2003 or 2004 onwards left the housing market vulnerable. Accelerating default contagion both collapsed the US housing market nationally (and that was different from the previous cycle) and spread through those exotic mortgage securities to stifle the wholesale money market and create the credit crunch which negatively impacted in many national housing markets across the OECD. Housing, and more particularly lending for housing, triggered a national market downturn which undermined wider international banking and thereafter fed back into other national housing systems.

Unfortunately, the data and analysis offered by Armstrong and Davis does not allow for this type of argument to be tested. In some senses, it requires a reconceptualisation of the housing (finance) market to recognise interdependence and network effects. It certainly requires a stronger focus on institutional innovations that is possible with the data available. To be fair, having presented their analysis, Armstrong and Davis note a range of factors and hypotheses ripe for further investigation. These include some of these institutional changes. So from our perspective it feels a little like the paper stops before it has a chance to grapple with some of the most interesting questions.

The analysis, understandably, constrains itself to using standard periods in order to attempt to capture national housing market cycles. Yet, despite the widely recognised increase in the synchronisation of housing market cycles cross-nationally, there is no reason to think that the OECD countries examined had similar period market cycles. The UK for instance moved into housing market downturn much later than the US. Moreover, downturns had different implications because of different default laws and bankruptcy implications. Getting a stronger sense of the timing of the turning points of these national cycles would itself be a useful contributor to the causal story being constructed.

Finally, the paper draws the policy inference that greater caution may be justified regarding the strength of the macroprudential case for regulating house prices and mortgage lending. It is important here to be clear what macroprudential regulation is seeking to achieve. Setting aside the macroeconomic stability arguments for a moment, isn’t there a housing-specific case for moderating the volatility of house prices and reducing market cycles? Whether macroprudential policy instruments are the right levers to use or are effective in damping price cycles are separate – and bigger – questions.

It may be that financial instruments are less effective than more direct housing policies in stabilizing the housing market. Or it may be that such policies can be complementary and work in tandem. Yet, in reality we face a context in which there is a willingness to consider active macroprudential regulation but a reluctance to intervene directly to generate greater housing market stability – if not an inclination among politicians to introduce policies that are more likely to increase volatility. Macroprudential tools can have more or less targeted impacts on housing markets. We should be cautious about bypassing them as a policy option. There is, of course, much more to learn about the most effective design for macroprudential policy instruments. This is an area in which a number of countries are experimenting with different approaches and there is undoubtedly scope for cross-national policy learning.

Alex Marsh is at the University of Bristol and is the purveyor of Alex’s archives at