VoxEU Column Macroeconomic policy

Housing policy: Learning from the past and looking to the future

The housing market faces major challenges in both the short and long run in terms of affordability, price variability, ownership structures, financing, and their impacts upon wider macroeconomic stability. This column summarises a conference on lessons for the future of housing, jointly organised by the Brevan Howard Centre for Financial Analysis at Imperial College Business School and CEPR.

The UK’s housing market faces major challenges, from regional disparities to affordability problems for the young and threats of financial stability. This column summarises some of the main themes of the CEPR-Brevan Howard Centre for Financial Analysis Conference, “Housing: Learning from the Past and Looking to the Future”, which took place on 19 January 2018 at Imperial College.

The rate of return on everything, 1870-2015

The first paper presented was Jordà et al. (2017).

The paper attempts to answer fundamental questions about the economy. Notably: what is the aggregate real rate of return? Is it higher than the growth rate of the economy? Which assets have the highest long-run returns? It does this by creating an entirely new dataset compiled from primary historical sources, in 16 advanced economies, dating from 1870 to the present day.

The investigation takes a long-run view of the returns to four asset classes. These are two ‘safe’ assets – bonds (long-run government debt, typically with a 10-year duration) and bills, i.e. short-run government debt – and two ‘risky’ assets, namely equities and, for the first time, housing. Equities act as a proxy for business investment, and real estate as a proxy for residential investment.

This is the first dataset with this amount of information on housing as an asset class. Although housing wealth is on average roughly one half of household wealth in a typical economy, and can fluctuate significantly over time (Piketty 2014), there has not previously been a rate-of-return database that can compare housing directly to other asset classes. The authors construct three types of returns: investment income (yield), capital gains (price changes), and total returns (the sum of the two).

This paper, and the work that the database makes possible, informs the current Piketty-inspired debates on inequality, and can add empirical weight to debates on secular stagnation (Summers 2014), risk premia (Mehra and Prescott 1985), and the declining natural rate (Holston et al. 2017). The countries covered are Australia, Belgium, Denmark, Finland, France, Germany, Italy, Japan, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, the UK, and the US, although completely comprehensive coverage at this stage has not been possible.

The researchers used first-hand sources in each year, including yearbooks of statistical offices and central banks, stock exchange listings, newspapers, and company reports. The rent series rely on the rent components of the cost of living of consumer price indices, as constructed by national statistical offices.

There are four main conclusions, all of which are puzzling.

  • The first, regarding risky assets, is that residential real estate and equities have similar, high real total gains (on average about 7% per year); the standard deviation of the return on real estate is half that of the return on equities, even though housing portfolios are harder to diversify.
  • Second, in safe assets, the returns have been low on average, in the 1%–3% range, but the volatility of 'safe' bonds has been as high as that of 'risky' housing.
  • Third, the risk premium has been volatile over the last 150 years, due almost entirely to changes in safe rates. But it has continuously reverted to its mean of between 4% and 5%.
  • Fourth, in terms of r minus g, the data gives a 'bottom up' validation of the stylised fact that r > g (Piketty 2014). The data further implies that, for most of the last 150 years, r >> g. The exceptions have been periods of wartime. The data also shows the r - g does not fluctuate systematically with the growth rate of the economy.

The macroeconomics of housing and the dynamics of wealth inequality

The second paper was Grossmann et al. (2018). The authors note that, first, housing expenditures represent the largest expenditure category for the household. Second, the share of housing expenditures, at a given point in time, declines with income. Finally, real rent has continuously increased over time.

This combination of forces may become a 'toxic mixture' that increases inequality over time. To demonstrate this effect, they create a model of long-run model of housing in which economic growth can trigger an increase in wealth inequality and asymmetric welfare effects, to the benefit of the wealthy. In the model both effects are amplified by heterogeneity in housing expenditure shares.

This brings together elements from research into the business cycle dynamics of housing prices (see Piazzesi and Schneider 2017 for a survey) and those that analyse the impact of housing on wealth distribution (e.g. Gabaix et al. 2016, Kaymak and Poschke 2016, Álvarez-Peláez and Díaz 2005).

The model used combines a housing and macro model that is designed to think long term (Grossmann and Steger 2017) and abstracts from any sort of financial market imperfections, with household heterogeneity (Caselli and Ventura 2000). Householders have non-heterogenous preferences, designed to capture status concerns. The model is calibrated to the US economy in 2010.

In the model, wealth inequality increases as long as the economy grows. The welfare benefits of economic growth go disproportionately to the rich. Adding status concerns amplifies both wealth divergence and the asymmetric welfare effects of economic growth.

This result is consistent with arguments first advanced by Ricardo (1817) that economic growth benefits landlords – the owners of the fixed factor – disproportionately in the longer run.

Houses across time and across place 

The third paper presented was Miles and Sefton (2018).  The paper aims to understand how housing wealth and the cost of housing have moved over the past in different countries, and how they might evolve in the future. It starts by noting three empirical facts (Knoll et al. 2017).

In nearly all developed countries, house prices have risen faster than consumer goods in recent decades – on average, relative prices rose by about 300% since 1945 (though little in the previous 75 years). In many countries, house prices have also risen faster than incomes, on average and measured over several recent decades. There is substantial variation in these trends across countries.

The paper sets out a model that attempts to explain these long-run trends in housing costs, calibrates it to observed data for the last 70 years, and then uses it to estimate the future growth path of housing costs. The model is a Ramsey two-sector growth model, with a model of the geography of residential development that tracks the change in location of the population over time. It endogenises growth, saving, and asset prices. Land is not homogenous.

Householders are expected to trade off the cost of living close to an (expensive) urban centre with the gain of having lower transport costs. Technological change means that distance (or its proxies, such as the ability to work at home) may have a varying effect on the value of houses.

In the model, as long as improvements in travel technology proceed at a pace that is in a certain critical proportion to the growth in productive potential (labour force growth plus general productivity growth), there is a balanced growth path with no change in real house prices.

But once travel improvements cease (as happened in the UK in recent decades), real house prices and rents rise. Plausible parameters may generate a path of inexorably rising housing costs, but this path is extremely sensitive to both elasticities of substitution between land and structure in creating housing services (Muth 1971) and substitutability between housing and consumption goods in utility.

Both of these are hard to pin down empirically, and so this sensitivity will be a challenge to policymakers who need to distinguish between sustainable and unsustainable paths at an early stage.

Listen to David Miles, Alan Taylor, Thomas Steger, and Jagjit Chadha discuss rising house prices and inequality in the Vox Talk here.

Policy panel

The panel was chaired by Jagjit Chadha (NIESR), and the discussants were Stephen Aldridge (Department for Communities and Local Government), Chris Giles (Financial Times), and Vasileios Madouros (Bank of England). The panel opened by outlining some of the issues on both sides (supply and demand) of the housing market, which were then explored in more detail by the panellists.

Problems with the provision of housing have created a significant shortfall in its availability at a national level. Between 2004 and 2014, for example, supply fell short by approximately half a million homes.  This has had two consequences: a decrease in affordability, and rising regional disparities. As a result, deposit requirements have risen, while the proportion of people entering the housing market has fallen.

However, several misconceptions surround popular understanding of housing supply issues. Six factors are variously attributed as the reason for a lack of supply: that there is a lack of availability of land because the country is mostly built up, that there is plenty of brownfield land available, and that the majority of problems are caused by either the buy-to-let scheme, foreign ownership, developers’ land banking, or Help-To-Buy. In reality, insufficient housing supply is a combination of these factors to a far smaller extent than widely held, while population growth, wealth concentration, and regional inconsistencies in both housing regulation and labour mobility are substantial factors. Several policy options exist to address these supply issues, including better measurement of housing needs, better interaction with transport and infrastructure policy, and a more diverse construction industry – including improving access for smaller developers.

But supply-driven declines in housing affordability have negatively impacted both individual welfare and its state provision. For example, one implication of declining affordability is that more people remain in the rental market for longer, meaning both that they are unable to accumulate wealth and that state housing benefits are spent more and more on increasing rents.

Wealth and intergenerational issues are a major policy challenge that must be confronted from the demand side as well. Though wealth distribution and inequality have not changed dramatically on a cross-sectional basis in the last few decades, there have been dramatic changes between age groups. The generation born between 1985 and 1995 are the first to have lower real wages – and lower living standards – than their predecessors. Young households that are not moving into home ownership are instead renting. Rents are now at 35% of average income of renters. Nor has the quality of rented housing improved, as rented housing is smaller than before, and ever-further from city centres. Meanwhile, as people are living longer, they bequeath wealth to their children later, rather than at the time when they would historically have entered the housing market. Because of all this, someone with an identical career path and prospects will have a worse standard of living than someone ten years older than them.

Housing may have added to intergenerational resentment. Both the Brexit referendum and the 2017 election showed clear voting patterns across age lines. Almost 60% of those over 65 voted to leave the EU, compared to less than 20% of those under 25. Home ownership is also a strong indicator of support for the Conservative Party – both characterised by older generations.

Measures to shift the generational distribution of wealth – such as dramatically increasing inheritance tax, for example – will be just as politically divisive, but nor can the government afford not to act.

Finally, the discussants reviewed some of the stability and risk implications of housing policy options. Given that a house purchase is the biggest investment most people make in their lifetime, that they heavily leverage themselves to do so, and that the housing and mortgage boom were at the heart of many past crises, risk policy must address two channels of risk in the system. First, in times of stress, lenders incur losses on loan defaults. Second, borrowers cut spending in order to repay debt. As housing prices are increasing relative to income, so is mortgage debt relative to income, which amplifies shocks – empirical evidence shows that the greater the debt-to-income ratio in a country, the greater the fall in consumption in an economic downturn. UK households with mortgages tend to prioritise debt repayments over spending, but debt serviceability pressures can still lead to repayment difficulties in stress. Thus, given that two-thirds of debt is in mortgages in the UK, even a small downturn can pose significant default risk.

There are two policy responses for this. For borrowers, affordability assessments can be improved by more sophisticated loan-to-income rules, which although they are designed to limit risk in the aggregate, can exclude people who otherwise could afford to keep up with repayments. For lenders, stress testing and capital buffers have been employed to ensure lenders have sufficient capital to withstand shocks, while still continuing to lend.


Álvarez-Peláez, M J and A Díaz (2005), "Minimum consumption and transitional dynamics in wealth distribution", Journal of Monetary Economics 52(3): 633—667.

Caselli, F and J Ventura (2000), "A Representative Consumer Theory of Distribution", American Economic Review 90(4): 909—926.

Gabaix, X, J-M Lasry, P-L Lions, and B Moll (2015), "The Dynamics of Inequality", Working Paper, Princeton University.

Grossmann, V and T Steger (2017), "Das House-Kapital: A Long Term Housing & Macro Model", IMF Working Paper No 17/80.

Grossmann V, B Larin, H Torben Löfflad, T Steger (2018), "The Macroeconomics of Housing and the Dynamics of Wealth Inequality", working paper.

Holston, K, T Laubach, and J C Williams (2017), “Measuring the Natural Rate of Interest: International Trends and Determinants”, Journal of International Economics 108(S1): 59–75.

Jordà, O, K Knoll, D Kuvshinov, M Schularick, and A M Taylor (2017), “The Rate of Return on Everything, 1870–2015”, CEPR Discussion Paper 12509.

Kaymak, B and M Poschke (2016), "The evolution of wealth inequality over half a century: The role of taxes, transfers and technology", Journal of Monetary Economics 77: 1-25.

Knoll, K, M Schularick and T Steger (2017), "No price like home: global house prices, 1870-2012", The American Economic Review 107(2): 331-353.

Mehra, R, and E C Prescott (1985), “The Equity Premium: A Puzzle”, Journal of Monetary Economics 15(2): 145–161.

Muth, R F (1971), "The derived demand for urban residential land", Urban Studies 8(3): 243-254.

Piazzesi, M and M Schneider (2016), "Housing and Macroeconomics", in J B Taylor and H Uhlig (eds), Handbook of Macroeconomics, Vol. 2, Elsevier, forthcoming.

Piketty, T (2014), Capital in the Twenty-First Century. Cambridge, MA: Harvard University Press.

Ricardo, D (1817), On the Principles of Political Economy and Taxation, John Murray.

Summers, L H (2014), "US Economic Prospects: Secular Stagnation, Hysteresis, and the Zero Lower Bound", Business Economics 49(2): 65–73.

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