Although the nexus between low interest rates and the recent house price bubble remains largely unproven, observers now worry that current loose monetary conditions will stir up froth in housing markets, thus setting the stage for another painful financial crash. Central banks are struggling between the desire to awaken economic activity from its post-crisis torpor and fear of kindling the next housing bubble. The Riksbank was recently caught on the horns of this dilemma, as Svensson (2012) describes. Our new research provides the much-needed empirical backdrop to inform the debate about these trade-offs.
The recent financial crisis has led to a re-examination of the role of housing finance in the macroeconomy. It has become a top research priority to dissect the sources of house price fluctuations and their effect on household spending, mortgage borrowing, the health of financial intermediaries, and ultimately on real economic outcomes. A rapidly growing literature investigates the link between monetary policy and house prices as well as the implications of house price fluctuations for monetary policy (Del Negro and Otrok 2007, Goodhart and Hofmann 2008, Jarocinski and Smets 2008, Allen and Rogoff 2011, Glaeser, Gottlieb et al. 2010, Williams 2011, Kuttner 2012, Mian and Sufi 2014).
Despite all these references, there is relatively little empirical research about the effects of monetary policy on asset prices, especially house prices. How do monetary conditions affect mortgage borrowing and housing markets? Do low interest rates cause households to lever up on mortgages and bid up house prices, thus increasing the risk of financial crisis? And what, if anything, should central banks do about it?
Monetary conditions and house prices: 140 years of evidence
In our new paper (Jordà et al. 2014), we analyse the link between monetary conditions, mortgage credit growth, and house prices using data spanning 140 years of modern economic history across 14 advanced economies. Such a long and broad historical analysis has become possible for the first time by bringing together two novel datasets, each of which is the result of an extensive multi-year data collection effort. The first dataset covers disaggregated bank credit data, including real estate lending to households and non-financial businesses, for 17 countries (Jordà et al. 2014). The second dataset, compiled for a study by Knoll et al. (2014), presents newly unearthed data covering long-run house prices for 14 out of the 17 economies in the first dataset, from 1870 to 2012. This is the first time both datasets have been combined.
House prices, interest rates, and mortgage credit aggregates are jointly determined in equilibrium, and this makes establishing causality difficult. To finesse this problem, we exploit the well-known policy trilemma in international macroeconomics (Obstfeld and Taylor 2004). Broadly speaking, when countries peg to some base currency they effectively import the base economy’s monetary policy. Exchange rate pegs therefore provide a source of exogenous variation in domestic monetary conditions that we can use as an instrumental variable (IV) to estimate the impact of changes in monetary conditions on real estate lending and house prices.
Using the trilemma to identify exogenous interest rate changes
The trilemma provides a novel way to identify domestic interest rate perturbations that are unrelated to domestic economic conditions. Earlier research embraced this logic in a variety of ways: di Giovanni and Shambaugh (2008) use the same instrument to look at postwar output volatility in fixed and floating exchange rate regimes; Ilzetzki et al. (2013) partition countries by their exchange rate regimes to study the impact of fiscal policy shocks. In our paper, we use the IV strategy to measure the effect of exogenous fluctuations in the price of credit on mortgage and house price booms and busts.
The core assumption for the validity of the instrument is that, under full capital mobility, countries that peg their exchange rate lose control of monetary policy. Instead, monetary policy is largely imposed from abroad by the base country’s policy needs. Monetary authorities in base countries, such as the US in the Bretton Woods era, typically pay scant attention to economic conditions in foreign countries when making policy choices. Examples for this disregard are legion. At the G10 Rome meetings in 1971, US Treasury Secretary John Connally declared to the world that “the dollar is our currency, but it’s your problem”. Or, as Richard Nixon put it more colourfully, “I don’t give a shit about the lira”. Today the recurrent mutterings about currency wars tell the same story: while the spillovers from US monetary policy to the ‘dollar bloc’ of emerging economies, especially India and China, are well understood, players on all sides harbour few illusions that the Federal Reserve will shape its interest rate policies to suit conditions in far-away countries.
The trilemma instrument is certainly not a weak instrument. First stage regressions indicate that the slope coefficients are significant at the 1% level, and the regression F-statistics exceed 15 in all cases. The coefficient estimates themselves are closer to 0.5 than 1, suggesting that the pass-through from base to home rates is not one-for-one. This is not surprising since the peg is sometimes implemented using bands. The results of the first stage regression match very closely those in Obstfeld et al. (2004, 2005). The insight that the trilemma is binding has been central to open economy macroeconomics since the work of Mundell and Fleming, and in the last decade has seen extensive empirical testing and validation (Obstfeld et al. 2004, 2005, Aizenman et al. 2008, Klein and Shambaugh 2013).
Monetary policy triggers bets on the house
The central estimation problem in our paper is to evaluate how changes in monetary conditions affect mortgage borrowing and house prices. The empirical strategy combines the local projection approach (Jordà 2005) with instrumental variable methods. Recent papers that have used this particular combination of procedures include Jordà and Taylor (2013), Leduc and Wilson (2013) and Owyang et al. (2013).
Figure 1 traces the cumulative effect of an exogenous one-percentage point (100 bps) decline in the short-term interest rate (measured using three-month government debt instruments) on long-rates (measured using government bonds between five and ten years maturity), mortgage lending (measured as a ratio to GDP) and house prices (measured as a log ratio to income). Because we are using a linear model, the effect is symmetric whether we are evaluating the impact of an increase or that of a decline in the short rate.
Year zero is the year when the shock is felt. An exogenous 100 bps decrease in the short rate results in about a 50 bps decrease in the long rate on impact, and an increase in mortgage loans to GDP of about 0.5 percentage points. Yet the effect of the initial shock keeps building over time, and by year four there is about a 3 percentage point increase in the ratio of mortgage loans to GDP.
In light of the response of long-term rates and mortgage lending, one might expect house prices to increase in response to an exogenous decline in interest rates. The bottom-right panel shows that this is indeed the case. A fall of the short rate of 1 percentage point builds up over time and leads to a 4% increase of the house price-to-income ratio after four years. (Or alternatively, an exogenous increase results in a sizeable decline instead.) Various robustness checks and sample splits further strengthen our core result that monetary policy has indeed a powerful influence on households’ willingness to take bets on the house.
Figure 1. Effect of an exogenous one-percentage point reduction of the short-term interest rate on long-term rates, mortgage lending and house prices
From housing boom to bust
We have established that loose/tight monetary conditions make credit cheaper/dearer and houses more expensive/affordable. But what about the dark side of low interest rates – do they also increase the risk of a financial crash?
The answer to this question is clearly affirmative, as we show in the last part of our paper using crisis prediction models. Over the past 140 years of modern macroeconomic history, mortgage booms and house price bubbles have been associated with a higher likelihood of a financial crisis. This association is even stronger in the post-WW2 era, which was marked by the democratisation of leverage through the expansion of housing finance relative to GDP and a rapidly growing share of real estate loans as a share of banks’ balance sheets.
Our findings have important implications for the post-crisis debate about central bank policy. We provide a quantitative measure of the financial stability risks that stem from extended periods of ultra-low interest rates. We also provide a quantitative measure of the effects of monetary policy on mortgage lending and house prices. These historical insights suggest that the potentially destabilising by-products of easy money must be taken seriously and considered against the benefits of stimulating flagging economic activity. Policy, as always, must strike a fine balance between conflicting objectives.
An important implication of our study is that macroeconomic stabilisation policy has implications for financial stability, and vice versa. Resolving this dichotomy requires central banks to make greater use of macroprudential tools alongside conventional interest rate policy. One tool is insufficient to do two jobs. That is the lesson from modern macroeconomic history.
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