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Foreclosures, house prices, and the real economy

Several academics, policymakers, and regulators emphasise the role of foreclosures in the Great Recession and subsequent global crisis. This column provides one of the first attempts to show this empirically. Using micro-level data from all US states, it shows that foreclosures had a significant negative effect on house prices, residential investment, durable consumption – and consequently the real economy.

How does a negative shock to the economy get amplified into a severe and long-lasting economic slump? The answer may be found in your house. An extensive body of theoretical research shows that the forced sale of durable goods – in many cases a house – can have two undesirable consequences. First, the price of these goods is driven down. Second, these negative price effects can lead to a significant decline in real economic activity (see for example Shleifer and Vishny 1992, Kiyotaki and Moore 1997, Krishnamurthy 2009, Lorenzoni 2008, and Shleifer and Vishny 2010 for a recent discussion). Indeed, many academics, policymakers, and regulators have emphasised these models in building an understanding of the recession of 2007 to 2009.

Unprecedented foreclosures

In recent research (Mian et al. 2011), we examine this idea in the context of the recent rise in foreclosures in the US. We ask to what extent this has been responsible for the recent collapse in house prices and the fall in durable consumption and residential investment – important factors in determining major macroeconomic fluctuations (Leamer 2007).

The stylised facts suggest a correlation at the very least. The top left panel of Figure 1 shows that aggregate foreclosure filings in the US increased from 750,000 in 2006 to almost 2.5 million in 2009. While we do not have data on foreclosures before 2006, the mortgage default rate increased above 10% in 2009, which is more than twice as high as any year since 1991. By any standard, the recent US mortgage default and foreclosure crisis is of unprecedented historical magnitude.

This sharp rise in foreclosures has been accompanied by large drops in house prices, residential investment, and durable consumption. As the top right panel of Figure 1 shows, nominal house prices fell 35% from 2005 to 2009. The drop in residential investment from 2005 to 2009 shown in the bottom left was larger than any drop experienced in the post World War II era. The drop in durable consumption is also large, but more comparable to recent recessions.

Figure 1. 

Empirical strategy

A glance at the aggregate data may lead to the conclusion that foreclosures have an obvious negative causal effect on house prices and therefore real economic activity. But isolating a causal effect of foreclosures on house prices is a significant challenge because house price declines or other negative economic shocks will lead to a rise in foreclosures. Or in other words, how do we know that foreclosures are the cause of declining house prices and economic weakness rather than an effect?

Our empirical strategy is designed to isolate as accurately as possible the causal effect of foreclosures on house prices and the broader economy. We start with a micro-level data set covering the entire US from 2006 to end 2009 with information on house prices, residential investment, auto sales, mortgage delinquencies, and foreclosures. We have all of these variables at the zip code-year level, with the exception of residential investment and auto sales which are at the county-year level.

Our strategy to isolate the effect of foreclosures on outcomes relies on variation in foreclosures that is driven by state rules on whether a foreclosure must take place through the courts (a judicial foreclosure). In states that require a judicial foreclosure, a lender must sue a borrower in court before conducting an auction to sell the property. In states without this requirement, lenders have the right to sell the house after providing only a notice of sale to the borrower (a non-judicial foreclosure). Figure 2 maps out those states with different rules. As first highlighted in the economics literature by Pence (2006), the 21 states that require judicial foreclosure impose substantial costs and time on lenders seeking to foreclose on a house.

Figure 2. 

Foreclosures and house

Using this instrumental variable approach, we find that foreclosures have a substantial effect on house prices. Our state-level baseline estimate suggests that a one standard deviation increase in foreclosures in 2008 and 2009 leads house price growth to be two-thirds of a standard deviation lower over the same period.

Our estimate of the effect of foreclosures on house price growth is robust to extensive controls for demographics and income differences across states. All specifications explicitly control for the effect of mortgage delinquencies on house prices. In other words, our estimate captures the incremental price effect of foreclosures above and beyond delinquencies. In addition, the effect is robust to the use of either the Fiserv Case Shiller Weiss or Zillow.com house price indices.

We also employ a zip code-level border regression discontinuity specification that is similar to the specification that Pence (2006) uses for credit. This specification allows us to compare zip codes that are very close to each other in geographical distance and observable characteristics. Consistent with the state level correlations, there is a sharp increase in the foreclosure rate as one crosses the border from a judicial requirement state into a state with no judicial requirement. However, there is no similar jump in other observable variables as one crosses the border. Focusing only on zip codes that are very close to the border between two states that differ in judicial foreclosure requirement laws, we find similar two-stage least squares estimates of the effect of foreclosures on house prices. The similarity of the results using the zip code-level design mitigates omitted variable concerns in our other regressions.

Our results confirm that foreclosures have a strong negative effect on house prices that goes beyond a simple correlation.

Foreclosures, investment, and consumption

We then turn to residential investment and durable consumption. Employing a similar two stage least squares estimation strategy, we find that a one standard deviation increase in foreclosures per homeowner leads to a two-thirds of a standard deviation decrease in permits for new residential construction. Further, a one standard deviation increase in foreclosures leads to a two-thirds of a standard deviation decline in auto sales. Our estimates are robust to controls for demographics and income.

We use our microeconomic estimates to quantify the aggregate effects of foreclosure on the macroeconomy. Our estimates suggest that foreclosures were responsible for 15% to 30% of the decline in residential investment from 2007 to 2009 and 20% to 40% of the decline in auto sales over the same period.

One advantage of our study relative to the existing literature is comprehensiveness. Our analysis covers the entire US as opposed to one state or one city and we examine foreclosures all the way through the to the end of 2009. We are also the first to use state laws on judicial requirement for foreclosure to identify the effect of foreclosures on house prices – the importance of an instrument for foreclosures has been highlighted throughout the in the literature. Further, to the best of our knowledge, we are the first to examine the effect of foreclosures on real economic activity.

Foreclosures and the Great Recession

It is important to emphasise that we do not take a stand on whether foreclosures help to bring house prices, durable consumption, or residential investment closer to or further from their long-run socially efficient levels. For example, in the absence of foreclosures, house prices may display downward rigidity given loss aversion (Genesove and Mayer 2001). Alternatively, house prices may be kept above their socially efficient level by government support. Further, it is conceivable that the declines we document would occur in the long run even in the absence of foreclosures; it is also conceivable that states where foreclosure is relatively easy will experience a faster housing recovery.

But our estimates suggest that foreclosures lead to more abrupt declines in these outcomes than would be observed in the absence of foreclosures, and these declines are likely to be more painful in the midst of a severe recession. This is consistent with the amplification mechanisms emphasised in Kiyotaki and Moore (1997) and Krishnamurthy (2003). We believe that these results demonstrate a direct connection between a financial friction – forced sales induced by foreclosures – and a reduction in residential investment and durable consumption during and after the recession of 2007 to 2009.

Our estimates of the effect of foreclosures on residential investment and auto sales can partially explain both the magnitude and length of the recession of 2007 to 2009. For example, the sharp rise in foreclosures began relatively late in the recession and continues into 2010. If we combine this fact with the finding in Leamer (2007) that residential investment is among the most powerful components leading the US out of recession, it is possible to argue that foreclosures have likely contributed to the length of the recession and sluggishness of the recovery. Similar arguments apply to our findings on auto sales.

Leamer (2007) identifies durables as the part of consumer spending with the strongest negative affect on economic growth during recessions . Under the assumption that our results on auto sales extend to the entire durable goods share of the economy (23.6 % of GDP in 2008), foreclosures can explain the relatively sluggish growth in durables well into 2010. Given that the 2007 to 2009 recession and its aftermath have been closely related to depressed levels of durable consumption and residential investment, our results thus highlight an important role for foreclosures and house prices in understanding weakness in the economy.


Genesove, David and Christopher Mayer (2001), “Loss Aversion and Seller Behavior: Evidence from the Housing Market”, Quarterly Journal of Economics, 116: 1233-1260.

Kiyotaki, Nobuhiro and John Moore (1997), “Credit Cycles”, Journal of Political Economy, 105:211-248.

Krishnamurthy, Arvind (2003), "Collateral Constraints and the Amplification Mechanism", Journal of Economic Theory, 119:104-127.

Krishnamurthy, Arvind (2009), "Amplification Mechanism in Liquidity Crises", American Economic Association Journals - Macroeconomics, 2:2.

Leamer, Edward (2007), “Housing IS the Business Cycle”, NBER Working Paper. 13248.

Lorenzoni, Guido (2008), “Inefficient Credit Booms”, Review of Economic Studies, 27:809-833.

Mian, Atif, Amir Sufi, and Francesco Trebbi (2011), “Foreclosures, house prices, and the real economy”, Working Paper.

Shleifer, Andrei and Rob Vishny (1992), “Liquidation Values and Debt Capacity: A Market Equilibrium Approach”, Journal of Finance, 47:1343-1366.

Shleifer, Andrei and Rob Vishny (2010), “Fire Sales in Finance and Macroeconomics”, NBER Working Paper 16642

Pence, Karen (2006), “Foreclosing on Opportunity? State Laws and Mortgage Credit”, Review of Economics and Statistics, 88:177-182.

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