Housing Bubbles

April 14, 2012
Christopher J. Mayer of Columbia University, Jose Scheinkman of Princeton University, and Robert Shiller of Yale University, Organizers

Fernando Ferreira and Joseph Gyourko, University of Pennsylvania and NBER

Anatomy of the Beginning of the Housing Boom: U.S. Neighborhoods and Metropolitan Areas, 1993-2009

Ferreira and Gyourko provide novel estimates of the timing, magnitudes, and potential determinants of the start of the last housing boom across American neighborhoods and metropolitan areas (MSAs) using a rich new micro data set containing 23 million housing transactions in 94 metropolitan areas between 1993 and 2009. They also match transactions data with loan information, enabling them to observe household income and other demographics for each neighborhood. They have five major findings: First, the start of the boom was not a single, national event. Booms, which are defined by the global break point in an area's price appreciation series, begin at different times over a decade-long period from 1995-2006. Second, the magnitude of the initial jump in house price appreciation at the start of the boom is economically, not just statistically, significant. On average, log house prices are over 4 points higher during the first year of the boom relative to the previous twelve month period for both MSAs and neighborhoods. There is no evidence that price growth was trending up prior to the start of the boom. Third, local income is the only potential demand shifter they find that also experienced an economically and statistically significant change around the time that local housing booms began. Contemporaneous local income growth is large enough to account for half or more of the initial jump in house price appreciation. Fourth, there is important heterogeneity in that result. Income growth is large and jumps at the same time as house price appreciation in areas that boomed early and have inelastic supplies of housing, but not in late booming areas and those with elastic supply sides. While these estimates indicate that the beginning of the boom was fundamentally justified on average, they do not imply that what followed was rational. Fifth and finally, none of the demand-shifters analyzed show positive pre-trends, but some such as the share of subprime lending, do lag the beginning of the boom. This suggests that key players in the lending market more responded to the boom, rather than caused it to start.

Alex M. Chinco, New York University's Stern School of Business, and Christopher J. Mayer

Distant Speculators and Asset Bubbles in the Housing Market

Chinco and Mayer investigate the role of out of town second house buyers (so-called "distant speculators") in bubble formation during the recent housing boom. Distant speculators are likely to rely excessively on capital gains for financial returns and to be less informed about local market conditions, much like noise traders in many financial models. Using transactions-level data that allows for identifying the address of the property owner, the authors show that increases in purchases by distant speculators (but not local speculators) are strongly correlated with high house price appreciation rates and large log-implied-to-actual rent ratios, which is a proxy for mispricing in the housing market. The authors develop a simple model that helps them to address the issue of reverse causality and to separate out circumstances when out of town second house buyers are simply responding to unobserved changes in home values and when they are helping to cause house price appreciation rates and log-implied-to-actual rent ratios to rise. Consistent with the model, they show that the size of the investment market in which out of town second house buyers live is positively related to their impact on house price appreciation rates and log-implied-to-actual rent ratios in the target area. The researchers conclude by showing the large impact that distant speculators have on the local economy, with out of town second house purchases representing as much as 5 percent of total output in Las Vegas during the boom.

Ing-Haw Cheng and Sahil Raina, University of Michigan, and Wei Xiong, Princeton University and NBER

Wall Street and the Housing Bubble: Bad Incentives, Bad Models, or Bad Luck?

Cheng, Raina, and Xiong analyze whether mid-level managers in securitized finance were aware of the housing bubble in 2004-6 by using their personal home transaction data. They find little evidence of the manangers timing the bubble or exercising caution in purchasing homes on average relative to uninformed control groups. On the other hand, real estate lawyers, a sophisticated outside group, performed better in their home transactions than securitization managers. These findings cast doubt on the popular "bad incentives" view of the recent financial crisis that Wall Street employees knowingly ignored warning signs of the housing bubble, as well as the "bad luck" view that the crisis was unpredictable by anyone. Instead, this analysis highlights distorted beliefs as a potentially important contributing factor to the crisis.

Sumit Agarwal, Federal Reserve Bank of Chicago, and Itzhak Ben-David, Ohio State University

Do Loan Officers' Incentives Lead to Lax Lending Standards?

To better understand the role of loan officers' incentives in the origins of the financial crisis, Agarwal and Ben-David study a controlled field experiment conducted by a large bank in which the incentive structure of a subset of small-business loan officers was altered from fixed salary to volume-based pay. Using a difference-in-difference design, the authors show that while the characteristics of loan applications did not change, the incentive-paid loan officers booked more loans (19 percent more) and larger loans (with dollar amounts that were 19 percent larger.) These loan officers also used their discretion more in the booking decisions. Although the loans booked by incentive-paid loan officers had better observable credit quality, they were 28 percent more likely to default. The increase in default was concentrated in loans that wouldn't have been booked in the absence of commission-based compensation, and in loans with excessive dollar amounts. These results support the idea that the explosion in mortgage volume during the housing bubble and the deterioration of underwriting standards can be attributed in part to the incentives of loan officers.

Elena Loutskina, University of Virginia, and Philip Strahan, Boston College and NBER

Financial Integration, Housing and Economic Volatility

The Financial Crisis and the Great Recession illustrate the sensitivity of the economy to a housing bust. Loutskina and Strahan show that financial integration, fostered by deregulation allowing banks to form nationwide branch networks, amplified housing-price volatility and increased the economy's sensitivity to local housing-price shocks. They exploit variation in credit-supply subsidies across local markets from the Government-Sponsored Enterprises to measure housing price changes unrelated to fundamentals. Using this instrument, they find that a 1 percent rise in housing prices causes a 0.25 percent increase in economic growth. This effect is larger in localities more financially integrated with other markets through bank ownership ties. Financial integration thus raised the effect of collateral shocks on the economy, thereby increasing economic volatility.

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