Recent Housing Bust Research Articles

How Do Foreclosures Exacerbate Housing Downturns?

AbstractThis article uses a structural model to show that foreclosures played a crucial role in exacerbating the recent housing bust and to analyse foreclosure mitigation policy. We consider a dynamic search model in which foreclosures freeze the market for non-foreclosures and reduce price and sales volume by eroding lender equity, destroying the credit of potential buyers, and making buyers more selective. These effects cause price-default spirals that amplify an initial shock and help the model fit both national and cross-sectional moments better than a model without foreclosure. When calibrated to the recent bust, the model reveals that the amplification generated by foreclosures is significant: ruined credit and choosey buyers account for 25.4% of the total decline in non-distressed prices and lender losses account for an additional 22.6%. For policy, we find that principal reduction is less cost-effective than lender equity injections or introducing a single seller that holds foreclosures off the market until demand rebounds. We also show that policies that slow down the pace of foreclosures can be counterproductive.

Adjusting Educational Decisions to the Housing Bust

This paper mainly utilizes short-run housing wealth changes during the recent housing bust to identify the effect of parental wealth on post-secondary educational decisions. I find that an increase in family wealth didn’t significantly affect young adults’ college enrollment, which is not quite consistent with previous literature’s prediction. For those already enrolled in college before the unexpected movement in housing price, the early dropout rate was hardly affected as the home value dramatically declined. In response to possible discontinued monetary support from parents during the housing bust, college students significantly increase the amount of debts taken on under their own names. Moreover, they chose to work more hours to finance educational expenses. According to the estimation in this paper, the decline in home value during the housing market crash from 2007 to 2009 contributed to more loans taken on by $113, and 14 more hours worked each year on average. I also examine whether parents cashed out money from a pension or an IRA to support their children. Having kids enrolled in college and under the age of 21 increases the likelihood of withdrawing money from pension or IRA by 3 percentage points.

From Housing Bust to Credit Crunch: Evidence from Small Business Loans

This paper provides evidence that the recent housing bust in the United States precipitated a “credit crunch” for small businesses. We compare banks’ small business lending in the same metropolitan areas, and find that those that originated or purchased more of their mortgage loans in depressed housing markets elsewhere reduced local lending more substantially. The findings suggest a substantial spill-over effect across sectors and geographical areas. The effect is greater for banks with more than $10bn in assets. Overall, the fall in house prices accounted for one third of the decline in small business loans originated by major banks in the U.S. from 2007 to 2009.

Time-warped growth processes, with applications to the modeling of boom–bust cycles in house prices

House price increases have been steady over much of the last 40 years, but there have been occasional declines, most notably in the recent housing bust that started around 2007, on the heels of the preceding housing bubble. We introduce a novel growth model that is motivated by time-warping models in functional data analysis and includes a nonmonotone time-warping component that allows the inclusion and description of boom-bust cycles and facilitates insights into the dynamics of asset bubbles. The underlying idea is to model longitudinal growth trajectories for house prices and other phenomena, where temporal setbacks and deflation may be encountered, by decomposing such trajectories into two components. A first component corresponds to underlying steady growth driven by inflation that anchors the observed trajectories on a simple first order linear differential equation, while a second boom-bust component is implemented as time warping. Time warping is a commonly encountered phenomenon and reflects random variation along the time axis. Our approach to time warping is more general than previous approaches by admitting the inclusion of nonmonotone warping functions. The anchoring of the trajectories on an underlying linear dynamic system also makes the time-warping component identifiable and enables straightforward estimation procedures for all model components. The application to the dynamics of housing prices as observed for 19 metropolitan areas in the U.S. from December 1998 to July 2013 reveals that the time setbacks corresponding to nonmonotone time warping vary substantially across markets and we find indications that they are related to market-specific growth rates.

Bubble-like housing boom–bust cycles: Evidence from the predictive power of households’ expectations

Abstract This study examines the role of households’ expectations in predicting the housing boom–bust cycles in the United States. It incorporates two nonlinear features of housing price dynamics: a threshold co-movement between households’ expectations and housing price growth and a structural break in their interrelation. It uses the monthly good-time-to-buy (GTTB) index as a proxy for households’ expectations about the U.S. housing market, and employs the structural break threshold vector autoregression (SBTVAR) to specify breakpoints in housing market dynamics during the recent decades. The findings indicate that shifts in interactions between households’ expectations and housing price growth are synchronous with the recent housing boom–bust cycles. The SBTVAR framework outperforms other models as it captures more of the housing market's unique dynamic characteristics. The GTTB index, which governs expectation regime-switching patterns, is able to signal the recent housing bust three periods in advance.

Falling House Prices and Labor Mobility: Evidence from Matched Employer-Employee Data

This study uses worker-level employment data from the U.S. Census Bureau to test whether falling home prices affect a worker’s propensity to take a job in a different metropolitan area from where he is currently located. Using a sample of workers from the American Community Survey, I employ a within-MSA-time estimation that compares homeowners to renters in their propensities to relocate for jobs according to data from the Longitudinal Employer Household Dynamics database. This strategy allows me to disentangle the influence of house prices from that of other time-varying, location-specific shocks. Estimates show that homeowners who have experienced declines in the nominal value of their home are approximately 20% less likely to take a new job in a location outside of the metropolitan area that they currently live and work in, relative to an equivalent renter. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decreased labor mobility of homeowners during the recent housing bust.

Revenge of the Optimum Currency Area

Revenge of the Optimum Currency Area

The Effect of Liquid Housing Wealth on College Enrollment

This article uses short-run housing wealth changes to identify the effect of housing wealth on college attendance. I find that households used their housing wealth to finance postsecondary enrollment in the 2000s when housing wealth was most liquid; each $10,000 in home equity raises college enrollment by 0.7 of a percentage point on average. The effect is localized to lower-resource families, for whom a $10,000 increase in housing wealth increases enrollment by 5.7 percentage points. These estimates imply that the recent housing bust could significantly negatively affect college enrollment through reduction in the housing wealth of families with college-age children.

THE PECULIAR ECONOMICS OF HOUSING BUBBLES

I. INTRODUCTION Housing differs from other consumption goods in important ways. Houses are extremely durable, changing houses involves large transactions costs so that households do not move very often, and in most cases, houses are financed through borrowing. Furthermore, houses represent status and allow access to other benefits, such as parks, schools, or desirable neighborhoods. Automobiles share most of these attributes, although to a lesser extent, but housing and automobiles differ in one key feature. Automobiles, except maybe collectibles, tend to diminish in value over time. However, during several periods in recent history house prices have appreciated significantly, providing an investment motive for homeownership in addition to its consumption benefits. Home values rise rapidly during housing bubbles, generating large capital gains. Households can take advantage of these capital gains in two ways: either by selling the house or borrowing against its increased value through home equity loans or new mortgages. If households are allowed to borrow against the current values of their homes, it is a small step to allow them to borrow against the expected future values of their homes, especially when both lenders and borrowers agree that house prices will keep rising. In fact, this has been happening. The Federal Reserve Act of 1913 limited the loan-to-value (LTV) ratio, that is, the fraction of the current price of a house one could borrow, to 50%. By 1970, that limit had grown to 90%, and in 1989 it rose to 100%. In 1997, the LTV limit increased to 125% allowing the mortgage loan to exceed the market value of the house, and these loans were aggressively marketed to consumers. (1) The purpose of this article is to explore the implications of these high LTV mortgage loans secured by expected future home values. The evidence regarding high LTV loans paints a bleak picture. Haughwout, Peach, and Tracy (2008) report that 30% of subprime mortgages originated in 2006 had LTVs of at least 100%. These new subprime mortgages were the primary contributors to the first increase in homeownership rates in three decades (Chambers, Garriga, and Schlagenhauf 2007). The high LTV originations led to high foreclosure rates during the recent housing bust. In 2007. 40% of the foreclosures in Massachusetts had origination LTVs of at least 100%. Fifteen years earlier, in contrast, fewer than 9% of foreclosures had such high origination LTVs (Foote et al. 2008). Haughwout and Okah (2009) note that roughly 10% of homes had negative equity in a December 2008 sample of 43 states that exclude boom and bust states. They report that the average origination LTV for the above-water homes was 83%, and that for below-water homes was 98%. Our analysis presumes a particular type of market failure. If markets are efficient, expected future prices are tied to current prices through the interest rate. Specifically, if markets expect the price of an asset to be $600,000 in 10 years and the 10-year interest rate is 50% (i.e., 50% over 10 years and not 50% per year), then the present value of the asset is $400,000. Conversely, if the current value of the asset, say a house, is $400,000 and the 10-year interest rate is 50%, then the expected future price of the house is $600,000. But what would happen if markets forecast home prices to grow faster than the interest rate? (2) For example, what would occur if current house prices are $400,000 and are expected to rise to $700,000, but the corresponding long-term interest rate is only 50%? This scenario could materialize if the recent house price growth rate has exceeded the interest rate and both borrowers and lenders expect such recent price trends to persist, thereby expecting the housing bubble to continue, not burst. (3) How do these beliefs coupled with access to high LTV loans impact behavior today? To answer this question, we use a simple, partial equilibrium, consumer theory framework. …

Irrational Exuberance in the U.S. Housing Market: Were Evangelicals Left Behind?

The recent housing bust has reignited interest in psychological theories of speculative excess (Shiller, 2007). I investigate this issue by identifying a segment of the U.S. population - evangelical protestants - that may be less prone to speculative motives, and uncover a significant negative relationship between their population share and house price volatility. Evangelicals' focus on Biblical prophecy could account for this difference, since it may enable them to interpret otherwise negative events as containing positive news, dampening the response of house prices to shocks. I provide evidence for this channel using a popular internet measure of prophetic activity and a 9/11 event study. I also analyze survey data covering religious beliefs and asset holding, and find that 'end times' beliefs are associated with a one-third decline in net worth, consistent with these beliefs providing a form of psychic insurance (Scheve and Stasavage, 2006a and 2006b) that reduces asset demand.

Irrational Exuberance in the U.S. Housing Market: Were Evangelicals Left Behind?

The recent housing bust has reignited interest in psychological theories of speculative excess (Shiller, 2007). I investigate this issue by identifying a segment of the U.S. population-evangelical protestants-that may be less prone to speculative motives, and uncover a significant negative relationship between their population share and house price volatility. Evangelicals' focus on Biblical prophecy could account for this difference, since it may enable them to interpret otherwise negative events as containing positive news, dampening the response of house prices to shocks. I provide evidence for this channel using a popular internet measure of prophetic activity and a 9/11 event study. I also analyze survey data covering religious beliefs and asset holding, and find that 'end times' beliefs are associated with a one-third decline in net worth, consistent with these beliefs providing a form of psychic insurance (Scheve and Stasavage, 2006a and 2006b) that reduces asset demand.