Forced Sales and House Prices

By John Y. Campbell, Stefano Giglio, Parag A. Pathak. 2011

883 citations recorded by the source corpus.

This paper uses data on house transactions in the state of Massachusetts over the last 20 years to show that houses sold after foreclosure, or close in time to the death or bankruptcy of at least one seller, are sold at lower prices than other houses. Foreclosure discounts are particularly large on average at 28% of the value of a house. The pattern of death-related discounts suggests that they may result from poor home maintenance by older sellers, while foreclosure discounts appear to be related to the threat of vandalism in low-priced neighborhoods. After aggregating to the zipcode level and controlling for regional price trends, the prices of forced sales are mean-reverting, while the prices of unforced sales are close to a random walk. At the zipcode level, this suggests that unforced sales take place at approximately efficient prices, while forced-sales prices reflect time-varying illiquidity in neighborhood housing markets. At a more local level, however, we find that foreclosures that take place within a quarter of a mile, and particularly within a tenth of a mile, of a house lower the price at which it is sold. Our preferred estimate of this effect is that a foreclosure at a distance of 0.05 miles lowers the price of a house by about 1%.

Subfields: Accounting, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/933948fe04429611a2ee0c834dcb142aab5f5fb3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

In Economics and Econometrics

In Finance

Citations in the corpus

Housing markets in a pandemic: Evidence from historical outbreaks (2020, background): “This mechanism has been well-documented for foreclosure sales (e.g. Campbell et al., 2011 ), but might also apply to regular ﬁre sales.”
Deep Learning for Mortgage Risk* (2016, methodology): “(2014), Campbell et al. (2011), Towe & Lawley (2013), and others.”
Household Debt: Facts, Puzzles, Theories, and Policies (2015, background): “Agarwal and Bos (2014) find a similar pattern for Swedish pawn borrowers. markups they could avoid with a seemingly modest amount of additional shopping effort or sophistication at origination (for cites see Campbell et al (2011), and the last paragraph in this sub-section ).”
Forecasting real estate prices (2012, background): “In addition, location identifiers (such as zip codes, location dummies for proximity to the ocean or nearby lakes)are usually included in the regression in order to account for unobserved heterogeneity, as in Campbell, Giglio, and Pathak (2011).”
Mortgage Market Design (2012, methodology): “Campbell et al. (2011a), using Massachusetts data from the 1980s through 2009, compare the prices of houses sold by mortgage lenders after foreclosure with the prices of comparable properties sold by owner occupants, and nd an average foreclosure discount of 27%.”
Policy Intervention in Debt Renegotiation: Evidence from the Home Affordable Modification Program (2016, neutral): “7 Posner and Zingales 2009 and Campbell et al. 2011).”
Wildfire risk, salience & housing demand (2018, background): “Examples include Loomis (2004), Troy and Romm (2004), Donovan et al. (2007), Mueller and Loomis (2008), Huggett Jr et al. (2008), Mueller et al.”
The Price of Wine (2015, neutral): “Hedonic models relate transaction prices to their value-determining characteristics (Rosen, 1974) and are commonly used to study price formation in markets for infrequently traded assets such as real estate (e.g., Campbell, Giglio, and Pathak, 2011) and art (e.g., Renneboog and Spaenjers, 2013).”
FINANCIAL LITERACY, FINANCIAL EDUCATION AND ECONOMIC OUTCOMES (2012, neutral): “Campbell et al. (2011b) lay out a useful framework for thinking about potential policy options to improve financial outcomes for consumers.”
The Effect of Foreclosures on Nearby Housing Prices: Supply or Disamenity? (2014, positive): “This strategy is employed by Campbell et al. [2011] and can be viewed as a kind of time-differencing.(17) The estimates reported for each type of foreclosure in the bottom panel of column (2) are calculated by subtracting the estimate on the count of foreclosures in the following year from the estim”