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Prior research indicates a discount for foreclosures sold through the multiple listing service (MLS). The purpose of this paper is to examine whether the effect of foreclosure on house value is consistent over submarkets based on property size in the US single family home market. The paper also tests whether the spillover effect of a nearby foreclosure on the specific property value varies across submarkets.

The full sample is split into four quartiles based on the square feet of all observations. The hedonic pricing models are estimated across full sample and three subsamples, in order to examine the effect of foreclosure on selling price. The number of neighborhood foreclosures within each combination of radii and timing intervals is used to investigate the spillover effect of a nearby foreclosure on the specific property value.

It is found that the quartile with smaller houses have the largest discount associated with a foreclosure of approximately 24 percent, while the medium and larger houses have a discount of approximately 19 percent. The results are robust after including a proxy for property quality. Second, the spillover effects of nearby foreclosures are lowest for small properties and highest for large properties. Adding additional controls for housing quality reduces the observed spillover effect.

The findings on foreclosure discount are consistent with Pennington‐Cross's argument, that the foreclosures in the smaller properties have lower appreciation than the larger ones. The paper's results about spillover effects also support the previous research, implying a greater stigma for foreclosed houses in neighborhoods with larger, more expensive houses.

The paper provides potential explanation for foreclosure discount and spillover effects of nearby foreclosure in the US single family residential markets.

Foreclosure risk is a key concern to lenders of real estate mortgages. Using auction data, this study provides the first analysis of mortgage foreclosure in Singapore by examining how macro‐economic variables affect the probability of foreclosure. The foreclosure rate for properties is found to be increasing in the first five years of purchase and decreases as the holding period lengthens. The likelihood of foreclosure increases with unemployment rate, mortgage rate and expenditure and decreases with equity, dividend yield and lending volume at fourth and twentieth quarters lag. Further analysis shows considerable differences between residential and non‐residential properties. However, when the analysis on non‐residential properties is further separated into office, retail and industrial sub‐sectors, the results are relatively similar among the three sub‐sectors. This implies that banks and financial institutions should apply different underwriting standards for residential properties, mainly for owner‐occupation and non‐residential properties for the purpose of businesses and rental income.

This paper aims to investigate the foreclosure discount for the German residential market in the years from 2008 to 2011.

The determinants of the foreclosure discount are estimated in a hedonic price model. The analysis is based on a unique data set compiled from three different data sources with 135,000 foreclosed properties.

The findings reveal that residential units in foreclosures are sold at a discount of 19 per cent compared to residential units with similar characteristics that are not in foreclosure. Second, a regional pattern can be observed, with discounts being negatively correlated to unemployment risk and liquidity. Third, the model with interaction terms shows that foreclosure discounts are linked to specific property characteristics. Fourth, these object-related risks are typically smaller than regional risks or locational risks.

Given the highly fragmented system of Gutachterausschüsse in Germany, who are responsible for collecting transaction data, we were not able to directly analyze transaction data, but only a proxy for this price information.

The results can be important for financial institutions that are trying to assess the risk of lending for a specific object in a specific location. So far, banks primarily try to assess the default risk of private lenders by analyzing the debtor’s financial position and the quality of the property. The analysis provides insights into which characteristics of a property might imply additional risk, and in which region these risks are biggest.

To the best of the authors’ knowledge, this is the first attempt to analyze the foreclosure discount for the German housing market.

The problem in alleviating homeowner mortgage distress through refinance is how to achieve meaningful alleviation without prospectively harming the financier. The problem revolves around two parameters from real estate finance – the probability that the distress leads to foreclosure and resulting foreclosure loss severity for the financier if foreclosure does occur. Previous analysis focuses on reducing the probability that homeowner distress leads to foreclosure. By contrast, the purpose of this paper is to focus on reducing foreclosure loss severity.

The study develops a new intuitive formula for foreclosure loss severity to quantify its dependence on transaction costs. The study shows that foreclosure loss severity reduction is feasible by introducing a new refinancing instrument that lowers foreclosure transaction costs and applying property law to derive the structure of the refinancing instrument.

Foreclosure loss severity reduction can subsidize concessions on scheduled payments for homeowners with arbitrarily poor credit without prospective harm to the financier.

Quantification of mortgage distress relief is limited to distressed mortgages described by representative parameter values from various government studies.

For most distressed homeowners, payment and principal reductions could exceed those available from the recent government programs.

Implementation should significantly enlarge the pool of homeowners eligible for mortgage distress relief.

The mortgage refinance is qualitatively different from that available under existing government refinance programs because it is based on an arms-length exchange of property rights that makes market sense regardless of whether the refinancing results in subsequent homeowner default.

This paper aims to examine the anatomy of a real estate bubble. In the process, the paper identifies three phases of the market's evolution: flips, flops and foreclosures. An examination of the Las Vegas real estate market illustrates the three phases.

The paper examines transaction data from the metropolitan Las Vegas area (Clark County) from 1994 to 2009. The first part of the analysis identifies the three phases of the bubble and is descriptive in nature. This is followed by more formal tests of Granger causality.

In the early part of the sample, a large percentage of transactions are speculative or “flips” causing prices to rapidly increase. Eventually, flipping loses its profitability and over the last three years, there is an increasing number of foreclosures leading to falling prices. The descriptive analysis of the Las Vegas market is augmented with causality tests which show that prices were the driving force behind all three phases in the market's evolution.

Future research might focus on underlying structural inter‐temporal relationships to augment the Granger causality tests.

Analysis shows that price is the driving force behind a bubble and that loan modification programs alone will not solve the current housing crisis.

Government entities might expand neighborhood stabilization programs to affect both demand and supply of homes. Moreover, it might be prudent to include information related to flipping on multiple listing service agreements. Additionally, local governments should be consistent in their record keeping.

To the best of the authors' knowledge, this is the first paper to examine the housing bubble using an extensive set of transaction data.

The purpose of this paper is to examine the determinants of property sale probability and sale price at auction in Kuala Lumpur, Malaysia.

A two-stage Heckman sample selection model is used for this research. The first stage involves the estimation of a probit model on a successful sale. The second stage introduces an additional selection variable, the inverse Mills ratio, as an explanatory variable to the sale price estimation equation.

The authors find that Chinese-owned auctioned properties have higher sale probability and are sold at higher prices as compared to Indian and Malay-auctioned properties. Properties auctioned by the largest auction house outperformed other smaller auctioneers. Auction characteristics such as proximity to the city center, number of previous auction attempts and number of online viewers are positively related to sale price and sale probability.

The findings on the substantially lower sale price obtained by Malay and Indian borrowers compared to their Chinese counterparts imply that it is much harder for these borrowers to be relieved from financial distress. The two plausible explanations offered in this paper for this price differential, i.e. racial residential segregation and ownership restriction, warrant further study.

First, the authors consider the explanatory power of seller ethnicity, number of online viewers and auctioning route which are new to the literature. Second, they use a Heckman model that addresses possible selection bias of sold properties. This methodology is unexplored in the auction literature.

In 2010 Drive Property Solutions, a special servicing firm in Chicago, had partnered with Spiner Capital to win an FDIC auction of distressed debt. Included in that auction was the defaulted mortgage note on Northwinds Community Crossing, a retail strip mall in suburban Savannah, Georgia, which had been in default since November 2009. Sam Schey, an asset manager at Drive, needed to decide how to maximize recoveries from the nonperforming loan.

Tax sales intersect with the market, housing policy and socioeconomic matters, but the topic in this context is understudied. The purpose of this paper is to investigate whether and how land banking is more effective in fostering positive property outcomes than tax lien sales and what market-based measures can be combined with land banking to reuse tax delinquent, vacant and abandoned properties.

This paper analyzes the consequences of tax lien sales and land banking in Indianapolis, Indiana, the USA. Various local data sources are used.

This paper finds that land banking, when compared to tax lien sales, results in less tax delinquency, less vacancy and abandonment, more increase in assessed value and fewer ownership changes after sales. Also, this paper shows the contributions of non-profit and for-profit developers as business partners to land banks.

This paper demonstrates the utility of the land banks that have become prevalent in some states in the USA over the past 20 years. The results of this paper recommend the realistic approach of combining government intervention and market forces.

This paper sheds light on the US practice of tax lien sales. It goes largely unnoticed, but malpractice risks harming the vulnerable members of community.

Housing policy needs to find common ground with the market. It is a dilemma, more or less, for every country. The results of this paper suggest a harmonized public policy approach that includes land banking and the market can be effective in combatting with troubled properties.

This paper aims to examine the determinants of socioeconomic factors on housing prices and their differential effects among regions.

This study employs a hierarchical linear model to analyze the housing and socioeconomic data of 363 metropolitan statistical areas (MSAs) in the USA.

This study generates four findings. First, the population, the percentage of the elderly in population, violent crime rates, and foreclosure rates produce greater effects on housing prices in the Northeast than those in the West. Second, the population produces a greater effect on housing prices in the Northeast than those in the Midwest. Third, mortgage rates produce less significant effects on housing prices in the Northeast than those in the Midwest. Fourth, the population, the percentage of the elderly in population, and rent-income ratio produce greater effects on housing prices in the Northeast than those in the South.

Based on data collected for 2010, this study analyzes socioeconomic factors on the demand side under the implicit assumption that supply side remains constant. Future research can lift the restriction on fixed supply assumption.

The results can provide information to buyers and sellers about how socioeconomic factors affect housing prices. Moreover, this study also provides useful information for the government to design and implement relevant housing policies.

This is the pioneering study to examine the differential effect of socioeconomic factors on metropolitan housing prices among regions by employing dummy regional variables to detect changes in slope coefficients. These detailed conclusions would enhance the efficiency of transaction in housing markets.

In this introductory essay, the authors describe a new public finance characterized by enduring revenue constraints; mounting budgetary claims from accruing liabilities for post-retirement benefits for government employees, rising health care costs, and an aging population; and uncertainty about future budgetary demands and resource limitations. The new public finance is described as a convergence of economic and demographic forces with past practices that increased the fiscal vulnerability of states and local governments. The authors explain that states and local governments will not overcome challenges by relying upon traditional ways of thinking about and conducting business but instead must revamp frameworks for practice. Symposium papers are described as tackling several of the most pressing issues facing governments today with an eye towards rethinking customary approaches.