Tom Mayock

Housing Bubbles and Busts: The Role of Supply Elasticity

Existing studies of the relationship between housing price dynamics and housing supply—which have relied upon questionable proxies for supply elasticity—have yielded highly mixed results. In this paper we provide new evidence on this relationship based on actual estimates of the price elasticity of supply for local markets in Florida. Intermarket differences in housing supply elasticity are found to explain much of the variation in housing price movements and new construction during the most recent boom-bust cycle. Additionally, we find that variance in the elasticity of housing supply can be attributed to differences in land availability and the local fiscal and regulatory environment. (JEL R14)

How Does Home Equity Affect Mobility

The impact of the housing crash on household mobility is theoretically ambiguous. Households that have little or negative equity are less likely to move because the proceeds from the sale of the home may not be large enough to pay off the original mortgage and provide a sufficient down payment on a new home. On the other hand, at sufficiently negative levels of home equity, household mobility may actually increase through the foreclosure channel. In this paper we develop and empirically test a model that incorporates both of these mechanisms. Our empirical results – based on data for Florida homeowners – provide evidence of a non-monotonic relationship between home equity and mobility. Although default-induced mobility did increase following the financial crisis, this increase did little to offset the substantial decline in voluntary moves due to home equity lock-in; we find that on net, household mobility declined by roughly 25% in our sample because of reductions in equity.

The Variance in Foreclosure Spillovers across Neighborhood Types

The estimation of foreclosure spillover effects has been the subject of a number of studies following the most recent housing market crash. An important issue largely overlooked by these studies is the extent to which these spillovers vary across neighborhoods. In this article, we use data from the South Florida metropolitan area to study the variance in these foreclosure spillovers across neighborhoods with different income levels and racial concentrations. We find that the largest foreclosure spillovers occur in higher-income neighborhoods. In low-income, minority neighborhoods, we find no evidence of spillover effects. The results have important implications for local governments.

Wages, Housing Prices, and Commutes

Whereas economic theory suggests that, all else equal, workers should be willing to accept disamenities such as higher housing costs and longer commutes only if they are compensated with higher wages, little is known about the magnitude of these compensating differentials. In this article, I address this gap in the literature by estimating an empirical model of the relationship between wages, housing prices and commutes that addresses the simultaneous determination of these variables. The results from the empirical models suggest that the wage premia associated with high housing costs and long commutes are substantial. Furthermore, results from baseline models reveal that estimates of these compensating differentials are seriously biased if endogeneity is not addressed.

Wages, Housing Prices and Commutes: Wages, Housing Prices and Commutes

Whereas economic theory suggests that, all else equal, workers should be willing to accept disamenities such as higher housing costs and longer commutes only if they are compensated with higher wages, little is known about the magnitude of these compensating differentials. In this article, I address this gap in the literature by estimating an empirical model of the relationship between wages, housing prices and commutes that addresses the simultaneous determination of these variables. The results from the empirical models suggest that the wage premia associated with high housing costs and long commutes are substantial. Furthermore, results from baseline models reveal that estimates of these compensating differentials are seriously biased if endogeneity is not addressed.

The Microdynamics of Household Credit Use through a Boom-Bust Cycle

In this paper we provide what we believe to be the first evidence on the nature of gross debt flows across consumers. We find that the aggregate dynamics in the consumer debt market are largely explained by the behavior of consumers with mortgage debt, and the behavior of such consumers is found to be sensitive to changes in housing market conditions. Our results show that there is a significant amount of consumer-level heterogeneity as evidenced by large amounts of simultaneous debt creation and debt destruction throughout the economic cycle. Finally, we find that there are important asymmetries in the debt adjustment process: whereas consumers are able to take on large amounts of additional debt quickly, short of defaulting debt is discharged very slowly. This slow deleveraging process may help explain why total consumer debt levels have been so slow to recover in the years following the Great Recession.

Adverse Selection in the Market for Mortgage Servicing Rights

Activity in the U.S. market for mortgage servicing rights has increased in recent years. Incumbent servicers are at a significant informational advantage relative to potential buyers of these servicing rights, introducing the possibility of adverse selection. This paper marks the first investigation of adverse selection in the market for mortgage servicing rights. Using data from mortgage servicers, we find that loans with higher ex ante measures of prepayment and default risk were more likely to experience a servicing transfer. Results from an ex post analysis in which we condition on these risk measures reveals that loans that experienced a servicing transfer were more likely to prepay and default, a finding that suggests that the market for servicing rights is characterized by adverse selection.

Mortgage Characteristics and the Racial Incidence of Default

Previous research has shown that relative to White borrowers, Black and Hispanic borrowers taking out mortgages at the height of the early-2000s housing boom experienced significantly higher delinquency rates. In this paper we attempt to gain a better understanding of the mechanisms that gave rise to these racial differences in mortgage delinquency. Using a database of nearly 9 million mortgages originated between 2005 and 2009, we find that minority borrowers were significantly more likely to have mortgages with high-risk contract characteristics, such as prepayment penalties, variable interest rates, balloon structures, and negative amortization periods. Results from mortgage default models and a decomposition exercise show that the concentration of minority buyers in such loans explains a significant fraction of the difference in default rates between racial groups. The totality of our results suggest that exotic loan characteristics acted as mortgage default accelerants for many minority homeowners that experienced significant income and equity shocks during the Great Recession.

If We Build it, Will They Come? The Housing Stock and the Socioeconomic Integration of Elementary Schools

Children from poor families achieve more academically if they are enrolled in schools that are socioeconomically integrated, but low-income students are increasingly attending schools characterized by high concentrations of poverty. Providing more housing opportunities for low-income families within the attendance zones of middle- and high-income schools has the potential to reverse this trend, but the link between the housing stock and the socioeconomic segregation of public schools has not been addressed in the existing literature. Using a panel of elementary schools in Florida, we show that increasing the stock of rental and affordable housing units in middle- and high-income neighborhoods has an important effect on the number of poor children attending these schools. Our results also reveal the types of housing units that have the largest impacts.Children from poor families achieve more academically if they are enrolled in schools that are socioeconomically integrated, but low-income students are increasingly attending schools characterized by high concentrations of poverty. Providing more housing opportunities for low-income families within the attendance zones of middle- and high-income schools has the potential to reverse this trend, but the link between the housing stock and the socioeconomic segregation of public schools has not been addressed in the existing literature. Using a panel of elementary schools in Florida, we show that increasing the stock of rental and affordable housing units in middle- and high-income neighborhoods has an important effect on the number of poor children attending these schools. Our results also reveal the types of housing units that have the largest impacts on socioeconomic segregation.

Should We Fear the Shadow? House Prices, Shadow Inventory, and the Nascent Housing Recovery

Abstract Although a broad-based increase in house prices has been observed over the past year, not everyone is convinced the rise of house prices will persist and lead to a steady recovery of the economy. The main reason for this skepticism is uncertainty about the “shadow inventory”: foreclosed homes held by investors or as REOs, which have not yet hit the market but likely will as market prices rise. The volume of shadow inventory itself in local markets is largely unknown, as is its impact on the housing market. This study quantifies the size of the shadow inventory and investigates the spatial impact of the out-flow of shadow inventory. The scope of our study is a set of housing markets (AZ, CA, and FL) that vary in both their historic housing price volatility as well as institutional factors - such as foreclosure law statutes - that may influence the relationship between the shadow inventory and house price dynamics. To address the endogeneity that characterizes the spatial interaction of house prices and the out-flow of the shadow inventory, we utilize a simultaneous equation system of spatial autoregressions (SESSAR). The model is estimated using measures of the shadow inventory derived from DataQuick’s national transaction history database and county-level house price indices provided by Black Knight. Lastly, because our estimate - as well as all other existing estimates - of the shadow inventory relies upon string matching algorithms to identify entry into and exit out of REO status, we validate the accuracy of our measures of REOs using loss mitigation data from the OCC Mortgage Metrics database.