Housing wealth represents the dominant form of savings for American households. Using detailed data on housing transactions across the United States since 1991, we find that single men earn 1.5 percentage points higher unlevered returns per year on housing relative to single women. The gender gap grows significantly larger after accounting for mortgage borrowing: men earn 7.9 percentage points higher levered returns per year relative to women. Approximately 45% of the gap in housing returns can be explained by gender differences in the location and timing of transactions. The remaining gap arises primarily from gender differences in execution prices: data on repeat sales reveal that women buy the same property for approximately 2% more and sell for 2% less. Women experience worse execution prices because of differences in the choice of initial list price and negotiated discount relative to the list price. Gender differences in upgrade and main- tenance rates, and preferences for housing characteristics and listing agents appear to be less important factors. Overall, the gender gap in housing returns is economically large and can explain 30% of the gender gap in wealth accumulation at retirement.
We use a five percent sample of Americans’ credit bureau data to study the effects of public health insurance on the geography of consumer financial health. Exploiting the (nearly) universal eligibility for Medicare at age 65, we find a 30 percent reduction in debt collections with limited effects on other financial outcomes. Medicare reduces the geographic variation in collections by two-thirds at age 65, and halves the geographic correlation between collections and demographics like race and education. Areas that experienced larger gains in financial health at age 65 had higher shares of black residents, people with disabilities, and for-profit hospitals.
The real estate market is highly intermediated, with 90 percent of buyers and sellers hiring an agent to help them transact a house. However, low barriers to entry and fixed commission rates result in a market where inexperienced intermediaries have a large market share, especially following house price booms. Using rich micro-level data on 10.4 million listings, we first show that houses listed for sale by inexperienced real estate agents have a lower probability of selling, and this effect is strongest during the housing bust. We then study the aggregate implications of the distribution of agents’ experience on housing market liquidity by building a dynamic entry and exit model of real estate agents with aggregate shocks. Several policies that raise the barriers to entry for agents are considered: 1) lower commission rates, 2) increased entry costs, and 3) more informed clients. Relative to the baseline, all three policies lead to an increase in average liquidity, with the largest effect during the bust.
This paper examines the effects of climate change on municipal financing costs. Using a sample of bonds issued by school districts in coastal counties, we show that municipal bond markets began pricing sea level rise (SLR) exposure following upward revisions in SLR projections in 2013. The effect is concentrated on the East Coast, where SLR is expected to be twice as large as on the West Coast, is increasing in states’ belief in climate change, and is driven largely by a district’s exposure to worst-case SLR scenarios. While the pricing effects of SLR are statistically significant, they are economically small and indicate that financial markets do not currently anticipate a high probability of SLR-induced default in the near future.
This paper argues that the debt forgiveness provided by the U.S. consumer bankruptcy system helped stabilize employment levels during the Great Recession. We document that over this period, states with more generous bankruptcy exemptions had significantly smaller declines in non-tradable employment and larger increases in unsecured debt write-downs compared to states with less generous exemptions. We interpret these reduced form estimates as the relative effect of debt relief across states, and develop a general equilibrium model to recover the aggregate employment effect. The model yields three key results. First, substantial nominal rigidities are required to rationalize our reduced form estimates. Second, with monetary policy at the zero lower bound, traded good demand spillovers across states boosted employment everywhere. Finally, the ex-post debt forgiveness provided by the consumer bankruptcy system during the Great Recession increased aggregate employment by almost two percent.
Recent innovations in statistical technology, including in evaluating creditworthiness, have sparked concerns about impacts on the fairness of outcomes across categories such as race and gender. We build a simple equilibrium model of credit provision in which to evaluate such impacts. We find that as statistical technology changes, the effects on disparity depend on a combination of the changes in the functional form used to evaluate creditworthiness using underlying borrower characteristics and the cross-category distribution of these characteristics. Employing detailed data on US mortgages and applications, we predict default using a number of popular machine learning techniques, and embed these techniques in our equilibrium model to analyze both extensive margin (exclusion) and intensive margin (rates) impacts on disparity. We propose a basic measure of cross-category disparity, and find that the machine learning models perform worse on this measure than logit models, especially on the intensive margin. We discuss the implications of our findings for mortgage policy.
Wharton School - WRDS award for the Best Empirical Finance Paper, WFA 2019
We document the representation of female economists on the conference programs at the NBER Summer Institute from 2001-2018. Over the period from 2016-2018, women made up slightly over 21 percent of all authors on scheduled papers. However, there was large dispersion in the female author share across programs. While the average share of women has slightly risen from 18 percent since 2001-2003, a persistent gap between finance, macroeconomics and microeconomics subfields remains. We examine several channels potentially affecting female representation including gender differences in acceptance and submissions rates, institutional rank, NBER affiliation, faculty seniority and the role of organizers.
We study credit ratings on subprime and Alt-A mortgage-backed-securities (MBS) deals issued between 2001 and 2007, the period leading up to the subprime crisis. The fraction of highly rated securities in each deal is decreasing in mortgage credit risk (measured either ex ante or ex post), suggesting that ratings contain useful information for investors. However, we also find evidence of significant time variation in risk-adjusted credit ratings, including a progressive decline in standards around the MBS market peak between the start of 2005 and mid-2007. Conditional on initial ratings, we observe underperformance (high mortgage defaults and losses and large rating downgrades) among deals with observably higher risk mortgages based on a simple ex ante model and deals with a high fraction of opaque low-documentation loans. These findings hold over the entire sample period, not just for deal cohorts most affected by the crisis.
We measure bank supervision using the database of supervisory issues, known as matters requiring attention or immediate attention, raised by Federal Reserve examiners to banking organizations. The volume of supervisory issues increases with banks’ asset size, especially for the largest and most complex banks, and decreases with profitability and the quality of the loan portfolio. Stressed banks are faster at resolving issues, but all else equal, resolving new issues takes longer the more issues a bank faces, which may suggest capacity constraints in addressing multiple supervisory issues. Using computational linguistic methods on the text of the issue description, we define five categorical issue topics. The subset of issues related to capital levels and loan portfolio are the most consequential in terms of regulatory rating downgrades and are directly related to changes in banks’ balance sheet characteristics and profitability. Other issues appear to reflect soft information and are less correlated with bank observables. By categorizing questions asked by analysts at banks’ quarterly earnings calls using the same linguistic approach, we find that market monitors raise issues similar to those of supervisors when the issues are related to hard information (such as loan quality or capital) and public supervisory assessment programs.
The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the Bartik instrument is numerically equivalent to using local industry shares as instruments. Hence, the identifying assumption is best stated in terms of these shares, with the national industry growth rates only affecting instrument relevance. We then show how to decompose the Bartik instrument into the weighted sum of the just-identified instrumental variables estimators, where the weights sum to one, can be negative and are easy to compute. These weights measure how sensitive the parameter estimate is to each instrument. We illustrate our results through three applications: estimating the inverse elasticity of labor supply, estimating local labor market effects of Chinese imports, and using simulated instruments to study the effects of Medicaid expansions.
Credit reports are used in nearly all consumer lending decisions and, increasingly, in hiring decisions in the labor market, but the impact of a bad credit report is largely unknown. We study the effects of credit reports on financial and labor market outcomes using a difference-in-differences research design that compares changes in outcomes over time for Chapter 13 filers, whose personal bankruptcy flags are removed from credit reports after 7 years, to changes for Chapter 7 filers, whose personal bankruptcy flags are removed from credit reports after 10 years. Using credit bureau data, we show that the removal of a Chapter 13 bankruptcy flag leads to a large increase in credit scores and economically significant increases in credit card and mortgage borrowing. Using administrative tax records linked to personal bankruptcy records, we estimate a precise zero effect of flag removal on employment and earnings outcomes. We rationalize these contrasting results by showing that, conditional on basic observables, “hidden” bankruptcy flags are strongly correlated with adverse credit market outcomes but have no predictive power for labor market outcomes.
Cross-listing on a US exchange does not force foreign firms to follow the exchange’s corporate governance rules. Hand-collected data show that 80% of cross-listed firms opt out of at least one exchange governance rule and those that opt out have a smaller share of independent directors. Cross-listed firms opt out more when coming from countries with weak corporate governance rules, but if these firms are growing and need external financing, they are more likely to comply. For firms in such countries, opting out also lowers firm valuations, decreases the value of cash holdings, and reduces investment sensitivity to market valuations.
This paper estimates the effect of Chapter 13 bankruptcy protection on post-filing financial outcomes using a new dataset linking bankruptcy filings to credit bureau records. Our empirical strategy uses the leniency of randomly-assigned judges as an instrument for Chapter 13 protection. Over the first five post-filing years, we find that Chapter 13 protection decreases an index measuring adverse financial events such as civil judgments and repossessions by 0.316 standard deviations, increases the probability of being a homeowner by 13.2 percentage points, and increases credit scores by 14.9 points. Chapter 13 protection has little impact on open unsecured debt, but decreases the amount of debt in collections by $1,315. We find evidence that both debt forgiveness and protection from debt collectors are important drivers of our results.
There is a large and growing literature on peer effects in economics. In the current article, we focus on a Manski-type linear-in-means model that has proved to be popular in empirical work. We critically examine some aspects of the statistical model that may be restrictive in empirical analyses. Specifically, we focus on three aspects. First, we examine the endogeneity of the network or peer groups. Second, we investigate simultaneously alternative definitions of links and the possibility of peer effects arising through multiple networks. Third, we highlight the representation of the traditional linear-in-means model as an autoregressive model, and contrast it with an alternative moving-average model, where the correlation between unconnected individuals who are indirectly connected is limited. Using data on friendship networks from the Add Health dataset, we illustrate the empirical relevance of these ideas.
We present and discuss preliminary evidence suggesting that credit ratings significantly influenced prices for subprime mortgage-backed securities issued in the period leading up to the recent financial crisis. Ratings are closely correlated with prices even controlling for a rich set of security- and loan-level controls. This incremental variation in ratings has much less predictive power for security defaults, however, based on findings to date from our ongoing research, suggesting prices were excessively sensitive to ratings relative to their informational content.
In September 2007, Northern Rock—the fifth largest mortgage lender in the United Kingdom—experienced an old-fashioned bank run, the first bank run in the U.K. since the collapse of City of Glasgow Bank in 1878. The run had been contained by the government’s announcement that it would guarantee all deposits in Northern Rock. This paper analyzes spillover effects during the Northern Rock episode and shows that both the bank run and the subsequent bailout announcement had significant effects on the rest of the U.K. banking system, as measured by abnormal returns on the stock prices of banks. The paper also shows that the effects were a rational response by investors to market news about the liability side of banks’ balance sheets. In particular, banks that rely on funding from wholesale markets were significantly affected, a result consistent with the drying up of liquidity in wholesale markets and the record-high levels of the London Interbank Offered Rate (LIBOR) during the crisis.
Goal scoring in sports such as hockey and soccer is often modeled as a Poisson process. We work with a Poisson model where the mean goals scored by the home team is the sum of parameters for the home team's offense, the road team's defense, and a home advantage. The mean goals for the road team is the sum of parameters for the road team's offense and for the home team's defense. The best teams have a large offensive parameter value and a small defensive parameter value. A level-2 model connects the offensive and defensive parameters for the k teams. Parameter inference is made by imagining that goals can be classified as being strictly due to offense, to (lack of) defense, or to home-field advantage. Though not a realistic description, such a breakdown is consistent with our model assumptions and the literature, and we can work out the conditional distributions and generate random partitions to facilitate inference about the team parameters. We use the conditional Binomial distribution, given the Poisson totals and the current parameter values, to partition each observed goal total at each iteration in an MCMC algorithm.