The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the typical use of a Bartik instrument assumes a pooled exposure research design, where the shares measure differential exposure to common shocks, and identification is based on exogeneity of the shares. Next, we show how the Bartik instrument weights each of the exposure designs. Finally, we discuss how to assess the plausibility of the research design. We illustrate our results through three applications: estimating the elasticity of labor supply, estimating local labor market effects of Chinese imports, and estimating the elasticity of substitution between immigrants and natives.

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.

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 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 the level of debts in 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 the largest gains in financial health at age 65 had higher shares of black residents, people with disabilities, and for-profit hospitals.

This paper analyzes the contagion effects associated with the failure of Silicon Valley Bank (SVB) and identifies bank-specific vulnerabilities contributing to the subsequent declines in banks' stock returns. We find that uninsured deposits, unrealized losses in held-to-maturity securities, bank size, and cash holdings had a significant impact, while better-quality assets or holdings of liquid securities did not help mitigate the negative spillovers. Interestingly, banks whose stocks performed worse post SVB also had lower returns in the previous year following Federal Reserve interest rate hikes. The stock market partially anticipated risks associated with uninsured deposit reliance, but did not price in unrealized losses due to interest rate hikes nor risks linked to bank size. While mid-sized banks experienced particular stress immediately after the SVB failure, over time negative spillovers became widespread except for the largest banks.

We document the representation of female economists on the conference programs at the NBER Summer Institute from 2001-2016. Over the period from 2013-2016, women made up 20.6 percent of all authors on scheduled papers. However, there was large dispersion across programs, with the share of female authors ranging from 7.3 percent to 47.7 percent. While the average share of women rose slightly from 18.5% since 2001-2004, a persistent gap between finance, macroeconomics and microeconomics subfields remains, with women consisting of 14.4 percent of authors in finance, 16.3 percent of authors in macroeconomics, and 25.9 percent of authors in microeconomics. We examine three channels potentially affecting female representation. First, using anonymized data on submissions, we show that the rate of paper acceptance for women is statistically indistinguishable to that of men. Second, we find that the share of female authors is comparable to the share of women amongst all tenure-track professors, but is ten percentage points lower than the share of women among assistant professors. Finally, within conference program, we find that when a woman organizes the program, the share of female authors and discussants is higher.

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.

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 maintenance 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.