I estimate the welfare benefits of eliminating idiosyncratic consumption shocks in the United States related (unrelated) to the business cycle as 36%–39% (lower than 1%) of household utility. Estimates of the former exceed earlier ones because I distinguish between idiosyncratic shocks related/unrelated to the business cycle, estimate the negative skewness of shocks, target moments of idiosyncratic shocks from household-level CEX data, and target market moments. Benefits of eliminating aggregate shocks are lower than 1% of utility. Policy should facilitate the insurance of idiosyncratic shocks related to the business cycle, such as job layoffs, with proof that individuals diligently seek suitable employment during periods of unemployment. (JEL D31, D52, E32, E44, G01, G12)

An extensive literature studies interactions of stock market anomalies using double-sorted portfolios. But given hundreds of known candidate anomalies, examining selected interactions is subject to a data mining critique. In this paper, we conduct a comprehensive analysis of all possible double-sorted portfolios constructed from 102 underlying anomalies. We find hundreds of statistically significant anomaly interactions, even after accounting for multiple hypothesis testing. An out-of-sample trading strategy that invests in the top backward-looking double-sort strategy generates equal-weighted (value-weighted) monthly average returns of 4% (2.7%) at an annualized Sharpe ratio of 2 (1.38), on par with state-of-the-art anomaly-based machine learning strategies.

How susceptible to contagion are bank deposits associated with financial inclusion? To assess this susceptibility, we analyze the behavior of deposits around three significant events of bank failure in the Philippines. We conduct the event studies with the advantage of a unique dataset that disaggregates deposits by size at the town level. We show that both small and large deposits are withdrawn up to 4–5 quarters before the bank’s closure. We take advantage of this distinction between small and large deposits to test for contagion. Applying difference-in-difference regressions, we find evidence of contagion: the closure of a large bank leads to withdrawals at banks in neighboring towns by depositors both large and small. This is the case for two of the three events, and when the data is taken collectively. That there is a market for information affects deposit insurance as a safety net for depositors and as a disciplining tool for banks. There are also liquidity considerations that banks need to consider. In any case, we consistently find the behavior of small depositors to be no different from that of large depositors. Hence, if financial inclusion is about access to bank deposits, it is not likely to heighten systemic risks nor mitigate them.

We provide a finite sample inference method for the structural parameters of Manski's semiparametric binary response model under a conditional median restriction. This is achieved by exploiting distributional properties of observable outcomes conditional on the observed sequence of exogenous variables. Moment inequalities conditional on the size n sequence of exogenous covariates are constructed, and the proposed test statistic is a monotone function of violations of the corresponding sample moment inequalities. The critical value used for inference is provided by the appropriate quantile of a known function of n independent Bernoulli random variables and does not require the use of a cube root asymptotic approximation employing a point estimator of the target parameter. Simulation studies demonstrate favourable finite sample performance of the test in comparison to several existing approaches. Empirical use is illustrated with an application to the classical setting of transportation choice.

Residential segregation is a central factor in explaining socioeconomic gaps across race and ethnicity in the United States. Place of residence directly impacts access to schools, jobs, and health care. There is an ever-evolving literature across the social sciences disciplines documenting the general patterns in residential segregation as well as the causes and consequences of those patterns. This article reviews key parts of that literature. We provide an overview of the measurement of segregation and the general evolution of segregation patterns over time and at different scales. We then review the literatures on both segregation’s determinants and its impact on a range of socioeconomic outcomes. We highlight the potential for new insights to be gained from new approaches to quantifying segregation and new frameworks such as stratification for understanding its complex roots. (JEL D72, I24, I32, J15, R23, R28)

We show that occupational licensing has significant negative effects on labor market fluidity, defined as cross-occupation mobility, and positive effects on wage growth. We find that occupational licensing represents a barrier to entry for both nonemployed workers and employed ones. The effect is more prominent for employed workers than those entering from nonemployment. We also find that average wage growth is higher for licensed workers than nonlicensed workers. We find significant heterogeneity in the licensing effect across different occupation groups. These results hold across various data sources, time spans, and indicators of being licensed.

This study presents a methodology for analyzing procyclical systemic risk arising from joint monetary and prudential policy decisions. We analyze the impact of different scenarios of the monetary policy interest rate on the leverage ratio of US commercial banks. The Dynamic Conditional Correlation - Semi-nonparametric model and bivariate spectral analysis are applied to model the dynamics among the variables. The results indicate that high and low interest rates increase leverage while medium rates reduce it. The importance of considering asymmetries and heavy tails of probability distributions in stress tests and the dynamics of the correlation between variables is highlighted when assessing financial stability.

A central question in applied research is to estimate the effect of an exogenous intervention or shock on an outcome. The intervention can affect the outcome and controls on impact and over time. Moreover, there can be subsequent feedback between outcomes, controls, and the intervention. Many of these interactions can be untangled using local projections. This method’s simplicity makes it a convenient and versatile tool in the empiricist’s kit, one that is generalizable to complex settings. This article reviews the state of the art for the practitioner and discusses best practices and possible extensions of local projections methods, along with their limitations. (JEL C32, C33, C36, E23, E24)

We use textual analysis of mandatory accounting filings to develop firm-level, time-varying measures of exposure to individual government agencies including the Securities Exchange Commission (SEC) and Internal Revenue Service (IRS). The measures vary predictably across industries and with agency-specific events such as the Sarbanes Oxley Act at the SEC and budget cuts at the IRS. The measures positively relate to undisclosed agency investigations and financial statement downloads. Firms' total exposure across government agencies negatively relates to their profitability, consistent with exposure to government agencies imposing net costs. Consistent with a causal interpretation of these results, the positive stock market reaction to the surprise election of Donald Trump, who promised to reduce the power of government agencies, positively varies with firms' exposure to government agencies. As initial applications of our measures, we demonstrate that expanded SEC oversight increases firms' stock liquidity and reduced IRS oversight decreases firms’ effective tax rates.