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 We show that both small and large deposits are withdrawn up to 4–5 quarters before the bank’s closure.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.

Using the case of the pogroms that took place in the historical region of the 'Pale of Settlement' in Eastern Europe, this paper analyzes the cultural legacy of ethnic violence and its long-term economic impact on access to finance and on corporate innovation. We find that firms in regions with a higher historical intensity of ethnic persecution face greater financial constraints, relying more on internal finance and experiencing reduced access to external finance. These financial limitations are linked to sluggish innovation activities among present-day firms. We propose that a mechanism of financial antipathy, rooted in a persistent anti-market culture fostered by historical ethnic animosity, explains these effects and reflects a long-term degradation of local social capital. Our results are supported by causal evidence using instrumental variables based on the precursors of historical inter-ethnic violence. The animosity and discrimination against the minority group appear to transfer to the broader economic activities in which that group was involved, creating lasting economic consequences for the majority population – consequences that continue to affect financial development and innovation to the present day.

Data-driven lending relies on the calibration of models using training periods. We find that this type of lending is not resilient in the presence of economic conditions that are materially different from those experienced during the training period. Using data from a small business fintech lending platform, we document that the small business credit supply collapsed during the COVID-19 crisis of March 2020 even though the demand for loans doubled relative to pre-pandemic levels. As the month progressed, most lenders significantly reduced or halted their lending activities, likely due to the heightened risk of model miscalibration under the new economic conditions.

We exploit staggered real estate transaction tax (RETT) hikes across German states to identify the effect on the growth rates of regional house prices and outstanding mortgage loans by all local German banks. The results show that a RETT hike by one percentage point reduces regional house prices by 3%–4%. Furthermore, IV-regressions yield that a 1 percentage point drop in regional house prices induced by a RETT increase leads to a 0.3% decline in regional mortgage lending, particularly among low-capitalized banks in rural regions.

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.

We approach the literature on housing and inequality from two angles. One is the impact of unequal endowments on housing. The second is the “memberships” inequality associated with neighborhoods, namely, households’ location in a geographic and social context. We elaborate on these two angles of inequality and focus on three distinctive features of housing: consumption, capital, and location. For owner-occupants, capital and consumption are bundled together in a single good. For both renters and owner-occupants, housing consumption inequality, access to good neighborhoods, and housing wealth follow from unequal endowments. Housing can propagate inequality by enabling owner-occupants to use it as collateral for other investments or to secure higher returns to human capital investments through the better schools in better neighborhoods. We use this approach to analyze key aspects of housing and inequality, paying special attention to the impacts of racial discrimination and segregation. (JEL D63, J15, J24, R21, R23, R31)

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.