We develop a theoretical framework to analyze the effects of immigration on native job amenities, focusing on work schedules. Immigrants have a comparative advantage in production at, and lower disamenity cost for nighttime work, which leads them to disproportionately choose nighttime employment. Because day and night tasks are imperfect substitutes, the relative price of day tasks increases as their supply becomes relatively more scarce. We provide empirical support for our theory. Native workers in local labor markets that experienced higher rates of immigration are more likely to work day shifts and receive a lower compensating differential for nighttime work.

This paper studies human capital responses to college in-state tuition policies for undocumented students. Using a sample of young, Hispanic immigrants from the 2000-2018 American Community Survey and 1997-2018 Current Population Survey, I exploit state and time variation in the adoption of these policies to estimate the causal effect of these policies on college enrollment for the affected students. I find in-state tuition policies significantly increased college attendance rates, particularly among young, Mexican immigrants four to five years after policy implementation. I also confirm my findings using 1998-2018 IPEDS data on college enrollment.

Post randomization methods are among the most popular disclosure limitation techniques for both categorical and continuous data. In the categorical case, given a stochastic matrix M and a specified variable, an individual belonging to category i is changed to category j with probability Mi,j. Every approach to choose the randomization matrix M has to balance between two desiderata: (1) preserving as much statistical information from the raw data as possible; (2) guaranteeing the privacy of individuals in the dataset. This trade-off has generally been shown to be very challenging to solve. In this work, we use recent tools from the computer science literature and propose to choose M as the solution of a constrained maximization problems. Specifically, M is chosen as the solution of a constrained maximization problem, where we maximize the mutual information between raw and transformed data, given the constraint that the transformation satisfies the notion of differential privacy. For the general categorical model, it is shown how this maximization problem reduces to a convex linear programming and can be therefore solved with known optimization algorithms.

The Washington Housing Initiative, launched by the local real estate firm of JBG Smith in partnership with the Federal City Council (a nonprofit civic organization), acquires rental buildings in neighborhoods facing rising property values and keeps a majority of the apartments affordable for households with moderate incomes.1 It is one of a handful of innovative models designed to address worsening problems of unaffordable housing and neighborhood displacement in rapidly growing urban regions across the US prior to the COVID crisis. Distinctive features of the Washington Housing Initiative include its focus on unsubsidized rental properties that currently serve households with low and moderate incomes, its lack of reliance on federal housing subsidies, and its potential to attract new private capital to help address urgent housing affordability challenges.

This paper examines the effect of the female-to-male wage ratio, "relative wage," on women's spouse quality, marriage, and labor supply over three decades. Exploiting task-based demand shifts as a shock to relative pay, I find that a higher relative wage (i) increases the quality of women's mates, as measured by higher spousal education, (ii) reduces marriage without substitution to cohabitation, and (iii) raises women's hours of work. These effects are consistent with a model in which a higher relative wage increases the minimum non-pecuniary benefits ("quality") women require from a spouse and therefore reduce marriage among low-quality husbands.

This paper examines effects of state Medicaid Expansion via the Affordable Care Act on the self-employed. We first examine impacts on the probability of self-employment and find no significant effect. We then examine the probability of having health insurance and the type of coverage for self-employed persons. Medicaid expansion increased overall health insurance coverage rates, with especially large impacts for the unincorporated self-employed. Medicaid expansion also increased the probability of Medicaid coverage as expected, but there is evidence of crowd out of other types of coverage. Impacts on health insurance rates of the self-employed also strengthened over time.

College completion rates declined from the 1970s to the 1990s. We document that this trend has reversed-since the 1990s, college completion rates have increased. We investigate the reasons for the increase in college graduation rates. Collectively, student characteristics, institutional resources, and institution attended do not explain much of the change. However, we show that grade inflation can explain much of the change in graduation rates. We show that GPA is a strong predictor of graduation rates and that GPAs have been rising since the 1990s. We also find that increases in college GPAs cannot be explained by student demographics, ability, and school factors. Further, we find that at a public liberal arts college, grades have increased over time conditional on final exam performance.

We analyze the supply-side disruptions associated with Covid-19 across firms and workers. To do so, we exploit differences in the ability of workers across industries to work remotely using data from the American Time Use Survey (ATUS). We find that sectors in which a higher fraction of the workforce is not able to work remotely experienced significantly greater declines in employment, significantly more reductions in expected revenue growth, worse stock market performance, and higher expected likelihood of default. In terms of individual employment outcomes, lower-paid workers, especially female workers with young children, were significantly more affected by these disruptions. Last, we combine these ex-ante heterogeneous industry exposures with daily financial market data to create a stock return portfolio that most closely replicate the supply-side disruptions resulting from the pandemic.

The Covid-19 outbreak and the murder of George Floyd have dramatically exposed the racial inequalities in US society. This column studies the association between the historical experience of slavery and the African American family structure. Results indicate that the extreme demographic conditions prevailing among slaves on sugar plantations in the US South may have persistently shaped African American family formation. Over the period of 1880-1940, higher sugar suitability is associated with a higher likelihood of single female headship among black households.

A rapidly growing literature uses quantitative general equilibrium models of economic geography to study the economic impact of historical events such as the railroad revolution, industrial takeoff , structural transformation and wars. I identify three key challenges facing this literature: the availability of historical data, the tractability of model structure, and issues related to identification. I review the literature by discussing how it has been addressing each of these challenges. While doing so, I point out the rich set of questions that this literature can address, as well as the methodological innovations it has conducted to answer these questions.

The application of a currently proposed differential privacy algorithm to the 2020 United States Census data and additional data products may affect the usefulness of these data, the accuracy of estimates and rates derived from them, and critical knowledge about social phenomena such as health disparities. We test the ramifications of applying differential privacy to released data by studying estimates of US mortality rates for the overall population and three major racial/ethnic groups. We ask how changes in the denominators of these vital rates due to the implementation of differential privacy can lead to biased estimates. We situate where these changes are most likely to matter by disaggregating biases by population size, degree of urbanization, and adjacency to a metropolitan area. Our results suggest that differential privacy will more strongly affect mortality rate estimates for non-Hispanic blacks and Hispanics than estimates for non-Hispanic whites. We also find significant changes in estimated mortality rates for less populous areas, with more pronounced changes when stratified by race/ethnicity. We find larger changes in estimated mortality rates for areas with lower levels of urbanization or adjacency to metropolitan areas, with these changes being greater for non-Hispanic blacks and Hispanics. These findings highlight the consequences of implementing differential privacy, as proposed, for research examining population composition, particularly mortality disparities across racial/ethnic groups and along the urban/rural continuum. Overall, they demonstrate the challenges in using the data products derived from the proposed disclosure avoidance methods, while highlighting critical instances where scientific understandings may be negatively impacted.

Preference queries are interesting tools to compute small representatives of datasets. In this thesis, we mainly focus on the optimization of Skyline queries in dynamic contexts. In a first part, we address the incremental maintenance of the multidimensional indexing structure NSC which has been shown efficient for answering skyline queries in a static context. More precisely, we address (i) the case of dynamic data, i.e. tuples are inserted or deleted at any time, and (ii) the case of streaming data, i.e. tuples are appended and discarded at specific interval of time. In a second part, we address the optimization of skyline queries in presence of dynamic orders, i.e, some or all attributes of the dataset are nominal and each user expresses his/her own partial order on these attributes’ domain. In that case, we propose scalable parallel algorithms that decompose an issued query into a set of sub-queries and process each sub-query independently.

On behalf of the Mayor’s Office of Criminal Justice (MOCJ), I am pleased to respond to Urban Institute’s (Urban) process evaluation, which identified strategies to better understand and measure program performance. The Police Athletic League’s (PAL) summer youth programs—Playstreets and VIBE—represent visible and popular parts of the City’s play-based programming strategy to reduce crime and victimization for vulnerable communities and their young people. We are heartened that the process evaluation conducted identifies the positive achievements of each of these programs while identifying opportunities to more deliberately integrate them into our year-round, comprehensive interventions. The Playstreets and VIBE programs are part of the Mayor’s Action Plan for Neighborhood Safety (MAP), a citywide strategy initiated by the de Blasio administration to increase community safety and well-being and build strong neighborhoods. MAP is a multiyear, multi-agency strategy focused on 15 public housing developments and their surrounding neighborhoods that, at inception, accounted for almost 20 percent of violent crime in the City’s public housing. Unsurprisingly, the MAP developments are in neighborhoods that have historically led the city in other economic and social stressors—poverty, unemployment, incarceration, and chronic disease. MAP’s driving principle is that public safety requires addressing disparities in opportunity, trust, and physical design in the places that need it most.

Historically, women in widowhood in the United States have been vulnerable, with high rates of poverty. However, over the past several decades, their poverty rate has fallen considerably. In this article, we look at why this decline occurred and whether it will continue. Using data from the Health and Retirement Study linked to Social Security administrative earnings and benefit records, we address these questions by exploring three factors that could have contributed to this decline: (1) women’s rising levels of education; (2) their increased attachment to the labor force; and (3) increasing marital selection, reflecting that whereas marriage used to be equally distributed, it is becoming less common among those with lower socioeconomic status. The project decomposes the share of the decline in poverty into contributions by each of these factors and also projects the role of these factors in the future. The results indicate that increases in education and work experience have driven most of the decline in widows’ poverty to date, but that marital selection will likely play a large role in a continuing decline in the future. Still, even after these effects play out, poverty among widows will remain well above that of married women.

Educators and scholars have been advocating for culturally sustaining pedagogies in the classroom that extends, honors, and sustains the cultures and backgrounds of our growing Students of Color population. Moving beyond pedagogies in classrooms, I examine culturally sustaining spaces in culture clubs and community-based organizations and how they cultivate the identity development and sense of belonging of Vietnamese American high school students. I find that these students have complex identities that are intersectional and ever changing, existing outside the Black-White binary. Vietnamese culture clubs provide a space that allows students to belong and express their identity in a positive way, but with curriculum as colonizer (Goodwin, 2010), schools have not yet become a place of belonging for all students. Community based organizations provide alternative spaces that center the experiences of Vietnamese American students, allowing them to engage with their complex identities in a place that becomes like a home.

This Paper We introduce a new STATA package (and a companion paper) implementing the standard errors correction approach proposed in Colella et al. (2019): ACREG: Arbitrary Correlation Regression ˆ Computes adjusted standard errors for: - Spatial data (coordinates or contiguity matrix), - Network data (adjacency matrix), - Multi-way clustering environments (infinite list of clustering variables) ˆ Suits OLS and 2SLS settings ˆ Includes temporal correlation for panel data

This report, prepared for the African American Leadership Alliance MKE (AALAM), presents an index of African American community well-being in Milwaukee and the nation’s 50 largest metropolitan areas. The index is based on Black community status for each metro area on 30 indicators of community well-being, in areas such as employment; income, poverty, and social conditions; community health; and conditions for youth and children. Ranks on all of the component indicators were then synthesized into a composite index, ranking each of the nation’s largest metropolitan areas on the wellbeing of their respective African American communities. This study finds, on almost all indicators examined, that Black Milwaukee consistently ranks at or near the bottom compared to African American communities in large metropolitan areas across the country. On the composite index of African American well-being, Milwaukee ranks worst, by a fairly wide margin. The AALAM aims “to redefine Milwaukee as a top-ranking city for African Americans by 2025.” This study reveals the magnitude of that challenge.

New research published Monday found that the top 1% of U.S. income earners have taken $50 trillion from the bottom 90% over the past several decades, and that the median worker salary would be around twice as high today as it was in 1945 if pay had kept pace with economic output over that period.

Working longer – in the sense of choosing to delay retirement beyond traditional retirement ages – is widely proposed as the best way for older Americans to boost their fragile retirement security. But the policy goal of increasing labor force participation among older Americans is fundamentally in tension with a precarious low-wage economy because jobs that feature low wages, high turnover rates, and few benefits do not provide a solid foundation for sustained employment at older ages. Many Americans in their 50s are already out of the labor force, and many retire involuntarily before traditional retirement ages – a situation that has been exacerbated by the COVID-19 pandemic. Better jobs for prime-age workers help to pave the way for longer working lives. I outline three specific policy proposals: improved minimum wage, fair workweek laws, and a universal paid family and medical leave benefit. As others have argued, these policies would improve the well-being of prime-age workers. What has been less appreciated is that these policies would also put older Americans in a better position to extend their working years.