Motherhood is the main contributor to gender gaps in the labor market. IVF is a method of assisted reproduction that can delay fertility, which results in decreased motherhood income penalty. In this research, I estimate the effects of expanded access to in vitro fertilization (IVF) arising from state insurance mandates. I use a difference-indifferences model to estimate the effect of increased IVF accessibility for delaying childbirth and decreasing the motherhood income penalty. Using the fertility supplement dataset from the Current Population Survey (CPS), I estimate how outcomes change in states when they implement their mandates compared to how outcomes change in states that are not changing their policies. The results indicate that IVF mandates increase the probability of motherhood by 38 by 3.1 percentage points (p < 0.01). However, the results provide no evidence that IVF insurance mandates impact women’s earnings.

Although living arrangements of American adults have changed significantly over the past decades, we know little about changes in the association between living arrangements and health. This study uses pooled data from 1997 to 2018 National Health Interview Survey to examine trends in living arrangements and health among middle-aged (ages 40–64) and older adults (ages 65–84). The results show that increasing share of middle-aged and older adults are living with persons other than their spouses or cohabiting partners, and this living arrangement is increasingly associated with poor health. Co-residence with persons other than spouses or cohabiting partners is particularly related to serious psychological distress among older adult women. Living alone in midlife is increasingly associated with poor health, but there has been little change in health of older adults living alone. The findings call for targeted policies and programs to address the needs of middle-aged and older adults in diverse living arrangements.

Do cities accelerate COVID-19 transmission? Increased transmission arising from population density prompts spatial policies for financial support and containment, and poorer prospects for recovery. Using daily case counts from over 3,000 counties in the U.S. from February to September 2020, I estimate a compartmental transmission equation. Rational sheltering behavior plausibly varies by location, so I propose two instruments that exploit unanticipated variation in exposure to potential infection. In the first month of local infections, an additional log point of population density raises the expected transmission parameter estimate by around 3%. After the first month, the relation vanishes: density effects occur only in the outbreaks. Public transport, work-from-home jobs and income explain additional variation in transmission but do not account for the density effects. Consistent with location-varying optimal sheltering behavior, I document stronger mobility declines in denser areas, but only after the first month of infections. These results suggest that differences in transmission between cities and other places do not motivate spatial policies for recovery or containment, or poorer prospects after the pandemic.

This book provides a detailed understanding of the process of seeking justice in cross-border disputes in Central Europe and a comprehensive and exhaustive presentation of the case law in 10 Central European Member States (Croatia, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia). It is the first of its kind to offer a comprehensive and analytical overview of the judicial practice in the region. The book is a product of the multi-year EU-funded CEPIL project (“Cross-Border Litigation in Central-Europe: EU Private International Law before National Courts”, 800789 — CEPIL — JUST-AG-2017/JUST-JCOO-AG-2017), which was based on the cooperation of six universities (University of Szeged, Hungary, Masarykova univerzita, Czech Republic, Sveučilište u Zagrebu, Croatia, Universitatea Sapientia din municipiul Cluj-Napoca, Romania, Univerzita Mateja Bela v Banskej Bystrici, Slovakia, Uniwersytet Śląski, Poland). The CEPIL project inquired whether EU private international law functions optimally in the Central European Member States to secure a Europe of law and justice and whether EU private international law instruments are applied correctly and uniformly. It analyzed whether national courts deal appropriately with disputes having a cross-border element and whether the current legal and institutional architecture is susceptible of securing legal certainty and an effective remedy for cross-border litigants.

People are on the move in unprecedented numbers within and between countries. How does demographic change affect local intergroup dynamics? Complementing accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the group reference dependence hypothesis: violence and negative attitudes towards each minoritized group will depend on the number and size of other minoritized groups in a community. Specifically, as groups increase or decrease in rank in terms of their size (for example, to the largest minority within a community), discriminatory behaviour and attitudes towards them should change accordingly. We test this hypothesis for hate crimes in US counties between 1990 and 2010 and attitudes in the United States and United Kingdom over the past two decades. Consistent with this prediction, we find that as Black, Hispanic/Latinx, Asian and Arab populations increase in rank relative to one another, they become more likely to be targeted with hate crimes and more negative attitudes. The rank effect holds above and beyond group size/proportion, growth rate and many other alternative explanations. This framework makes predictions about how demographic shifts may affect coalitional structures in the coming years and helps explain previous findings in the literature. Our results also indicate that attitudes and behaviours towards social categories are not intransigent or driven only by features associated with those groups, such as stereotypes.

Micro-databases are unique datasets that contain person-specific information about individuals. Preserving the privacy of such datasets has become a cause for serious concern since this massive repository of personalized data regularly gets published in the public domain. Sanitization mechanisms are specialized techniques that provide the required privacy guarantees to the published data. The work in this article establishes an efficient framework for quantitatively estimating the effectiveness of any privacy-preservation scheme which employs the anonymization principle. In our study, we have introduced an information-theoretic metric termed as Sanitization Degree (η) which assigns a cumulative score in the range [0,1] for a generic anonymization process. The design of our proposed metric is based on the fundamental fact that any sanitization mechanism attempts to reduce the amount of correlated information within the database attributes while simultaneously preserving the utility of the original dataset.

Low wages and poor job quality undermine employment experiences and outcomes for all direct care workers, but how do these experiences and outcomes vary within the workforce? This research brief offers a detailed snapshot of the direct care workforce by gender and race/ethnicity. We show that women of color now comprise more than half of all direct care workers, but women and people of color in this workforce experience heightened economic instability compared to their white and male counterparts. These and other findings from this research underscore the pressing need to implement policy and practice interventions that explicitly address disparities in the direct care workforce.

Children who are nurtured, protected, and supported in the first years of life tend to have better individual outcomes and are more likely to grow to become healthy, productive adults. Child well-being varies across states, yet the field lacks a comprehensive review of infant and toddler indicators measured at the state-level. This paper reviews indicators of well-being from the prenatal period to three years that meet certain a priori criteria. Most of the child-level indicators identified were in the physical health domain; relatively fewer indicators were found in the early cognition and language or social-emotional-behavioral domains. While some states are making progress toward developing integrated early childhood data systems, more work is needed to provide robust data on infant and toddler development. These results highlight the need to develop a broader range of indicators of infant and toddler well-being and improve measurement sources to better inform policies and programs advancing population health.

Over the last decade, California’s population growth has slowed to a crawl and, in the last two years, has even begun to decline. This stunning shift is a function of slowing birth rates, an increase in deaths due to the pandemic and an aging population, and less immigration. Adding to these drags on growth, the flow of Californians moving to other states has also accelerated. On net, California lost over a quarter of a million residents to other states in 2021 alone.

The 2019 public charge rule published by the Trump administration has left substantial impacts on public safety net participation for immigrant families. Utilizing data from the Current Population Survey (CPS), I examine the effects of the the updated public charge rule (UPCR) on public safety net participation on citizen children with non-citizen mothers (treatment group), using citizen children with citizen mothers as a control group. I employ a difference-in-differences model to explore the before and after effects of the rule to look at participation rates in Medicaid, SNAP, and lunch subsidies. I find statistically significant results showing that the odds of SNAP participation is approximately 27% lower for the treatment group in comparison with the control group during the years that the UPCR is in effect. Interestingly, I did not find significant results on the effect of the UPCR on Medicaid and lunch subsidy participation. The UPCR exacerbated food insecurity among children living in immigrant households in a time when immigrants were already facing economic hardship as a result of the ongoing COVID-19 pandemic.

This issue examines 1) employment trends from 2011 to 2021, including the impact of COVID-19, and 2) employment projections through 2030.

In Shelby County v. Holder (2013), the U.S. Supreme Court declared unconstitutional Section 4(b) of the Voting Rights Act of 1965, which required jurisdictions with histories of voter disenfranchisement to receive federal preclearance before altering voting laws. Since Shelby, 1688 polling sites across 13 states have closed. Utilizing a sample of eligible voters from the Current Population Survey, I first predict the likelihood of voting. Then, I analyze how Shelby has influenced the likelihood of ballot box access issues among non-voters. Overall voter turnout is 0.9pp lower in post-Shelby elections. Black eligible voters are 5.4pp less likely to vote after Shelby. However, Shelby is not associated with a higher likelihood of ballot box access issues. While the mechanisms through which Shelby affects voting behavior remain inconclusive, Shelby is significantly associated with widespread voter disenfranchisement. These findings are relevant for policymakers in creating a revised preclearance formula to curb voter disenfranchisement.

Anecdotal evidence suggests that the affordable housing crisis is forcing households to seek lower cost housing in the outer reaches of major metropolitan areas, helping to explain recent increases in commute distance. To test this relationship, we use spatial regression to examine the relationship between the availability of affordable housing in close proximity to jobs (jobs-housing fit) and commute distance in the Los Angeles metropolitan area. The analysis draws on 2015 Longitudinal Employer-Household Dynamics (LEHD) Origin–Destination Employment Statistics (LODES) by workplace supplemented with data from the 2013–2017 5-Year American Community Survey on affordable housing units. We find substantial variation in jobs-housing fit across Los Angeles neighborhoods. The imbalance is greatest in higher-income neighborhoods located along the coast and in Orange County, south of Los Angeles. Controlling for other determinants of commute distance, a higher ratio of jobs to affordable housing is associated with longer distance commutes. To address growing commute distances, policymakers must greatly expand and protect the supply of long-term rental housing particularly in job-rich neighborhoods.

Ultimately, several questions can be raised here: How deep are the roots of democratic institutions in Africa? How effective are the constraints on the political elite? And what does this entail for the distribution of resources? This thesis tries to provide some insights into these questions by studying them from three angles. First, it addresses the behavior of citizens. Second, it deals with the perspective of the political elite. Lastly, it takes a more encompassing view on specific governance outcomes.

US earnings inequality has not increased in the last decade. This marks the first sustained reversal of rising earnings inequality since 1980. We document this shift across eight data sources using worker surveys, employer-reported data, and administrative data. The reversal is due to a shrinking gap between low-wage and median-wage workers. In contrast, the gap between top and median workers has persisted. Rising pay for low-wage workers is not mainly due to the changing composition of workers or jobs, minimum wage increases, or workplace-specific sources of inequality. Instead, it is due to broadly rising pay in low-wage occupations, which has particularly benefited workers in tightening labor markets. Rebounding post–Great Recession labor demand at the bottom offset enduring drivers of inequality.

The worrying combination of the labor market tightness and the wage inflation in the US since the pandemic raises a question on how the business closure orders affected the fragile segments of the labor force and contributed to mounting inflationary wage pressure. We develop a macroeconomic model with heterogeneous labor and a nested CES production function. We estimate the model using the newly collected data from the CPS and the BEA. The recent crisis leads to a contraction in total hours worked, makes wages more volatile, and sustains wage inflation. The model also generates differential effects of the business closure orders on productivity and the labor market in the US. The earning rates and hours responses to the crisis differ by age, skills, and origin of the worker.

In the United States, young adults raised in stably married two-parent families complete college, enter full-time employment and dealy family formation more often than peers raised in other fmaily forms (Fomby and Bosick 2013; Hofferth and Goldscheider 2010). These events and statuses mark the transition into adulthood and are associated with positive long-term economic, physical, and emotional well-being. Yes, two in five contemporary U.S. children grow up in other living arrangments, a disparity that largely cleaves along racial, ethnic, and social class lines (Payne 2019). Given the perceived long-term gains to growing up with stably married parents and children's divergent experiences of family composition, a substantial social science literature has emerged over the last 50 years to explore what sets paretns' marriage apart from other forms of family organization as a context for child rearing and why or whether family sturcture matters for the transition to adulthood.

Machine learning may be oblivious to human bias but it is not immune to its perpetuation. Marginalisation and iniquitous group representation are often traceable in the very data used for training, and may be reflected or even enhanced by the learning models. To counter this, some of the model accuracy can be traded off for a secondary objective that helps prevent a specific type of bias. Multiple notions of fairness have been proposed to this end but recent studies show that some fairness criteria often stand in mutual competition. In the present work, we introduce a solvable high-dimensional model of data imbalance, where parametric control over the many bias-inducing factors allows for an extensive exploration of the bias inheritance mechanism. Through the tools of statistical physics, we analytically characterise the typical behaviour of learning models trained in our synthetic framework and find similar unfairness behaviours as those observed on more realistic data. However, we also identify a positive transfer effect between the different subpopulations within the data. This suggests that mixing data with different statistical properties could be helpful, provided the learning model is made aware of this structure. Finally, we analyse the issue of bias mitigation: by reweighing the various terms in the training loss, we indirectly minimise standard unfairness metrics and highlight their incompatibilities. Leveraging over the insights on positive transfer, we also propose a theory-informed mitigation strategy, based on the introduction of coupled learning models. By allowing each model to specialise on a different community within the data, we find that multiple fairness criteria and high accuracy can be achieved simultaneously.

We develop a notion of projections between sets of probability measures using the geometric properties of the 2-Wasserstein space. It is designed for general multivariate probability measures, is computationally efficient to implement, and provides a unique solution in regular settings. The idea is to work on regular tangent cones of the Wasserstein space using generalized geodesics. Its structure and computational properties make the method applicable in a variety of settings, from causal inference to the analysis of object data. An application to estimating causal effects yields a generalization of the notion of synthetic controls to multivariate data with individual-level heterogeneity, as well as a way to estimate optimal weights jointly over all time periods.

Widespread urbanization in the United States over the years has changed the economic landscape of the country dramatically. This study explores the effect of working in a rural versus an urban area on wages in Illinois. General research suggests that there may be wage premium for working in urban areas, but this study takes a slightly different approach by focusing on county-by-county data as opposed to regional data. Labor market wages are considered in the context of efficient market theory. Linear regression models are run using data from the American Community Survey in order to explore whether there is a wage premium for those working in an urban county in Illinois.