Objective: To examine rural-urban differences in reproductive-aged Wisconsin women's expectations for contraceptive and abortion care at a hypothetical Catholic hospital. Study design: Between October 2019 and April 2020, we fielded a 2-stage, cross-sectional survey to Wisconsin women aged 18 to 45, oversampling rural census tracts and rural counties served by Catholic sole community hospitals. We presented a vignette about a hypothetical Catholic-named hospital; among participants perceiving it as Catholic, we conducted multivariable analyses predicting expectations for contraceptive services (birth control pills, Depo-Provera, intrauterine device or implant, tubal ligation) and abortion in the case of serious fetal indications. Results: The response rate was 37.6% for the screener and 83.4% for the survey (N = 675). Among respondents (N = 376) perceiving the hospital as Catholic, expecting the full range of contraceptive methods was more common among rural (70.9%) vs urban (46.7%) participants (adjusted odds ratio = 3.99, 95% confidence interval: 1.99–7.99). In adjusted models, odds of expecting each contraceptive method were at least 3 times greater among rural vs urban participants. About one-third expected provision of abortion for serious fetal indications, with no difference by rurality (p > 0.05). Conclusions: In Wisconsin, rural women were more likely than urban women to expect a hypothetical Catholic hospital to provide the full range of contraceptive methods as well as each method individually. Disparities were especially large for tubal ligation and long-acting reversible contraceptives—methods that other studies suggest are least-likely to be available in Catholic healthcare settings—which may indicate a mismatch between patients’ expectations and service availability. Implications: Many reproductive-aged Wisconsin women—especially in rural areas—hold misperceptions about availability of reproductive care in Catholic hospitals. Policies mandating greater transparency in service restrictions and interventions enabling patients to make informed decisions about care may help connect patients to the care they need more quickly.

Objectives: The population of older adults is growing rapidly, creating high demand for the involvement of working family caregivers. This concurrent mixed-methods study sought to obtain information from working family caregivers regarding their perceptions of the usefulness of an online employee assistance support tool. Methods: Working family caregivers (n = 15) participated in a semi-structured focus group completing a demographic survey and the Modified Caregiver Strain Index (MCSI). Results: Total MCSI score had a statistically significant positive relationship with hours of care provision per week and presented an inverse association with caregiver age. Caregiver age had a statistically significant inverse relationship with the perception of caregiving as confining. Qualitative data identified needs for family caregivers support in three major themes: knowledge, understanding, and connection. Discussion: This study highlights a myriad of caregiver burden experiences and the necessity of various supports for each caregiver’s unique situation beyond the traditional workplace polices.

This dissertation studies a range of topics in automation and globalization. Chapter 1 studies the role of industrial robots in the US in expanding the occupational wage polarization. Chapter 2 explores the effect of industrial robots in Japan on employment and wages in each industry and region. Chapter 3 investigates the impact of recent growth in multinational enterprises on headquarter country’s labor demand and labor share. Chapter 1 studies the distributional and aggregate effects of the rising use of industrial robots across occupations. I construct a novel dataset that tracks the cost of robots from Japan by occupations. The dataset reveals a relative one-standard deviation drop of Japan’s robot cost induces a 0.2-0.3% drop in the US occupational wages. I develop a general equilibrium model where robots are internationally traded durable goods that may substitute for labor differently across occupations. The elasticities of substitution between robots and labor within an occupation drive the occupation-specific real-wage effects of robotization. I estimate the model using the robot cost shock from my dataset and the optimal instrumental variable implied by the model. I find that the elasticities of substitution between robots and labor are heterogeneous across occupations, and higher than those between general capital goods and labor in production occupations such as welding. The estimated model implies that the industrial robots explain a 0.9 percentage point increase in the 90-50th percentile ratio of US occupational wages, and a 0.2 percentage point increase of the US real income from 1990 to 2007. Chapter 2 explores the impacts of industrial robots on employment in Japan, the country with the longest tradition of robot adoption. We employ a novel data set of robot shipments by destination industry and robot application (specified task) in quantity and unit values. These features allow us to use an identification strategy leveraging the heterogeneous application of robots across industries and heterogeneous price changes across applications. For example, the price drop of welding robots relative to assembling robots induced faster adoption of robots in the automobile industry, which intensively uses welding processes, than in the electric machine industry, which intensively uses assembling process. Our industrial-level and commuting zone-level analyses both indicate that the decline of robot prices increased the number of robots as well as employment, suggesting that robots and labor are grossly complementary in the production process. We compare our estimates with the ones reported by existing studies and propose a mechanism that explains apparent differences between the results. Chapter 3 investigates the impact of multinational enterprises (MNEs) on the source-country labor share. Our model shows that source-country factor demand elasticities with respect to foreign factor prices affect aggregate labor share. To identify these elasticities, we develop an estimator that leverages a foreign factor-productivity shock. We apply this estimator to a unique natural experiment: the 2011 Thailand Floods, which negatively impacted the foreign operation of Japanese MNEs. We employ a uniquely combined Japanese firm- and plant-level microdata and find that the Floods decreased fixed assets in Japan more than employment, suggesting that foreign factor productivity growth reduces Japan’s labor share.

Medical divorce occurs when couples divorce so that one spouse’s medical bills do not deplete the assets of the healthy spouse. We develop a model of medical divorce that demonstrates that divorce is optimal when a couple’s joint assets exceed the exempted asset level. We use the Affordable Care Act’s Medicaid expansion which removed asset tests to qualify for Medicaid as exogenous variation in the incidence of divorce. We find that the ACA expansion decreased the prevalence of divorce by 11.6% among those ages 50-64 with a college degree. Our results suggest that Medicaid expansion reduced medical divorce.

Evidence-based linkage to care interventions (LTCs) help recently diagnosed HIV+ individuals engage in care in a timely manner yet are heavily impacted by the systems in which they are embedded. We developed a prototype agent-based model informed by data from an established LTC program targeting youth and young adults aged 13–24 in Memphis, Tennessee. We then tested two interventions to improve LTC in a simulated environment: expanding testing sites versus using current testing sites but improving direct referral to LTC staff from organizations providing testing, to understand the impact on timely linkage to care. Improving direct referral to the LTC program decreased days to successful linkage from an average of 30 to 23 days but expanding testing sites increased average days to 31 days unless those sites also made direct referrals. We demonstrated how LTC is impacted by the system and interventions for shortening days to linkage to care.

While a growing literature shows that women prefer investments in child welfare and increased redistribution, little is known about the long-term effect of empowering women. Exploiting plausibly exogenous variation in U.S. suffrage laws, we show that children from economically disadvantaged backgrounds who were exposed to womens political empowerment during childhood experienced large increases in educational attainment, especially blacks and Southern whites. We also find improvements in earnings, particularly among whites that experienced educational gains. We use newly-digitized data to link these long-term effects to contemporaneous increases post-suffrage in local education spending and, to a lesser extent, improvements in childhood health.

Increased automation, globalization, and longevity demand new thinking by employers and employees regarding productivity. Throughout the lifespan, fuller engagement in education and paid and unpaid productive activities can generate a wealth of benefits, including better health and well-being, greater financial security, and a more vital society. We review challenges and opportunities to advance long, healthy, and productive lives. When possible, we review inequities by gender, race, ethnicity, and other social determinants of health to reveal heterogeneity within the growing U.S. population and workforce. We conclude with implications for research, social policy, advocacy, education, and practice.

This paper has two aims. First, we apply Bourdieu’s field theory to investigate media discourse on race and immigration, demonstrating how features of news organizations influence news content. Second, we compare contemporary natural language processing (NLP) techniques with qualitative hand-coding. Extending a previous study, we compare newspaper articles from the mainstream and black press in Atlanta. We find significant differences in both word-use and topical coverage in immigration articles aimed at the two audiences. With a focus on organizational resources and values, our quantitative approach to field theory facilitates a better understanding of the journalistic landscape.

In the US, Filipinxs are the third largest Asian subgroup and have represented a crucial part of the country’s health care workforce since the mid-20th century. Although the 2.9 million Filipinxs in the US represent about 1% of the population, approximately 1 of 4 Filipinx working adults are frontline health care workers.1 The COVID-19 pandemic has exacted a disproportionate toll on Filipinx communities in the US and on Filipinx health care workers, specifically. The absence of disaggregated race/ethnicity data for COVID-19 has masked how the pandemic has affected Filipinxs in the US. Policy makers and researchers must recognize that these disparities are not limited to COVID-19 but are a critical example of how data aggregation under a single Asian category has hidden the health needs of the Filipinx population.

Flexible exchange rates can facilitate price adjustments that buffer macroeconomic shocks. We test this hypothesis using adjustments to the gold standard during the Great Depression. Using prices at the goods level, we estimate exchange rate pass-through and find gains in competitiveness after a depreciation. Using novel monthly data on city-level economic activity, combined with employment composition and sectoral export data, we show that American exporting cities were significantly affected by changes in bilateral exchange rates. They were negatively impacted when the UK abandoned the gold standard in 1931 and benefited when the US left the gold standard in April 1933. We show that the gold standard deepened the Great Depression, and abandoning it was a key driver of the economic recovery.

The American economy had pervasive disparities before the pandemic. The pandemic exacerbated many of those disparities in market outcomes but the policy response, in many ways, was successful in combatting some of the widening disparities. The policy response, however, was temporary and the pre-existing structural problems in the U.S. economy will remain. That is why I am so pleased that this Select Committee is tackling what I view as the fundamental challenge our economy, and perhaps our society more broadly, faces. My testimony makes six points: 1. American families are making much slower economic progress than they have in the past. 2. The source of this slower progress is a combination of slower productivity growth, higher inequality, and a reduction in work. 3. Disparities are pervasive by income, education, race, ethnicity, gender and many other dimensions. They express themselves in almost every area including the economy, education, environment, health, housing, clean water, crime, and more. 4. Inequality has many causes and it also has commensurately many solutions—there is no single magic bullet. 5. There are many opportunities to reduce disparities while boosting overall growth and policymakers should pursue all of them. 6. Finally, there are additional ways policymakers could reduce disparities in order to help American families with relatively little impact on growth and policymakers should purse those as well. The remainder of my written testimony expands on these six points.

The length of time from the implementation of an occupational licensing statute (i.e., licensing duration) may matter in influencing labor-market outcomes as entry requirements evolve. In addition, states enact grandfather clauses that allow existing workers to continue employment following these regulations, while ratcheting up requirements to increase entry costs for new entrants. We analyze the labor-market influence of the duration of occupational licensing statutes for fifteen state universally licensed occupations over a 75-year period. We find a positive nonlinear wage effect for licensing duration. Further, we find that occupational licensing raises the wages of grandfathered workers by almost 5 percent. The licensed occupations, however, exhibit heterogeneity in outcomes. Duration of occupational licensing influences wage determination when measured over longer time periods.

Background Drug overdose is a leading cause of unintentional death in the United States and has contributed significantly to a decline in life expectancy during recent years. To combat this health issue, this study aims to identify the leading neighborhood-level predictors of drug overdose and develop a model to predict areas at the highest risk of drug overdose using geographic information systems and machine learning (ML) techniques. Method Neighborhood-level (block group) predictors were grouped into three domains: socio-demographic factors, drug use variables, and protective resources. We explored different ML algorithms, accounting for spatial dependency, to identify leading predictors in each domain. Using geographically weighted regression and the best-performing ML algorithm, we combined the output prediction of three domains to produce a final ensemble model. The model performance was validated using classification evaluation metrics, spatial cross-validation, and spatial autocorrelation testing. Results The variables contributing most to the predictive model included the proportion of households with food stamps, households with an annual income below $35,000, opioid prescription rate, smoking accessories expenditures, and accessibility to opioid treatment programs and hospitals. Compared to the error estimated from normal cross-validation, the generalized error of the model did not increase considerably in spatial cross-validation. The ensemble model using ML outperformed the GWR method. Conclusion This study identified strong neighborhood-level predictors that place a community at risk of experiencing drug overdoses, as well as protective factors. Our findings may shed light on several specific avenues for targeted intervention in neighborhoods at risk for high drug overdose burdens.

We investigate quantity and quality effects of agglomeration in the careers of Amer-ican authors. We combine novel yearly data on publications and work location of 471 eminent authors with US Census data to provide a complete picture of industry concentration and agglomeration economies from 1850-2000. We find that, on aggregate, an author has 40% higher odds of publishing while living in New York City. The effect size increases with industry concentration but declines with industry maturity and technological progress after WWII. Taking relocation of working-age authors to New York City as an event study, we see a significant immediate increase in publications after arriving. In comparison, the penalty of moving away from the city is mild. Works published while an author lived in New York City were more likely to achieve critical acclaim and are more likely to have lasting influence in terms of present-day popularity. JEL-codes: N30 • N90 • R11 • Z11

By facilitating early re-entry to the labor market after childbirth, public kindergarten might positively affect maternal human capital and labor market outcomes: Are such effects long-lasting? Can we rely on between-individuals differences in quarter of birth to identify them? I isolate the effects of interest from spurious associations through difference-in-difference, exploiting across-states and over-time variation in public kindergarten eligibility regulations in the United States. The estimates suggest a very limited impact in the first year, and no longer-run impacts. Even in states where it does not affect kindergarten eligibility, quarter of birth is strongly and significantly correlated with maternal outcomes.

Public attitudes and policies toward LGBTQ individuals have improved substantially in recent decades. Economists are actively shaping the discourse around these policies and contributing to our understanding of the economic lives of LGBTQ individuals. In this paper, we present the most up-to-date estimates of the size, location, demographic characteristics, and family structures of LGBTQ individuals in the United States. We describe an emerging literature on the effects of legal access to same-sex marriage on family and socioeconomic outcomes. We also summarize what is known about the size, direction, and sources of wage differentials related to variation in sexual orientation and gender identity. We conclude by describing a range of open questions in LGBTQ economics.

COVID-19 has generated several quarantines and economic lockdowns as the main public policy responses that dramatically affected the dynamic of economic growth and labor markets worldwide. These effects impact remittance inflows to developing countries, in particular those coming from the US, which affect poverty reduction paths in Latin America. Using data from the US labor market and economic performance indicators of the US and remittance recipient countries, this paper estimates the distributional impacts of the change in remittances post-COVID-19 for the region that most rely on remittances, Central America. Results suggest that after COVID-19, remittance inflows are expected to decrease 14 % in the region during 2020 and that effects are heterogeneous among countries: El Salvador and Nicaragua are expected to be the most affected countries while Panama is expected to be the least affected one. The model allows to estimate impacts in other countries in Latin America and the Caribbean. However, due to the lack of household survey availability, this paper only explores the distributional impacts of the change in remittance inflows in Central America. The expected impacts on poverty are also heterogeneous. While poverty in El Salvador is expected to increase by 6 % due to the change in remittances, poverty in Guatemala is expected to increase by 1 %. Results are robust to different specifications.

Four databases with data on individual historical life courses are tested for FAIRness: the TRA, Umeå, HSN and IPUMS databases. All databases make their data much more Findable than they were in the original sources. But as databases, they are best findable if their name is a unique acronym, and if different subdatasets all use that same acronym. Sensitive data have to be protected. Two databases make anonymous data sets or those only containing information on deceased individuals Accessible without any formalities, and other databases could follow this example. To increase Interoperability a large number of tools are offered by the databases. Reusability is among the raisons d’être of these databases.

This paper utilizes the city-level variation in housing prices in the U.S. to test whether the effect of sibship size on firstborns' educational attainment is different for homeowner and renter households during the housing bust from 2007-12. To solve the potential endogeneity problem, we use the sex composition of the first two children in each family as an instrumental variable for the number of children. Our results indicate no quantity-quality trade-off for either homeowner or renter households during our study period. However, after we consider the effect of housing price growth, we find that a large family size is negatively associated with college enrollment of the firstborn children of homeowners living in areas with only a moderate increase or a decrease in housing prices, but this relationship becomes positive if homeowner households are located in cities with relatively high housing price growth. Again, we find no quantity-quality trade-off for renters, even after we consider local housing price growth. Our results indicate that owning a house is not always better than renting in terms of the quantity-quality trade-off, depending on changes in local housing prices.

Better access to reproductive healthcare increases women's propensity to become entrepreneurs. Access correlates positively with female entrepreneurial activity and negatively with female entrepreneurial age. Examining firm size and personal income suggests it also improves the success of female-led businesses. None of these results hold when tested on men, women above 40, or other placebo professions. To establish causality, I exploit Roe v. Wade, state laws restricting abortion providers, and an index tracking state-level regulation of reproductive care. All three analyses suggest that policies securing better reproductive care enable more women to become entrepreneurs. I conclude by discussing various possible channels and mechanisms.