Child care workers are the backbone of our economy. High-quality child care allows parents to stay in the workforce, and is particularly important for mothers, who still typically take on most of the caregiving responsibilities at home.1 Child care workers also provide an essential role in supporting children’s learning and healthy development—more critical than ever for children experiencing the disruption of the public health crisis. Yet even before the pandemic began, child care workers—nearly all of whom are women— were underpaid and undervalued. As COVID-19 forced many providers to close, the child care industry has suffered massive job losses. Between February and April 2020, the industry lost 370,600 jobs, over a third of its workforce, with women accounting for 95% of those losses.2 Between April and July, only about 4 in 10 (42%) of the lost jobs returned.3 As of July, the child care workforce is only 79% as large as it was in February, before the pandemic began.

The benefits of owning a home in the United States are well documented. Homes can create wealth for their owners that in turn can benefit families for generations. Homeownership can also reduce economic risk by protecting families from rising rent prices. Owning a home has also been associated with better psychological health and greater stability for homeowners’ children. [1] Decennial census data can be used to monitor trends in homeownership and differences across geographic areas. The 2017 American Community Survey data provide a preview of patterns in the 2020 decennial housing data

This is the first study to examine the effect of experiencing a widespread, deadly epidemic on voting behavior. Using data on elections to the U.S House of Representatives and leveraging cross-district variation in HIV/AIDS mortality during the period 1983-1987, we document the effects of the HIV/AIDS epidemic on votes received by Democratic and Republican candidates. Beginning with the 1994 elections, there is a strong, positive association between HIV/AIDS mortality and the vote share received by Democratic candidates. Congressional districts that bore the brunt of the HIV/AIDS epidemic also saw substantial increases in Democratic voter turnout and contributions made to Democratic candidates.

Internal migration's effect on family planning behaviour depends upon migration circumstances. While many studies describe instability and displacement's effect on family planning access, fewer studies consider the positive association between internal migration and family planning behaviour. Using Performance Monitoring for Action (PMA) survey data, we examine the relationship between internal migration and unmet need for family planning in Ethiopia from 2017 to 2018. We describe determinants of family planning behaviour by migrant status and model migration's effect on unmet need for family planning using multilevel logistic regression. Internal migrants tend to be more educated and wealthier and have less unmet need than nonmigrants, likely due to different fertility preferences and human capital. This contributes to existing research by illustrating how rural–urban migration in Ethiopia relates to family planning behaviour. Findings will be of interest to social scientists and policymakers evaluating family planning resource allocation to reduce unmet need in African contexts

Disparities in healthcare access prevent uniform distribution of the best possible care to all individuals. Accessing pediatric surgical care requires parents to navigate complex healthcare systems. Disparities in comprehension, socioeconomics, and provider biases may disproportionately impact different racial and ethnic groups. Pediatric surgical disparities are largely unknown as studies are limited to specific pathology or are single center with minimal assessment of sociodemographic variables1-3. Larger studies of pediatric surgical epidemiology are limited to either inpatient or outpatient database studies without assessment of patient racial or socioeconomic associations4,5. Here, we report a nationally representative health survey to assess disparities in pediatric surgical care in the United States from 1999-2018.

This dissertation presents three essays in financial economics. The essays study the impact of trade globalization through the lens of the financial market. The first chapter investigates the effect of trade liberalization policy on firm value. I identify this effect by exploiting cross-sectional differences in firms' exposure to potential tariff hikes imposed on U.S. imports from China. I find that the Chinese equity market responded negatively to a major U.S.-China trade liberalization event in 2000, and the responses were driven by inefficient state-owned institutions. The analysis also implies that policy uncertainty elimination may generate distributional gains from market share reallocation. The second chapter focuses on the role of implicit protection from trade globalization and its impact on the U.S. equity market. The third chapter explores the consequences of the U.S.-China trade war.

We study the role played by foreign born U.S. citizens in shaping migration policy between 18971924. Using a novel district level dataset, we find systematic evidence that this constituency supported an open door policy. At the same time, more stringent residency requirements led to a decline in the election turnout rates of naturalized Americans, and thus in their ability to affect congressmen immigration stance. Our analysis highlights also the importance of the electoral booth: congressmen were responsive to the immigrant constituency only if they were elected in a close race, or if they were not already ideologically committed to an open door policy.

Home energy use is a major source of a typical US household’s carbon emissions. This study uses the American Community Survey (ACS) micro data to estimate the impact of building energy codes on household electricity expenditures, using multiple regression and difference-in-difference models. In California and US samples, I present new evidence that energy codes were modestly effective. Homes built in the decade after energy codes were first adopted spend between 1.5% and 4% less on electricity compared to homes built prior to their adoption.

In an otherwise insightful article on how the medical system profits from surprise medical bills, medical doctor and journalist Elisabeth Rosenthal fails to mention the detrimental role played by private equity firms.1 Most patients don’t know that hospitals and physician’s practices negotiate separate contracts with insurers, and that it’s possible for a hospital to be in-network for an insured patient, but for a doctor that cares for them to be out-of-network. Emergency room doctors, anesthesiologists, radiologists — doctors that patients do not get to choose — are most likely to be out-of-network. Hospitals contract with doctors’ practices or with large physician staffing firms for these doctors. In these situations, patients do not get to choose their doctor and cannot select a doctor that is in-network. The doctors will see a steady stream of patients and will not lose business because their patients have been hit with surprise medical bills that may be hundreds or even thousands of dollars more than what their health insurance companies pay for the same care. A Stanford University study found that by 2016, 42.8 percent of trips to the ER — more than 4-in-10 — led to patients getting surprise medical bills.

This is the first study to examine the effect of experiencing a widespread, deadly epidemic on voting behavior. Using data on elections to the U.S House of Representatives and leveraging cross-district variation in HIV/AIDS mortality during the period 1983-1987, we document the effects of the HIV/AIDS epidemic on votes received by Democratic and Republican candidates. Beginning with the 1994 elections, there is a strong, positive association between HIV/AIDS mortality and the vote share received by Democratic candidates. Congressional districts that bore the brunt of the HIV/AIDS epidemic also saw substantial increases in Democratic voter turnout and contributions made to Democratic candidates.

This archive provides two Jupyter Notebooks to explore metadata and retrieve data using the IPUMS NHGIS API. American Community Survey (ACS) 5-year estimates 2005-2009 at the block group and county levels are requested and downloaded for Galveston County, Texas. Data of interest are race and ethnicity, and median household income. Block group and county shapefiles are also downloaded. The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration and management.The notebooks use Google Drive for file storage and include extensive markdown and comments. The notebooks can be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive). The first notebook explores metadata in order to identify relevant datasets and tables and necessary parameters for subsequent data request and retrieval. The second notebook uses the parameters identified from the first notebook. A data request is constructed and the data extract is downloaded and files unzipped and made ready for analysis. The data that were downloaded are also stored separately with this archive. The data referenced in this archive have research applications listed in the Related Publications section and in ongoing research at the Texas A&M University Department of Landscape Architecture and Urban Planning (LAUP), and the Hazard Reduction and Recovery Center (HRRC).

Trade can affect the development process of a country via various direct and indirect mechanisms. Empirically, it is difficult to identify causal effects, as trade is likely to be endogenous to other socio-economic factors that also affect development. To overcome this problem, this study uses a trade policy experiment called the African Growth and Opportunity Act (AGOA) which conferred many sub-Saharan African countries largely duty-free and quota-free access to US markets. Using retrospective birth histories from Demographic and Health Survey (DHS), I develop a large micro panel dataset that spans 30 sub-Saharan African countries and carry out a within-mother variation in survival of infant to find a causal impact of the policy. Identification in this analysis is based on each country's exposure to the trade policy at different points in time. I find that the policy reduces infant mortality by about 9% of the sample mean, even after controlling for country-time linear trends as well as mother's time invariant characteristics. Event study reveals no effects prior to AGOA implementation, corroborating that the decrease in infant mortality is due to AGOA. I also find strong heterogeneous effects at the country and household level. The effects range from there being no significant effect to a strong increase or a strong decrease in infant deaths at the country level. The effect of AGOA on infant survival is stronger for countries that export large amounts of agricultural goods and mineral ores as compared to oil exporting countries. At the micro level, I see stronger effects for the uneducated, rural, and poor women via those women employed in agriculture or using manual labor, indicating increasing incomes as a possible mechanism. This study provides the first estimates of the effects of AGOA on infant mortality and adds to the literature on the quantitative impact of trade on health.

This dissertation consists of two essays on labor markets. The first essay explains differences in unemployment duration among displaced workers by differences in their skills, using the unemployed worker's previous occupation and years of education to capture skill level. I use the cumulative incidences approach from the statistics literature, a better alternative to the standard survival analysis methods in the case of competing risks. I find that the higher the displaced worker is on the skill ladder, based on their previous occupation, the faster their exit rate to a full-time job by 55%. An extra year of education will increase the exit rate to a full-time job by 7%. The impact of education, however, on exiting unemployment is less pronounced the higher the displaced worker's previous occupation is on the skill-ladder. The second essay investigates changes in the plucking behavior of employment growth, as well as changes in its relationship with the output cycle in the G7 countries. Using both revised and real-time data, we consider several popular measures of the output cycle. We find evidence in favor of substantial disparities across countries, both in the responses of employment to employment gaps and in the responses of employment to the output cycle. Furthermore, for most countries, we see signicant evidence in favor of structural changes in the response coefficients, suggesting much slower recoveries in labor markets, consistent with the jobless recoveries hypothesis.

Pivot tables are one of the most popular tools for data visualization in both business and research applications. Although they are in general easy to use, their comprehensibility becomes progressively lower when the quantity of cells to be visualized increases (i.e., information flooding problem). Pivot tables are largely adopted in OLAP, the main approach to multidimensional data analysis. To cope with the information flooding problem in OLAP, the shrink operation enables users to balance the size of query results with their approximation, exploiting the presence of multidimensional hierarchies. The only implementation of the shrink operator proposed in the literature is based on a greedy heuristic that, in many cases, is far from reaching a desired level of effectiveness. In this paper we propose a model for optimizing the implementation of the shrink operation which considers two possible problem types. The first type minimizes the loss of precision ensuring that the resulting data do not exceed the maximum allowed size. The second one minimizes the size of the resulting data ensuring that the loss of precision does not exceed a given maximum value. We model both problems as set partitioning problems with a side constraint. To solve the models we propose a dual ascent procedure based on a Lagrangian pricing approach, a Lagrangian heuristic, and an exact method. Experimental results show the effectiveness of the proposed approaches, that is compared with both the original greedy heuristic and a commercial general-purpose MIP solver.

Using the 2012–2013 American Time Use Survey, I show that both “who” people spend time with and “how” they spend it affect their life satisfaction, adjusted for numerous demographic and economic variables. Life satisfaction among married individuals increases most with additional time spent with one’s spouse. Among singles, satisfaction decreases most as more time is spent alone. Additional time spent sleeping or TV-watching reduces satisfaction, while longer usual workweeks and higher incomes increase it. Nearly identical results are shown using the 2014–2015 British Time Use Survey. The US estimates are used to simulate the impacts of Covid-19 lock-downs on life satisfaction.

Over the last two decades, the share of U.S. children under age 18 who live in a multigenerational household (with a grandparent and parent) has increased dramatically. Yet we do not know whether this increase is a recent phenomenon or a return to earlier levels of coresidence. Using data from the decennial census from 1870 to 2010 and the 2018 American Community Survey, we examine historical trends in children’s multigenerational living arrangements, differences by race/ethnicity and education, and factors that explain the observed trends. We find that in 2018, 10% of U.S. children lived in a multigenerational household, a return to levels last observed in 1950. The current increase in multigenerational households began in 1980, when only 5% of children lived in such a household. Few differences in the prevalence of multigenerational coresidence by race/ethnicity or education existed in the early part of the twentieth century; racial/ethnic and education differences in coresidence are a more recent phenomena. Decomposition analyses do little to explain the decline in coresidence between 1940 and 1980, suggesting that unmeasured factors explain the decrease. Declines in marriage and in the share of White children most strongly explained the increase in multigenerational coresidence between 1980 and 2018. For White children with highly educated parents, factors explaining the increase in coresidence differ from other groups. Our findings suggest that the links between race/ethnicity and socioeconomic status and multigenerational coresidence have changed over time, and today the link between parental education and coresidence varies within racial/ethnic groups.

Recent cohorts of U.S. children increasingly consist of immigrants or the immediate descendants of immigrants, a demographic shift that has been implicated in high rates of child poverty. Analyzing data from the 2014-2018 Current Population Survey (CPS) and using the U.S. Census Bureau’s Supplementary Poverty Measure, we describe differences in child poverty rates across immigrant generations (first-, second-, and third+-generation immigrant children) and how these are rooted in generational differences in the prevalence and impact of key poverty risk factors. We find that (1) poverty rates among Hispanic children are very high, particularly among first- and second- generation with two foreign-born parents children; (2) limited parental employment is by far the greatest risk factor for child poverty compared to having a young or poorly educated parent, living in a single-headed family or disadvantaged place of residence; (3) inter-generational differences in risk factor prevalence explain non-trivial shares of corresponding child poverty gaps; and (4) the patterns observed among the Hispanic population are moderated by race and ethnicity. Understanding the intersection of poverty risks, immigrant generation, and race has significant policy implications has America’s population continues to grow more diverse along multiple social axes.

Eastelin’s hypothesis stresses the importance of relative income for young adults. We examine the impact of young men’s relative income on marriage rates. The latter is investigated by employing data for the United Stated that spans the period 1981-2016. The evidence reveals a positive and statistically significant relationship between young men’s relative income and marriage rates (for males, females, and both). Relative income has a greater impact on marriage than absolute income for three out of four of the methods employed. Causality runs from relative income to marriage in five out of six cases examined. We infer that young adults are more likely to get married if they feel affluent relative to the level of their material aspirations formed by large in childhood.

We read with great interest the article by Jakeman et al, “Addressing Latent Tuberculosis Infection Treatment Through a Collaborative Care Model With Community Pharmacies and a Health Department,” which addressed latent tuberculosis infection (LTBI) treatment through a collaborative approach in New Mexico (1). The authors described a new approach to aim at the ever-moving target of eradication of tuberculosis in the United States. The approach of involving community pharmacies and pharmacy visits is a brilliant idea for reaching the appropriate populations and improving health care access (2). Lal et al studied the rates of initiation and completion of LTBI treatment in a teaching hospital in Massachusetts and found that the immigrant population had a higher completion rate (93.7%) than did the population born in the United States (69.7%) (3). According to the Integrated Public Use Microdata Series, Current Population Survey, New Mexico has a large immigrant population with a potentially high prevalence of LTBI (4). It is well known that LTBI is a dormant source of tuberculosis disease in patients who are not treated. Jakeman et al carefully selected an appropriate cohort to implement their intervention. The study by Lal et al also found that having at least 4 visits with a health care provider increased the odds of completing treatment and that the time spent during the initial visit was an important factor in completing treatment (3). We suggest that any initiative introducing a collaborative approach, such as the one described by Jakeman et al, should emphasize the importance of the initial visit. More time spent during the initial visit can potentially save time during subsequent visits and improve treatment completion rates. Although the treatment initiation and completion rates Jakeman et al achieved by using a collaborative approach are encouraging, reaching the public health goals of higher completion rates and, ultimately, disease eradication will require use of all reasonable measures. We congratulate the authors on their work in addressing LTBI treatment. Collaborative working relationships between community pharmacies and physicians have improved patient care in many communities (2). Moving forward with an approach like the one implemented by Jakeman et al can best be achieved through better patient education and a decentralization of resources and responsibility, with a shift from large hospitals and departments of health toward community-based pharmacies and pharmacists.

This paper examines how college students in the United States altered their college majors during the energy boom and bust of the 1970s and 1980s. We focus on petroleum engineering and geology, two majors closely related to the energy industry. We find strong evidence that the energy boom increased the prevalence of these two energy-related majors and the energy bust lowered the prevalence of these majors. Effects are particularly strong for young people born in energy intensive states. Thus, college major decisions responded to industry fluctuations with important location-specific effects consistent with frictions to migration and information flows.