Digital platforms have significantly transformed our daily lives by offering convenience in various daily affairs. Even though the prior literature on the societal impacts of digital platforms has been steadily growing, emerging platforms have received limited attention in the information systems (IS) literature. Moreover, as some digital platforms have been related to unexpected societal issues, digital platforms and policymakers have shown increasing interest in the implications of regulating digital platforms. This dissertation aims to fill these gaps by studying emerging digital platforms with a focus on their significant societal impacts and regulatory implications. The first essay empirically examines how online grocery delivery platforms impact obesity rates and nutritional inequalities between the wealthy and the poor in the U.S. The second essay investigates how imposing regulation on data harvesting impacts social media platforms and users by developing a game-theoretic model. The third essay empirically investigates the impact of the Internet Dating Safety Act on intramarriage (i.e., marriage between two individuals with the same racial background) and intermarriage (i.e., marriage between two individuals with different racial backgrounds). Overall, this dissertation expands the body of knowledge on the societal impacts of digital platforms and provides important and timely implications for digital platforms and policymakers.

Encouraging women to pursue STEM employment is frequently touted as a means of reducing the gender wage gap. We examine whether the attributes of computer science workers–who account for nearly half of those working in STEM jobs–explain the persistent gender wage gap in computer science, using American Community Survey (ACS) data from 2009 to 2019. Our analysis focuses on working-age respondents between the ages of 22 and 60 who had a college degree and were employed full-time. We use ordinary least squares (OLS) regression of logged wages on observed characteristics, before turning to regression decomposition techniques to estimate what proportion of the gender wage gap would remain if men and women were equally rewarded for the same attributes–such as parenthood or marital status, degree field, or occupation. Women employed in computer science jobs earned about 86.6 cents for every dollar that men earned–a raw gender gap that is smaller than it is for the overall labor force (where it was 82 percent). Controlling for compositional effects (family attributes, degree field and occupation) narrows the gender wage gap, though women continue to earn 9.1 cents per dollar less than their male counterparts. But differential returns to family characteristics and human capital measures account for almost two-thirds of the gender wage gap in computer science jobs. Women working in computer science receive both a marriage and parenthood premium relative to unmarried or childless women, but these are significantly smaller than the bonus that married men and fathers receive over their childless and unmarried peers. Men also receive sizable wage premiums for having STEM degrees in computer science and engineering when they work in computer science jobs, advantages that do not accrue to women. Closing the gender wage gap in computer science requires treating women more like men, not just increasing their representation.

Over the past two decades IPUMS has engaged in collaborations with three genealogical organizations to produce large census microdata collections of the United States spanning the period from 1850 to 1940. This paper briefly describes how each of these collaborations began and what they entailed.

Researchers generally recognize that ethnoracial identification may shift over the life course. However, the prevalence of these shifts across cohorts and among older adults remains open questions. Using administrative data from Social Security applications from 1984 to 2007, we quantify the magnitude and direction of later-life shifts in ethnoracial self-identification between Black, White, Asian, American Indian, and Hispanic categories for the “Greatest Generation,” those born between 1901 and 1927. Overall, 2.3% of persons in these data changed their ethnoracial identification after the age of 57, with distinct patterns of change for ethnoracial subgroups. By linking to the 1940 Census, we find a positive and significant association between socioeconomic status in early life and a shift from non-White to non-Hispanic White identification in later life. We conclude that ethnoracial self-identification fluidity continues even among older adults, varying in response to social position, ethnoracial climate, and events in greater society.

Over the past 30 years, agricultural employers have been required to pay their workers at least a minimum wage, called the Adverse Effect Wage Rates (AEWRs). These wage rates were established to protect the American workforce from any adverse effects potentially caused by foreign workers, but its economic effects on labor markets are not yet explored. By using the Temporary Agricultural Worker data from the US Department of Labor (DOL) along with the 2005-2019 American Community Survey (ACS), I assess the impact of the AEWRs on US agricultural employment and on different groups of farmworkers. The AEWR policy leads to reduction in agricultural employment, especially for less-educated workers. The estimation results also indicate that the AEWRs have a negative relationship with the employment of less-educated domestic non-Hispanic Whites and unauthorized workers, but a positive relationship with the employment of less-educated domestic Hispanics and foreign workers (H-2A workers). However, the jobs left by one group are not sufficiently filled by the other groups. This finding suggests that the AEWRs tend to shorten job opportunities especially for domestic agricultural workers which is unintended consequence of the AEWR policy

We provide the first causal evidence that economic conditions can affect a family's decision to practice female genital cutting (FGC). In a conceptual framework that overlays economic intuition with an extensive review of ethnographic literature, we argue that economic shocks can affect the (perceived) costs and benefits of FGC in multiple ways, and the direction of their impact is unclear a priori. Empirically, on average, families in Sub-Saharan Africa delay or forgo FGC in response to droughts. Conservatively, a drought changes outcomes for 7 percent of girls at risk of undergoing FGC. Additionally, we show new stylized facts on the diversity of ethno-cultural traditions around practicing FGC and find suggestive evidence that these traditions affect the sign of the impact of droughts. We also find evidence of intra-household spillovers—droughts that are relevant for an older daughter also affect younger daughters. While norms are sticky, economic conditions can change those norms.

This paper estimates the impact of occupational licensing at the extensive margin (existence) and intensive margin (qualifications) on the occupational mobility of US workers. Using 2015–2022 Current Population Survey data on worker occupational choices matched to licensing-policy data, I show that the existence of licensing regulation significantly reduces the probability that a worker enters an occupation. This reduced mobility is largely due to licensing fees and minimum thresholds for age and education. This finding may help explain the weak relationship between licensure and product market quality, as binding licensing qualifications likely have mixed links to worker skills.

Importance: Children who do not receive any routine vaccinations (ie, who have 0-dose status) are at elevated risk of death, morbidity, and socioeconomic vulnerabilities that limit their development over the life course. India has the world's highest number of children with 0-dose status; analysis of national and subnational patterns is the first important step to addressing this problem. Objectives: To examine the patterns among children with 0-dose immunization status across all 36 states and union territories (UTs) in India over 29 years, from 1993 to 2021, and to elucidate the relative share of multiple geographic regions in the total geographic variation in 0-dose immunization. Design, Setting, and Participants: This repeated cross-sectional study analyzed all 5 rounds of India's National Family Health Survey (1992-1993, 1998-1999, 2005-2006, 2015-2016, and 2019-2021) to compare the prevalence of children with 0-dose status across time-space and geographic regions. The Integrated Public Use of Microdata Series was used to construct comparable geographic boundaries for states and UTs across surveys. The study included a total of 125619 live children aged 12 to 23 months who were born to participating women. Main Outcomes and Measures: The outcome was a binary indicator of children's 0-dose vaccination status, coded as children aged 12 to 23 months at the time of the survey who had not received the first dose of the diphtheria-tetanus-pertussis-containing vaccine. The significance of each geographic unit was computed using the variance partition coefficient (VPC). Results: Among 125619 children, the national prevalence of those with 0-dose status in India decreased from 33.4% (95% CI, 32.5%-34.2%) in 1993 to 6.6% (95% CI, 6.4%-6.8%) in 2021. A substantial reduction in the IQR of 0-dose prevalence across states from 30.1% in 1993 to 3.1% in 2021 suggested a convergence in state disparities. The prevalence in the northeastern states of Meghalaya (17.0%), Nagaland (16.1%), Mizoram (14.3%), and Arunachal Pradesh (12.6%) remained relatively high in 2021. Prevalence increased between 2016 and 2021 in 10 states, including several traditionally high-performing states and UTs, such as Telangana (1.16 percentage points) and Sikkim (0.92 percentage points). In 2021, 53.0% of children with 0-dose status resided in the populous states of Uttar Pradesh, Bihar, and Maharashtra. A multilevel analysis comparing the share of variation at the state, district, and cluster (primary sampling unit) levels revealed that clusters accounted for the highest share of the total variation in 2016 (44.7%; VPC [SE], 1.04 [0.32]) and 2021 (64.3%; VPC [SE], 0.38 [0.12]). Conclusions and Relevance: In this cross-sectional study, findings from approximately 3 decades of analysis suggest the need for sustained efforts to target populous states like Uttar Pradesh and Bihar and northeastern parts of India. The resurgence of 0-dose prevalence in 10 states highlights the importance of programs like Intensified Mission Indradhanush 4.0, a major national initiative to improve immunization coverage. Prioritizing small administrative units will be important to strengthening India's efforts to bring every child into the immunization regime.

The mission of the National Breast and Cervical Cancer Early Detection Program's (NBCCEDP) mission is to improve access to mammography and other health services for underserved women. Since its inception in 1991, this national program has improved breast cancer screening rates for women who are uninsured and underinsured. However, the literature has shown that NBCCEDP screenings are decreasing, and only reach a portion of eligible women. Reliable estimates at the sub-county level are needed to identify and reach eligible women. Our work builds upon previous estimates by integrating uninsured and insurance status into spatially adaptive lters. We use spatially adaptive lters to create small area estimates of standardized incidence ratios describing the utilization rate of NBCCEDP services in Minnesota. We integrate the American Community Survey (2010-2014) insurance status data to account for the percentage that an individual is uninsured. We test ve models that integrate insurance status by age, sex, and race/ethnicity. Our composite model, which adjusts for age, sex, and race/ethnicity insurance statuses, reduces 95% of the estimation error. We estimate that there approximately 49,913.7 women eligible to receive services for Minnesota. We also create small geography (i.e., county and sub-county) estimates for Minnesota. The integration of the insurance data improved our utilization estimate. The development of these methods will allow state programs to more eciently use their resources and understand their reach.

Climate change is increasing the frequency and intensity of natural disasters, which might induce significant changes in housing markets. While research has acknowledged that flooding can have heterogeneous effects on homeowners and renters, few studies have analyzed the effect of flooding on homeownership rates. Using a panel fixed effect model, we find that flooding events can decrease average homeownership rates by 1.2%. Using a major flood in 2008 as a natural experiment, we decompose the effect of migration responses to the flood and find that the negative effect on homeownership can be persistent for over 6 years in inundated areas. We also find that the decrease in homeownership rate is driven largely by outmigration of existing owners. Our findings add to the literature on the effect of natural disasters on housing markets and inform policymakers about major channel for this transitions.

The interwar isolationist movement constrained US governments from intervening to deter Fascist aggression. But what motivated this movement? We digitize archival records relating to 24,000 donors to the America First Committee, the largest isolationist group, which we merge into the 1940 US Census. German immigrants, especially those with stronger German identities as measured by naming and intermarriage, made up the rank and file of America First. We find little evidence that sectoral economic interests drove isolationism. These results indicate the importance of immigrant diasporas for foreign policy. Underscoring the link between German identity and isolationism, we find that German immigrants resident in counties with higher First World War casualties, which stimulated anti-German discrimination, had weaker German identities by 1940 and were less likely to donate. Isolationism was not born of isolation.

During the COVID-19 pandemic, the number of Unemployment Insurance (UI) benefit recipients rose to unprecedented levels. This spike in benefits was especially dramatic for the number of recipients collecting partial benefits-UI benefits earned while working part time-which doubled from around 8% of total UI recipients pre-pandemic to 16% in early 2021. This rise coincided with some key temporary changes to the UI program, most prominently the Federal Pandemic Unemployment Compensation (FPUC), which paid a fixed $600 bonus to all workers collecting any amount of UI benefits. The FPUC induced a substantial cliff in disposable income for many workers, such that returning to full-time or near-full-time work would result in a loss of hundreds of dollars of weekly income, compared to working part-time just under the threshold required to collect benefits. This paper seeks to understand the effect this program had on aggregate employment and underemployment. To that end, I construct a job search model with moral hazard in which workers have the option to work part-time (even when they have full time job offers) and collect partial UI benefits. I calibrate this model to the pre-pandemic and then study the effects during the pandemic, using it to quantify the extent to which this newly introduced incentive discouraged workers from returning to full-time work.

Introduction: The impact of cigarette smoking on mortality is well studied, with estimates of the relative mortality risks for the overall population widely available. However, age-specific mortality estimates for different sociodemographic groups in the U.S. are lacking. Methods: Using the 1987–2018 National Health Interview Survey Linked Mortality Files through 2019, all-cause mortality relative risks (RRs) were estimated for current smokers or recent quitters and long-term quitters compared with those for never smokers. Stratified Cox proportional hazards regression models were used to estimate RRs by age, gender, race/ethnicity, and educational attainment. RRs were also assessed for current smokers or recent quitters by smoking intensity and for long-term quitters by years since quitting. The analysis was conducted in 2021–2022. Results: All-cause mortality RRs among current smokers or recent quitters were generally highest for non-Hispanic White individuals than for never smokers, followed by non-Hispanic Black individuals, and were lowest for Hispanic individuals. RRs varied greatly by educational attainment; generally, higher-education groups had greater RRs associated with smoking than lower-education groups. Conversely, the RRs by years since quitting among long-term quitters did not show clear differences across race/ethnicity and education groups. Age-specific RR patterns varied greatly across racial/ethnic and education groups as well as by gender. Conclusions: Age-specific all-cause mortality rates associated with smoking vary considerably by sociodemographic factors. Among high-education groups, lower underlying mortality rates for never smokers result in correspondingly high RR estimates for current smoking. These estimates can be incorporated in modeling analyses to assess tobacco control interventions’ impact on smoking-related health disparities between different sociodemographic groups.

This paper explores the factors associated with the non-payment of property taxes during the Great Depression. US cities experienced skyrocketing levels of property tax non-compliance during 1929–1933, with an average loss of a quarter of their tax revenue in 1933. We present two main findings. First, we find that tax delinquency, the American term for non-payment of taxes, is negatively associated with economic conditions and taxpayers’ ability to pay, and is positively correlated with the presence of elections. Cities that experienced higher levels of delinquency tended to have less construction of new housing units and lower median income, and delinquency was higher during mayoral election years. We find no association between delinquency and either the burden of taxation (the property tax rate) or tax administrations, measured by the salaries of tax assessors and the presence of reduced rates for personal property. Second, despite the transitory nature of this episode, tax delinquency had a persistent impact on municipal revenue. Moving from the 25th to the 75th percentile of delinquency in 1929–1933 is associated with a 5% lower tax base valuation, tax revenue, and municipal spending at the end of the Great Depression.

Pew Research Center conducted this analysis to look at changing marriage rates among 40-year-olds in the United States from 1850 to 2021. This analysis uses decennial census data and the American Community Survey (ACS). The ACS is the largest household survey in the U.S., with a sample of more than 3 million addresses. Collected by the Census Bureau since 2001, it covers the topics previously included in the long form of the decennial census. The ACS is designed to provide estimates of the size and characteristics of the nation’s resident population. These large datasets allow for reliable estimates of outcomes for people at a given age. The data on cohabitation comes from the Census Bureau’s Current Population Survey (CPS) 2022 Annual Social and Economic Supplement. The microdata files used for this analysis were provided by the Integrated Public Use Microdata Series (IPUMS) from the University of Minnesota. IPUMS standardizes variable names and coding across years as much as possible, making it easier to analyze the data over time. The first census after the American Revolution occurred in 1790. IPUMS has decennial census samples from 1850 on. The 1850 and 1860 census samples only include the free population.

Administrative data allow researchers to examine the reach and composition of the child welfare system service population, as well as the correlates and consequences of child welfare involvement. State- and regional-level analyses have been carried out with a range of linked administrative data systems. At the national level, two federal data systems provide a means to estimate population-level patterns of involvement, the National Child Abuse and Neglect Data System (NCANDS), and the Adoption and Foster Care Analysis and Reporting System (AFCARS). This chapter details the use of synthetic cohort life table methods to leverage these cross-sectional national data files to examine lifetime prevalence and distribution of child welfare system involvement. This chapter also addresses an important challenge to the assumptions of these methods—the lack of harmonization across state reporting agencies—which limits the ability to account for cross-state migration and may bias prevalence estimates.

Recessions create enduring effects, or scars, on young individuals' careers, notably when they occur around critical periods such as high school graduation and college enrollment. I investigate how educational choices amplify or mitigate these scarring effects across income levels. Low-income young people face dual scarring effects: increased likelihood of dropping out of college and enduring negative labor market entry effects. High-income young people strategically evade these repercussions, delaying labor market entry through timely college enrollment during economic downturns. I quantify the lifetime repercussions of experiencing a recession during these critical phases. The poorest individuals endure a 40% reduction in lifetime consumption if a recession occurs while they are enrolled in college. A recession that occurs around the time of high school graduation hinders the college attendance of the middle-to-low-income group, causing a 24% lifetime consumption loss.

Ventura County is home to approximately 55,000 children under age six, many of whom enroll in early care and education (ECE) programs (KidsData, 2023). The ECE workforce provides vital learning and growth for these children, complex work that demands energy and expertise. Around 140 child care centers operate in the county, along with 540 family child care (FCC) providers operating in their homes. Building on the California Early Care and Education Workforce Study conducted by the Center for the Study of Child Care Employment (CSCCE), this report offers a snapshot of the licensed ECE workforce in Ventura County.1 In Chapter 1, we provide a profile of its core members: FCC providers and center-based educators (directors, teachers, and assistants).2 In Chapter 2, we describe the state of educator well-being; and in Chapter 3, we explore current headwinds affecting the field.

The COVID-19 pandemic produced a significant decline in international immigration to the USA between 2020 and 2021. This paper documents the timing, characteristics, and heterogeneity of the change in immigration across states and economic sectors. Additionally, we describe the trends in internal native mobility in the USA prior to and after the pandemic, investigating whether natives responded to the decrease in immigration by relocating either geographically or across sectors. Despite the substantial drop in international migration, we do not observe any significant changes in native internal mobility. Employing a panel regression and a shift-share IV, we study the effect of foreign immigration, the emergence of remote-work, and changes in labor demand on cross-state native mobility. Our results indicate that the decline in immigration following COVID-19 and the differential availability of remote-work opportunities across sectors and states did not drive changes in natives’ cross- state or cross-sector mobility.

Time spent waiting for services represents unproductive time lost while fulfilling needs. We use time diary data from the nationally representative American Time Use Survey to estimate the difference between high- and low-income people in time spent waiting for basic services. Relative to high-income people, low-income people are one percentage point more likely to wait on an average day, are three percentage points more likely to wait when using services, spend an additional minute waiting for services on a typical day and spend 12 more minutes waiting when waiting occurs. The unconditional gap in waiting time suggests low-income people spend at least six more hours per year waiting for services than high-income people. The income gap in waiting time cannot be explained by differences in family obligations, demographics, education, work time or travel time. Further, high-income Black people experience the same higher average wait times as low-income people regardless of race. Holt and Vinopal use nationally representative data from the American Time Use Survey to find that low-income people are more likely to wait, and to wait longer, when using basic services relative to high-income people.