This dissertation consists of three chapters examining issues relevant to higher education outcomes. The first essay examines the impact of state merit-aid program adoption on the stock of human capital across rural and urban populations. Using data from the 1990 and 2000 Decennial Censuses and the 2008-2012 American Community Survey, I utilize a staggered difference-in-difference methodology that exploits the exogenous variation in the timing of program adoption to produce causal estimates. Program adoption reduces bachelor’s degree holders in rural counties by 1.2 percentage points. The second essay measures the impact of honors college participation on collegiate outcomes at a large, public-land grant midwestern university by leveraging strict eligibility criteria using a fuzzy regression discontinuity design. For compliers near the threshold, honors participation increases first- and senior-year cumulative grade-point averages but has no statistically significant effect on persistence or graduation rates. The third essay is a descriptive analysis that measures the extent to which education-job mismatch and its consequences vary by degree field for Ph.D. recipients from a large, publicland grant midwestern university from 2011 to 2020. The study relies on a novel dataset compiled from publicly accessible sources online. Relative to other degree fields, engineering Ph.D. graduates were the most likely to work in occupations for which they were over-educated or outside of their field. There is also some evidence that mismatch may be positively correlated with occupation-level earnings.

Social demographers and historians have devoted extensive research to patterns of racial segregation that emerged under Jim Crow and during the post-Civil Rights era but have paid less attention to the role of slavery in shaping the residential distribution of Black populations in the United States. One guiding assumption has been that slavery rendered racial segregation to be both unnecessary and impractical. In this study, I argue that apart from the master–slave relationship, slavery relentlessly produced racial segregation during the antebellum period through the residential isolation of slaves and free people of color. To explain this pattern, I draw on racial threat theory to test hypotheses regarding interracial economic competition and fear of slave mobilization using data from the 1850 Census, as well as an architectural survey of antebellum sites. Findings suggest that the residential segregation of free people of color increased with their local prevalence, whereas the segregation of slaves increased with the prevalence of the slave population. These patterns continue to hold after controlling for interracial competition over land or jobs and past slave rebellions or conspiracies.

This dissertation is composed of three chapters on the effects of import exposure. For my dissertation I mainly use the variation of import competition across local labor markets to explore its impact on labor market outcomes (e.g., wages and employment status), human capital investment decisions (choice of college major), and education-job mismatch. Chapter one explores the relationship between increasingly intense Chinese import competition and American college students’ choice of major in the 2000s. By employing a modified version of the measure for Chinese import competition from Autor, Dorn, and G. Hanson (2013) and analyzing the relationship between industries and college majors, I find that rising Chinese trade exposure of nineteen industries in the 2000s has a negative effect on American students’ choice of six engineering majors. The magnitudes of the effects range from 0.62 to 0.69 percentage point decreases in the probability of choosing those six engineering majors. I also find that males are more negatively affected by Chinese import competition in terms of the choice of the six engineering majors, whereas no significant results exist if I restrict my sample to females. Chapter two analyzes how increased trade exposure affects students’ choice of STEM major. I first present a simple model to illustrate how trade exposure impacts students’ utility functions through their self-beliefs about labor market outcomes and then use assorted data to show that import competition positively affects the choice of STEM major. I find that increased import exposure in the 2000s leads to 1.05 and 0.72 percentage point increases in the probability of choosing STEM majors for college underclassmen and upperclassmen, respectively. As for labor market outcomes, my results suggest that a rise in import competition leads to a pronounced negative effect on weekly wages, employment status, and full-time employment across STEM and non-STEM occupations from the late 1990s through the 2000s. STEM occupations, however, are less negatively impacted by import competition, which helps explain why a rise in import exposure increases the probability of students choosing STEM majors. Chapter three investigates the impact of import exposure on education-occupation mismatch. I first use the concept of a matching function to explain the connection between mismatch and the supply of and demand for college graduates. Next, I use an input-output table to construct a measure of import exposure that accounts for both direct and indirect trade shocks. Findings show that increased import exposure leads to a rise in education-occupation mismatch from 2011 through 2019. Moreover, for the supply side I present that a rise in import exposure significantly increases the number of bachelor’s degrees awarded in 4-year colleges and in most degree fields. However, for the demand side, I do not observe corresponding increases in occupational employment for most fields of education. The unbalanced demand for and supply of college graduates might potentially explain the rise in education-occupation mismatch.

The racial wealth gap is the largest of the economic disparities between Black and white Americans, with a white-to-Black per capita wealth ratio of 6 to 1. It is also among the most persistent. In this paper, we construct the first continuous series on white-to-Black per capita wealth ratios from 1860 to 2020, drawing on historical census data, early state tax records, and historical waves of the Survey of Consumer Finances, among other sources. Incorporating these data into a parsimonious model of wealth accumulation for each racial group, we document the role played by initial conditions, income growth, savings behavior, and capital returns in the evolution of the gap. Given vastly different starting conditions under slavery, racial wealth convergence would remain a distant scenario, even if wealth-accumulating conditions had been equal across the two groups since Emancipation. Relative to this equal-conditions benchmark, we find that observed convergence has followed an even slower path over the last 150 years, with convergence stalling after 1950. Since the 1980s, the wealth gap has widened again as capital gains have predominantly benefited white households, and income convergence has stopped.

Accurate estimates of subnational populations are important for policy formulation and monitoring population health indicators. For example, estimates of the number of women of reproductive age are important to understand the population at risk of maternal mortality and unmet need for contraception. However, in many low-income countries, data on population counts and components of population change are limited, and so subnational levels and trends are unclear. We present a Bayesian constrained cohort component model for the estimation and projection of subnational populations. The model builds on a cohort component projection framework, incorporates census data and estimates from the United Nation's World Population Prospects, and uses characteristic mortality schedules to obtain estimates of population counts and the components of population change, including internal migration. The data required as inputs to the model are minimal and available across a wide range of countries, including most low-income countries. The model is applied to estimate and project populations by county in Kenya for 1979–2019 and is validated against the 2019 Kenyan census.

Between 2008 and 2018, southern states saw the fastest growth of Latinxs of any other U.S. region (Flores et al., U.S. Hispanic population reached new high in 2018, but growth has slowed, 2019), transforming states in this region into what many researchers call 'the Nuevo South.' Drawing on literature that explores factors that influence ethnic identification, a dimension of ethnic identity development, among Latinx college students and results from survey research on ethnic identification of Latinx undergraduates in the Nuevo South, this article presents evidence of the effects of cocurricular experience, curricular experience, the sociopolitical context of the Nuevo South, and ethnicity on ethnic identification of undergraduate students who identify as Latinx and attend two higher education institutions in the Nuevo South. Results reveal that cocurricular experience, the sociopolitical context of the Nuevo South, and ethnicity are significant predictors of ethnic identification. At the same time, results suggest that curricular experience is not a significant predictor of ethnic identification. Results are discussed within the unique context of higher education institutions located in the Nuevo South. Implications and recommendations for research and practice are provided. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

We investigate the drivers of gender differentials in hiring chances. More concretely, we test (i) whether recruiters perceive job applicants in gender stereotypical terms when making hiring decisions and (ii) whether the activation of these gender stereotypes in recruiters' minds varies by the salience of gender in a particular hiring context and the gender prototypicality of a job applicant, as hypothesised in Ridgeway and Kricheli-Katz (2013). To this end, we conduct an innovative vignette experiment in the United States with 290 genuine recruiters who evaluate fictitious job applicants regarding their hireability and 21 statements related to specific gender stereotypes. Moreover, we experimentally manipulate both the gender prototypicality of a job applicant and the salience of gender in the hiring context. We find that employers perceive women in gender stereotypical terms when making hiring decisions. In particular, women are perceived to be more social and supportive than men, but also as less assertive and physically strong. Furthermore, our results indicate that the gender prototypicality of job applicants moderates these perceptions: the less prototypical group of African American women, who are assumed to be less prototypical, are perceived in less stereotypical terms than white women, while some stereotypes are more outspoken when female résumés reveal family responsibilities.

Occupational regulation affects many people across many aspects of life. Most anyone knows someone affected or themselves are affected by some form of occupational regulation. This dissertation research investigates the consequences of occupational regulation across three different areas of study: economic history, urban and regional economics, and health policy. The first chapter investigates the historic licensing of emigrant agents. In the period following the US Civil War, firms wished to capitalize on the availability of African American labor. To do so they hired emigrant agents, also known as labor agents, to hire and help with the migration of individuals from the South. Faced with out-migration at the hands of the labor force, some southern states licensed the profession as a substantial barrier to practice. I use linked full-count US Censuses to determine the effect that licensing emigrant agents had on the individual probability of migration both out of state, and out of the South. A difference-in-differences analysis on the border counties of North and South Carolina suggests that the licensing of emigrant agents reduced the probability of migration out of the South by more than 1 percentage point. The second chapter deals with cross-border competition and the effects of licensing massage therapists. Occupational licensing has been shown to have many pervasive economic effects. Licensing restricts competition, which causes wage premiums, potentially induces rent seeking, and ultimately results in consumers having to pay high prices through both channels of reduced supply and producers passing on increased cost of doing business. Licensing laws are passed at the state level; and thus, there can be considerable variation across states. Should there be much economic activity at state borders, this would be inconsequential. Yet, the existence of metropolitan areas spanning state borders begs the question of what effects can restricting competition be when competitive substitutes are easily available. This theory is tested using major MSAs that cross state borders and data from the American Community Survey to show how the differing licensing schemes affect the incomes of practicing massage therapists. Ultimately, it appears that the effect of easily available substitutes of massage therapists in the border state mutes the effect of the wage premium that would be caused by a more restrictive licensure scheme. Not only do wage premiums not appear in geographically adjacent states, it is especially missing in border MSAs. The third chapter is joint work with Dr. Bobby W. Chung of St. Bonaventure University and presents an analysis of the effect of expanding scope of practice for nurse practitioners. As a response to the Covid-19 Pandemic many states choose to expand nurse practitioner scope of practice. We analyze the effects of the expansion of scope of practice on daily Covid related mortality using a synthetic control design. Our results suggest that expanding scope of practice for NPs reduced daily Covid related mortality and was most effective in non-rural areas. The total effect of expanding scope of practice is a reduction of hundreds of deaths over a 30 day period compared to the synthetic control.

Importance Little is known about emergency department (ED) use among people with diabetes and whether the pattern of ED use varies across geographic areas and population subgroups. Objective To estimate recent national- and state-level trends in diabetes-related ED use overall and by race and ethnicity, rural or urban location, and insurance status. Design, Setting, and Participants This cross-sectional study of adults visiting the ED with a diabetes-related diagnosis used serial data from the Nationwide Emergency Department Sample, a nationally representative database, and discharge records from 11 state emergency department databases for 2008, 2011, 2014, and 2016 to 2017. Data were analyzed from March 16 to November 9, 2020. Exposures Reported race and ethnicity, rural or urban location, and insurance status. Data were stratified to generate state-specific estimates. Main Outcomes and Measures Rates of ED use for all-cause visits among adults with diabetes (all-cause diabetes visits) and visits with primary diagnoses of diabetes-specific complications. Results A larger portion of all-cause diabetes ED visits (n = 32 433 015) were by female (56.8%) and middle-aged (mean [SD] age, 58.4 [16.3] years) adults with diabetes. Nationally, all-cause diabetes ED visits per 10 000 adults increased 55.6% (95% CI, 50.6%-60.6%), from 257.6 (95% CI, 249.9-265.3) visits in 2008 to 400.8 (95% CI, 387.6-414.0) visits in 2017. All-cause diabetes ED visits increased more for urban (58.3%; 95% CI, 52.5%-64.1%) and uninsured subgroups (75.3% [95% CI, 59.8%-90.8%]) than for their counterparts. Diabetes-specific ED visits (weighted number of 1 911 795) nationally increased slightly among all subgroups. State-specific ED use rates show wide state-to-state variations in ED use by race and ethnicity, rural or urban location, and insurance. On average across states, diabetes-specific ED use among Black patients was approximately 3 times (rate ratio, 3.09 [95% CI, 2.91-3.30]) greater than among non-Hispanic White patients, and among Hispanic patients, it was 29% greater (rate ratio, 1.29 [95% CI, 1.19-1.40]) than among non-Hispanic White patients. The mean rate of ED use among rural patients was 34% greater (rate ratio, 1.34 [95% CI, 1.26-1.44]) than among urban patients. The mean rates of ED use among patients with Medicaid (rate ratio, 6.65 [95% CI, 6.49-6.82]) and Medicare (rate ratio, 4.37 [95% CI, 4.23-4.51]) were greater than among privately insured adults. Conclusions and Relevance This study suggests that disparities in diabetes-related ED use associated with race and ethnicity, rural or urban location, and insurance status were persistent from 2008 to 2017 within and across states, as well as nationally. Further geographic and demographic-specific analyses are needed to understand the sources of inequity.

This Profile examines marriage and divorce in the years preceding and following the first year of the COVID-19 Pandemic. Using administrative data from the National Center for Health Statistics, and survey estimates from the U.S. Census Bureau and IPUMSUSA, we deconstruct state-level crude marriage and divorce rates (rates per 1,000 total population) and compute adjusted rates (rates per 1,000 women eligible for a marriage or a divorce) for the years 2010 through 2020. Then, using a demographic technique like that employed to quantify excess mortality, we estimate p-scores between the expected number of marriages and divorces for 2020 and the number observed. The expected 2020 marital events are based on the percent change in the respective observed number by state between 2018 and 2019.

The labour markets in both Canada and US experienced turmoil following the disruption caused by the COVID-19 pandemic. This paper compares recent changes in gross labour flows and worker transitions between the labour markets of the US and Canada during Covid. Exploiting the longitudinal dimension of the Current Population Survey from the US and the Labour Force Survey from Canada, I measure worker reallocation and transition probabilities in different labour force states. I find significant crosscountry heterogeneity in worker flows in and out of some labour force states such as temporary unemployment and labour force marginal attachment.

Does personal and family history influence legislative behavior in democracies? Linking members of Congress to the census, we observe countries of birth for members, their parents, and their grandparents, allowing us to measure ancestry for the politicians in office when American immigration policy changed dramatically, from closing the border in the 1920s to reshaping admittance criteria in the 1960s. We find that legislators more proximate to the immigrant experience support more permissive immigration legislation. A regression discontinuity design analyzing close elections, which addresses selection bias and holds district composition constant, confirms our results. We then explore mechanisms, finding support for in-group identity in connecting family history with policymaking. Holding fixed family history, legislators with more visible indicators of immigration based on surnames are even more supportive of permissive immigration legislation. However, a common immigrant identity can break down along narrower ethnic lines when restrictive legislation targets specific countries. Our findings illustrate the important role of personal background in legislative behavior in democratic societies even on major and controversial topics like immigration and suggest lawmakers' views are informed by experiences transmitted from previous generations.

The association between women's labor force participation, their alcohol consumption patterns, and mortality risk is unclear. This study assessed all-cause mortality risk among women in the United States, considering their labor force status and alcohol drinking. This study used discrete-time hazard models to examine this association using 2001–2015 National Health Interview Survey-Linked Mortality Files (NHIS-LMF) data (n = 147,714) for women aged 25 to 65 with 5725 deaths in this sample. Complex survey-weighted adjustments and E-values calculations were used to limit quantitative and observational biases. Alcohol consumption and labor force status together lead to substantial mortality risks. There is a statistically significant mortality risk among unemployed women (HR 2.15, 95% CI 1.18–3.91) and women not in labor force (HR 2.38, 95% CI 1.87–3.01). In the stratified models, non-Hispanic blacks (HR 1.48, 95% CI 1.30–1.67) and Asians (HR 1.93, 95% CI 1.54–2.44) have heightened mortality risks borne out of employment. Women with higher psychological distress have a 26% higher risk of all-cause mortality when not in labor force. With the help of cross-sectional data, this study demonstrates that women not in labor force and unemployed women are more likely to be affected by their drinking habits, and their employment status is associated with lower mortality risk. Further research should be focused on cause-specific mortality, gender roles and norms, reasons for unemployment, and comorbidities using more recent data, causal modeling techniques, and an extended mortality follow-up period.

Although gender and racial/ethnic equity have been primary concerns in planning, little research has examined whether the planning profession has achieved such equity in its workforce. In this stud...

Infant sex ratios that differ from the biological norm provide a measure of gender status inequality that is not susceptible to social desirability bias. Ratios may become less biased with educational expansion through reduced preference for male children. Alternatively, bias could increase with education through more access to sex-selective medical technologies. Using National Vital Statistics data on the population of live births in the United States for 1969–2018, we examine trends in infant sex ratios by parental race/ethnicity, education, and birth parity over five decades. We find son-biased infant sex ratios among Chinese and Asian Indian births that have persisted in recent years, and regressions suggest son-biased ratios among births to Filipino and Japanese mothers with less than a high school education. Infant sex ratios are more balanced at higher levels of maternal education, particularly when both parents are college educated. Results suggest greater equality of gender status with higher education in the United States.

The substantial share of births to unmarried women (FP-21-17), as well as the older median age at first marriage than at first birth (FP-21-12; FP-20-06), provide evidence of the decoupling of marriage and childbearing in recent decades. This profile uses data from the 2020 American Community Survey (ACS)* to examine the demographic characteristics of currently married and unmarried women aged 15-50 who had a birth within the past 12 months. This profile updates previous profiles using the most recent data available (FP-20-17; FP-13-10).

This paper documents the emergence of a race gap in incarceration after the abolition of slavery in the U.S. Counties that relied more on slave labor incarcerated more African Americans, with no comparable effects for whites. An increase of slave reliance by 10% increases black incarceration rates by 1.8-per-1,000. This effect is associated with an increased use of prison labor. Consistent with this, I show that arrests increase before cotton harvesting and incarceration declines after exogenous shocks that decrease the demand for labor. I find no evidence for supply-side mechanisms, according to which former slaves commit more crimes.

The traditional approach to the quantitative study of segregation is to employ indices that are selected by "desirable properties''. Here, we detail how information theory underpins entropy-based indices and demonstrate how desirable properties can be used to systematically construct models of segregation. The resulting models capture all indices which satisfy the selected properties and provide new insights, such as how the entropy index presumes a particular form of intergroup interactions and how the dissimilarity index depends on the regional composition. Additionally, our approach reveals that functions, rather than indices, tend to be necessary mathematical tools for a comprehensive quantification of segregation. We then proceed with exploratory considerations of two-group residential segregation, finding striking similarities in major U.S. cities, subtle segregation patterns that correlate with minority group diversity, and substantive reductions in segregation that may be overlooked with traditional approaches. Finally, we explore the promise of our approach for segregation forecasting.

Municipalities debating land value taxation or split-rate taxation need empirical evidence to understand how the transition of property tax regimes will affect their tax base. Using a valuable dataset on split-rate taxation from municipalities in Pennsylvania, this article empirically estimates the impacts of split-rate taxation on real estate market values and land values. The estimated impact of switching from conventional property taxation to split-rate taxation on aggregate market values is significantly positive, but the average impact from changing split-rate tax parameters during the sample period is smaller depending on the empirical specification and the sample used. In addition, the impacts vary across property types. Commercial properties appear to benefit more from split-rate taxation compared to residential and industrial uses. The Pennsylvania experience also suggests that split-rate taxes have a negative impact on land values during the sample period, but it does not appear that land values would drastically fall. The findings have important policy implications.

Over the past decade, inequality has gained increasing prominence in academic and policy circles. Importantly, one of the most significant shifts in the study of inequality is a growing appreciation of geographic inequality, specifically inequality across the 50 US states. Sparked in part by the landmark work of Raj Chetty and his colleagues, which has demonstrated that geography matters—where a child is born, or where an economically vulnerable family lands, shapes their wellbeing, and ultimately their life chances (Chetty and Hendren 2018; Chetty, Hendren, and Katz 2016; Chetty et al. 2020). Growing attention to the geographic aspects of inequality has focused greater attention on distributional inequalities within and between particular settings and jurisdictions (country, state, or local area). Social policy and policy variation are central to our understanding of these distributional inequalities.