For low-and middle-income households, homeownership is a pathway to building wealth and ensures stable and secure housing. People with disabilities, low-income households, and Black families all experience a substantially lower rate of homeownership than others. A large body of literature examines the historical and policy context for these outcomes for each of these populations. Of note, each of these groups is substantially overrepresented among those receiving Supplemental Security Income, or SSI. SSI is a means-tested federal program, with varying levels of additional state support, that provides monthly income to those who are blind or disabled. Recipients may not own assets totaling more than $2,000 (or $3,000 per married couple). While homes are excluded from this assessment, the strict cap on savings generally means that SSI recipients who do not already own a home when they begin to receive benefits cannot accrue enough savings to qualify for a mortgage. There is a gap in the literature on homeownership patterns in that it does not examine the role of receiving SSI or SSI policy. Using data from the 2019 American Community Survey, this analysis explores the relative importance of receiving SSI in influencing homeownership among these populations by using logistic regression to examine the impact of each of these characteristics-having a disability, receiving SSI income, being low-income, or being Black-on the odds of homeownership, controlling for other demographic measures. In addition, I present marginal effects to identify the average predicted probabilities of homeownership for these populations to demonstrate the extent to which SSI asset limits impact each of these groups differently and further discuss how this may be a contributing factor to the racial wealth gap.

This study examines the sociodemographic and occupational characteristics of nativeborn U.S. citizens, naturalized U.S. citizens, and noncitizens in the Washington statehealth care labor force using data from the 2018 American Community Survey.

I document a new empirical pattern of internal mobility in the United States. Namely, county-to-county migration and commuting drop off discretely at state borders. People are three times as likely to move to a county 15 miles away, but in the same state, than to move to an equally distant county in a different state. These gaps remain even among neighboring counties or counties in the same commuting zone. This pattern is not explained by differences in county characteristics, is not driven by any particular demographic group, and is not explained by pecuniary costs such as differences in state occupational licensing, taxes, or transfer program generosity. However, county-to-county social connectedness (as measured by the number of Facebook linkages) follows a similar pattern. Although the patterns in social networks would be consistent with information frictions, nonpecuniary psychic costs, or behavioral biases such as a sate identity or home bias, the data suggest that state identity and home bias play an outsized role. This empirical pattern has real economic impacts. Building on existing methods, I show that employment in border counties adjusts more slowly after local economic shocks relative to interior counties. These counties also exhibit less in-migration and in-commuting, suggesting the lack of mobility leads to slower labor market adjustment.

This dissertation explores several issues on labor market from the macro perspective. Chapter 2 develops an extended version of Diamond-Mortensen-Pissarides model to understand the sources of disparities existed in U.S. labor market. Chapter 3 studies the evolution of labor market fundamentals in the last 4 decades and how they have impacted the GDP growth and divergence/convergence of gender/racial gaps. Chapter 4 focuses on the bargaining power of U.S. workers and builds a theoretical framework to explain the recent declining trend of U.S. labor compensation share. Chapter 5 concludes.

Using a compiled dataset of 441 censuses and surveys between 1787 and 2015, representing 103 countries and 48.4 million mothers, we find that: (1) the effect of fertility on labor supply is typically indistinguishable from zero at low levels of development and large and negative at higher levels of development; (2) the negative gradient is stable across historical and contemporary data; and (3) the results are robust to identification strategies, model specification, and data construction and scaling. Our results are consistent with changes in the sectoral and occupational structure of female jobs and a standard labor-leisure model.

Immigration to a host culture often involves significant changes in parenting norms and behaviors. The authors take an acculturation lens to explore parental involvement among different generations of Latin American immigrant families. It compares the quantity and type of parental involvement of first- and second-generation Latin American immigrants to that of parents who are at least a third generation in the United States while examining whether differences exist between mothers and fathers. Data from the 2003–2013 American Time Use Survey are used for our analyses, which finds differences between parenting behaviors of first-generation immigrants from Latin America and third-generation parents. Second-generation mothers were also found to be significantly different from third-generation mothers in almost every type of parental involvement, while second-generation Latin American fathers were similar to third-generation fathers in quantity and type of parental involvement.

America's worst drought induced mass migration from the Great Plains during the 1930s. But, outside of qualitative research, little is known about how drought migrants fared at their destinations. I study drought-migrant employment status and wage income compared to non-migrants and to non-drought migrants. I find that migrants with little formal education were less likely to be employed and made less than non-migrants from their origin counties. Migrants with more education did better both in employment and wage income compared to less-educated migrants. There was little difference in outcomes between migrants from drought versus non-drought origins. My results contribute to our understanding of labor market opportunities for climate migrants across the skill distribution and how climate-induced migrants compare to other migrants.

This dissertation contains three chapters. The first chapter evaluates the effect of a gun control act in California. State legislators in the U.S. are striving to curb gun violence. A common approach is to extend the existing firearms ban list. This paper examines the effect of legislation restricting sales of selected firearms in California using the synthetic control method. This case study method forms a synthetic unit using a linear combination of other states in the U.S. as the control group. The results show substantial increases in firearm sales in California from the point of passage until the law becomes effective. After the surge ends when the law becomes effective, the sale of firearms is only moderately affected thereafter. This paper also creates robustness checks to confirm that the synthetic control method is working properly with low firearm density in California, which calls into question some of the assumptions underlying the synthetic control method. The Differencein-Difference regression reaches the same conclusion. The second chapter focuses on immigrant assimilation in the U.S. Assimilation is the process in which immigrants improve earnings as they become more adapted to the host country society. Cross-sectional studies show that immigrants have lower earnings upon arrival and faster earnings growth compared to natives. Longitudinal studies conclude that estimates based on cross-sectional data are positively biased due to decreasing cohort quality and negatively selected outmigration. I reproduce such estimates with recent U.S. data. The estimates wouldx appear to show “bias,” as inclusion of cohort fixed effects alter estimates. However, in contrast to expectations based on the current literature, decreasing cohort quality and outmigration do not explain the difference. Next, I apply a non-parametric method to make the wage distributions visually comparable across cohorts and time. I find that the linear specification of assimilation is misleading. Finally, I revisit the classic model with a quadratic assimilation term and expand it to explore the assimilation process’s heterogeneity. I find that the “bias” disappears with a quadratic assimilation effect. The assimilation effect is sensitive to age at arrival and country of origin. The third chapter considers an unexplained puzzle in one of the most widely used public datasets in the U.S. The American Community Survey (ACS) replaced the Decennial Census as the primary data source for identifying immigrants’ socioeconomic characteristics. This paper focuses on cohort analysis, in which a cohort combines immigrants arriving in a given year from surveys in multiple years. Tracking the sizes of cohorts from 2006 to 2019 using the ACS, we observe an abnormal increase in cohort size in the 10th and 20th years since arrival. Two hypotheses are tested, population estimate structural break andthe renewal of green card. Neither appears to explain the puzzle.

I document new and robust empirical evidence of earnings differences between teachers and non-teachers. First, I employ three complementary approaches that were not considered previously to alleviate pay differentials related to individual or job characteristics. These three approaches provide unifying estimates that turn an earnings penalty between female teachers and non-teachers of around 10%, based on a standard approach in the literature, into an earnings premium on the order of 5% to 10%. Likewise, estimates based on these approaches erase up to two-thirds of the earnings gap between male teachers and non-teachers. Second, going beyond the traditional focus on the mean, I decompose the pay gap across the entire earnings distribution. Estimates show that while teachers have a substantial earnings premium at the bottom of the distribution, they also have a large earnings penalty at the top.

This paper investigates the effect of discrimination on volunteer military enlistment rates, which we interpret as a component of state capacity. We use weekly enlistment data to document that WWII African American enlistment rates immediately after the Pearl Harbor attack were negatively associated with the intensity of racial discrimination across U.S. counties. White enlistment rates were unassociated with discrimination. These patterns are robust to controlling for a large number of fixed effects and race-county-time-specific controls. The data show similar negative relationships between the degree of discrimination and enlistment rates for Japanese Americans. The empirical findings are evidence that discrimination reduced state capacity.

This research examined social media’s role in understanding perceptions about the spaces in which individuals interact, what planners can learn from social media data, and how to use social media to inform urban regeneration efforts. Using Twitter data from 2010 to 2018 recorded in one U.S. shrinking city, Detroit, Michigan, this paper longitudinally investigated topics that people discuss, their emotions, and neighborhood conditions associated with these topics and sentiments. Findings demonstrate that neighborhood demographics, socioeconomic, and built environment conditions impact people’s sentiments.

We document the dynamics of labor—changes in employment and hours worked—and of actual telework use during the pandemic. We find that employment losses are unrelated to telework use starting in 2020-Q4. This is in stark contrast with the onset of the pandemic that disproportionately affected skills, occupations and industries with low telework use. Our findings are the results of two phenomena. First, labor is dynamically heterogeneous: employment of skill and occupation groups that are most affected by the initial Covid19 shock recover quickly, catching up with the rest of the economy by October 2020. Second, the use of telework has homogeneously declined within skills, occupations and industries—by 40 percent on average—leaving the relative ranking of telework use across groups unaltered. Finally, there is substantial and persistent cross-industry heterogeneity in labor market outcomes one year into the pandemic that is unrelated to the use of telework.

Understanding trends in assortative mating is essential to understanding how inequality may change over time. Little research has been done on trends in assortative mating in the early 20th century, especially during a period known as the "high school movement" which saw a rapid increase in the availability of secondary education and a decline in economic inequality. I use the Seperable Extreme Value Index developed by Chiappori et al. (2020) to determine changes in assortative mating and perform a counterfactual analysis. I find that positive assortative mating decreased among high school-educated people between the 1880-89 and 1890-99 birth cohorts. This is consistent with a counterfactual simulation which suggests that the value of positive assortative mating also decreased. I use the general openness, saturation, and status-attainment hypotheses to rationalize the trends in assortative mating over the entire 20th century.

This paper uses data from the Survey of Income and Program Participation to investigate how intra-year caregiver work-hours volatility is related to child poverty, measured through both the official poverty measure (OPM) and the supplemental poverty measure (SPM). I further assess varying degrees of buffering effects of cash benefits, in-kind benefits, and tax transfers on income in the context of work-hours volatility. Results indicate that Black and Hispanic children, as well as those living with unpartnered single mothers, faced substantially higher variability in household market hours worked. Hispanic children experienced not only greater volatility in their caregivers’ work hours, but also higher poverty levels, even after taking government programs into account. I find that a 10 percent increase in intra-year hours volatility is linked to roughly a 2 percent and 1.6 percent increase in OPM and SPM child poverty, respectively. Inkind benefits are more effective in buffering household income declines resulting from unstable caregiver work hours, followed by tax transfers and cash benefits, which each offer somewhat less of a buffering effect. The effectiveness of near-cash benefits is particularly salient among Black children and children of unpartnered single mothers. Hispanic children also benefited from these transfers’ compensating effects, but to a lesser degree. These results provide new evidence to inform public policy discussions surrounding the best ways to help socioeconomically disadvantaged families to retain benefits and smooth their income in the face of frequent variation in work hours and, thus, earnings.

In California, removing cars from the road by expanding transit ridership is lauded as a large part of climate change action. Buses and trains are the most efficient ways to move people and are a necessary element for mitigating traffic congestion. In addition, because the transit-dependent are overwhelmingly low-income, communities of color, a safe, reliable public transportation system is a social justice issue. In Los Angeles County, bus ridership was already declining before COVID-19. This research hopes to fill the gap on what ridership was lost due to the pandemic and how that loss varies spatially. Using station/stop-level Los Angeles County Metro bus ridership data aggregated into census block groups as the dependent variable, a Spatial Lag Regression and a Getis-Ord were performed. Built environment as well as demographic data was used to evaluate ridership between 2019 and 2020, considered pre and during pandemic. The results indicate that, in addition to land use diversity, percentage of persons of color, median household income, and median age, COVID-19 had a huge impact on Metro bus ridership. While most recent public transit expansion has focused on rail, bus and bus rapid transit would be a better avenue for creating an equitable transportation system for the riders that abandoned busses in much smaller numbers than their higher income, whiter counterparts. In the hot spot areas of Gateway Cities, Southbay, and Westside Central that generates 34.38% of ridership, the level of service was only 27.95% of total service studied. Boosting service to match ridership in those areas would serve Los Angeles County’s most loyal and/or captive riders of public transportation. As the residents of these hot spots also match the profile of the essential worker, serving these residents would help to make Los Angeles more resilient in the next public health emergency.

The COVID-19 pandemic that began in the United States in March of 2020 had a profound adverse effect on the economy. In particular, the pandemic had a harsh impact on women, minorities, and self-employed individuals. However, research on why the pandemic hit some groups harder is in its nascent stages. We contribute to the growing body of knowledge by comparatively analyzing the inability to work due to the pandemic in the wage and self-employment sectors. We utilize data from the Current Population Survey from May 2020 to May 2021 to investigate the effect of individual, business, and geographic characteristics on the probability of work interruption in each sector. We find that self-employers were much harder hit but fared better than wage workers in several of the harder-hit sectors and when they had incorporated businesses. We also find that women, non-Whites, and Hispanics were more adversely affected in both sectors.

Objective: This study examines parents' time use in developmental child care by parental education and assesses whether the educational gap has widened or narrowed over the period of 2003–2017. Background: The diverging trends in work hours between mothers with different levels of education since the early 2000s, along with the proliferation of the ideal of intensive parenting, suggest that education disparities in developmental child care time have likely converged, opposite to the widening trend before then. Method: Using the 2003–2017 American Time Use Survey (N = 30,072), ordinary least squares regression models estimate minutes per day mothers and fathers with children under age 5 spend on developmental child care, after accounting for demographic characteristics, family income, and hours at work. The interaction terms between parental education and years estimate the trend in the educational gap. Results: The educational disparity in developmental child care has narrowed between 2003 and 2017 due to opposite trends at both ends of the educational spectrum: whereas time spent among parents with a bachelor's degree or higher has stalled, time spent among counterparts with high school or less education has continuously increased. For mothers, the converging trend is partly attributable to differential trends in hours at work by education. Conclusion: In contrast to the claim of diverging destinies, parents' time use in developmental child care is likely not contributing to diverging resources for children between more- and less-educated parents.

Background Older age is a risk factor for tuberculosis (TB) in low incidence settings. Using data from the US National TB Surveillance System and American Community Survey, we estimated trends and racial/ethnic differences in TB incidence among US-born cohorts aged ≥50 years. Methods In total, 42 000 TB cases among US-born persons ≥50 years were reported during 2001–2019. We used generalized additive regression models to decompose the effects of birth cohort and age on TB incidence rates, stratified by sex and race/ethnicity. Using genotype-based estimates of recent transmission (available 2011–2019), we implemented additional models to decompose incidence trends by estimated recent versus remote infection. Results Estimated incidence rates declined with age, for the overall cohort and most sex and race/ethnicity strata. Average annual percentage declines flattened for older individuals, from 8.80% (95% confidence interval [CI] 8.34–9.23) in 51-year-olds to 4.51% (95% CI 3.87–5.14) in 90-year-olds. Controlling for age, incidence rates were lower for more recent birth cohorts, dropping 8.79% (95% CI 6.13–11.26) on average between successive cohort years. Incidence rates were substantially higher for racial/ethnic minorities, and these inequalities persisted across all birth cohorts. Rates from recent infection declined at approximately 10% per year as individuals aged. Rates from remote infection declined more slowly with age, and this annual percentage decline approached zero for the oldest individuals. Conclusions TB rates were highest for racial/ethnic minorities and for the earliest birth cohorts and declined with age. For the oldest individuals, annual percentage declines were low, and most cases were attributed to remote infection.

Ever since the eighteenth century, experts have tried to tell farmers how to farm. The agricultural enlightenment in Europe marked the beginning of a long arc of new experts aiming to change agricultural knowledge and practice. This dissertation analyzes the pivotal period in the late nineteenth and early twentieth century in Germany and the United States when scientists, improvers, and market agents began to develop comprehensive ways to communicate agricultural innovation to farmers. In a functional approach to analyzing the negotiation of agricultural knowledge through its communication in things, words, and practices, this dissertation argues that the process of change in German and American farming in response to globalizing markets for agricultural commodities included a multi-tiered process of conflict and knowledge negotiation between a variety of actors. Scientists, improvers, market agents, farmers, and others all shaped the future of farming as part of an agrarian-industrial knowledge society. While the path of each innovation to each farm was historically and geographically contingent, actors shared perspectives, strategies, and evidence to establish their own expertise, form expert communities, and reach their own goals. The agrarian-industrial knowledge society brought their patchwork of expertise into agreement, but also excluded those farmers as “backward” who were unwilling or unable to use capital-intensive innovation and extracted nutrients and labor from soils and nonwhite people of the American South and European and American colonies around the world. This dissertation advances this argument through an entangled and comparative history of livestock feeding in the United States and Germany. To integrate the perspectives of actor groups and to bring their negotiations into sharper relief, this study analyses interconnections and comparisons between two case study areas in challenging agricultural conditions where innovation for ideal farming conditions required more significant adaptation: western Maine in New England and the Sauerland in Westphalia. The analysis combines print and manuscript sources by all actor groups with Geographic Information Systems (GIS) mapping and spatial and statistical analysis of cadastral and census data in microhistorical case studies situated in Serkenrode, Westphalia, and South Paris, Maine. This approach argues for an integrated, global history of agricultural knowledge.

We question the growing consensus in the literature that European Americans behave as a homogenous pan-ethnic coalition of voters. Seemingly below the radar of scholarship on voting groups in American politics, we identify a group of white voters that behaves differently We question the growing consensus in the literature that European Americans behave as a homogenous pan- ethnic coalition of voters. Seemingly below the radar of scholarship on voting groups in American politics, we identify a group of white voters that behaves differently from others: German Americans, the largest ethnic group, regionally concentrated in the ‘Swinging Midwest’. Using county level voting returns, ancestry group information from the American Community Survey (ACS), current survey data and historical census data going back as early as 1910, we provide evidence for a partisan and a non-partisan pathway that motivated German Americans to vote for Trump in 2016: a historically grown association with the Republican Party and an acquired taste for isolationist attitudes that mobilizes non-partisan German Americans to support isolationist candidates. Our findings indicate that European American experiences of migration and integration still echo into the political arena today.