Disparities in Black and White employment outcomes in the United States have been well- documented and persist despite decades of anti-discrimination efforts through adaptations to human resource management practices. Taking an interdisciplinary approach, this dissertation investigated the differences in employment outcomes of monoracial Black and monoracial White job individuals in the U.S. by introducing another group of comparison – their Black-White biracial counterparts. Although Black-White biracial individuals are often categorized as Black in U.S. society, this dissertation is based on the prediction that Black-White biracial individuals may have better employment outcomes than monoracial Black individuals in the workplace, referred to here as the “biracial advantage.” This advantage may be explained by a comparatively higher alignment with White culture. Using U.S. data from the National Longitudinal Survey of Youth-1997 cohort (NLSY97), Study 1 found that monoracial Black and Black-White biracial individuals receive similar, yet lower starting wages than monoracial White individuals. However, as tenure increases, the rate of growth of wages is higher for Black-White biracial employees than for the other racial groups, leading to employment outcomes more similar to White employees over time. Study 2 was an online experiment that investigated perceived White cultural alignment (PWCA) as a mechanism contributing to differences in outcomes amongst racial groups. The second study found support for the theories that (a) while race and White cultural indicators influence PWCA, information regarding one’s parents’ races does not; b) PWCA positively influences employment outcome recommendations; and c) White cultural indicators are positively related to monoracial Black and Black-White biracial candidates’ PWCA and employment outcome recommendations, but these relationships are not stronger for Black or Black-White biracial candidates than for White candidates.

Background: The co-occurrence of anaemia and stunting (CAS) presents acute development and morbidity challenges to children particularly in sub-Saharan Africa (SSA). Evidence on the effect of child feeding recommendations on CAS is scarce. Methods: We used data from 22 recent Demographic and Health Surveys in SSA countries to examine the association between caregivers’ implementation of recommendations on infant and young child feeding and the CAS in their 6- to 23-mo-old children. Results: Overall, in multiple logistic regression models, child feed index score, high wealth of household, increasing household size, household head with at least secondary school education, improved sanitation of household, an increase in caregiver’s age and caregiver’s with at least secondary education were associated with lower odds of CAS (i.e., AOR: 0.86; 95% CI; 0.84 – 0.88: 0.75; 0.69 – 0.82: 0.98, 0.98 – 0.99: 0.76, 0.70 – 0.83: 0.81, 0.74 – 0.87: 0.87, 0.81 – 0.94: 0.69, 0.62 – 0.77 respectively). Having a diarrhoea in the past 2 weeks and having fever in the past month were associated with higher odds of CAS (AOR:1.1, 95% CI; 1.0 – 1.2: 1.1, 1.0 – 1.2, respectively). Results from the decision tree analysis showed that the educational level of women was the most important predictor of CAS, followed by child feeding score, the level of education of the family head and state of drinking water. Conclusion: The results buttress the importance of interventions aimed at improving feeding practices and parental educational as a vehicle to improve children’s nutritional status.

Gender gaps in labor market activity are pervasive, longstanding, and a regular subject of policy debates. Relative to men, women tend to work fewer hours per week, more conventional hours, and fewer years over the course of their lives.2 These differences in the intensity and timing of work contribute to gender disparities in promotions and pay.3 But despite decades of research on this topic, little attention has been paid to the timing of work throughout the year. To motivate our inquiry, Figure 1 plots the monthly labor force participation rates of prime-age US women and men using non–seasonally adjusted data, with June, July, and August shaded gray. Summer after summer, women's labor force participation drops sharply while men's participation does not.

This thesis contains four independent essays studying the consequences of household heterogeneity for Macroeconomics. The first chapter studies the implications of household heterogeneity for equilibrium prices. I break with the canonical assumptions of homothetic preferences and the law of one price to show how heterogeneity in consumption baskets and search for price bargains affects posted prices. Analytical results from search theory and empirical evidence from big data on households’ grocery transactions show that price distributions respond to the composition of buyers. In a quantitative heterogeneous agent model with endogenous price dispersion for multiple varieties, I find that the response of retailers to households’ search effort is quantitatively important to differentiate between inequality in expenditure and consumption. It more than doubles the direct effect of paying more or less given posted prices, which has been the focus of previous literature. Furthermore, I find that household heterogeneity helps to account for the empirical cyclicality of retail prices and markups in response to aggregate shocks, and has implications for the response of prices to redistributive policies. In the second chapter, which is joint work with Annika Bacher and Philipp Grübener, we show how households with two members can insure themselves against the job loss of a primary earner through the labor force entry of a nonparticipating spouse. We document empirically that this margin is predominantly used by young households. In a two-member life cycle model with endogenous arrival rates, human capital accumulation, and extensive-margin labor supply, we explore how differences in labor market opportunities and asset holdings contribute to this pattern. Our findings suggest that the age difference is predom- inantly explained by better insurance through asset holdings for the old, while differences in arrival rates and human capital play a smaller role. In the third chapter, which is joint work with Caterina Mendicino and Marcel Peruffo, we study differences in the exposure to bank distress along the income distribution. We develop a two-asset heterogeneous agent model with a financial sector and use this framework to show that banking sector losses disproportionately harm low-income households while rich households adjust their savings behavior to profit from fluctuations in asset prices. This is why welfare losses from bank distress are considerably more dispersed than consumption responses. We find the model-implied consumption responses to be in line with empirical evidence on the relationship between bank equity returns and consumption across households. In the forth chapter, I study how wealth holdings can affect households’ incentives to form precise expectations about future inflation rates. I document empirically how the dispersion of expectations changes along the wealth distribution and develop a consumption-savings model with costly expectation formation to study implications for the effectiveness of forward guidance policies. I show endogenous expectation formation to significantly lower the effectiveness of forward guidance policies due to selection in which households are paying attention to news about inflation.

Evolutionary approaches in economic geography have contributed substantially to the growing body of knowledge of regional development processes and their underlying mechanisms. One key concept in the literature on evolutionary economic geography is that of related variety. Herein, regional industry structure is represented through the level of related variety of technologies, skills, or outputs. The related variety concept proposes that regional economic development is favored when an economy diversifies into products or technologies that are closely related to the stock of existing activities. In this article, we raise substantive questions regarding the internal logic of the concept of related variety, its spatial expressions, measurement specifics, empirical regularities and biases, and its possible short- and long-term effects on regional development. Based on this investigation, we make suggestions for improvements to future research.

Car access is practically a necessity to get around in rural areas of the United States. Yet approximately 4% of rural residents or 4.3 million people do not have a car. Despite important rural–nonrural differences in the built environment and how people travel, research on rural mobility disparities by car access is limited. This paper addresses this gap by asking and answering the following questions: (1) What are the scope and scale of rural car access in the U.S. and what are the factors associated with not having a car? (2) How do rural carless residents get around relative to their nonrural peers? (3) What are the consequences of not having car access in rural areas? We used a dichotomous rural–nonrural classification to evaluate differences in car access and mobility outcomes between rural and nonrural areas using the U.S. Census Bureau Public Use Microdata Sample and the National Household Travel Survey. The results reveal new evidence on socioeconomic and mobility disparities by car access within and between rural and nonrural areas. Rural carless households earn 64% less and 40% less than their counterparts with full car access and their nonrural counterparts, respectively. Rural Native Americans, Black, and Asian populations have a 2.1 times, 1.3 times, and 1.3 times the odds of being carless, respectively, than their rural white peers, after controlling for other factors. Despite their lack of access to a car, a significantly smaller proportion of rural carless residents bike, walk, or take transit for work trips than their nonrural peers (38.9% vs. 74.6%), which may indicate infeasibility of sustainable modes in some rural areas. Consequently, rural carless residents are 2 times more likely to forsake trips than their nonrural peers due to a lack of transportation options. Our findings highlight rural mobility inequities that carless people face relative to their nonrural peers, which merit attention and tailored policy interventions to improve rural mobility, sustainability, accessibility, and equity.

In this dissertation, I explore two topics related to Hispanic discrimination and identity. In chapter one, I study discrimination against Hispanics in the labor market. I compare the children of inter-ethnic marriages to study the impact of having a Hispanic last name. While males born to Hispanic father-White mothers earn less than those born to White father-Hispanic mothers, the gap could be completely explained by educational differences. I also study the effect of identifying as Hispanic on earnings. I find that men who identify as Hispanic earn significantly less than those who do not, even after controlling for educational differences. In chapter two, I study the determinants of the choice to identify as Hispanic among those who could—those whose parents, grandparents, or selves were born in a Spanishspeaking country. I find that individuals with Hispanic ancestry are significantly less likely to self-identify as Hispanic if they live in states with high levels of implicit ethnic bias. A one standard deviation increase in bias decreases self-reported Hispanic identity by 7-13 percentage points for first and second-generation Hispanics, respectively. These effects are more prominent among second-generation immigrants whose mothers and fathers were born in a Spanish-speaking country than among children of inter-ethnic parents. These findings have implications for the interpretation of economic research on racial and ethnic gaps in a variety of contexts, including labor market outcomes, redistributive policies, and political representation.

The tech industry profoundly impacts our lives and has gained great economic and political influence. Yet, we know little about the people inside tech firms, whose actions and decisions shape technological progress and its impact on society. What is of particular relevance is their opinions and beliefs about the proper order of society and the societal role of tech firms – that is to say, their political ideologies. The few existing studies on this topic mainly concentrate on tech leaders. Our study shifts attention to the workers who develop the technology. Numerous works highlight their influence on the affordances of technology and decisions taken by their firms. Our quantitative analysis of campaign contributions shows that American tech workers exhibit a unique combination of left-wing (liberal) and anti-establishment attitudes. Moreover, we expose a substantial ideological divide between tech workers and their leaders. We discuss these findings in relation to the development of new technologies, employee activism, and tech workers as a distinct class fraction.

As policy debates concerning LGBTQ+ students and staff continue across the American education system, there is not a clear description of the prevalence of local policy protections, even in states with legislative mandates, nor a strong understanding of how to expand reform initiatives. After conducting a document analysis of policies with a statewide, representative sample of districts, this study uses Illinois as a case study to describe several educational policy levers to scale gender and sexual diversity (GSD) reforms across federal, state, intermediary, and local institutions. The results indicate all districts complied with top-down legislative mandates, but few policies referenced gender or sexual diversity if not state-mandated. A minority of districts enacted policies through administrative guidance (27%), often using language from a state intermediary organization. Results from the regression analysis suggest local factors, such as district size, per pupil spending, and rurality, contribute to adopting guidance, but not policy protections. This study indicates both top-down and bottom-up pathways matter for expanding GSD-related reforms.

This dissertation explores two aspects of rental housing markets and the structure of housing in cities. The main chapter studies how multifamily rental housing is financed and how changes in financing costs affect landlords management and rental pricing. The second chapter analyzes demand for rental housing. I study the causal effects of changes in the income of low-wage earners on rent-to-income ratios, using variation coming from minimum wage increases. The first chapter of my dissertation studies how and why landlords change their behavior when their mortgage financing changes. This paper provides evidence on how much landlords raise (or change) their rental prices when they face higher (or lower) mortgage rates. I study changes in the size of their mortgage payments, and opportunities to refinance, renovate, or sell their property. I find that landlords change their behavior in each of those cases, even when we would not expect them to respond. Analyzing city-level variation in the share of multifamily apartments refinancing or selling annually, this rental financing variation is strongly correlated with average rental price growth. I conclude by discussing some implications of changing financing costs on rental housing markets, particularly for monetary policymakers. The second chapter of this dissertation studies how changes in minimum wage laws affect low-wage renters. Policymakers and advocates have expressed concern about whether landlords capture the bulk of income gains when minimum wages rise. In difference-in-differences regressions, comparing states with rising minimum wages to those without, I find that minimum wage increases lead to declining rent-to-income ratios for low-wage householders. For policymakers, this suggests that landlords do not capture all of the welfare gains for low-wage workers (e.g. from rental price increases). This result also suggests that housing demand, especially for low-wage workers is non-homothetic—an increase in income does not lead to an equal increase in spending on housing.

The closure of schools to in-person instruction during the COVID-19 pandemic posed a unique shock to parents. This paper reexamines the effect of schooling mode on parental labor supply. The effects are undetectable using a full suite of controls for unobserved heterogeneity, which can be motivated by the failure of more parsimonious models to pass simple placebo tests. Even abstracting from such controls, though, a shift from fully virtual to in-person implies an increase in hours worked of 2 to 2.5 hours per week. We present a simple model of parental time allocation and child development to formalize why these estimates appear unexpectedly small. We then introduce telework and nonparental care into the theory, demonstrate that these features can support realistic labor supply outcomes, and illustrate how our estimates in turn discipline the inference of salient structural parameters. Evidence from time use diaries indicates that telework did support both market work and childcare, chiefly among parents with college degrees. Time use data and other surveys also provide suggestive evidence of the increased utilization of nonparental care.

In the absence of a national universal paid parental leave policy, access to parental leave is stratified in the United States. While several states have implemented paid family leave policies, workers typically rely on their employers to provide such a benefit. Previous qualitative research demonstrates that the share of women in labor unions may influence the provision of family-friendly benefits. I utilize two nationally-representative datasets—the 2017-18 American Time Use Survey and the 2013-2017 American Community Survey—to analyze the relationship between union membership, occupational gender composition, and their interaction on access to paid and unpaid parental leave. Using weighted logistic regressions, I find a significant and positive interaction between union membership and the share of women in an occupation on access to both paid and unpaid parental leave. Unionized workers in female-dominated occupations are the most likely to have access to parental leave, while unionized workers in male-dominated occupations are the least likely to have access. My results indicate that unions are gendered institutions that may implicitly reinforce gendered norms of childcare and caregiving through the differential provision of parental leave benefits.

Background and objective: To date, the impact of the COVID-19 pandemic on life expectancy for the Asian American (AA) population has been reported in aggregate. This study provides estimates of life expectancy at birth before and during the pandemic, with a set of demographic, health, and socioeconomic risk factors for the four largest subgroups: Asian Indians, Chinese, Filipinos, and Vietnamese. These estimates are placed in context of the broader U.S. population. Methods: This study uses age-specific all-cause mortality from CDC WONDER and population counts from the American Community Surveys. We apply methodologies to address variability in population sizes over time (smoothing) and data quality issues at older ages (Brass relational model life table system) to produce three sets of sex-specific life expectancy estimates by subgroup for 2019, 2020, and 2021. Results: Almost all estimates show that the four AA subgroups experienced greater losses between 2019 and 2020 than Whites. These losses ranged from 1.1 to 3.9 years, with the largest drops among Chinese women (2.0–2.4) and Filipino men (3.5–3.9). Under all scenarios, losses in life expectancy were considerably smaller in 2021 than in 2020 among the four subgroups – with several subgroups experiencing a modest rebound – but these improvements did not compensate for the large increases in death rates in 2020. Filipino men had the largest decline in life expectancy from 2019 to 2021 among the four subgroups (3.4–4.2 years), and Vietnamese men and women experienced large losses which continued into the second year of the pandemic. Conclusions: Despite high pre-pandemic life expectancies, AAs suffered a large, and rarely acknowledged, increase in mortality during the pandemic, with substantial heterogeneity across subgroups and between women and men. This variability is due in part to the pronounced differences in risk factors for infection and severity which have been documented within the AA population.

In the United States, much has been learned about the determinants of longevity from survey data and aggregated tabulations. However, the lack of large-scale, individual-level administrative mortality records has proven to be a barrier to further progress. We introduce the CenSoc datasets, which link the complete-count 1940 U.S. Census to Social Security mortality records. These datasets—CenSoc-DMF (N = 4.7 million) and CenSoc-Numident (N = 7.0 million)—primarily cover deaths among individuals aged 65 and older. The size and richness of CenSoc allows investigators to make new discoveries into geographic, racial, and class-based disparities in old-age mortality in the United States. This article gives an overview of the technical steps taken to construct these datasets, validates them using external aggregate mortality data, and discusses best practices for working with these datasets. The CenSoc datasets are publicly available, enabling new avenues of research into the determinants of mortality disparities in the United States.

We develop a method suitable for detecting whether racial homophily is on the rise and also whether the economic divide (i.e., the gap between individuals with different education levels and thereby with different abilities to generate income) is growing in a society. We identify these changes with the changing aggregate marital preferences over the partners’ race and education level through their effects on the share of inter-racial couples and the share of educationally homogamous couples. These shares are shaped not only by preferences, but also by the distributions of marriageable men and women by traits. The method proposed is designed to control for changes in the trait distributions from one generation to another. By applying the method, we find the economic divide in the US to display a U-curve pattern between 1960 and 2010 followed by its slightly negative trend between 2010 and 2015. The identified trend of racial homophily suggests that the American society has become more and more permissive towards racial intermarriages since 1970. Finally, we refute the aggregate version of the status-cast exchange hypothesis based on the joint dynamics of the economic divide and the racial homophily.

Over the past 30 years, rising income inequality and income-based residential segregation have threatened to widen income-based achievement gaps. Yet, there are no national data which combine a consistent measure of parental income and achievement for individual students to measure those gaps over time. We take two alternative approaches to inferring income-based achievement gaps: First, we reconstruct the student-level relationship using school-level estimates of means and variances of achievement and income. Second, we combine estimates of mean income by race, mother's education, urbanicity and state with mean achievement for the corresponding subgroups on a national assessment. Using both methods, we find that income-based achievement gaps in 4th and 8th grade narrowed between 1992 and 2015-while math scores rose at all income levels.

Focusing on transnational entrepreneurship and immigrant businesses in new destinations, this paper studies entrepreneurship of Chinese immigrants in the U.S. using data from three surveys. In the analysis of transnational connections, we focus on the temporal dimension that links pre-migration and post-migration business activities. Results from logistic models reveal that the prospect of being self-employed among Chinese immigrants is significantly enhanced if they are from households in China with business backgrounds. This finding highlights the fact that transnational entrepreneurship is embedded in the multi-stranded connections between the immigrant sending and receiving societies. In the second part of the paper, sequence analysis is used to describe and classify business trajectories in traditional and new immigrant destinations. The results establish that while it may take a longer time for immigrants to achieve business ownership in new destinations than in traditional destinations, new immigrant destinations increase the chance of business expansion from one business to multiple businesses. These findings indicate a transition in immigrant entrepreneurs’ business models. Businesses in traditional destinations mainly follow a survival strategy, while those in new destinations are adopting models that are akin to mainstream business operations, which gives rise to more opportunities for socioeconomic mobility.

This paper analyzes the occupational status and distribution of free women in the antebellum USA. It considers both their reported and unreported (imputed) occupations, using the 1/100 microdata files from the 1860 Census of Population, the only Census that asked free women’s occupations while slavery was legal. After developing and testing the model based on economic and demographic variables used to explain whether a free woman has an occupation, analyses are conducted comparing their occupational distribution to free men, along with analyses among women by marital status, nativity, and the prevalence of slavery. This paper highlights the importance of including unreported family workers in discussions of free female labor market contributions, as their inclusion dramatically shifts the overall female labor force participation rate, as well as their occupational distribution.

The ability to move to different neighborhoods and cities is crucial in shaping people's access to better job opportunities, housing, education, and economic prospects. From a macroeconomic perspective, the mobility of workers and firms to more productive locations contributes to local and national economic growth while reducing regional inequality. Literature on neighborhood effects and economic mobility has also highlighted the significant role that a person's childhood neighborhood plays in determining their long-term economic and educational outcomes (Chetty and Hendren, 2017). Households migrate across space, voluntarily or involuntarily, in response to personal life events, changes in their physical, political, and social environment, and broader housing and labor market conditions. However, with housing supply constraints and affordability challenges faced by many large cities, households may struggle to move to or remain in neighborhoods that offer better economic opportunities. Therefore, it is essential to understand the factors and policies that influence household mobility decisions and the consequences of these moves. My dissertation includes three chapters that explore different aspects of migration and residential mobility, and their interplay with housing policy and the housing market. These papers examine the factors and policies influencing migration decisions, the destinations households choose, and the potential implications for spatial inequality. The first chapter examines the effect of relaxing land-use regulations on the local housing market and households’ migration patterns. In response to housing affordability challenges, some local governments adopt land-use reforms to increase residential development capacity within the city. These “upzoning” policies aim to increase housing supply and lower local housing costs, but they can also generate positive amenity effects that attract high-income households to the neighborhood. This paper studies how large-scale neighborhood upzoning in New York City between 2004 and 2013 affected local housing supply, prices, and residential mobility patterns using a difference-in-difference method. To analyze this, I construct a parcel-level dataset by combining zoning amendment maps with microdata tracking individual address histories. By using a difference-in-difference method and comparing upzoned areas and the adjacent areas outside the upzoned boundaries, I find that housing supply increases after upzoning. There is suggestive evidence that existing properties on parcels with a greater increase in residential capacity experience increases in housing prices, whereas properties on parcels that are not effectively upzoned do not show the same trend. This difference could be attributed to different changes in option values of redevelopment after upzoning. Furthermore, incumbent residents in upzoned areas are more likely to move to a different neighborhood or leave the metropolitan area, but there is no evidence of a higher likelihood of moving to lower-income areas. Lastly, the study indicates that in-migrants, following upzoning, originate from slightly higher-income neighborhoods. These results suggest that in this context, upzoning can both increase housing supply and change the composition of local residents in the neighborhood. The second chapter, co-authored with Sewin Chan and Katherine O’Regan, uses the American Community Survey to study the extent to which young adults (YAs) aged 24-29 return to their parents’ home (“boomerang”). We find that the share of YA moves that are boomerangs is higher among more disadvantaged groups in terms of race/ethnicity, education, recent marital dissolution, and employment disruption. Differences by marital status and presence of children vary by sex and by whether moves cross metropolitan areas. Importantly, within-metro boomerang moves are more likely in metros with weaker labor markets and cross-metro boomerang moves disproportionately land in higher unemployment and lower earnings metros than their origin. To shed light on where YAs could land if they boomeranged, we create a synthetic cohort of YAs who would have been 17 and living with parents in 2006-2012, and we examine the quality of these parental locations in 2018-2019. The patterns suggest that Black and Hispanic YAs, and those from lower socioeconomic status families, face weaker labor markets and opportunities when boomeranging. To the extent that these are not offset by parental supports, combined with higher boomerang propensities among the disadvantaged, our results suggest another channel through which racial and socioeconomic disparities are perpetuated. The third chapter examines another factor that could influence people's migration behavior and housing outcomes: adverse health events. Adverse health events not only affect individuals' physical activity and labor productivity but also have persistent effects on various aspects of their lives. Using the Panel Study of Income Dynamics (PSID) and event study models with individual fixed effects, I investigate how the initial diagnosis of chronic diseases is associated with housing stability and homeownership transitions. The findings reveal that female renters are more likely to move after the onset of chronic disease, and they are also more likely to live in overcrowded housing. In terms of housing tenure, male homeowners are more likely to transition out of homeownership following a chronic disease diagnosis, and male renters are also significantly less likely to transition into homeownership after developing a chronic illness. These findings highlight the importance of assisting individuals in preventing chronic diseases or accessing healthcare and housing services when they experience adverse health events, as it can be crucial in mitigating the long-term negative consequences on housing outcomes.

The Centers for Disease Control and Prevention recommends that individuals aged 13–64 test for HIV at least once during their lifetime. However, screening has been disproportionate among racial/ethnic populations. Using the National Health Interview Survey data (2006–2018), we examined HIV screening prevalence within racial/ethnic groups in the United States (US), and factors associated with testing among 301,191 individuals. This consisted of 195,696 White, 42,409 Black, 47,705 Hispanic and 15,381 Asian individuals. Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) to estimate the association between ever testing for HIV and demographic, socioeconomic and health-related factors. Approximately 36% of White, 61% of Black, 47% of Hispanic and 36% of Asian individuals reported ever testing for HIV. Hispanic (OR = 1.28, 95% CI [1.25–1.32]) and Black individuals (OR = 2.44, 95% CI [2.38–2.50]) had higher odds of HIV testing, whereas Asian individuals (OR = 0.74, 95% CI [0.71–0.77]) had lower odds of HIV testing compared to White individuals. Individuals who identified as males, married, between the ages of 18–26 years or greater than or equal to 50 years were less likely to ever test for HIV compared to their counterparts. Similarly, those with lower education, lower income, better self-reported health, no health professional visits or living in the midwestern US were less likely to ever test for HIV compared to their counterparts (OR range: 0.14–0.92). Understanding the factors associated with HIV testing opens opportunities to increase testing rates for all and reduce health disparities in HIV detection.