Focusing on LA, we show that 1) socioeconomic inequality in LA has increasingly emerged since the 1970s along two axes, Black-Latino and White-Asian, and that 2) the structure of residential segregation in LA intersects immigration dynamics to create unique patterns of isolation within groups and exposure between groups, setting distinctive conditions for interaction and identity formation. Two case studies — South LA and the San Gabriel Valley (SGV) — shed light on the mechanics of spatialization amid hyperdiversity. In South LA, Latino immigrants live alongside Black residents. Shared experiences of racism and socioeconomic deprivation widen BlackBrown linked fate to create novel platforms for place-based identity formation and political resistance. In SGV, Chinese immigrants of diverse class and ethnic backgrounds carve out a different path to residential assimilation by building an American ethnoburb without much contact with Whites. Despite clear inequalities across the Black-Latino and White-Asian axes, neither case converges uniformly towards Whiteness.

This paper examines how immigration affects native children’s economic opportunities leveraging linked U.S. censuses in the early twentieth century. Using the shift-share instrument for county-level immigration exposure, I find that childhood exposure to immigrants enhances native-borns’ adulthood economic performance. However, children of high-skilled fathers enjoy a higher positive impact than their peers, given the same exposure level. I investigate two potential channels and show that immigration-induced into-city migration explains only around 10% of the exposure effect. In addition, immigration encourages native children to advance on the occupational ladder and to specialize in less immigrant-intensive jobs.

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15–50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5–15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

Objectives. To assess the relationship between poverty, delayed care, unaffordable care, and functional limitations among individuals with chronic obstructive pulmonary disease (COPD). Methods. Using the National Health Interview Survey data, we selected respondents with COPD, aged 40 years and older. The predictor variables were poverty and measures of delayed and unaffordable care. The outcome variable was functional limitations. We performed a survey-weighted multivariate logistic regression analysis, adjusting for sociodemographic characteristics. Results. Respondents classified as poor had three times the odds of functional limitations compared with those classified as not poor. Respondents who reported having measures of delayed care or unaffordable care had two to nine times and two to four times the adjusted odds of functional limitations compared with those who did not report such measures of delayed and unaffordable care, respectively. Conclusions. Poverty and delayed and unaffordable care are associated with functional limitations among individuals with COPD.

The main objective of this thesis is to investigate the potential sources of the gender wage gap in Germany and the United States. For that purpose, we employ high quality microdata sets in Germany and the United States. For that purpose, we employ high quality microdata sets from the German Socio-Economic panel (SOEP) and IPUMS CPS. We use cross-sectional from the German Socio-Economic panel (SOEP) and IPUMS CPS. We use cross-sectional data for the years 1989 and 2019 to study a representative sample of full-time employees data for the years 1989 and 2019 to study a representative sample of full-time employees between the age of 25 to 64. By employing the Kitagawa-Oaxaca-Blinder (KOB) between the age of 25 to 64. By employing the Kitagawa-Oaxaca-Blinder (KOB) decomposition method (Kitagawa 1955; Oaxaca 1973; Blinder 1973) we estimate how much decomposition method (Kitagawa 1955; Oaxaca 1973; Blinder 1973) we estimate how much of the unadjusted gender wage gap in the countries is attributed gender differences in measured of the unadjusted gender wage gap in the countries is attributed gender differences in measured characteristics. Furthermore, by applying a Juhn, Murphy, and Pierce (JMP) (1991) characteristics. Furthermore, by applying a Juhn, Murphy, and Pierce (JMP) (1991) decomposition we investigate how relative improvements in terms of characteristics and rising decomposition we investigate how relative improvements in terms of characteristics and rising return to these characteristics affects the gender wage gap over time. The aim is to understand return to these characteristics affects the gender wage gap over time. The aim is to understand if increasing overall inequality counterbalances women's progress in the labour market and if increasing overall inequality counterbalances women’s progress in the labour market and has a widening effect on the gender wage gap. Lastly, Blau and Kahn (1996) find that countries has a widening effect on the gender wage gap. Lastly, Blau and Kahn (1996) find that countries with more compressed wage distributions have smaller gender wage gaps. We investigate this with more compressed wage distributions have smaller gender wage gaps. We investigate this by a JMP decomposition of the U.S.-German difference in the gender wage gap to understand by a JMP decomposition of the U.S.-German difference in the gender wage gap to understand if differences in return to characteristics is the most important contributor to international if differences in return to characteristics is the most important contributor to international differences in the gender wage gap. differences in the gender wage gap. The results show that the gender wage gap declines in Germany and the United States between The results show that the gender wage gap declines in Germany and the United States between 1989 and 2019. The results from the KOB decomposition show that gender differences in 1989 and 2019. The results from the KOB decomposition show that gender differences in observable characteristics in total no longer explain the gender wage gap for these countries observable characteristics in total no longer explain the gender wage gap for these countries in 2019. Gender differences in distribution by industry however continues to explain male- in 2019. Gender differences in distribution by industry however continues to explain male- female wage disparities over the period studied. The JMP results show that changes in the female wage disparities over the period studied. The JMP results show that changes in the return to characteristics negates some of the progress made by female workers over the period. return to characteristics negates some of the progress made by female workers over the period. Lastly, the most important factor for explaining the U.S- German difference in the gender Lastly, the most important factor for explaining the U.S- German difference in the gender wage gap is the relative differences in return to characteristics. This effect was however wage gap is the relative differences in return to characteristics. This effect was however stronger in 1989 and reflects that the wage distribution in Germany have become more stronger in 1989 and reflects that the wage distribution in Germany have become more dispersed over the period of study and is thus more similar to that observed in the United dispersed over the period of study and is thus more similar to that observed in the United States.

The purpose of this descriptive study was to explore factors associated with perceptions of grandparent responsibility for grandchildren in three-generation households, focusing especially on a comparison of grandparents’ and parents’ financial contributions to the household and ethnicity of grandparent(s). The analysis used information about three-generation families in the 2011–2015 American Community Survey, retrieved through the Integrated Public Use Microdata Series. In 30% of these families, grandparents said they were “primarily responsible” for the grandchildren, even though the child’s parent was also in the household. Logistic regression models showed that grandparents who contributed a larger share of household income and grandparents who were householders were significantly more likely to report being primarily responsible for grandchildren in three-generation households, suggesting that the distribution of financial resources (or resource balance) within the household was associated with perceptions of responsibility. However, grandparents’ race and ethnicity moderated this association, indicating that cultural norms may intersect with resources in shaping these reports. The findings suggest that perceived responsibilities of grandparents in three-generation households may be shaped by the balance of financial resources among household members, but also by cultural norms of grandparenting.

Changes in U.S. migration trends during the COVID-19 pandemic show that many moved to less populated cities from larger cities, deviating from previous trends. In this study, building on prior work in the literature showing that the abundance of family ties are inversely related to population size, we analyze these migration changes with a focus on the crucial, yet overlooked factor of extended family. Employing two large-scale data sets, census microdata and mobile phone GPS relocation data, we show a collection of empirical results that paint a picture of migration change affected by family. Namely, we establish that people migrated closer to family at higher rates after the COVID-19 pandemic started. Moreover, even controlling for factors such as population density and costs of living, we find that changes in net in-migration tended to be larger and positive in cities with larger proportions of people who can be parents to adult children, our proxy for parental family availability. Our study suggests an underexplored explanation for internal migration patterns during a crisis and advances the demography-disaster nexus.

Historians have taken as a defining characteristic of Chinese experience in the United States their inability to naturalize until the repeal of Chinese Exclusion in 1943. It is certainly true that treaty agreements, court rulings, and discrimina-tory legislation conspired to prevent the existence of Chinese American citizens. But scholars may have taken for granted Chinese migrants’ alien status and disen-franchisement more than they themselves did. In 1900, the US census recorded that 6.7 percent of the Chinese population had naturalized. These naturalized Chinese accomplished a seemingly impossible task and in so doing they exposed broader truths about the uncertain nature of citizenship in the postbellum era.

Entity resolution (ER) is the process of linking records that refer to the same entity. Traditionally, this process compares attribute values of records to calculate similarities and then classifies pairs of records as referring to the same entity or not based on these similarities. Recently developed graph-based ER approaches combine relationships between records with attribute similarities to improve linkage quality. Most of these approaches only consider databases containing basic entities that have static attribute values and static relationships, such as publications in bibliographic databases. In contrast, temporal record linkage addresses the problem where attribute values of entities can change over time. However, neither existing graph-based ER nor temporal record linkage can achieve high linkage quality on databases with complex entities, where an entity (such as a person) can change its attribute values over time while having different relationships with other entities at different points in time. In this paper we propose an unsupervised graph-based ER framework that is aimed at linking records of complex entities. Our framework provides five key contributions. First, we propagate positive evidence encountered when linking records to use in subsequent links by propagating attribute values that have changed. Second, we employ negative evidence by applying temporal and link constraints to restrict which candidate record pairs to consider for linking. Third, we leverage the ambiguity of attribute values to disambiguate similar records that however belong to different entities. Fourth, we adaptively exploit the structure of relationships to link records that have different relationships. Fifth, using graph measures we refine matched clusters of records by removing likely wrong links between records. We conduct extensive experiments on seven real-world data sets from different domains showing that on average our unsupervised graph-based ER framework can improve precision by up-to 25% and recall by up-to 29% compared to several state-of-the-art ER techniques.

Geographically aggregated data are often considered to be safe because information can be published by group as population counts rather than by individual. Identifiable information about individuals can still be disclosed when using such data, however. Conventional methods for protecting privacy, such as data swapping, often lack transparency because they do not quantify the reduction in disclosure risk. Recent methods, such as those based on differential privacy, could significantly compromise data utility by introducing excessive error. We develop a methodological framework to address the issues of privacy protection for geographically aggregated data while preserving data utility. In this framework, individuals at high risk of disclosure are moved to other locations to protect their privacy. Two spatial optimization models are developed to optimize these moves by maximizing privacy protection while maintaining data utility. The first model relocates all at-risk individuals while minimizing the error (hence maximizing the utility). The second model assumes a budget that specifies the maximum error to be introduced and maximizes the number of at-risk individuals being relocated within the error budget. Computational experiments performed on a synthetic population data set of two counties of Ohio indicate that the proposed models are effective and efficient in balancing data utility and privacy protection for real-world applications.

This dissertation consists of three papers at the intersection of social policy and immigration. The first paper analyzes the impact of immigrant welfare exclusion on government social spending at both an aggregate and specific social program level, using cross-national social expenditure panel data from 21 Organization for Economic Co-operation and Development (OECD) countries between 1990 and 2015, and taking advantage of the significant variation in welfare exclusivity across OECD countries by year. The second paper utilizes the variation in states’ response to the Affordable Care Act’s Medicaid expansion to investigate its effects on lowincome immigrants’ inter-state mobility, specifically in-migration and out-migration. Finally, the third paper utilizes data from the National Survey of Children’s Health to examine the effect of the announcement of the Trump administration’s revised Public Charge rule on insurance coverage and other health outcomes for children of immigrant parents.

In the United States, the labor market participation rate of older workers aged 50 and above has increased, and one-third of the labor force is made up of older workers in 2020. The trend of lifetime employment with one firm has been displaced by contingent employment in the current flexible labor market. Consequently, many older workers experience frequent employment transitions until they exit the labor market completely. However, the dynamics of labor market participation among older workers, especially those experiencing repetitive unemployment and employment in older age, are not well understood. This dissertation aimed to investigate trends in employment transitions among older workers, with a focus on job search activity, job availability in the community market, and employment support program participation in a state. In Chapter 1, the historical and theoretical evolution of aging populations was discussed, with three specific periods defined in this study: the initial introduction of welfare provisions, the looming individual safety net collapse, and visualized risks and retirement insecurity. Chapter 2 utilized latent class analysis, which identified five latent classes in the patterns of job search activities among older workers from the Health and Retirement Study. Multinomial regression analysis revealed that the patterns of job search activities are significantly associated with different types of employment outcomes, in addition to individual and employment characteristics. Chapter 3 examined job availability in the local market using two datasets, including the O*NET database and the American Community Survey. The findings showed low rates of matching between job vacancies and older workers, with higher concentrations in three occupational groups among older workers despite a wide range of available occupations. Chapter 4 demonstrated that workforce development programs under the Workforce Innovation and Opportunity Act improved the employability of older female participants but not for other disadvantaged participants who were older in age or non-white individuals. This study found that commonly chosen training programs aligned well with common occupations of the older workforce throughout the state. Finally, Chapter 5 provides implications of the three studies in this dissertation and discusses future directions to improve employment transitions among older workers in the United States.

Policies supporting families with young children provide an important context for human development. The two primary public policies available to caregivers around and after childbirth are parental leave and early care and education (ECE). A substantial body of research evaluates the effects of parental leave and ECE policies on various outcomes, but most existing studies focus on average treatment effects in the population. We know much less about how policy effects vary by family demographics or by child care program characteristics. The three studies in this dissertation aim to increase our understanding about the circumstances under which child and family policies are more or less effective in supporting families with young children. Study 1 documents maternal wage dynamics around childbirth and their heterogeneity by education using German administrative data. Women with low education experience a smaller drop and a faster recovery of their wages than women with higher levels of education. These differences are largely explained by the fact that women with low education have their first child at a younger age. To investigate whether public policies can influence these wage dynamics, I exploit a paid family leave policy change in 2007 to set up a differences-in-regression- discontinuities design. The policy change shortened the duration of monthly benefit receipt, increased the amount of monthly transfers, and encouraged secondary caregivers to spend at least two months on leave. I find suggestive evidence that the policy did not have an effect on wage loss after childbirth for women with high education. Women with low education earn a larger share of their pre-birth wage in the second year after childbirth under the new policy regime. This is most likely because they return to work faster. My results suggest that the policy change only influenced labor market behavior of mothers with economic constraints. Study 2 provides novel insights into ECE access by using a new indicator: distance traveled for child care. It documents trends in how far families travel to access care in the United States by neighborhood income using geographic mobility data for 2019 for n = 106,916 child care programs. The findings indicate that distance traveled follows an inverted U-shaped pattern. Families who live in the lowest and highest income neighborhoods tend to travel less for child care than families in the middle of the income distribution. In a case study examining the state of Illinois, the pattern is consistent with the physical availability of child care. Findings are discussed in terms of how distance traveled as an indicator can help define the child care market and its implications for early childhood policy. Study 3 focuses on the effect of ECE on parental outcomes. In this paper, coauthored with Professor Terri Sabol, we use family stress theory to argue that the financial and logistical burden of paying for and managing child care arrangements can act as repeated stressors in families’ lives, and may negatively influence parental mental well-being. We examine whether the provision of free and high-quality early care alleviates these stressors and leads to better parental health and well-being. We use data from the Head Start Impact Study, a nationally representative randomized controlled trial from the early 2000s, to answer the research question. Next to documenting the average effect of offering Head Start on parental well-being, we also explore heterogeneity in these effects by program characteristics, including family-centered services and supports in a program. The three studies in this dissertation inform our understanding of how birth-to-5 child and family policies influence lives of families with young children within two different national contexts, Germany (with high public funding) and the United States (with lower public funding). Moving beyond documenting average effects, they showcase how policy impacts vary by family demographics and child care center characteristics. These insights contribute to policy design and could help researchers, practitioners, and policy makers to work together to build policies that better support families with young children

The number of tubal sterilization procedures increased dramatically in the United States in the 1970s due to legal and technological advances, quickly becoming the most popular form of contraception among married women. This method of permanent contraception afforded women almost perfect control over the end of their fertility. This paper studies how the increase in sterilizations affected completed fertility-particularly age at last birth-and female labor supply. Using variation across regions and over time in sterilization rates by age, I show that women more exposed to tubal sterilization at childbirth were less likely to have a subsequent birth. The increase in tubal sterilizations between 1965 and 1985 reduced women's age at last birth by 1.9 years and the probability of childbirth after age 30 by over 30%. As women spent fewer years caring for young children following the diffusion of tubal sterilization, female labor force participation increased. I also find suggestive evidence that women were more likely to select into occupations that reward experience and tenure, consistent with the power of tubal sterilization to reduce the risk of career interruptions.

Background: Older workers experience higher rates of fatal occupational injury than younger workers worldwide. In North Carolina, the population of older workers more than doubled between 2000 and 2017. In 2008, the Great Recession changed occupational patterns among all age groups. We examined annual rates and distribution of fatal occupational injuries experienced by older workers, comparing the prerecession period (2000–2007) to the post-recession period (2009–2017). Methods: Detailed information on all fatal occupational injuries during the period between 1 January 2000 and 31 December 2017 were abstracted from the records of the North Carolina Office of the Chief Medical Examiner and the office of vital records. The decennial Census and American Community Survey were used to estimate the population at risk and derive annual rates of fatal occupational injury. Results: During the study period, 537 occupational fatalities occurred among workers 55+ years of age. The rate of fatal occupational injury among older workers declined 2.8% per year, with a 7.7% yearly decline in the pre-recession period compared with a 1.4% increase per year in the post-recession period. Workers 65+ years of age experienced rate increases in both periods. The highest rates of unintentional fatal occupational injury (injuries that were not purposefully inflicted) were observed in forestry, fishing hunting and trapping, and wood building manufacturing. Intentional fatal occupational injury rates (homicide, suicide) were highest in transportation, gas/service stations and grocery/food stores. Conclusions: Older workers have persistently high rates of fatal occupational injury in North Carolina before and after the Great Recession.

This dissertation studies the role of migration adaptation channel and the effectiveness of existing public policies towards climate change. Chapter 1 starts from the fact that post-Katrina (New Orleans) migration behaviors largely differ from the prediction suggested by the existing migration model used for the adaptation analysis. Katrina migrants disproportionately moved to urban places in the region in which New Orleans is located, which violates location’s equal substitutability assumption imposed in the extant literature. On this subject, I develop a full-fledged dynamic nested logit migration framework, in which nests depend on both geography and location’s characteristics, that allows for heterogeneous migration responses. Then, I propose a reduced-form approach to identify and estimate migration elasticities governing the asymmetric migration response. Through simulation, I verify that my model offers a prediction about the disproportionate nature of migrants’ relocation (Katrina), better than previous models do. Finally, my model delivers an important policy implication that there should also be public assistance designed to mitigate congestion effects in destinations that are close substitutes, caused by overflow of migrants. Chapter 2, joint with Xinle Pang, explores the welfare implications of flood relief policies. We develop a quantifiable general equilibrium migration model with rich geographic linkages, industry structure, and flood risk for this analysis. We also apply the Neural Network approach to overcome the curse of high dimensionality in the simulation. We show that existing post-Harvey relief transfer improves U.S. welfare compared to a zero-relief economy. Chapter 3, joint with Douglas Noonan and Lilliard Richardson, utilizes the Regression Discontinuity (RD) design with two unique parcel-level datasets to examine the actual effect of flood zoning policy on the housing market as well as the flood risk discontinuity at floodplain boundaries.

In the United States, the labor market participation rate of older workers aged 50 and above has increased, and one-third of the labor force is made up of older workers in 2020. The trend of lifetime employment with one firm has been displaced by contingent employment in the current flexible labor market. Consequently, many older workers experience frequent employment transitions until they exit the labor market completely. However, the dynamics of labor market participation among older workers, especially those experiencing repetitive unemployment and employment in older age, are not well understood. This dissertation aimed to investigate trends in employment transitions among older workers, with a focus on job search activity, job availability in the community market, and employment support program participation in a state. In Chapter 1, the historical and theoretical evolution of aging populations was discussed, with three specific periods defined in this study: the initial introduction of welfare provisions, the looming individual safety net collapse, and visualized risks and retirement insecurity. Chapter 2 utilized latent class analysis, which identified five latent classes in the patterns of job search activities among older workers from the Health and Retirement Study. Multinomial regression analysis revealed that the patterns of job search activities are significantly associated with different types of employment outcomes, in addition to individual and employment characteristics. Chapter 3 examined job availability in the local market using two datasets, including the O*NET database and the American Community Survey. The findings showed low rates of matching between job vacancies and older workers, with higher concentrations in three occupational groups among older workers despite a wide range of available occupations. Chapter 4 demonstrated that workforce development programs under the Workforce Innovation and Opportunity Act improved the employability of older female participants but not for other disadvantaged participants who were older in age or nonwhite individuals. This study found that commonly chosen training programs aligned well with common occupations of the older workforce throughout the state. Finally, Chapter 5 provides implications of the three studies in this dissertation and discusses future directions to improve employment transitions among older workers in the United States.

In Finland, student housing is subsidized with general housing allowance and by supporting the production of student apartments. In this thesis, the relationship between housing subsidies and student outcomes is examined. The context is loosely built around the reform that came into effect in Finland in year 2017, in which students were moved under the general housing allowance system. The main research method of the thesis is a literature review on the impact of student aid and housing choices on students’ time use and academic outcomes. To support the results of the literature review, an empirical analysis is conducted regarding the differences in students’ time use by their living situation. The link between housing subsidies and student outcomes is closely connected to working while studying; working decreases the time available for spending on educational tasks. Based on previous research, it seems that increasing student aid (especially direct cash transfers) leads to decreases in working while studying, and shorter times-to-degree. Changes in the aid level seem to have a larger impact in the earlier study years, and for students from lower socioeconomic backgrounds. The housing aid affects housing choices through the incentives created by the system. Increasing the level of the aid may increase the demand for more expensive apartments. In addition, subsidies affect other types of housing choices: for example, the general housing allowance encourages to live alone due to the fact that it takes into account the whole household’s income level, and not just the individual’s, who is seeking for aid. Housing choices, in turn, impact students’ time use, and through that potentially their academic performance. My empirical analysis on the time use of American students implies that students living with their partner and/or children spend less time on studies. On the other hand, students with roommates tend to spend more time. The results of the analysis are descriptive in nature, and their purpose is to serve as evidence of the potential link between the living situation and the time used on studies.

In the United States (U.S.), exposure to ambient PM2.5 – fine particulate matter smaller than 2.5 micrometers in diameter – is responsible for the largest share of premature deaths associated with air pollution. Despite declines in average annual concentrations, significant disparities in PM2.5 exposure between racial and ethnic groups continue to persist. Existing research characterizes PM2.5 exposure disparities across a range of different indicators, but few studies compare these metrics against one another nor do these studies explore these metrics at different geographic scales and demographic shifts over time. As policymakers begin to prioritize environmental justice concerns through the identification of disproportionately impacted communities, careful selection of indicators and metrics will be vital for ensuring that inequities are properly captured in decision-making processes. Using population demographics from the U.S. Census and land-use regression PM2.5 concentration estimates from the Center for Air, Climate, and Energy Solutions (CACES), we compare the calculations of absolute and relative exposure disparities at different geographic scales and changing demographic shifts. Further, we discuss the policy implications of our findings and provide recommendations for both regulatory and community-centered measures to address existing racial/ethnic disparities.

This paper describes an emerging literature in economics that aims to merge macro issues of structural change and growth with micro data and analysis. This literature focuses on a set of related patterns of change that accompany the processes of growth and development. Traditionally, the focus has been on industrialization – and more broadly the reallocation of employment and economic activity from agriculture to manufacturing and services. The new literature considers a broader set of transformations: from rural to urban, from home to market (and from market to home), from informal to formal, and from self-employment to wage work. Drawing on new data sources, including micro data and administrative records, the literature tries to understand the complex interactions of a broad set of market failures, policy distortions, and impediments to the growth process. In broadening the understanding of structural transformation – to encompass processes beyond industrialization – this literature opens the door to a richer understanding of the processes of growth and a wider set of potential levers for policy.