In rural, suburban, and urban counties throughout North Carolina, serious housing challenges undermine economic success and resident well-being. The urgency of these issues both preceded and is exacerbated by the economic and health risks caused by the COVID-19 pandemic. No county has enough affordable housing to meet the needs of its residents with the lowest incomes, leading to strained household budgets and elevated rental market risks. Building on pre-2020 population projections from the state demographer, we project a net growth of approximately 866,000 households statewide, with substantial growth in urban counties and more populous suburban counties; moderate growth in higher-cost rural counties, rural recreation economies, and less-populous suburban counties; and more modest growth in the more affordable rural counties. Unless stakeholders across the state work together toward a healthier housing market, current gaps in the low-cost housing supply, added household demand, and increased arrears related to the pandemic will combine to exacerbate affordability challenges for households while undermining the viability of the rental and homeownership markets.

The Amish collective objection to high school education and refusal to comply with compulsory schooling laws can be interpreted with a religious-club-good framework. According to the religious-club interpretation, the Amish use the restriction on secular education as a religious prohibition and sacrifice to improve the welfare of sect members. I exploit the 1972 U.S. Supreme Court's decision in Wisconsin vs. Yoder, which exempts Amish children from compulsory high school education, as a policy shock to test several key predictions of the religious-club explanations. The evidence suggests that the successful restriction on high school education helped the Amish sect exclude individuals with low religious participation, lower members' shadow cost of time, and grow the sect through higher fertility.

This dissertation focuses on the reasons why men and women make different choices when it comes to investing in human capital. The common thread of all three essays is a focus on one particular dimension of the human capital investment decision: the choice of college major. I study gender differences in college major choice in three different contexts. The first, the dot-com crash, is a large negative shock to the relative payoffs of different college majors. The second, the transition to coeducation at former women’s colleges, is a structural change in colleges. The third is long-run changes over time. Chapter 1 studies the change in women’s college major choices in response to a large, negative labor market shock, and how gender differences in STEM grades might lead women to have a stronger reaction to a labor market shock than men do. Although the dot-com crash had similar labor market effects for new graduates in engineering and computer science, it had different effects on who chose each major: women disproportionately left computer science, but not engineering. I investigate the mechanism behind the gender difference in reaction to the dot-com crash using administrative data on students from a four-year public university. At said university, the gender gap in grades (in favor of men) is larger in computer science than engineering. I estimate a structural model of major choice where students choose a major to maximize expected lifetime utility, conditional on grades, the labor market, and other factors. I find that if the distribution of grades had been the same in engineering and computer science, the gender difference in reaction to the dot-com crash would have been 33 to 42% smaller, suggesting that students reacted to the dot-com crash in accordance with their perceived comparative advantage. My results suggest that grades are an important component in retaining women in computer science degree programs. Universities hoping to encourage women to major in computer science should investigate the sources of gender gaps in STEM grades and work to help women improve their performance. Chapter 2 studies the change in women’s college major choices induced by the introduction of male peers. Though American women earn college degrees at higher rates than men, they are still under-represented in quantitative fields such as STEM and economics. Researchers have speculated gender differences in labor market decisions may originate in part from psycho-social factors such as gender norms and competition, many of which become more relevant to women when they are in more male environments. We leverage a unique setting that generated variation in women’s exposure to male peers: colleges that transitioned from women-only to coeducation. At such colleges, we observe a steady decrease in the share of women majoring in STEM over the decade following the transition to coeducation. This corresponds to a 17% decrease in the share of women majoring in STEM for a 10 percentage point increase in the male share of the graduating class. We find no evidence that the female share of faculty declines in response to the switch to coeducation, suggesting that our results are driven primarily by peer rather than by role-model effects. Our results suggest that women’s human capital investments are affected by the gender mix of their fellow students and have implications for gender gaps in the labor market. Chapter 3 studies long-run changes in men’s and women’s choices of college major over time, in particular whether a Schelling tipping pattern exists in the gender composition of college majors. Following Pan’s (2015) model of tipping in occupations, I build a framework that can produce a tipping pattern in the gender composition of college majors. However, I find that no evidence of a tipping pattern in college major. By relaxing two assumptions in previous tipping models, I explain theoretically why tipping may not occur in this context. I test the modified framework and find that the lack of tipping is most likely explained by men facing only small utility costs of being in highly female majors.

Attribute reduction is one of the challenging problems in rough set theory. To accomplish an efficient reduction algorithm, this paper analyzes the shortcomings of the traditional methods based on attribute significance, and suggests a novel reduction way where the traditional attribute significance calculation is replaced by a special core attribute calculation. A decision table called the positive region sort ascending decision table (PR-SADT) is defined to optimize some key steps of the novel reduction method, including the special core attribute calculation, positive region calculation, etc. On this basis, a fast reduction algorithm is presented to obtain a complete positive region reduct. Experimental tests demonstrate that the novel reduction algorithm achieves obviously high computational efficiency.

This thesis consists of three chapters on labor markets and economic growth. Chapter 1 examines the role of offshoring in the flattening out of the female to male hours ratio in the US since the early 1990s. The leveling off of the gender hours ratio coincides with the rise in service offshoring and the fall in the share of occupations with high offshoring potential in female hours worked. We propose a model with two genders, two sectors, and a continuum of tasks. Due to higher female intensity in the service sector, the gender hours ratio falls when offshoring of service rises. Quantitatively, the increase of service offshoring plays an important role in explaining the plateau of the gender hours ratio after the 1990s. Chapter 2 studies firm dynamics in Korea before and after the 1997-98 Asian crisis and pro-competitive reforms that reduced the dominance of chaebols. We find that in industries that were dominated by chaebols before the crisis, labor productivity and TFP of non-chaebol firms increased markedly after the reforms (relative to other industries). Furthermore, entry of non-chaebol firms increased significantly in all industries after the reform. Finally, after the crisis, the non-chaebol firms also significantly increased their patenting activity (relative to chaebol firms). These results are in line with a neo-Schumpeterian view of transition from a growth model based on investment in existing technologies to an innovation-based model. Chapter 3 investigates the factors behind long hours worked in Korea. Koreans work longer hours than Americans although they face higher labor tax rates and lower family care related subsidies. We propose a two-period OLG model incorporating education costs and pension benefits to explain this observation. In Korea, education costs are high due to prevalence of private after-school lessons and limited student loans for college education, restricting households’ budgets and driving the prime-aged to work longer. The old receive lower pension benefits, staying longer in the labor market. The calibrated model is successful in generating longer hours worked of the prime-aged and the old in Korea.

The leisure and hospitality sector—which includes restaurants, hotels, museums, spectator sports, and more—is a major driver of the American economy and a source of millions of jobs; this sector alone accounted for 9.4% of the entire workforce in 2018, employing roughly 1 in 11 workers in the U.S.1 But the spread of COVID-19 has ravaged this sector—making it the hardest-hit sector in terms of job losses2 —as both public health restrictions and changes in individual behavior to avoid the virus have limited travel, dining out, and many other leisure activities. And women of color, who are disproportionately represented in leisure and hospitality jobs that have long been underpaid and undervalued, are likely to suffer the most.

There is a well-known gender difference in time allocation within the household, which has important implications for gender differences in labor market outcomes. We ask how malleable this gender difference in time allocation is to culture. In particular, we ask if US immigrants allocate tasks differently depending upon the characteristics of the source countries from which they emigrated. Using data from the 2003-2017 waves of the American Time Use Survey (ATUS), we find that first-generation immigrants, both women and men, from source countries with more gender equality (as measured by the World Economic Forum’s Global Gender Gap Index) allocate tasks more equally, while those from less gender equal source countries allocate tasks more traditionally. These results are robust to controls for immigration cohort, years since migration, and other own and spouse characteristics. There is also some indication of an effect of parent source country gender equality for second-generation immigrants, particularly for second-generation men with children. Our findings suggest that broader cultural factors do influence the gender division of labor in the household.

Since its creation in 1973, California’s Occupational Safety and Health Act has excluded an entire class of workers—those employed in private households as nannies, housecleaners, home health aides, and home attendants. Today, these workers provide vital services to an estimated two million households across the state.1 This report documents the human cost of their exclusion from safety and health laws at a time when COVID-19 and ecological disaster compound typical workplace hazards. Predominantly women of color and immigrants, California’s domestic workers have long faced low wages, scant benefits, and persistent job insecurity. The devaluation of this workforce is reflected in its systematic exclusion from basic legal protections that apply to most other occupations. The federal minimum wage, for instance, was denied to home care aides for nearly eighty years, from 1938 until 2015, when this exemption finally ended.2 Domestic workers, however, have not yet gained inclusion in other bedrock labor protections. Their exemption from California’s safety and health law is now nearly fifty . . .

One of the major unresolved questions in the study of vulnerability to climate change is how human migration will respond in low and middle-income countries. The present study directly addresses this lacuna by using census data on migration from 4 million individuals from three middle-income African countries over a 22-year period. We link these individuals to climate exposures in their origins and estimate climatic effects on migration using a fixed-effects regression model. We show that climate anomalies affect mobility in all three countries. Specifically, mobility declines by 19% with a 1-standard deviation increase in temperature in Botswana. Equivalent changes in precipitation cause declines in migration in Botswana (11%) and Kenya (10%), and increases in migration in Zambia (24%). The mechanisms underlying these effects appear to differ by country. Negative associations between precipitation anomalies, unemployment, and inactivity suggest migration declines may be due to an increased local demand for workers to offset production risk, while migration increases may be indicative of new opportunities in destinations. These country-specific findings highlight the contextually-specific nature of climate-migration relationships, and do not support claims that climate change is widely contributing to urbanization across Africa.

How much of the spatial distribution of economic activity today is determined by history rather than by geographic fundamentals? And if history matters for the distribution, does it also affect overall efficiency? This paper develops a tractable theoretical and empirical framework that aims to provide answers to these questions. We derive conditions on the strength of agglomeration externalities, valid for any geography, under which temporary historical shocks can have extremely persistent effects and even permanent consequences (path dependence). We also obtain new analytical expressions, functions of the particular geography in question, that bound the aggregate welfare level that can be sustained in any steady-state, thereby bounding the potential impact of history. Our simulations—based on parameters estimated from spatial variation across U.S. counties from 1800-2000—imply that small variations in historical conditions have substantial consequences for both the spatial distribution and the efficiency of U.S. economic activity, both today and in the long-run.

Coastal populations along the Atlantic Coast of the United States face a persistent threat of tropical cyclones. Tropical cyclones of any strength can cause significant damages and losses to both life and property. As coastal populations continue to rise in a changing climate, the power of knowing which communities are the most and least vulnerable to future tropical cyclone events can assist in mitigating some of the losses. This paper explores the factors that make a coastal community more or less vulnerable to tropical cyclones based on prior natural hazards research and creates a relative index that will tell what counties along the Atlantic Coast are the most and least vulnerable to tropical cyclone events. This index uses normalized and standardized social demographic data as well as historical physical factors to create a summative index that is widely applicable. In this paper, the index was calculated for 2015 census data and 1980 census data in order to provide a look at changes in vulnerability over time. The index in both time periods highlights the relative greater vulnerability of counties that exhibit greater numbers of marginalized or poorer populations and experience tropical cyclone events more frequently. Those counties that are better prepared for tropical cyclones are primarily counties with greater levels of wealth. These patterns of vulnerability to tropical cyclones are clear and in a climate that has the possibility of producing increasingly more devastating storms, knowledge of these factors and patterns provide useful insights that can be used to help better respond to future events.

Urban researchers have long debated the extent to which metropolitan employment is monocentric, polycentric, or diffuse. In this paper I use high-resolution data based on unemployment insurance records to show that employment in US metropolitan areas is not centralized but is spatially concentrated. Unlike residents, who form a continuous surface covering most parts of each metropolitan area, jobs have a bimodal spatial distribution, with most blocks containing no jobs whatsoever and a small number having extremely high employment densities. Across the 100 largest Metropolitan Statistical Areas, about 75% of jobs are located on the 6.5% of built land in Census blocks with at least twice as many jobs as people. These relative proportions are extremely consistent across cities, even though they vary greatly in the physical density at which they are constructed. Motivated by these empirical regularities, I introduce an algorithm to identify contiguous business districts and classify them into four major types. Based solely on the relative densities of employment and population, this algorithm is both simpler to implement and more flexible than current approaches, requiring no metro-specific tuning parameters and no assumptions about urban spatial layout.

The Great Recession was the worst economic downturn in the U.S. since the Great Depression of the 1930s. This research focusses on children in five income-quintile groups before, during, and following the Great Recession by analyzing changing disparities across these groups using a new Index of Parental Employment Insecurity, nine additional well-being indicators, and the overall Child Well-Being Index. The new Index of Parental Employment Insecurity captures employment insecurity more fully than the official U.S. monthly unemployment rate by using a comprehensive approach spanning 15-month periods (combining January-to-December measures for a calendar year with measures for March of the following year), based not only on two traditional unemployment indicators, but also two indicators of “hidden unemployment” and two indicators of “underemployment”. The other nine well-being indicators, also with children or youth as the unit of analysis, are median family income, health insurance coverage, Prekindergarten enrollment, three health indicators – very good or excellent health, obesity, and activity limitations – two indicators reflecting family experience – one-parent families and residential mobility – and idle or disconnected youth. For each of the 10 indicators in 1994, children in the lowest-income, lower-middle-income, and middle-income families had lower levels of well-being, often much lower, than children in the highest-income families. These had gaps narrowed, as of 2014, for all three of the lowest-income groups by about two-thirds for health insurance coverage and by about two-fifths for Prekindergarten enrollment. Compared to the highest-income group, however, the gaps had widened for the middle-income group for most indicators, the direction of changes in gaps was mixed for the lower-middle-income group, and the gaps had narrowed, usually by about one-fourth, for the lowest-income group, leaving gaps for the lowest-income group for seven of the ten indicators in 2014 that were at least three-fourths as large as they had been in 1994. In addition, median family income for the highest-income group grew by $32,500 reaching $173,600 in 2014, and the corresponding disparities expanded for the middle-income, lower-middle-income, and lowest-income groups, respectively, to $113,300, $139,400, and $160,800.

Rising profitability and market valuations of US businesses, sluggish wage growth, and reduced unemployment and inflation, have defined the macroeconomic environment of the last generation – especially the period of recovery from the financial crisis. This paper offers a unified explanation for these phenomena based on reduced worker power, and argues that the declining worker power exploration is both most compelling on scientific grounds and is most usefully prescriptive for policy. In particular we present a variety of evidence that declining worker power explains more than increases in monopoly or monopsony power.

Background: Transactional sex, a causal exchange of gifts, money and services for sex is practiced globally. Transactional sex is associated with risky sexual behaviors, unintended pregnancy, gender based violence and HIV infection. Proportionally in 2016, TS among young women not in union in Uganda was almost twice in rural areas (16.4%) compared to urban (8.9%) areas. Despite the negative consequences associated with transactional sex, no study in Sub-Saharan Africa Uganda inclusive has provided a detailed account of the contribution of the variations in characteristics and variations in effects of characteristics to the rural-urban gap in transactional sex among young women not in union. This study therefore provides a detailed account of the rural-urban gap in TS by variations in characteristics and variations in effects of characteristics of young women in Uganda. Methods: The study utilized data from UDHS 2016 comprising of 1,595 records of young women (15-24 years) not in union (not currently married or living with a man). Statistical analysis was done . . .

This thesis broadly investigates the impacts of skill-biased technical change (SBTC) on income distributions. In Chapter 1, I develop a SBTC model with an intergenerational framework, where heterogeneously-skilled households make intergenerational transfers that determine the skill outcome of the next generation. By increasing the skill-premium, an SBTC shock increases these transfers, thus improving the probability that children from both high and low-skilled households will become skilled. With diminishing returns on investments, the relative improvement in skill outcomes is larger for children from low-skilled households compared to children from high-skilled households, implying that relative skill mobility also improves. I test the model's predictions in Chapter 2, using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM (Science, Technology, Engineering, and Mathematics) workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. The findings from Chapters 1 and 2 thus suggest that SBTC can improve both absolute and relative skill mobility. Chapter 3 examines how the skill-premium from the SBTC model can impact between-group inequality among skilled and unskilled workers. I construct a Gini measure for the SBTC model, and find that if the proportion of skilled workers is more than half, a rising skill-premium can actually reduce between-group inequality if the skill-share is also growing. For empirical validation, I observe trends in the skill-portion, skill-premium and two inequality indices (Gini & Theil) for full-time, full-year workers in the U.S from 1980-2018. With the proportion of college-equivalent workers continually increasing, I find that the relationship between the skill-premium and between-group inequality has changed: from 1980-2005, the relationship was strongly positive, while from 2005 onward, it has become negative. Thus, the skill-premium's impact on between-group inequality is not unidirectional

The Charlotte-Mecklenburg school district (CMS) is the 18 th largest district in the United States and Charlotte is one of the fastest growing cities in the United States, leading to several severely overcrowded schools. Therefore, CMS is in desperate need of an effective mathematical model to create school attendance zone plans that maximizes efficiency and equity. This paper presents Voronoi mathematical models to fairly partition the CMS district. The models created balance school socioeconomic demographics, minimizes school overcrowdedness, and reduces inconvenient commutes. These factors are aligned with the CMS school board goals for attendance zone plans and are considered for their impact on student success. This paper provides a unique contribution to the pursuit of equity in the CMS district by constructing mathematical models which have not been seriously considered as a helpful tool in the fight against this complex issue.

“In the 21st century America, Black males’ perception of and experiences with the openness at PWI (predominantly White institutions) can have a significant impact on students’ learning experience” (Sinaan, 2012, p. 1). However, the true understanding of the kinds of experiences and support that Black males feel they receive directly from the institution is limited in its scope. The transition from high school to college presents the need for the kind of emotional support Black males receive in high school. Educational experiences are important for Black students to pave their educational journey. The purpose of this study was to examine the perceptions of adult Black males regarding the emotional support experienced at a predominantly White Jesuit high school that facilitated transition to an institution of higher learning. More precisely, through a qualitative methodology and utilizing House’s theory of social support, this study explored emotional support as it pertains to aid, affect, and affirmation. Major findings revealed teachers were seen as the most affirming source of emotional support by Black males. The study showed that connecting cultural competence with pedagogy is a way to connect with students. Similarly, the literature evidences the need for the administrators to be fully engaged in the life of Black males following a targeted approach (Davis, 2015). Black males felt that administrators should go beyond just providing resources and aim to establish a more personal connection. The limitation of this study was its small sample size, which means the findings are not transferable and limited solely to the research site. However, the need for White Jesuit high schools to create a more culturally competent environment through pedagogy and professional development to meet the needs of Black males is evident from the results.

The COVID-19 pandemic has thrown hundreds of thousands of Angeleno households into financial turmoil, with low-income renters among the most vulnerable. The faltering economy means that state and local governments are facing massive revenue shortfalls and must make difficult choices about who to prioritize for assistance. In this brief I argue that Los Angeles should prioritize support for long-term residents of rent-stabilized housing, for three reasons: 1. Long-term rent-stabilized tenants are among the poorest households in the city, putting them at greater risk of losing their homes due to economic disruption. 2. Because many are poor and at risk, households who are displaced may place a substantial burden on social services at a time when we can least afford these costs. 3. Monthly rents for long-term tenants are low, on average, so it’s relatively inexpensive to provide assistance and preserve these rent-stabilized units at below-market rents. The city of Los Angeles has about 600,000 rent-stabilized units — units where once a tenant moves in their rent can rise by only about 3% each year (Phillips, 2019). Santa Monica and Beverly Hills have similar programs, as do about a dozen other cities in California. California rent control programs are subject to “vacancy decontrol,” meaning that landlords can raise rents to market rates when new tenants move in. Because market rents increased by an average of more than 3% annually over the past decade (Fleming, 2019), tenants who have lived in the same unit for many years are often paying considerably below market rents.

Universal Basic Income (UBI) has been featured in political discussions over the last years. Both people in favour and against its adoption, have provided numerous arguments to support either its positive or negative impact. Empirical literature on the topic is scarce since, with few exceptions, not many experiments have been conducted so far to empirically assess its effects. I use the Alaska Permanent Fund Dividend, a UBI-like programme, to assess the implications of unconditional cash transfers on educational decisions. I use data from various governmental sources, and predominantly Consumer Population Survey (CPS) data from the Integrated Public Use Microdata Series (IPUMS), to construct a panel dataset of 2,091 stateyear observations. Using a synthetic control approach, I investigate how college enrolment and bachelor completion have been affected since the implementation of the dividend. The results show that college enrolments have no significant change with the implementation of the dividend but there is a significantly negative effect on bachelor degree completion.