Higher price levels in the destination relative to the origin increase the effective real wages of immigrants, thereby affecting immigrants' reservation and entry wages as well as their subsequent career trajectories. Based on micro-level longitudinal administrative data from Germany and exploiting within-country and across-cohort variations in the real exchange rate (RER) between Germany and countries that newly joined the European Union in the 2000s, we find that immigrants arriving with high RERs initially settle for lower paying jobs than comparable immigrants arriving with low RERs. In subsequent periods, however, wages of high RER arrivals catch up to that of their low RER counterparts, convergence achieved primarily through changes to better paying occupations and firms. Our findings thus point to the persistent regional price differences as one possible reason for immigrants' downgrading, with implications for immigrants' career profiles and the assessment of labor market impacts of immigration.

The expansion of women’s educational attainment may seem to be a promising path toward achieving economic equality between men and women, given the consistent rise in the economic value of higher education. Using yearly data from 1980 to 2017, we provide an updated and comprehensive examination of the gender gap in education premiums, showing that it is not as promising as it could and should be. Women receive lower rewards to their higher education across the entire wage distribution, and this gender gap increases at the very top education pre­mi­ums—the top quar­ter and, even more so, the top dec­ile. Moreover, insuf­fi­cient theoretical and methodological attention to this top premium effect has left gender inequal­ity concealed in the exten­sive empir­i­cal stud­ies on the topic. Specifically, when we artificially cen­sor the top at the 80th wage per­cen­tile, the gen­der gaps in education premium reverse. Lastly, the growth in earnings inequality in the United States, which is greatly affected by the expansion of top earnings, is associated with the growing gender gap in education premiums over time. We discuss the meaning and implications of this structural disadvantage at a time when women’s educational advantage keeps growing and higher education remains the most important factor for economic attainment.

This paper will focus on answering the question, is pursuing higher education worth it? The answer will be reached by reviewing a great deal of academic literature and graduate-level study experience. The paper will make use of the most recent public data sets available and will include statistical models, graphs, and tables to confrm that income is positively correlated with levels of education.

Background Low-income individuals without health insurance have limited access to health care. Medicaid expansions may reduce kidney failure incidence by improving access to chronic disease care. Methods Using a difference-in-differences analysis, we examined the association between Medicaid expansion status under the Affordable Care Act (ACA) and the kidney failure incidence rate among all nonelderly adults, aged 19–64 years, in the United States, from 2012 through 2018. We compared changes in kidney failure incidence in states that implemented Medicaid expansions with concurrent changes in nonexpansion states during pre-expansion, early postexpansion (years 2 and 3 postexpansion), and later postexpansion (years 4 and 5 postexpansion). Results The unadjusted kidney failure incidence rate increased in the early years of the study period in both expansion and nonexpansion states before stabilizing. After adjustment for population sociodemographic characteristics, Medicaid expansion status was associated with 2.20 fewer incident cases of kidney failure per million adults per quarter in the early postexpansion period (95% CI, −3.89 to −0.51) compared with nonexpansion status, a 3.07% relative reduction (95% CI, −5.43% to −0.72%). In the later postexpansion period, Medicaid expansion status was not associated with a statistically significant change in kidney failure incidence (−0.56 cases per million per quarter; 95% CI, −2.71 to 1.58) compared with nonexpansion status and the pre-expansion time period. Conclusions The ACA Medicaid expansion was associated with an initial reduction in kidney failure incidence among the entire, nonelderly, adult population in the United States; but the changes did not persist in the later postexpansion period. Further study is needed to determine the long-term association between Medicaid expansion and changes in kidney failure incidence.

A renewed interest in understanding the relationship of the built environment with neighborhood crime patterns has encouraged researchers to utilize novel methods (e.g., risk terrain modeling) to better examine the influence of environmental risk factors on types of crime. The current study engages with this research by operationalizing neighborhoods using Hipp and Boessen’s egohood strategy and using Drawve’s aggregate neighborhood risk of crime measure to assess the relationship of a neighborhood’s physical environment with its spatial vulnerability of experiencing a homicide. Findings demonstrate that the physical environment was a significant predictor of neighborhood homicide; however, social structural neighborhood characteristics were more important. This suggests crime prevention strategies like crime prevention though environmental design or blight remediation may provide prudent and straightforward methods to inhibit lethal violence in a community in the short run, but that addressing a neighborhood’s social structural characteristics may be more effective at reducing homicides in the long term.

Over a million refugees and other immigrants arrived in the United States from Southeast Asia starting in 1975. Forty-five years later, their adult children have completed their education in the United States and entered the labor force. This study uses a large microdata sample from the American Community Survey to describe and compare the socioeconomic status of Southeast Asian American adults and native-born white adults. Results are disaggregated by gender, generation (Generation 1.5 and Generation 2), and ethnic group (Hmong, other Laotian, Cambodian, and Vietnamese). Regression analysis—controlling for age, educational attainment, and other factors—shows that native-born white men generally have higher predicted median hourly wages and earnings and higher labor force participation rates than Southeast Asian men, although Vietnamese men surpass white men in some measures. On the other hand, Southeast Asian women’s predicted median wages, earnings, and labor force participation rates exceed those of native-born white women

Objectives: Patterns of healthy leisure are dependent upon age, but people with disabilities are particularly susceptible to passive and disengaged types of activities. This study evaluates how individuals with disabilities spend their time in passive, active, social, and isolated forms of leisure over the life course, and how these patterns vary by age. Method: I analyze nationally representative data from 70,165 respondents ages 15 and older in the 2008, 2010, and 2012–2016 American Time Use Survey. Linear regression models estimate the association between disability and leisure time, net of self-rated health and sociodemographic controls. Interactions between age and disability are also evaluated, as well as the robustness of results by sensory, cognitive, physical, and multiple disability status. Results: People with disabilities report significantly more, and poorer quality, leisure than people without disabilities. This includes more than 2 hr more time in passive leisure as well as a disproportionate amount of isolated leisure spent at home, alone. These differences are not fully explained by health and sociodemographic controls. The isolated leisure time of people with disabilities is most different from people without disabilities in later life—whereas differences in total and passive leisure time, by disability status, are greatest in midlife. Discussion: People with disabilities spend less time in health-promoting forms of leisure at all ages, but these patterns are unique across midlife and older age.

We document stark differences in the cross-sectional age-earnings profiles between the U.S. and China, the two largest economies in the world, during the past thirty years. We find that, first, the peak age in cross-sectional age-earnings profiles, which we refer to as the "golden age," stays almost constant at around 45-50 years old in the U.S., but decreases sharply from 55 to around 35 years old in China; second, the age-specific earnings grow drastically in China, but stay almost stagnant in the U.S.; and third, the cross-sectional and life-cycle age-earnings profiles look remarkably similar in the U.S., but differ substantially in China. We propose and empirically implement a unified decomposition framework to infer from the repeated cross-sectional earnings data the life-cycle human capital accumulation (the experience effect), the inter-cohort productivity growth (the cohort effect), and the human capital price changes over time (the time effect), under an identifying assumption that the growth of the experience effect stops at the end of the working career. The decomposition suggests that China has experienced a much larger inter-cohort productivity growth and increase in the rental price to human capital compared to the U.S., but the return to experience is higher in the U.S. We also use the inferred components to revisit several important and classical applications in macroeconomics and labor economics, including the growth accounting and the estimation of the TFP growth, then sources of the human capital price changes, the college wage premium, and the skill-biased technological change.

This project arose from 2 months of work over the summer of 2020 during the COVID-19 pandemic. Boston Chinatown Neighborhood Center (BCNC) hired me to assist with onboarding of a new fundraising staff member as well as research on community demographics and programmatic impact. As part of this work, I analyzed a dataset related to an income replacement program for local immigrant families affected by the COVID-19 lockdown. My capstone project attempts to build on this initial analysis with more detailed, geospatial modeling of this dataset paired with Census bureau data. This work highlights ways in which non-profit service data can be repurposed for advocacy, in keeping with historical community organizing efforts in Boston’s Chinatown. This paper is divided into several parts. The Background section provides an overview of the history of Boston Chinatown, American community organizing tactics and critiques, and a brief analysis of political economy and successful community advocacy initiatives in Boston’s Chinatown. In the Technical section, I create and analyze multi-variate linear and geographically-weighted regression (GWR) models predicting unemployment of Asian non-citizen residents of Suffolk county, and compare the results with a dataset from an income replacement program conducted during the early stages of the COVID-19 pandemic. In the final section, I discuss findings from the regression models and potential applications for non-profits, researchers, policy makers and advocates.

Greene County, like the rest of Ohio, has seen an increase in the number of individuals age 65 and over. The Greene County Council on Aging (Council) is interested in planning for the current and future needs of the older adults in its area. In 2019, Greene County’s 29,995 older adults (age 65+) comprised about 18% of the population, similar to Ohio’s statewide average of 17.6%.1 While close to the state average, Greene County is a relatively young county, with 64 of Ohio’s 88 counties having larger proportions of older adults in 2020. While Greene County’s total population has grown 14% since 2000, its population 65 and over has increased nearly 70%. Greene County has a tax levy that assists in funding services and programs for older adults, administered by the Council. The levy funds home- and community-based services as well as the county’s senior centers. As the COVID-19 pandemic forced senior centers to close and increased demand for other services, the Council saw an opportunity to address some questions about their current and future programming and the future needs of older adults in Greene County. To assist older adults in Greene County, the Council contracted with Scripps Gerontology Center to provide data about the older adult population at the county subdivision level. Research has shown that certain socio-demographic, physical, and social factors can have an impact on the everyday lives of older adults. Variables such as age, marital status, and educational attainment have often been cited in the literature as potential factors influencing the support individuals have when experiencing issues related to aging. Likewise, factors such as cognitive impairment and living alone could impact the resources they might be able to draw upon, as well as their need for assistance.

The US fertility transition in the nineteenth century is unusual. Not only did it start from a very high fertility level and very early in the nation's development, but it also took place long before the nation's mortality transition, industriali-zation, and urbanization. This paper assembles new county-level, household-level, and individual-level data, including new complete-count IPUMS microdata databases of the 1830-1880 censuses, to evaluate different theories for the nineteenth-century American fertility transition. We construct cross-sectional models of net fertility for currently-married white couples in census years 1830-1880 and test the results with a subset of couples linked between the 1850-1860, 1860-1870, and 1870-1880 censuses. We find evidence of marital fertility control consistent with hypotheses as early as 1830. The results indicate support for several different but complementary theories of the early US fertility decline, including the land availability, conventional structuralist, ideational, child demand/quality-quantity tradeoff, and life cycle savings theories.

The 2019 coronavirus (COVID-19) pandemic has led to more than 235,000 deaths and 9 million reported positive cases in the United States. Most of the country implemented stay-at-home orders to prevent the spread of COVID-19, which has led to job losses and more than 40 million claims for unemployment insurance. The objective of this study was to estimate the potential impact of COVID-19-related closures in employment and healthcare access by sexual orientation. We used data from the 2015 to 2018 National Health Interview Survey and employment industry codes to describe the working adult population who may be vulnerable to COVID-19 job losses by sexual orientation. Multivariable logistic regression models identified the risk factors for working in a COVID-19-sensitive industry and differences in healthcare access by sexual orientation. We estimate that there may be approximately 1.7 million sexual minorities and 36.6 million heterosexual adults employed in industries that make them vulnerable to unemployment, uninsurance, and limited access to care. Nearly two-thirds of working adults—regardless of sexual orientation—are at risk of severe illness should they become infected with COVID-19. Almost half of the sexual minority and heterosexual adults in industries sensitive to COVID-19 may remain or become uninsured during the pandemic. Approximately 60% of sexual minorities and 40% of heterosexual adults in COVID-19-sensitive industries are renting their home or apartment (rather than owning their home). Because sexual minority adults vulnerable to the COVID-19 pandemic are renting or within family income ranges for premium tax credits in the individual insurance marketplaces, policymakers should consider expanding protections for renters and broadening special enrollment periods for people seeking coverage in the federal and state-based marketplaces.

The current crisis of capitalism did not originate with COVID-19, but has been brewing for several years. It is a systemic crisis with multiple dimensions: it is expressed politically in the ungovernability of nation states, their inability to exercise economic control, and their subordination to the needs of large transnational conglomerates and their dependence on them; economically, in the exhaustion of financialized neoliberalism and the savage exploitation of the workforce under cruel modalities of labor flexibility and precariousness at the local and global levels; environmentally, in the pollution, plundering, and devastation of natural resources that have led to climate change consequences that are tending toward global collapse. For example, in the emergence of the COVID-19 pandemic, the industrial food and agricultural systems have played a key role, as has deforestation (Ribeiro, 2020).

The COVID-19 (SARS-CoV-2) pandemic has refocused attention on remote working, raising questions about its future trajectory, the reasons for its prevalence, and the potential implications for urban areas. Examining data from four large-scale U.S. surveys from 2000 to the cusp of the pandemic, this paper provides historical perspective. The plurality of those working at home for pay was doing so as a supplement to tasks performed in the workplace. However, in 2019, 5.8 percent of those engaged in paid employment generally worked from home (forgoing a workplace journey), increasing by an average of .14 percent annually. On any given day, 13.2 percent were working from home, increasing by .29 percent per year. Many of those working from home were professional workers concentrated in select low-touch sectors. By 2019, the majority were formal employees (v. self-employed or gig workers). The age distribution of those working from home suggests that a significant portion of remote work is an outcome of the informalization of late-career employment relations among the highly-educated. Remote work is but one of several cost-reduction strategies available to firms.

Functional principal component analysis (FPCA) has played an important role in the development of functional time series analysis. This paper investigates how FPCA can be used to analyze cointegrated functional time series and proposes a modification of FPCA as a novel statistical tool. Our modified FPCA not only provides an asymptotically more efficient estimator of the cointegrating vectors, but also leads to novel FPCA-based tests for examining some essential properties of cointegrated functional time series. As an empirical illustration, our methodology is applied to two empirical examples: U.S. age-specific employment rates and earning densities.

We experimentally vary signals and senders to identify which combination will increase vaccine demand among a disadvantaged population in the United States – Black and White men without a college education. Our main finding is that laypeople (non-expert concordant senders) are most effective at promoting vaccination, particularly among those least willing to become vaccinated. This finding points to a trade-off between the higher qualifications of experts on the one hand, but lower social proximity to low socio-economic status populations on the other hand, which may undermine credibility in settings of low trust.

Careful readers will note that we did not include the work–life balance subject in the prior chapter about barriers to women’s success in IM. That is because we do not view it as any more of a barrier for the majority of investing jobs than it is in corporate America. We recognize that the intensity of some asset classes and IM firm cultures—such as with certain types of hedge fund and smaller, lean investment managers—can create an environment where work–life balance is aspirational rather than achievable. However, as one of us with a very good work–life balance at a small firm can attest, even some small firms are good places to find balance.

This paper examines the effect of the increase in the Social Security Full Retirement Age (FRA) and the associated decrease in benefits for early claimants on retirement rates at ages 62 to 65. It uses information on age, sex, and labor force participation from the monthly Current Population Survey from 1976 to 2019. Critical components of the analysis include a difference-in-difference framework, comparison of three measures of retirement status, estimation of nonparametric and parametric models, and a test of the assumptions underlying the difference-in-difference approach. Although our model satisfied that test, the results do not guarantee that our specification is valid.

March 24 is Equal Pay Day, the day that marks how far into this year women must work to catch up to what men made last year alone. Women working full-time, year-round are typically paid just 82 cents for every dollar paid to men.1 And one year into a global health crisis with devastating health and economic consequences, part of the story of the pandemic’s impact on women and the families who depend on them is the story of racial and gender wage gaps, which are especially harmful right now. A gender wage gap exists in 94 percent of occupations.2 Women, and women of color are overrepresented in front-line jobs and are being paid less than men in the same jobs – which means we are undervaluing their work even as we depend on it more than ever before

We examine effects of the COVID-19 pandemic on employment losses across metropolitan area status and population size. Non-metropolitan and metropolitan areas of all sizes experienced significant employment losses, but the impacts are much larger in large metropolitan areas. Employment losses manifest as increased unemployment, labor force withdrawal, and temporary absence from work. We examine the role of individual and local area characteristics in explaining differing employment losses across metropolitan status and size. The local COVID-19 infection rate is a major driver of differences across MSA size. Industry mix and employment density also matter. The pandemic significantly altered urban economic activity.