Background: Middle-aged adults (40-65 years) report higher stress levels than most other age groups. There is a need to determine the feasibility of using a meditation app to reduce stress and improve stress-related outcomes in middle-aged adults with a focus on men, as previous meditation app–based studies have reported a low proportion of or even no male participants. Objective: This study aims to (1) determine the feasibility (ie, acceptability and demand with a focus on men) of a consumer-based meditation app (Calm), to reduce stress among middle-aged adults reporting elevated stress levels, and (2) explore the preliminary effects of Calm on perceived stress, psychological outcomes (anxiety, depressive symptoms, mindfulness, and general coping), health behaviors (physical activity and eating habits), and COVID-19 perceptions. Methods: This feasibility randomized controlled trial evaluated an app-based meditation intervention in middle-aged adults (N=83) with elevated stress levels (ie, Perceived Stress Scale score ≥15) and limited or no previous experience with meditation. Participants were randomized to the intervention group (Calm app) or a control (educational podcasts; POD) group. Participants completed self-report assessments at baseline and postintervention (week 4). Feasibility was measured as acceptability and demand using Bowen framework. Feasibility and COVID-19 perceptions data were examined using descriptive statistics, and preliminary effects were evaluated using repeated measures analysis of variance. Results: Participants were satisfied with Calm (27/28, 96%) and found it appropriate or useful (26/28, 93%). Most reported they would likely continue using the Calm app (18/28, 64%). More Calm users reported satisfaction, appropriateness or usefulness, and intent to continue app use than POD users. Calm users (n=33) completed a mean of 20 (SD 31.1) minutes of meditation on the days they meditated and 103 (SD 109.1) minutes of meditation per week. The average adherence rate to the prescribed meditation was 71% among Calm app users, compared to 62% among POD users. Recruitment rate of men was 35% (29/83). Of those randomized to Calm, 55% (15/29) were men, and retention among them was higher (14/15, 93%) than that among women (12/20, 60%). No significant within or between group differences were observed. Conclusions: A 4-week, app-based mindfulness meditation intervention (Calm) may be feasible for middle-aged adults and a useful stress-management tool. Calm users expressed satisfaction with the app and felt it was appropriate and useful. Significant improvements in perceived stress and psychological outcomes or stress-related health behaviors were not observed. Even though men spent less time in meditation than women did and completed fewer weekly sessions, they were more likely to adhere to the prescription. Further research is needed for improving stress and stress-related outcomes among middle-aged adults with emphasis on the effects of mindfulness meditation apps for men. Trial Registration: ClinicalTrials.gov NCT04272138; https://clinicaltrials.gov/ct2/show/NCT04272138

Recent neighborhood studies have focused on longitudinal aspects of neighborhood change and data-mining methodologies that identify neighborhood trajectory patterns using time-series multivariate census data. Existing neighborhood trajectory models capture neighborhood change by stacking cross-sectional neighborhood clustering results across years and analyzing the discrete stepwise switching patterns between the clusters. Taking a different approach, we employ the functional data analysis (FDA) method to analyze longitudinal patterns of neighborhood change from mathematically represented multivariate time-dependent curves to identify neighborhood trajectory clusters. This FDA-based neighborhood trajectory model incorporates a multivariate functional principal component analysis and k-means clustering. We have applied our model to neighborhoods in the Charlotte and Detroit metropolitan areas to identify ongoing racial and socioeconomic segregation patterns and the time dynamics of neighborhood change.

There is limited understanding of how older adults evaluated the federal government’s COVID-19 response, despite their increased health risks during the pandemic and their important role in politics. We conducted qualitative thematic analysis on a nationally representative subsample of respondents aged 55+ from the COVID-19 Coping Study ( N = 500) who were asked: “How do you feel about federal government responses to and handling of the COVID-19 pandemic?” Analyses identified largely negative opinions about the federal government and former President Trump’s leadership, though some were neutral or positive. Participants expressed concerns that the federal government was undermining science, and that sending mixed messages about personal protective equipment and masks was dangerous. Perspectives were divergent and reflective of the country’s polarization surrounding COVID-19 policies. Results can inform efforts to build unity between political parties and identify strategies that governments can use to better respond to future public health crises.

This study uses the Current Population Survey to explore the intersections of gender, marriage, and parenthood on Asian American workers’ labor market outcomes. Asian Americans are unique socioeconomically compared to other racial/ethnic minority groups in the US that have been historically and contemporarily disadvantaged. Previous studies measuring the economic attainments of Asian Americans found that both men and women are nearing income parity with White Americans (Greenman 2010, Kim and Sakamoto 2010). However, this raises the question of whether familial factors (i.e., marriage and parenthood) differentially affect Asian American workers’ yearly income and how this may vary by gender at multiple points of the income distribution. I use OLS and quantile regression models to analyze the intraracial gender differences in income by marriage and parenthood factors. Among Asian American workers, I find that men benefit from both the fatherhood and marriage premium. Still, married fathers and single fathers have comparable income suggesting parenthood drives the overall increase in income rather than marriage. Asian American mothers are not affected by the motherhood penalty and see a slight increase in pay after having children, whereas married mothers show negligible differences in pay relative to single mothers. Further, there are larger pay discrepancies among workers in the upper third of the income distribution for married parents, suggesting there is still a gender pay gap regardless of the variation in marital and parental statuses. These findings imply that gendered and racialized views within the labor market influence the perceptions of Asian American workers and produce diverse economic outcomes.

Geographic inequality and racial disharmony are considered major factors in America's political divergence. This paper calculates geographic earnings inequality from 1960 to 2016 separately by race. From 2000 to 2016, White geographic inequality was significantly higher, and Hispanic geographic inequality was significantly lower, than Black and Asian geographic inequality. White geographic inequality rose from 1980 to 2008. Black and Hispanic geographic inequality fell from 1960 to 1980. Rural controls explain substantial shares of White geographic inequality in all years. Region and rural controls account for large shares of Black geographic inequality, especially from 1960 to 1990. Post-1990, geographic inequality changes are largely explained by changes in overall earnings inequality, but 1960–1990 changes are not. Between-race differences in geographic inequality translate into high-income metropolitan statistical areas having had, since 1980, significantly smaller shares of Whites among their low-income residents.

Data on women’s living conditions and socio-economic development are important for understanding and addressing the pronounced challenges and inequalities faced by women worldwide. While such information is increasingly available at the national level, comparable data at the sub-national level are missing. We here present the LivWell global longitudinal dataset, which includes a set of key indicators on women’s socio-economic status, health and well-being, access to basic services and demographic outcomes. It covers 447 regions in 52 countries and includes a total of 265 different indicators. The majority of these are based on 199 Demographic and Health Surveys (DHS) for the period 1990–2019 and are complemented by extensive information on socio-economic and climatic conditions in the respective regions. The resulting dataset offers various opportunities for policy-relevant research on gender inequality, inclusive development and demographic trends at the sub-national level.

Introduction: This study assesses the proportion of New York City Medicaid participants diagnosed with type 2 diabetes who did not have any claims for diabetes medication for an entire year and the association between nonuse of diabetes medication and subsequent hospitalizations. Methods: The 2014‒2016 New York State Medicaid claims data were used for this cohort study. Two types of hospitalizations were examined: all-cause hospitalizations and preventable diabetes hospitalizations. A potential association between medication nonuse and the number of hospitalizations in the following year was assessed using the negative binomial regression model, adjusting for individual- and neighborhood-level factors. The study was conducted in 2019‒2020. Results: Among the 117,183 individuals included in this study, 27.5% did not use any diabetes medication for an entire year. Compared with individuals using oral hypoglycemic medication only, the crude rate of all-cause hospitalizations among individuals who used no medication was approximately twice as high (37,111 vs 19,209 per 100,000 population), and the crude rate of preventable diabetes hospitalizations was almost 3 times as high (1,488 vs 537 per 100,000 population). Adjusting for individual- and neighborhood-level characteristics, medication nonuse was still associated with higher levels of all-cause hospitalizations (incidence rate ratio=1.26; 95% CI=1.21, 1.31) and preventable diabetes hospitalizations (incidence rate ratio=1.66; 95% CI=1.39, 1.99). Conclusions: Medication use and adherence are important for managing diabetes. However, almost 30% of New York City Medicaid participants with type 2 diabetes had no claims for diabetes medication for an entire year. Significantly higher hospitalization rates among this group warrant attention from providers and policy makers.

Objective Estimate agricultural work's effect on hemoglobin (Hgb) level in men. A negative effect may indicate presence of chronic kidney disease of uncertain etiology. Methods We use Demographic and Health Surveys data from seven African and Asian countries and use matching to control for seven confounders. Results On average, Hgb levels were 0.09 g/dL lower among agricultural workers compared with matched controls. Significant effects were observed in Ethiopia, India, Lesotho, and Senegal, with effects from 0.07 to 0.30 g/dL lower Hgb level among agricultural workers. The findings were robust to multiple control groups and a modest amount of unmeasured confounding. Conclusions Men engaged in agricultural work in four of the seven countries studied have modestly lower Hgb levels. Our data support integrating kidney function assessments within Demographic and Health Surveys and other population-based surveys.

We investigate the wage return to studying economics by leveraging a policy that prevented students with low introductory grades from declaring the major. Students who barely met the GPA threshold to major in economics earned $22,000 (46%) higher annual early-career wages than they would have with their second-choice majors. Access to the economics major shifts students' preferences toward business/finance careers, and about half of the wage return is explained by economics majors working in higher-paying industries. The causal return to majoring in economics is very similar to observational earnings differences in nationally representative data.

Landlord-tenant laws, which regulate the rights, duties, and responsibilities of landlords and their tenants, are primarily enacted by state governments. Resultantly, there is significant variation in the landlord-tenant policies governing the rental arrangements of American households depending on where they live. Given the conflicting results of existing research, little consensus has been reached on how landlord-tenant policies influence renter mobility - a complex topic related to positive and negative social outcomes. This study utilizes data from the Policy Surveillance Program and the 2019 Annual Social and Economic Supplement of the Current Population Survey to test the relationship between fifteen common landlord-tenant policies on the probability of a local, intracounty moves among renters while controlling for relevant environmental, socioeconomic, demographic, and familial factors. Multivariate analyses reveal evidence that some landlord-tenant policies do, in fact, have a significant effect on the likelihood of a local move. Secondly, the findings suggest that policies may interact in ways that significantly influence their joint effect on renter mobility.

There has been a recent surge in papers estimating local multiplier effects. However, existing studies rely on arbitrary periods of observation, limit samples to more populous regions, and commonly use relatively aggregated industrial categories. When we address these and other methodological issues, we find that, in the United States, each new traded sector job adds half a nontraded job to a local economy, and that the addition of each high-tech job adds less than one job to the local nontraded sector. Furthermore, we find that the multiplier effect of the manufacturing sector is no higher than the multiplier effect of the average traded sector. We provide robust evidence that higher-paying traded sectors yield more nontraded jobs than lower paying sectors, and that multiplier effects are higher in larger cities. Furthermore, we generate IV estimates that remedy weak instrument problems in the existing multipliers literature. These findings offer needed clarity on the likely employment impacts of incentive policies aimed at attracting industries in the traded sector of the economy.

This study demonstrates that the existing Labour Utilisation Framework does not appropriately measure the actual level of underemployment. Therefore, it proposes a Dynamic Labour Utilisation Framework (DLUF) that includes a systematic method for setting the underemployment threshold. Applying these methods using data from the United States suggests that the country has yet to attain full employment as the underemployment rate averaged 13.11% (±2.5) between 1999 and 2019. Furthermore, the threshold for underemployment varies widely across groups. For example, while adult men aged 25-54 would be willing to work for about 44.18 hours per week, same-age women, on the other hand, would only be available for about 38.17 hours per week, and young men and women aged 15-24 could work only for 26.81 hours.

Rosen (1974, 1979) and Roback (1982) imply that wage differentials across locations between similar workers arise from the differences in local amenities and cost of living. If the valuation of amenities varies across individuals (or groups of individuals), this affects the geographical sorting of households (Bayer and Timmins, 2007; Bayer et al., 2009; Lee, 2010; Moretti, 2013; Couture et al., 2019; Baum-Snow and Hartley, 2020). As a result, although the free mobility assumption ensures that the indirect utility of each worker type within the same group should be equalized across areas, this does not imply that interregional wage differentials should be the same for all groups of workers. The first essay proposes an approach to measuring interarea wage differentials by matching individuals with similar demographic and education characteristics to adjust for the effects of differences in preferences for local amenities and cost of living on wages. Given that the preferences for amenities, housing, and local public goods vary across individuals, workers are disaggregated into highly detailed subgroups based on their observable demographic characteristics under the hypothesis that people in the same group share similar utility functions and have similar preferences. The results show that disaggregating workers can overcome measurement problems in estimating amenity and house price variables commonly found in previous literature and can also adjust for preference heterogeneity across worker types. The results confirm the theoretical prediction that a commonly used aggregate Mincer equation underestimates the compensating variation required by the average worker, suggesting that disaggregating workers into highly detailed subgroups can be an effective method of explaining differences in intercity real wage differentials. The second essay applies the method developed in the first essay to investigate the effects of potential monopsony power on interregional wage differentials for a particular occupation. Current research investigates the effect of monopsony on wages by constructing a concentration measure (Herfindahl-Hirschman Index, for example) or estimating labor supply elasticity for a particular occupation or in a specific region. However, the problem with conducting direct tests for lower wages for a particular occupation that is susceptible to monopsony is that living cost and amenities also cause wage differentials. Higher wages for a given category of worker in city A than in city B might not arise just from a lower degree of monopsony, but from a higher cost of living or lower amenities in city A, and thus workers are paid more as compensation. The potential effect of monopsony on wages cannot be identified separately without adjusting for the effect of local cost of living and amenity differences, and thus classical Mincer-type wage equations with monopsony measures added could be subject to substantial omitted variable biases. The second essay matches each potentially monopsonized occupation with comparable occupations that are less prone to monopsony. Then, the effect of interregional differences in monopsony power for a particular occupation on interregional relative wage differentials with respect to a similar occupation is analyzed using five proxy measures of monopsony power taken from previous literature. The third essay concerns measurement of intercity differences in housing cost. Intercity housing price indexes that rely on median house price, pooled hedonic regressions, or repeat sales adjust imperfectly for differences in housing characteristics. In addition, intercity house price indexes that rely on asset value are a biased measure of differences in the rental price of housing, because capitalization rates vary dramatically across cities. To mitigate these shortcomings, the third essay creates a Fisher Ideal intercity housing price index for rental rates and asset value using a twofold Blinder-Oaxaca decomposition. The original method introduced in the third essay improves upon current house price indexes by allowing implicit prices to vary across locations.

We provide the first systematic account of summer declines in women’s labor market activity. From May to July, the employment-to-population ratio among prime-age US women declines by 1.1 percentage points, whereas male employment rises; women’s total hours worked fall by 11 percent, twice the decline among men. School closures for summer break—and corresponding lapses in implicit childcare—provide a unifying explanation for these patterns. The summer drop in female employment aligns with cross-state differences in the timing of school closures, is concentrated among mothers with young school-age children, and coincides with increased time spent engaging in childcare. Decomposing the gender gap in summer work interruptions across job types defined by sector and occupation, we find large contributions from both gender differences in job allocation and gender differences within jobs in the propensity to exit employment over the summer. Summer childcare constraints may contribute to gender gaps in career choice and earnings: women—particularly those with young school-age children—disproportionately work in the education sector, which offers greater summer flexibility but lower compensation relative to comparable jobs outside of education.

Gender inequality is one of the few fundamentally persistent inequalities within society, especially in the United States. This thesis will use a Marxist-feminist approach to explore the impact of the United States’ capitalist market economy on gender-specific public and private life structures. Specifically, how inequality is exacerbated as women transition to motherhood. This paper hypothesizes that a mandated paid parental leave would alleviate some of this ‘second burden’ by encompassing fathers in its eligibility. We formulate a difference-indifference model to estimate the causal effects of two current states who mandate paid parental leave and evaluate the average treatment effect when compared to the untreated group. Since the results do not provide support for the hypothesis, we present possible explanations for the limitations of the model and the data

This dissertation is comprised of three divergent chapters in macroeconomics. In the first chapter, I document how many countries have employment protections that create two-tiered labor markets in which some jobs are more secure than others. I model the selection of younger workers into more precarious jobs, as documented empirically. I then estimate the effects of changes to employment protection legislation. By including human capital accumulation in employment and human capital loss during unemployment, the effects of reducing employment protections differ qualitatively from previous work, which ignores the human capital channel. Reducing employment protections increases the job-finding rate for young workers while reducing average income and employment. This result is driven by lower average human capital in the economy without employment protections. The second chapter discusses how wage-proportional staffing fees provide motivation for domestically outsourced workers to invest less in human capital under certain conditions. This may partially explain why, after controlling for observables, workers in these positions earn about 10% less. I document wage and wage growth differences among workers in the employment services industry. A simple model with firm-specific skill investment is then used to generate endogenous firm-specific skill and wage differences between outsourced and non-outsourced workers. Additionally, the model shows how the prevalence of outsourcing responds to changes in policy and aggregate conditions. The third chapter considers policies to promote the spread of technologies that drive the growth of whole eras and entire sectors. Recent years have seen interest in using regulatory power to internalize the benefits of one such technology: broadband internet. This chapter develops a framework to study how competition among providers affects firm and household technology adoption and subsequent macroeconomic outcomes. With a novel data set on broadband availability, speed, and prices, a model of broadband provider entry and quality choice relates prices to market structure. These pricing results then inform a model of household and firm decisions. An additional provider is estimated to be most effective in boosting firm profitability in markets with relatively educated populations with previously few to no providers. In terms of increasing household adoption, an additional low-speed provider is most effective where median household income is low. An additional high-speed provider is most effective in markets with no high-speed and few low-speed providers.

The geographic mobility of citizens significantly influences the political effects of globalization. Within import-shocked regions, immobile voters support anti-trade populism while those who can migrate to globalizing cities favor trade openness. To test this theory, I train a machine learning model on 9.7 million Census observations of actual geographic mobility to predict an individual's probability of migrating between US commuting zones. I pair this with a panel of voters tracked across the 1992-1996 presidential elections, and a regional import shock from NAFTA between those elections. Among immobile respondents, NAFTA caused a 30 percentage point increase in the probability of voting for the anti-trade populist Ross Perot while mobile voters continued to support mainstream candidates. These patterns are consistent with NAFTA's effects on respondents' wages, employment, and trade policy preferences, but not with alternative cultural hypotheses. These findings challenge the growing consensus that economic concerns over trade have only muted political consequences.

Scholars have long debated whether home rule powers help improve municipal financial well-being; however, a consensus has yet to be reached. This study advances the home rule literature by causally estimating the impact of home rule in Texas on municipal revenue stability. To accomplish this, we employed a difference-in-differences estimator coupled with event-study specifications on a 40-year-long panel data set. This approach revealed strong empirical evidence that cities adopting a home rule charter had a significant reduction in the probability of experiencing revenue decline. This finding remained robust with multiple measures of revenue change, an alternative sample, and different model specifications. Moreover, we found that home rule cities’ revenue stability was likely to come from their increase in property taxes.

This paper studies how belief disagreement across households affects aggregate demand. I develop a model in which households are heterogeneously exposed to business cycles and show that the impact of disagreement can be summarized by a simple statistic-correlated disagreement which captures the correlation between beliefs and individual business-cycle exposure. I endogenize disagreement via heterogeneous attention, which implies that attention increases with exposure. So, correlated disagreement is positive. Then, I show that disagreement amplifies general-equilibrium effects and acts as a propagation mechanism amplifying business cycles. I also provide evidence of this positive correlation using survey data on expectations. To quantify the implications of disagreement, I extend the analysis to a Heterogeneous-Agent New Keynesian model featuring multiple sources of heterogeneity. I show that belief disagreement can substantially amplify business-cycle fluctuations. Finally, I show that targeting spending to the most cyclical workers can significantly increase the spending multiplier.

Health disparities between different racial/ethnic groups in the United States are substantial. When reviewed across an extensive body of literature, these disparities have been demonstrated to persist even when socioeconomic status, geographic region, health conditions, treatment methods, and patient access-related variables are controlled for. This ultimately leads to higher mortality rates among minority patients, making disparities in health a highly prevalent issue. However, the literature suggests that while racial and ethnic disparities in health have been widely examined, research documenting the evolution of these changes over time is lacking. This motivates the research questions: (1) How has the impact of racial biases on disparities in health outcomes evolved over the past decade?; (2) To what extent do race and ethnicity impact variation in health outcomes?; and (3) To what extent are race and ethnicity correlated with the socioeconomic gradient in health?; Last, (4) How present were these disparities when looking at outcomes related to the COVID-19 Pandemic? This thesis aims to address these questions through a two-part empirical analysis using publicly available data from the National Health Interview Survey (NHIS) and the COVID-19 Case Surveillance Public Use Dataset from the Centers for Disease Control and Prevention (CDC).