Using data from the two cohorts of the NLSY, we examine whether income losses due to involuntary job separations have changed over time. We find that wage losses among men are similar between the two cohorts. However, women in the 1979 cohort show little evidence of wage losses while women in the 1997 cohort experience wage losses similar to those of men. We present evidence that changes in occupations across cohorts help explain these results.

We evaluate how extractive capacity and migration respond to the introduction of the income tax, drawing on novel panel data on U.S. states from 1900 to 2010. States which introduced the income tax experienced a 15 percent increase in revenue per capita over the long run. However, there was no long-term increase in the absolute level of revenue. To explain this divergence, we document how the introduction of the income tax induced significant outmigration to nonincome tax states. Our analysis suggests that migration responds more to tax introductions than to equivalent increases in existing taxes.

Government agencies and academic researchers typically report the size and legal composition of the foreign-born population as point estimates. As these estimates are generally produced using survey data, they are impacted by both sampling and nonsampling error. This paper considers nonsampling error due to item nonresponse in the estimates of the size and legal composition of the foreign-born produced using the American Community Survey. The standard practice to deal with item nonresponse is to impute values under the assumption that nonresponse is conditionally random. We follow a procedure that allows us to form credible interval estimates that make no assumptions about the values of missing data by taking into account all uncertainty due to item nonresponse. Without any assumptions on the distribution of citizenship status among non-respondents, the size of the foreign-born population in the US falls somewhere between 40.4 and 59.4 million as of 2019 compared to the Census estimate of 44.9 million. When taking into account item nonresponse from all questions used in the imputation procedure to assign legal status, the size of the undocumented population fall between 7.3 and 18.3 million compared to the widely accepted estimate of 11 million undocumented immigrants.

We present a two-area endogenous growth model where abstract knowledge flows at no cost across space but tacit knowledge arises from the interaction among researchers and is hampered by distance. Digital communication reduces this “cost of distance” and reinforces productive specialization, leading to an increase in the system-wide growth rate but at the cost of more inequality within and across areas. These results are consistent with evidences on the rise in the concentration of innovative activities, income inequality, and skills and income divergence across US urban areas.

Study Objectives: Over 75% of US high school students obtain insufficient sleep, placing them at risk for adverse health outcomes. Identification of modifiable determinants of adolescent sleep is needed to inform prevention strategies, yet little is known about the influence of the built environment on adolescent sleep. Methods: In this prospective study, actigraphy was used to assess sleep outcomes among 110 adolescents for 14 days each in eighth and ninth grades: duration (hours/night), onset and offset, and sleeping ≥8 hours. Home addresses were linked to built environment exposures: sound levels, tree canopy cover, street density, intersection density, population density, and housing density. Mixed-effects regression estimated associations of built environment measures with sleep outcomes, adjusting for sex, race, parent education, household income, household size, grade, weeknight status, and neighborhood poverty. Results: A 1-standard deviation (SD) increase in neighborhood sound was associated with 16 minutes later sleep onset (β = 0.28; 95% confidence interval (CI): 0.06, 0.49) and 25% lower odds of sleeping for ≥8 hours (odds ratio (OR) = 0.75, 95% CI: 0.59, 0.96). A 1-SD increase in neighborhood tree canopy was associated with 18 minutes earlier sleep onset (β = -0.31, 95% CI: -0.49, -0.13) and 10 minutes earlier sleep offset (β= -0.17, 95% CI: -0.28, -0.05). No associations were observed for density-based exposures. Conclusions: Higher neighborhood sound level was associated with lower odds of sufficient sleep, while higher tree canopy cover was associated with more favorable sleep timing. Neighborhood sound levels and tree canopy cover are potential targets for policies and interventions to support healthier sleep among adolescents.

We argue that employers subject workers to time theft by controlling workers’ time—both on and off the clock. Time theft considers employer control of workers’ time without the promise of pay through unstable scheduling practices as well as beyond their scheduled work hours. We develop a typology of time theft through a discussion of survey and workshop data with retail workers in Los Angeles. We underscore how federal labor law is inadequate to address unstable scheduling and we discuss retail worker organizing and the implications of time theft for labor policy and worker movements.

This article examines referendums for open space conservation, focusing on an assessment of their likelihood in cities. It presents data on conservation referendums, over 15 years, based on the Trust for Public Land’s LandVote® database. Economic and institutional factors of influence are explored across cities, testing whether those factors explain differences in the likelihood of referendums and their passage. One finding is that the frequency of conservation referendums varies dramatically across American cities. Additional findings, from a pooled time-series analysis, are that economic and institutional contexts of cities affect the likelihood of conservation referendums. The likelihood of referendums and their passage is further tested across alternative models to evaluate the robustness of the findings. While its central contribution is to research on local referendums, the article connects to the political market framework to identify factors influencing the likelihood of open space referendums.

The COVID-19 pandemic has prompted many school districts to turn to distance or at-home learning. Studies are emerging on the negative effects of distance learning on educational performance, but less is known about the socio-economic, geographic, and demographic characteristics of students exposed to distance-learning. We introduce a U.S. School Closure & Distance Learning Database that tracks in-person visits across more than 100,000 schools throughout 2020. The database, which we make publicly-accessible and update monthly, describes year-over-year change in in-person visits to each school throughout 2020 to estimate whether the school is engaged in distance learning. Our findings reveal that school closures from September to December 2020 are more common in schools with lower third-grade math scores and higher shares of students who are racial/ethnic minorities, who experience homelessness, are of limited English proficiency, and are eligible for free/reducedprice school lunch. The findings portend rising inequalities in learning outcomes.

PURPOSE: In East Africa, cervical cancer is a leading cause of morbidity and mortality among women diagnosed with cancer. In this study, we describe the burden of risk factors for cervical cancer among women of reproductive age in five East African countries. METHODS: For each country, using STATA13 software and sampling weights, we analyzed the latest Demographic and Health Survey data sets conducted between 2014 and 2017 in Burundi, Kenya, Rwanda, Tanzania, and Uganda. We included women age 15-49 years and considered six risk factors (tobacco use, body mass index, age at first sexual intercourse, age at first birth, number of children, and hormonal contraceptive use). RESULTS: Of the 93,616 women from the five countries, each country had more than half of the women younger than 30 years and lived in rural areas. Pooled proportion of women with at least one risk factor was 89% (95% CI, 87 to 91). Living in a rural area in Burundi (adjusted incidence rate ration 0.94; 95% CI, 0.9 to 0.99; P = .019) and Rwanda (adjusted incidence rate Ration 0.92; 95% CI, 0.88 to 0.96; P < .001) was associated with a lower number of risk factors compared with living in an urban area. In all the countries, women with complete secondary education were associated with a lower number of risk factors compared with those with no education. CONCLUSION: This study reveals a high burden of risk factors for cervical cancer in East Africa, with a high proportion of women exposed to at least one risk factor. There is a need for interventions to reduce the exposure of women to these risk factors.

Inter-regional migration – the movements of the population from one region to another within the same country – can be an important mechanism of spatial economic adjustment, affecting regional demographic and growth patterns. This paper examines the economic and housing-related factors that affect the decision of people to migrate to another region within the same country, drawing empirical evidence from country-specific gravity models of inter-regional migration for 14 OECD countries. The results suggest that inter-regional migrants move in search of higher income and better employment opportunities, but are discouraged by high housing costs. In particular, house prices are found to be an important barrier to migration, especially in countries having experienced strong increases in the level and cross-regional dispersion of house prices. There is however large heterogeneity across countries in terms of what factors matter the most and in terms of the magnitude of the migration response.

BACKGROUND: The federal government uses multiple definitions for identifying rural communities based on various geographies and different elements of rurality. OBJECTIVES: The objectives of this study were to: (1) assess the degree to which rural definitions identify the same areas as rural; and (2) assess rural-urban disparities identified by each definition across socioeconomic, demographic, and health access and outcome measures. RESEARCH DESIGN: We determined the rural status of each census tract and calculated the rural-urban disparity resulting from each definition, as well as across the number of definitions in which tracts were designated as rural (rurality agreement). SUBJECTS: The population in 72,506 census tracts. MEASURES: We used 8 federal rural definitions. Population characteristics included percent with a bachelor's degree, income below 200% poverty, population density, percent with health insurance and whether various health care services were within 30 minutes driving time of the tract centroid. RESULTS: The rural population varied from slightly < 6.9 million people to >75.5 million across definitions. The largest rural-urban disparities were found using Urban Influence Codes. Urbanized Area and Urbanized Cluster tended to generate smaller disparities. Population characteristics such as population density and percent White had notable discontinuities across levels of rurality, while others such as percent with a bachelor's degree and income below 200% poverty varied continuously. CONCLUSIONS: Rural-urban populations and disparities were sensitive to the specific definition and the relative strength of definitions varied across population characteristics. Researchers and policymakers should carefully consider the choice of outcome and region when deciding the most appropriate rural definition.

Prior research has shown improvements in low-income individuals' financial well-being as a consequence of the Affordable Care Act's Medicaid expansion. Given the connection between financial well-being and housing, we investigate the extent to which the provision of Medicaid to previously ineligible, low-income childless adults affects their household composition. Using a staggered adoption difference-in-differences design on an urban sample of individuals with less than a high school degree, we find that 26 to 39 year olds experience a significant 4.2% decline in the number of individuals living in the household, which is due to living with fewer extended family members. At the same time, 26 to 39 year olds experience a relatively smaller decline in the number of rooms (1.8%), leading to a 3.1% reduction in the level of household crowding, as measured by persons per bedroom. These reductions in household crowding are strongest for Hispanic individuals and those living in areas with above-median housing costs. In comparison, there are no significant impacts on household composition for 40 to 64 year olds as a consequence of the policy.

Private-sector unionization rates have fallen precipitously in the United States over the past half century, from 25% in 1973 to only 7% in 2018. We take a skill-based approach to studying this decline, using data from the Current Population Survey combined with occupation-specific task requirements from the Dictionary of Occupational Titles and the Occupational Information Network. We find that for both men and women, private sector unionized jobs became higherskilled by requiring more non-routine, cognitive skills and fewer manual or routine skills. We further show that union, non-union skill differences have polarized, with unionized worker occupations becoming relatively more intensive in non-routine, cognitive skills and in manual/routine skills. These changes have been more pronounced for women than for men. Next, we decompose these skill changes into three parts: (1) changes in skills within an occupation, (2) changes in worker concentration across existing occupations, and (3) changes to the occupational mix from both entry and exit. Most of the skill changes we document are driven by the second two forces. The third part of the analysis estimates union wage premiums that account for changing skill mix. We find that accounting for skills has a small effect on the union wage premium and that the premium remains high at over 20% for both men and women. Finally, we show how this evidence can be reconciled with a model of skill-biased technological change that explicitly accounts for the institutional framework surrounding collective bargaining.

Objective: To contextualize experiences of activities during the day and investigate whether the contour of the day is correlated with well-being during activities. Methods: Drawing on American Time Use Surveys, we employ sequence and cluster analyses to create distinct typologies of daily life patterns, and bivariate analyses to describe whether well-being across activities varies by these typologies. Results: We identified four typologies characterized by different primary activity of the day: leisure (22.7%), TV (22.4%), housework (47.5%), and work (7.5%). Individuals in the work and leisure clusters tend to report more positive well-being and individuals in the housework and TV clusters tend to report more negative well-being in experiences of activities during the day. We also found that well-being experiences in the same activity differed across individuals in the different typologies. Conclusion: Understanding the daily life patterns of older adults may be important, given its correlation with well-being during activities.

This paper examines the persistent effects of eliminating tariffs on Mexican imports, following the implementation of the North American Free Trade Agreement (NAFTA), on Americans’ human capital investment. We leverage quasi-experimental changes in tariffs on Mexican imports following NAFTA across birth cohorts and within states. We show that NAFTA increases the probability of ever attending college and earning a degree. These results, however, mask important heterogeneous effects within the sample. In terms of race and ethnicity, gender, and their intersection, we find white Americans drive these positive effects, which in turn are smaller for white women. In contrast, the educational attainment of racial and ethnic minorities, especially men, shrank under NAFTA, decreasing their probability of graduating from high school.

One of the most concerning aspects of the ongoing COVID-19 pandemic is that it disproportionately affects people from some specific ethnic and socio-economic minorities. In particular, since from the beginning of the pandemic it has been clear that people from Black and African American backgrounds seem to be hit especially hard by the virus, creating a substantial infection gap. The observed abnormal impact on these ethnic groups could probably be due to the co-occurrence of other known risk factors, including co-morbidity, poverty, level of education, access to healthcare, residential segregation and response to cures, although those factors do not seem able to explain fully and in depth the excess incidence of infections and deaths among African Americans. Here, we introduce the concept of diffusion segregation, that is the extent to which a given group of people is internally clustered or exposed to other groups, as a result of mobility and commuting habits. By analyzing census and mobility data on major US cities, we found that the weekly excess COVID-19 incidence and mortality in African American communities at the beginning of the COVID-19 pandemic is significantly associated with their level of diffusion segregation. The results confirm that knowing where people commute to, rather than where they live, is potentially much more important to contain and curb the spreading of infectious diseases.

This dissertation consists of three essays on self-employment, income taxation, non-compete agreements, and sports betting. First two essays aim to measure the impact of economic incentives on entrepreneurs. I examine government interventions such as noncompete agreements (NCA) policy and taxation and their effects on entrepreneurial activity in the United States. Third essay examines the growth and variability of the novel tax base sports betting. First chapter splits self-employment, which has mostly been used as a proxy for entrepreneurship, into two different entrepreneur types with incorporated and unincorporated businesses. I examine how these two types differ in sensitivity to individual-specific marginal and average personal income tax rates in the US. I analyze the probability of becoming an incorporated or unincorporated self-employed worker by utilizing IV models. I use the Annual Social and Economic (ASEC) rotating panel data of the Current Population Survey (CPS) from 2005 to 2019 to track a paid employee's decision to become self-employed. My empirical findings show that reducing personal income tax rates increase overall self-employment activity. Higher personal income tax rates encourage incorporated entrepreneurship but discourage unincorporated entrepreneurship. These results imply that future research and tax policy should take into account that different types of entrepreneurs respond differently to tax incentives. Second chapter investigates how NCA policies affect different types of entrepreneurship with incorporated and unincorporated businesses. We exploit policy changes as quasi-experiments in Utah in 2016 and in Massachusetts in 2018. Both states decreased the enforceability of NCAs by limiting the duration of the NCAs to one year, and in addition, Massachusetts banned non-compete agreements for low-wage workers. We estimate the effects of the reforms on the probabilities of being either type of entrepreneur using Synthetic Control Methods and difference-in-differences regressions based on the American Community Survey (ACS) data. Our findings show that the decrease in the enforceability of NCAs in Massachusetts resulted in a higher rate of unincorporated entrepreneurship, while there was no sizable effect on the rate of incorporated entrepreneurship. For Utah, our results indicate that the reform increased both types of entrepreneurship. The findings imply that states can promote entrepreneurial activity by reducing the enforceability of NCAs, and the way of changing the enforceability of NCAs matters, as different provisions encourage different types of entrepreneurship in a given state. Third chapter examines Nevada’s gross sports revenue as an actual tax base in terms of growth and volatility. In May 2018, the US Supreme Court overturned the Professional and Amateur Sports Protection Act which limited gambling on sports to four states (Nevada, Delaware, Oregon, and Montana). Since the court’s decision, twenty five states have legalized sports betting, with nineteen of those having launched statewide sports wagering as of November 2020. The primary catalyst behind this legalization is the generation of tax revenue. What is the growth potential of sports betting? Will sports betting be a volatile or stable source of tax revenue? To address these questions, this paper examines sports betting revenue in Nevada from 1990 to 2019. Nevada provides a unique case study in that, prior to the Supreme Court decision, it was the only state to provide fullfledged sports betting and it is the only state that provides sufficient data for empirical analysis. Long-run (growth) and short-run (volatility) relationships between total sports gambling revenue and personal income are estimated using state-level gambling revenue and income. Estimates for individual sports (football, basketball, baseball, and racebook/horse races) are also provided. Inferences about the importance of online betting are made using data from New Jersey. This is the first study analyzing the growth and volatility of sports gambling revenues in the United States. We contribute to the broader literature that analyzes the growth and volatility of more traditional tax bases (i.e., sales tax, personal income tax, and casino gambling tax). Our findings suggest that sports gambling grows at a similar rate as state income and is stable and insensitive to short-run shocks to income. Sports betting revenue offers a long-term growth potential that is lower than the personal income tax elasticity but similar to casino gambling and sales tax. However, the amount of money retained by casinos from sports betting, and hence the state, is small compared to other traditional tax bases.

We construct the first long-term comparison of cross-sectional and panel estimates of immigrant earnings assimilation in the United States from a single data source. Unlike previous results, we find that selective out-migration of higher-earning immigrants biases downward cross-sectional estimates for all education groups. Cross-sectional estimates dramatically understate earnings growth for high-skilled foreign-born workers. The bias stems from both selective out-migration and selective employment; among high-skilled immigrants, low earners find employment with a substantial delay, while high earners work immediately on arrival. We present suggestive evidence that the H-1B visa program may play a role in estimated immigrant earnings dynamics.

Immigration policymaking has been active at the local level in the United States over the past few decades. This study examines whether the economic development-oriented immigrant-welcoming efforts that started in 2010 in Detroit have increased the local immigrant population. It uses the synthetic control method to construct a comparison region that resembles Detroit in the preintervention periods to serve as a counterfactual. Empirical results reveal a statistically significant increase in the immigrant share of the population in the metropolitan area during the postintervention period of 2011–2014. The increase is robust to various sets of specifications and placebo tests. The share of high-skilled immigrants in the local population also increased during this time, albeit with a weak statistical significance. These findings point to the potential of immigrant-welcoming programs in attracting and retaining immigrants and immigrant talent.

This paper shows that rising income inequality reduces job creation at small firms. High-income households save relatively less in the form of bank deposits while small firms depend on banks. We argue that a higher share of income accruing to top earners therefore erodes banks' deposit base and their lending capacity for small businesses, thus reducing job creation. Exploiting variation in top incomes across US states and an instrumental variable strategy, we establish that a 10 percentage point (pp) increase in income share of the top 10% reduces the net job creation rate of small firms by 1.5–2 pp, relative to large firms. The effects are stronger at smaller firms and in bank-dependent industries. Rising top incomes also reduce bank deposits and increase deposit rates, in line with a reduction in the supply of household deposits. We then build a general equilibrium model with heterogeneous households that face a portfolio choice between high-return investments and low-return deposits that insure against liquidity risk. Banks use deposits to lend to firms of different sizes subject to information frictions. We study job creation across firm sizes under counterfactual income distributions.