Using 1990 5% Census and American Community Survey data, we examine the economic integration of Afghan refugees to the US, focusing on employment rates and income levels. First-wave Afghan refugees (those arriving 1980–90) have made significant income and employment gains, while poverty rates and reliance on government assistance have decreased dramatically. The most recent wave is not doing as well at comparable points in time. Controlling for factors such as cultural capital, cost of living, and length of residence in the US, Afghan refugees’ incomes are the lowest of seven refugee/immigrant comparison groups. This is largely explained by lower employment levels, especially among less-educated Afghan women and highly educated Afghan women and men. Factors explaining this may include Afghans’ strong gender division of labour, greater levels of physical and mental disability resulting from pre-migration and migration traumas, and inability to develop occupational niches providing pipelines to jobs for recent arrivals and less-educated women. Highly educated Afghan refugees’ lower income is largely explained by the low incomes of those who earned their credentials outside the US. Although unmeasured, we suspect some of the unexplained direct negative effect of Afghan refugees on income is explained by anti-Muslim and anti-Afghan prejudice.

This thesis has three separate parts. In the first part I report the first ex post study of the economic impact of sea level rise. I apply two econometric approaches to estimate the past effects of sea level rise on the economy of the USA, viz. Barro type growth regressions adjusted for spatial patterns and a matching estimator. The unit of analysis is 3063 counties of the USA. I fit growth regressions for 13 time periods and I estimate numerous varieties for both growth regressions and matching estimator. Although there is some evidence that sea level rise has a positive effect on economic growth, in most specifications the estimated effects are insignificant. Therefore, I cannot confirm the implicit assumption of previous ex-ante studies, in particular that sea level rise has in general negative effect on economies. In the second part I fit Ricardian regressions of agricultural land values for 2830 counties of the USA on past sea level rise, taking account of spatial autocorrelation and heteroscedasticity. I find a significant, hill-shaped relationship. Hence, the outcomes are mixed. Mild sea level rise increases, while more pronounced sea level rise causes land values to fall. The results are robust to a set of variations. In the third part I explore an unprecedented dataset of almost 6,000 observations to identify main predictors of climate knowledge, climate risk perception and willingness to pay (WTP) for climate change mitigation. Among nearly 70 potential . . .

At the heart of urban economics are agglomeration economies, which drive the existence and extent of cities and are also central to structural transformation and the urbanization process. This paper evaluates the use of different measures of economic density in assessing urban agglomeration effects, by examining how well they explain household income differences across cities and neighborhoods in six African countries. We examine simple scale and density measures and more nuanced ones which capture in second moments the extent of clustering within cities. The evidence suggests that more nuanced measures attempting to capture within-city differences in the extent of clustering do no better than a simple density measure in explaining income differences across cities, at least for the current degree of accuracy in measuring clustering. However, simple city scale measures such as total population are inferior to density measures and to some degree misleading. We find large household income premiums from being in bigger and particularly denser cities over rural areas in Africa, indicating that migration pull forces remain very strong in the structural transformation process. Moreover, the marginal effects of increases in urban density on household income are very large, with density elasticities of 0.6. In addition to strong city level density effects, we find strong neighborhood effects. For household incomes, both overall city density and density of the own neighborhood matter.

This paper examines the role of labor market frictions and moving costs in explaining the migration behavior of US workers by employment status. Using data on low-skilled workers from the Survey of Income and Program Participation (SIPP), I estimate a dynamic model of individual labor supply and migration decisions. The model accounts for the fact that geographical moves are not random, and that workers may move for reasons unrelated to the labor market. My estimates show that moving costs are substantial, and that labor market frictions particularly inhibit movement of the employed. I use the model to study migration responses to local labor market shocks and to a moving subsidy. Workers' preferences for non-market amenities, coupled with substantial moving costs and employment frictions, grant market power to incumbent employers. This market power is most likely to exist in specialized industries where within-location job hopping is infeasible.

This paper documents a rise in high-technology workers in the financial services sector and finds evidence that financial regulation has contributed to this change in labor force composition. First, we show that the share of science, technology, engineering, and math (STEM) workers in finance has grown from 6.7% to 9.4% over the past decade, moderated by a 4.9% decline in their earnings premium. Moreover, the overall increase in STEM workers is heavily concentrated in metropolitan areas that have a higher finance employment share. Second, we estimate how financial regulation has affected the composition of jobs in financial services. Using data from QuantGov as well as a difference-in-difference estimator motivated by differential exposure to post-crisis regulatory reforms, we show that regulation increases the share of STEM workers and crowds out employment in more routine occupations.

This dissertation covers the topics of substance abuse, crime, health insurance, and child maltreatment. Demand-side approaches should be strongly considered when attempting to combat America’s illegal drug problems. Implementing an identification strategy that leverages variation driven by substance-abuse-treatment facility openings and closings measured at the county level, estimations show that substance-abuse-treatment facilities reduce both violent and financially motivated crimes in an area. These effects are particularly pronounced for relatively serious crimes. There is a role the employment relationship plays in determining the provision of health benefits at the establishment level. Using restricted data from the Medical Expenditure Panel Survey Insurance Component (MEPS-IC) and the Coarsened Exact Matching technique, the analysis extends previous studies by testing the relationships between premium costs, employment relationships, and the provision of health benefits between 1999 and 2012. Both establishment- and state-level union densities increase the likelihood of employers providing health plans, while right-to-work legislation depresses the provision. Furthermore, state-level union density reduces the adverse impact of premium costs. These results indicate that the declining provision of health benefits is in part driven by the transformation of the employment relationship in the United States and that labor unions remain a critical force in sustaining employment sponsored healthcare coverage over the past two decades. Child maltreatment is vastly underreported. School attendance takes children out of the home and places them under the supervision of educators trained to notice symptoms of abuse and neglect. Using state-age level enrollment data, estimations show that school attendance increases maltreatment reporting by 77%. This increase stems solely from reports initiated by educators with no evidence that these reports crowd out reporting from other entities. The effect is not caused by seasonal maltreatment nor hypersensitivity in reporting from educators

Importance Aging adults face unique barriers to care and have unique health care needs with a high prevalence of chronic conditions. A high proportion of individuals in this group have voice disorders, in part due to age-related changes in laryngeal anatomy and physiologic features. These disorders contribute significantly to health care costs and remain poorly understood. Objective To describe sociodemographic characteristics and response to treatment among aging adults with voice disorders. Design, Setting, and Participants A cross-sectional study using the 2012 National Health Interview Survey was used to evaluate adults who reported voice disorders in the past 12 months. Self-reported demographics and data regarding health care visits for voice disorders were analyzed. Statistical analysis was conducted from March 1, 2017, to February 1, 2018. Main Outcomes and Measures Self-reported voice disorders, whether or not treatment was sought, which types of professionals were seen for treatment, and whether or not the voice disorder improved after treatment. Results Among 41.7 million adults in the United States 65 years or older, 4.20 million (10.1%; 2 683 199 women and 1 514 909 men; mean [SE] age, 74.5 [0.3] years) reported having voice disorders. Of those with voice disorders, 10.0% (95% CI, 8.3%-11.7%) sought treatment. Of individuals seeking treatment, 22.1% (95% CI, 7.9%-36.3%) saw an otolaryngologist and 24.3% (95% CI, 10.6%-38.0%) saw a speech language pathologist. By controlling for race/ethnicity, income, sex, and geography, it was found that men were less likely than women to report voice disorders (36.1% [95% CI, 31.7%-40.5%] vs 63.9% [95% CI, 59.5%-68.3%]; odds ratio, 0.70; 95% CI, 0.57-0.86). Race/ethnicity, income, and geography were not significantly associated with the likelihood that an individual 65 years or older reported voice disorders. A greater percentage of elderly adults seeking treatment than not seeking treatment reported improvement in symptoms (32.4%; 95% CI, 17.9%-47.0% vs 15.6%; 95% CI, 10.4%-20.8%). Among adults treated for a voice disorder, a lower proportion of adults 65 years or older reported improvement in symptoms with treatment compared with adults younger than 65 years (32.4%; 95% CI, 17.9%-47.0% vs 56.0%; 95% CI, 42.5%-69.6%). Conclusions and Relevance A small percentage of older adults with voice disorders seek treatment; even fewer are treated by an otolaryngologist or a speech language pathologist. A greater percentage of those who undergo treatment experienced symptomatic improvement compared with those who did not undergo treatment. These trends highlight the need for greater access to and awareness of services available to older adults with voice disorders.

Health care has been cited as a job engine for the U.S. economy. This study used the Current Population Survey to examine the sector and occupation shifts that underlie this growth trend. Health care has had a cyclical relationship with retail trade, leisure and hospitality, education, and professional services. The entering workforce has been increasingly taking on low-skilled occupations. The exiting workforce has not been necessarily retiring or going back to school, but appeared to be leaving without a job, with potentially more child care duties, and with high rates of disability and poverty levels. This study also found that the number of workers staying in health care has been slowly declining over time. As the United States moves toward team-based care, more attention should be paid to the needs of the lower skilled workers to reduce turnover and ensure delivery of quality care.

Partnering with the US Census Bureau, we implement a new survey of “structured” management practices in two waves of about 35,000 manufacturing plants each in 2010 and 2015. We find enormous dispersion of management practices across plants, with 40% of this variation across plants within the same firm. This variation in management practices accounts for about a fifth of the spread of productivity, a similar fraction as that accounted for by R&D, and larger than the fraction explained by ICT and human capital. Management practices are more predictive of long-term survival than productivity. We find causal evidence that two drivers are very important in improving management. Regulation of the business environment (as measured by the Right-toWork laws) boosts management practices associated with incentives. Learning spillovers as measured by the arrival of large new entrants in the county (“Million Dollar Plants”) increases the management scores of incumbents.

I use new data on employment and job placements during WWII to characterize the wartime surge in female work and its subsequent impact on female employment in the United States. The geography of female wartime work was primarily driven by industrial mobilization, not drafted men’s withdrawal from local labor markets. After the war, returning veterans and sharp cutbacks in war-related industries displaced many new female entrants, despite interest in continued work. As a result, areas most exposed to wartime work show limited overall effects on female labor force participation in 1950 and only marginal increases in durables manufacturing employment.

I exploit differences in the generosity of unemployment insurance (UI) benefits across states and over time to investigate the link between UI and children's academic achievement. Estimates show that a 1% increase in maximum weekly UI benefits reduces the probability that a child repeats a grade by around 0.03 percentage points. The effect is concentrated among children of low‐ and middle‐income families. This paper's findings, which are the first in the literature to show evidence of a positive effect of UI on children's educational outcomes, provide insight into the role of UI in the human capital accumulation of children.

This dissertation explores individuals’ investment in human capital and how that interacts with public policy interventions. I focus on two forms of investment in human capital: investments in skills and health. First, I focus on parents’ investment in children and parental labor supply and asset accumulation decisions as they interact with private schooling. Second, I investigate whether individuals rely on outside sources of information, such as expert reviews and word-of-mouth, when making investments in their health. In the first chapter, “Dynamic Female Labor Supply, Investment in Children and Private Schooling”, I explore how the private schooling investment decision for the child affects maternal labor supply and savings over the life cycle. Women with children face a well-known trade-off between working, which allows greater monetary investments in children, and spending more time with the child. I build and estimates a dynamic model of female labor supply to investigate how the option of private schooling affects this trade-off. The model extends existing work on female labor supply and children by incorporating private versus public schooling choice, allowing for risk aversion and savings, and nesting within the model a child ability production function. Results of the structural estimation show that mother’s time with the child and private schooling are complements, and that the availability of private schooling leads to more work and more saving among less educated women. However, more educated women drop out of the labor force and increase the time they spend with their child when the child is going to private elementary school. In addition, I estimate the price elasticity of private school enrollment to be -0.25. Policy simulations show that targeted private school subsidies to low income and less educated mothers can reduce inequality in children’s outcomes. Moreover, by inducing women to increase their labor supply to be able to top up subsidies and send their children to private schools, targeted subsidies can help women at the margin accumulate higher assets and experience wage growth of up to 20 percent over the life cycle. The second chapter of the dissertation, titled “Housing Demand and Private Schooling ”, studies the effect of house price increases on the choice to enroll children in private schools. I exploit cross-city variation in local housing booms during the 2000s, which increased net worth of households and allowed them to borrow using home equity lines of credit. To establish a causal relationship between the housing boom and the demand for private schooling, I employ instrumental variables tech- niques used in the literature studying the effects of the house price boom on different facets of the economy. Results show that a one standard deviation larger increase in local housing demand shock of 2000-2006 increased average private school enrollment by 18%. However, this increase was counteracted by an equal decline in private school enrollment during the subsequent housing bust starting in 2007. This indicates that changes in parental income can have significant effects on the choice of schooling and that the housing boom of 2000s can potentially have lasting positive effects on the human capital of the next generation. In the third chapter, “Positively Aware? Conflicting Expert Reviews and De- mand for Medical Treatment”, which is joint work with Nicholas Papageorge and Jorge Balat, we study the impact of expert reviews on the demand for HIV treat- ments. Reviews are provided by both a doctor and an activist in the HIV lifestyle magazine Positively Aware, which we merge with detailed panel data on HIV-positive men’s treatment consumption and health outcomes. To establish a causal relationship between reviews and demand, we exploit the arrival of new drugs over time, which provides arguably random variation in reviews of existing drugs. We find that when doctors and activists agree, more positive reviews increase demand for HIV drugs. However, doctors and activists frequently disagree, most often over treatments that are effective but have harsh side effects, in which case they are given low ratings by the activist but not by the doctor. In such cases, relatively healthy consumers favor drugs with higher activist reviews, thus defying the doctor, which is consistent with a distaste for side effects. This pattern reverses for individuals who are in worse health and thus face stronger incentives to choose more effective medication despite side effects. Findings suggest that consumers demand information from experts according to the trade-offs they face when making health investments in the presence of adverse treatment side effects.

EXECUTIVE SUMMARY Critics of immigration often allege that immigration worsens US-born workers' labor market outcomes, such as their employment and earnings. A large body of economic research has examined how immigration has affected natives' wages. Most of these studies have concluded that immigration has little or no adverse effect on US natives' wages. However, few studies have examined other key dimensions of US natives' success in the labor market: unemployment and labor force participation. Understanding how immigration affects unemployment and labor force participation among US natives is important for several reasons. The foreign-born share of the population is the highest in a century, and immigrants account for 1 in 6 workers. Although unemployment is currently near a record low, it soared during the Great Recession of 2007-2009 and was slow to return to pre-recession levels. Labor force participation, meanwhile, has been declining for years, a trend that accelerated with the recession and has yet to reverse. Unemployment and labor force participation are markedly worse among disadvantaged groups, such as less-educated workers, that may compete the most intensively with immigrants in the United States. This study examines the relationship between immigrants' share of the labor force and US natives' unemployment and labor force participation rates using comprehensive data from 2005-2013. The study controls for economic conditions that may affect the number of immigrants in a state and presents two-stage least squares estimates that control for endogeneity. The results of the state-level analysis indicate that immigration does not increase US natives' unemployment or reduce their labor force participation. Instead, having more immigrants reduces the unemployment rate and raises the labor force participation rate of US natives within the same sex and education group. Specifically, this study finds: • A 1 percentage point increase in the share of the labor force comprised of immigrants appears to reduce the unemployment rate of US natives in the same sex-education group by 0.062 percentage points, on average. • A 1 percentage point increase in the share of the labor force comprised of immigrants appears to raise the labor force participation rate of US natives in the same sex-education group by 0.045 percentage points, on average. • There is no evidence of significant adverse effects among less-educated US-born workers, while immigration appears to boost labor force participation among more-educated US-born workers. • Having more immigrants overall does not significantly affect US natives' unemployment or labor force participation rate.

Over the last 10 years, tornadoes have caused the highest number of fatalities among natural hazards in the United States. Supercell-spawned tornadoes can be in excess of 1 km wide and often have long tracks that can pass through an entire community, resulting in numerous casualties and potentially several billions of dollars in direct and indirect damages for a single event. For example, the EF5 tornado in Joplin, Missouri on May 22, 2011 is the deadliest and costliest tornado in the US since 1950. In order to study the resilience of a community, life safety constraints should be satisfied along with other resilience metrics at the community level. In this study, a multivariate regression model is presented to assess the expected number of injuries and fatalities caused by a tornado as a function of tornado intensity, the number of people located in the tornado path, and the tornado path length. Moreover, the time of the day and month of the year when a tornado happens and the property damage caused by a tornado were used in predicting injuries and fatalities. In this regard, the United States tornado database and the US census database at the block level were used to provide a dataset for the regression model. Two prediction models for injuries and fatalities were developed for moderate tornadoes (i.e., EF0 and EF1), strong tornadoes (i.e., EF2 and EF3), and violent tornadoes (i.e., EF4 and EF5). The proposed models outperform existing predictive models in that they estimate casualties better with fewer explanatory variables. This is primarily due to the use of block level census data instead of county level, which is shown to be critical at tornado model scale. These models can be used to design a resilient community or upgrade an existing community by applying a probabilistic life safety constraint at the community level beside the resilience metrics

Family planning helps countries achieve manageable levels of population growth through voluntary choices about the number and timing of pregnancies, making family planning programs an important contributor to economic development. Regulating fertility through safe and effective contraception also has numerous health benefits for both the mother and infant (Seltzer, 2002). Family planning programs must both deliver commodities and services and collect data to track progress toward national goals. In 2012, countries agreed on an ambitious global goal of achieving, by 2020, 120 million new users of modern contraception in 69 of the world’s poorest countries. This Family Planning 2020 (FP2020) goal, and the initial commitment by at least two dozen of those countries, triggered support by major donors for various programs to help countries advance toward the FP2020 goal. Among such efforts, the Bill & Melinda Gates Foundation launched two key programs in early 2013 to help countries collect, analyze, and use data to monitor progress toward the FP2020 goal. The Performance Monitoring and Accountability 2020 (PMA2020) program, implemented by Johns Hopkins University’s Gates Institute for Population and Reproductive Health, was to focus on supporting data collection in nine countries through annual, rapid-turnaround, national surveys typically led by university-based experts, using mobile phone technology and local “resident enumerators.” The Track20 program, implemented by Avenir Health, was to work with governments in a larger number of countries to gather data from various sources, analyze and model the data to derive estimates for core family planning indicators, facilitate consensus around data to be reported globally, and promulgate the effective use of these data. In early 2017, roughly the midpoint between the launch of these programs and the 2020 target date, the Gates Foundation sought to take stock of the progress of PMA2020 and Track20 in order to inform its future directions. It contracted with the RAND Corporation to undertake an objective external evaluation of the two programs. The study team conducted the evaluation from April through September 2017. The findings should be of interest to the Bill & Melinda Gates Foundation, the two programs, the governments of countries participating in one or both programs, associated donors and implementing partners, and the larger global family planning and development communities.

This project explores the mechanisms of exclusion and oppression of a Haitian population in a rural community in South West Florida. The analytical approach taken is an analysis of the social field and habitus as dispositions and embodied culture. Language has been identified as a tool to marginalize the population in the general social order. Through this process, language operates as a form of color-blind racism which justifies the exclusion of the Haitian community but is insufficient in explaining their overall social outcomes. Qualitative data were collected for this project in the form of unstructured interviews, focus groups, photographs of the local community, and observational field notes. Participants principally came from the Haitian population in the target community. Other community stakeholders, including elected county officials, were interviewed to obtain background and contextual information. Also consulted were county documents and demographic planning profiles. Secondary data were used for the quantitative analysis portion of this project. These data were taken from the US Census Bureau American Community Survey. Both aggregated data from the American Factfinder website and individual-level data from the IPUMS repository were downloaded in the completion of the secondary data analysis. The findings indicate that the habitus of the social field operates to exclude the Haitian population from the overall community in the areas of labor, health care, education, services, and local governance. In each of these arenas, language was cited as being a primary source of exclusion and problem for the Haitian population. Popular conceptions that the Haitian population needs to “learn English” in order to improve their status in the overall social structure were problematized as inferential testing indicated that proficiency in English is not a significant explanation for poverty status.

Modern business cycle theory focuses on the study of dynamic stochastic general equilibrium models that generate aggregate fluctuations similar to those experienced by actual economies. We discuss how this theory has evolved from its roots in the early real business cycle models of the late 1970s through the turmoil of the Great Recession four decades later. We document the strikingly different pattern of comovements of macro aggregates during the Great Recession compared to other postwar recessions, especially the 1982 recession. We then show how two versions of the latest generation of real business cycle models can account, respectively, for the aggregate and the cross-regional fluctuations observed in the Great Recession in the United States.

Immigrants to the United States live disproportionately in metropolitan areas where nominal wages are high, but real wages are low. This finding is justified in a spatial equilibrium model, as these areas offer more desirable quality-of-life amenities. Relative to natives, immigrants do sacrifice more to be in larger, coastal cities and also sort towards areas that are hilly, sunny, less-educated and subject to greater land-use regulations. Immigrants are coming more from countries that are coastal, cloudy, and less violent. Moreover, they choose cities that resemble their home countries in terms of winter temperature, safety, coastal proximity, and education level.

Tourism is the focus of increasing scrutiny in New Orleans. In May of this year, workers protested lack of health benefits at the New Orleans Tourism Marketing Corporation board meeting.1 And a proposal to publicly subsidize a new hotel at the foot of Convention Center Boulevard received significant criticism from analysts at the Bureau of Governmental Research.2 More broadly, New Orleanians have grumbled for decades that tourism capitalizes on New Orleans’ culture but does little to benefit those who create that culture.3 As the debate on tourism has heated up, The Data Center has been called upon frequently to provide objective data on the tourism economy in New Orleans. Promoters and critics alike are eager to know the actual number of jobs “created” by the cluster as well as actual wages, with comparisons to other cities. This brief provides a complete and transparent documentation of the data we have on tourism in New Orleans and provides additional details about both the hotel and full-service restaurant industries.

This paper investigates the pre/post labor market implications of the Affordable Care Act’s (ACA) Medicaid expansion for a population near the eligibility cutoff. Using an arguably exogenous variation at the eligibility cutoff, I find that Medicaid enrollment increases for adults without dependent children. This leads to an employment transition from full-time (≥35 Hrs) to part-time employment (<35 Hrs) after the expansion. The employment transition is mainly driven by the increase in employment for working less than 20 hours. Falsicification checks show no effect on employment for non-expansion states and Medicare-eligible adult groups. The estimates are robust to the inclusion of early expansion states, increasing bandwidths, and various functional forms of the running variable. These findings imply that individuals primarly work to secure private health insurance (“employment lock”) prior to the expansion. When replicating the existing studies that use a difference-in-differences (DD) model with expansion states as the treatment group, I find no employment effects. The main limitation of this DD model is the large and heterogeneous treatment group that includes adults who are less likely to be eligible for Medicaid.