I have two main goals with this brief. First, instead of looking at correlates with overall DI participation, as much of the previous literature has explored, I look at correlates of DI benefit receipt for people with mental disorders. I do not seek to provide a specific causal explanation for DI participation for mental disorders-instead, I explore a variety of potential factors including economics, demographics, policy, health, and access to the health care system.

Este trabajo tiene doble propósito, por un lado, revisar los factores de mayor peso en la explicación de la inserción laboral de los inmigrantes calificados latinoamericanos en Estados Unidos en tres momentos, 2000, 2009 y 2013. Por otra parte, verificar los determinantes de dicha inserción en Chile en 2013. Para delimitar qué variables tienen mayor peso en la incorporación laboral se utiliza como fuente de información la American Community Survey, 2000, 2009 y 2013 (ACS) y la Encuesta de Caracteri-zación Socioeconómica Nacional, 2013 (CASEN) y para probar la hipótesis de la su-butilización de las capacidades de los inmigrantes altamente educados en los lugares de destino se usa el modelo de regresión logística binaria, basado en la explicación comparativa considerando la dimensión del capital humano, el demográfico y el de contexto.

Texas is the uninsured capital of the United States and has the largest number of children and adults who are uninsured. Lack of healthcare access can be detrimental to a child’s health. Compared to children who are insured, uninsured children are 20% less likely to be in good or excellent health. The two main federal polices addressing the coverage of low-income uninsured children are the Children Health Insurance Program and Children’s Medicaid. The Children’s Health Insurance Program Reauthorization Act (CHIPRA) was passed in 2009 as a part of the Affordable Care Act. With the enactment of CHIPRA funding for CHIP was extended and enrollment and retention provisions for both CHIP and Medicaid were implemented. This dissertation evaluated whether the CHIPRA expansion worked to get more children covered under health insurance coverage in Texas. An IPUMS extract of the Current Population Survey from 2006 to 2008 and the American Community Survey from 2009 to 2015 was utilized for the analysis. Children were stratified into eligibility and coverage subgroups (e.g., private, public and uninsured) from each year’s extract. Through further stratification of the IPUMS extract, Medicaid and CHIP enrollment numbers were calculated based on eligibility criteria of federal poverty level, household size, citizenship/permanent . . .

Evidence from the American Time Use Survey 2003-12 suggests the existence of small but statistically significant racial/ethnic differences in time spent not working at the workplace. Minorities, especially men, spend a greater fraction of their workdays not working than do white non-Hispanics. These differences are robust to the inclusion of large numbers of demographic, industry, occupation, time and geographic controls. They do not vary by union status, public- private sector attachment, pay method or age; nor do they arise from the effects of equal- employment enforcement or geographic differences in racial/ethnic representation. The findings imply that measures of the adjusted wage disadvantages of minority employees are overstated by about 10 percent.

This thesis comprises four papers on the economics of networks. The first provides a survey of methods for econometric work with networks, summarising what is known in the economics literature, and incorporating methods from other fields including mathematics, computer science, and sociology. The second explains why informal insurance networks are able to provide consumption smoothing, but not credit for investment. It develops a dynamic contracting model to explain the difference in these motivations, generates from this a number of testable predictions, and then provides evidence in support of the model using data from Bangladesh. The third examines the trade-off between economic and cultural incentives for migrants. It develops a model of network formation combined with a game-on-a-network, to capture this trade-off. The model’s predictions are then tested using data from US censuses in the early 1900s. The fourth studies the impact of tax audits by HMRC, the UK tax authority, on the future tax reporting behaviour of self-assessment taxpayers. It shows that income sources which are not also reported by a third party are more likely to be initially underreported, and that being . . .

This paper links gender wage gaps with the urban wage premium. First, the study documents gender wage gaps are narrower in larger U.S. metropolitan areas in 2000 and 2010. Skill agglomerations are then considered to explain this. Specifically, if men and women employ heterogeneous skills, and these skills have differential productivities across city sizes, agglomerative forces may differentially reward men and women. Occupational data show that women are concentrated in jobs relatively more intensive in interactive and cognitive skills, while men are comparatively in physical skill-intensive jobs. Decomposing the gender wage gap shows that explanatory factors (education, skills, and location) predict women would outearn men. Instead, agglomerative skill returns account for majority of the gap. These estimates suggest that even as women employ skills rewarded in agglomeration economies, they benefit less from agglomerations than men, resulting in the observed gap.

This paper documents that the blackwhite gap in self-rated health declined by approximately 50% between 1972 and 2015.

Using the US Census Bureau’s Current Population Survey (CPS), which samples US working age adults in non-institutional settings, we were able to calculate average income over time by age cohort. The results of this analysis (Figure 1), show that, while for most age groups median income has grown since the 1960s, for 18-24 year-olds, income has remained relatively flat. In other words, while the economy has grown to about 28 times its size in the 1960s, and while other age groups have seen their incomes rise as a result of this growth, the youngest Americans have realized none of these gains; a Millennial today is doing only about as well as her Boomer parents were doing in the 1960s.

This dissertation, which consists of four chapters, uses historical patent data to understand invention in the United States. The first chapter studies how institutions of higher education affect invention. The second chapter seeks to understand the importance of informal social interactions for the creation of new ideas. The third chapter answers the question of what types of individuals are most likely to become inventors. The fourth chapter discusses various historical patent datasets in detail. In Chapter 1, I exploit historical natural experiments to identify the causal effect of the establishment of new colleges on local patenting. Using losing finalist counties that did not receive a new college as counterfactuals, I find that the establishment of a new college caused 33% more patents per year in college counties relative to the losing finalists. To understand the role of a college education in driving patenting in college towns, I use a novel dataset of graduates from college yearbooks and find that a college’s graduates and faculty account for a very small share of the patents granted in that college’s county. Changes in county population account for 45-65% of the increase in patenting in college counties. In Chapter 2, I exploit a different historical policy to understand the importance of informal social interactions for invention. More specifically, I examine the effects of state-level alcohol prohibition in the U.S. Prior to the enactment of statewide alcohol laws, each county determined its own alcohol policies. Thus, statewide prohibition differentially treated counties depending on whether they were wet or dry prior to statewide adoption. The imposition of statewide prohibition reduces the number of patents by 15% per year in previously wet counties relative to previously dry counties. The effect is largest in the first three years after the imposition of prohibition and diminishes thereafter. Consistent with this decrease being driven by a disruption of informal social interactions, the patenting rate for men decreased more than that for women in previously wet counties. In Chapter 3, my coauthors and I match the Annual Reports of the Commissioner of Patents from 1870 to 1940 to the corresponding U.S. Federal Population Censuses. This matching procedure provides a rich set of demographic information on a comprehensive set of inventors, allowing us to answer the fundamental question of who invents. We first document that patentees are more likely to be older, white, male and to be living in a state other than the one in which they were born. These patterns are very persistent over space and time. We then attempt to identify correlates of the demographics of patentees focusing on county-level economic and demographic characteristics. Beyond the most obvious, such as the fraction of a particular demographic group in that county, very little explains differences in the demographics of inventors across counties. In Chapter 4, I compare the strengths and weaknesses of four historical patent datasets and consider the suitability of each for use in economic research. I describe in detail differences in terms of the type and reliability of included information and potential sample selection issues. I show that while there are differences across datasets, overall they paint a remarkably consistent picture of invention in U.S. history

The government is facing a severe shortage of skilled workers, especially in information technology and cyber security jobs. The conventional wisdom in branches of policy and public administration is that the shortage is driven by low salaries that are not competitive for attracting top talent. Using longitudinal data on high skilled workers between 1993 and 2013, this paper shows that, if anything, government employees earn more than their private sector counterparts. Although government work- ers tend to earn less in the raw data, these di erences are driven by the correlation between unobserved ability and selection into private sector jobs. These results are robust to additional data from the Census Bureau between 2005 and 2016. Instead, this paper shows that a more plausible culprit behind the worker shortage in government is a lack of development opportunities and poor management. The paper represents only the views of the author and not those of any a liated institutions or the United States.

AOI-HEP (Attribute Oriented Induction High Emerging Pattern) as new data mining technique has been success to mine frequent pattern and is extended to mine similar patterns. AOI-HEP is success to mine 3 and 1 similar patterns from IPUMS and breast cancer UCI machine learning datasets respectively. Meanwhile, the experiments showed that there was no finding similar patterns on adult and census UCI machine learning datasets. The experiments showed that finding AOI-HEP similar pattern in dataset is influenced by learning on chosen high level concept attribute in concept hierarchy and it is applied to AOI-HEP frequent pattern in previous research as well. The experiments chosed high level concept attributes such as workclass, clump thickness, means and marts for adult, breast cancer, census and IPUMS datasets respectively. In order to proof that the chosen high level concept attribute will influences the AOI-HEP similar pattern in dataset, then extended experiments were carried on and the finding were census dataset which had been none AOI-HEP similar pattern, had AOI-HEP similar pattern when learned on high level concept in marital attribute. Meanwhile, Breast cancer which had been had 1 AOI-HEP similar pattern, had none AOI-HEP similar pattern when learned on high level concept in attributes such as cell size, cell shape and bare nuclei. The 2 of 3 finding Similar patterns in IPUMS dataset have strong discriminant rule since having large growth rates such as 1.53% and 3.47%, and having large supports in target dataset such as 4.54% and 5.45 respectively. Moreover, there have small supports in contrasting dataset such as 2.96% and 1.57% respectively.

The gap between native and immigrant wages in the U.S. has increased significantly since the 1980s. While part of this may be attributable to declines in the relative quality of immigrant labor, this paper explores whether the growing importance of social skills also played a role. Using historical routine employment share to measure cities’ likely technology adoption and its process of replacing routine labor, I show that local labor markets that specialized in routine tasks experienced differential increases in native-immigrant wage gaps. This is consistent with the hypothesis that native workers have a comparative advantage in U.S.-specific social skills, and the returns to these skills have increased as a result of technology replacing routine labor. Results do not seem to be driven by selective migration between cities but are strongly related to immigrants’ English language abilities as well as other measures of their social assimilation.

For forty years, the Tuskegee Study of Untreated Syphilis in the Negro Male passively monitored hundreds of adult black males with syphilis despite the availability of effective treatment. The studys methods have become synonymous with exploitation and mistreatment by the medical profession. We find that the disclosure of the study in 1972 is correlated with increases in medical mistrust and mortality and decreases in both outpatient and inpatient physician interactions for older black men. Our estimates imply life expectancy at age 45 for black men fell by up to 1.5 years in response to the disclosure, accounting for approximately 35% of the 1980 life expectancy gap between black and white men and 25% of the gap between black men and women.

We study the economic assimilation of childhood immigrants to the United States. The linguistic distance between English and the predominant language in ones country of birth interacted with age at arrival is shown to be closely connected to occupational sorting in adulthood. By applying big-data techniques to occupations detailed skill requirements, we provide evidence that childhood immigrants from English-distant countries who arrived after the primary school years reveal comparative advantages in tasks distinct from those for which (close to) Anglophone immigrants are better suited. Meanwhile, those who arrive at younger ages specialize in a bundle of skills very similar to that supplied by observationally equivalent workers. These patterns emerge even after we net out the effects of formal education. Such findings are compatible with the existence of different degrees of complementarity between relative English-learning potential at arrival and the acquisition of multiple capabilities demanded in the U.S. labor market (math/logic, socioemotional, physical, and communication skills). Consistent with the investment-complementarity argument, we show that linguistic distance and age at arrival also play a significant role on the choice of college major within this population.

One of the most defining events of the twentieth century in the United States was the mass migration of African Americans out of the southern states to the northern regions of the country. Historians estimate between 6 and 8 million African Americans made the trip from the Jim Crow states, driven by racial discrimination and the hope for a better life, to the more liberal parts of the country in the northwest and along the Pacific coast. 1 2 The major demographic shift of black communities settling into northern cities was accompanied by a transformation of America’s political landscape, as the Democratic party . . .

Broadband (high-speed) internet access expanded rapidly from 1999 to 2007. This expansion is associated with higher economic growth and labor market activity. In this paper, we examine whether the rollout also affected the social connections teens make. Specifically, we look at the relationship between increased broadband access and teen fertility. We hypothesize that increasing access to high-speed internet can influence fertility decisions by changing the size of the market as well as increasing the information available to participants in the market. We seek to understand both the overall effect of broadband internet on teen fertility as well as the mechanisms underlying this effect. Our results suggest that increased broadband access explains at least thirteen percent of the decline in the teen birth rate between 1999 and 2007. Although we focus on social markets, this work contributes more broadly to an understanding of how new technology interacts with existing markets.

Research has consistently demonstrated that children living in low-income families, particularly those in poverty, are at a greater risk of child maltreatment; however, causal evidence for this relationship is sparse. We use child maltreatment reports from the National Child Abuse and Neglect Data System: Child File from 2004 to 2013 to investigate the relationship between changes in a state's minimum wage and changes in child maltreatment rates. We find that increases in the minimum wage lead to a decline in overall child maltreatment reports, particularly neglect reports. Specifically, a $1 increase in the minimum wage implies a statistically significant 9.6% decline in neglect reports. This decline is concentrated among young children (ages 0-5) and school-aged children (ages 6-12); the effect diminishes among adolescents and is not significant. We do not find that the effect of increases in the minimum wage varies based on the child's race. These findings are robust to a number of specifications. Our results suggest that policies that increase incomes of the working poor can improve children's welfare, especially younger children, quite substantially.

The national imperative to increase the presence of women and people of color in science, technology, engineering, and mathematics (STEM) coupled with the growing presence of Latinos in the United States has led to the dramatic rise of programs and initiatives aimed at improving access to and equity in STEM careers and education for Latino youth. Through the use of critical social theory and critical theory of education as guiding frameworks, the dissertation examines an instantiation of STEM reform efforts to analyze the classroom participation structure that emerged in a piloted introduction to data science course at a local high school in one of the largest school districts in the country. The study is particularly concerned with identifying emergent classroom norms and practices, and understanding whether and how they came to support and/or hinder students’ opportunities to learn richly with data through an analysis of the development of student learning identities. This qualitative case study draws on audio-recorded student interviews, video-recorded classroom observations, and field notes collected during the second year of the curriculum’s implementation. To identify classroom norms and practices as they relate to the development of student identities as data science doers, the study examines the classroom participation structure (Cobb and Hodge, 2002) and employs Cobb, Gresalfi, and Hodge’s (2009) interpretive scheme for analyzing the development of mathematical student identity (also see Cobb & Hodge, 2010). While the multiperspectival approach of this study will provide innovatively insightful contributions to a number of fields including education, cultural studies, data and computer science, the study will also push how educators, learning science researchers, curriculum writers, and policymakers think about the pursuit of equity in STEM education in general and data science-oriented programs and initiatives in particular as they relate to STEM reform efforts.

Broadband (high-speed) internet access expanded rapidly from 1999 to 2007 and is associated with higher economic growth and labor market activity. In this paper, we examine whether the rollout also affected the social connections that teens make. Specifically, we look at the relationship between increased broadband access and teen fertility. We hypothesize that increasing access to high-speed internet can influence fertility decisions by changing the size of the market as well as increasing the information available to participants in the market. We seek to understand both the overall effect of broadband internet on teen fertility and the mechanisms underlying this effect. Our results suggest that increased broadband access explains at least 7 % of the decline in the teen birth rate between 1999 and 2007. Although we focus on social markets, this work contributes more broadly to an understanding of how new technology interacts with existing markets.

Cómo el Big Data nos ayuda a comprender los retrocesos seculares en la participación de los trabajadores en edad de máximo rendimiento en la fuerza laboral de EEUU Una juventud indolente, robots destructores, invasores extranjeros, una epidemia... Parece el elenco de nuevas series de Netflix que podremos consumir este otoño. Sin embargo, todos esos temas forman parte de la creciente lista de explicaciones sobre las fricciones residuales en el mercado laboral que, en igualdad de otros factores, cabría esperar que no persistieran con una tasa de desempleo de 4.4%, nivel cercano a su mínima de 15 años. Debido a ello, la atención ha pasado de estar en indicadores del mercado laboral (anteriores criterios de referencia), como la tasa de desempleo, a medidas más matizadas sobre la solidez del mercado laboral, como puedan ser la proporción de empleo a población y la tasa de participación. Este cambio en el foco de atención se debe en parte a la toma de conciencia de que las tendencias seculares en forma de envejecimiento de la población estaban teniendo un impacto desmesurado sobre las medidas tradicionales, por cuanto los anormales flujos de salida de jubilados propiciaban caídas artificiales en la tasa de desempleo. Además, la magnitud y duración de la crisis financiera generaron también un incremento desproporcionadamente mayor en la infrautilización laboral, que se evidencia en mayor grado en las medidas más generales de desempleo y subempleo; esto incluye a las personas desalentadas que dejaron de buscar empleo o a aquellas que trabajan a tiempo parcial por motivos económicos. Con todo, estas medidas con un gran componente cíclico han regresado a niveles coherentes con un mercado laboral en su tasa constante, o próximo a ella, con lo que la atención pasa de la recuperación cíclica a los factores seculares que podrían explicar la persistente debilidad. Gráfica 1. Tasa de participación en la fuerza laboral, % Gráfica 2. Proporción empleo a población, %