For Chapter 1: This paper offers a meta-regression analysis of the controversial impact of EU structural funds on the growth of the recipient regions. It identifies the factors that explain the heterogeneity in the size of 323 estimates of their impact recorded in 17 econometric studies. Heterogeneity comes from the publication status, the period examined, controlling for endogeneity, from the presence of several regressors but not from differences in functional forms. For Chapter 2: Recent spatial econometric contributions call for theory-driven spatial models and W matrices capturing actual and time-varying interregional linkages. This paper answers this call by developing theoretically Griliches' well-known knowledge production function to add knowledge externalities to it. They capture how human and private capital originating from one region benefit the creation of innovation elsewhere. Furthermore, we measure interregional interaction based on the actual flows of patent creation-citation and of migration of the educated workers. They have the advantage of capturing clearly the direction of the knowledge transfers. Their presence in the theoretical model leads to a reduced-form spatial cross-regressive model which differentiates better the role of each type of externality - and displays a better goodness of fit - than the spatially lagged model where spillovers depend on geographical proximity only. Both models are estimated on spatial panel data covering the dynamics of innovation across US states over the 1986-1999 period. For Chapter 3: The Ricardian framework is increasingly used for the study of the impact of climate change on farmland values. While most of the Ricardian studies assume no interaction between the geographical units under study, the few that do rely on traditional proximity-based dependence. In this paper we argue that since the larger share of agricultural goods produced by a state is not for its own local market, including interregional trade in the Ricardian framework provides new perspectives, avoids a missing variable bias and prevents erroneous conclusions. Our new framework is applied to the system of the U.S. states over the four most recent censuses (1997-2012) and demonstrate that climate and socio-economic conditions experienced in a state's trade partners have a significant role on that state's local farmland values.

This paper finds evidence of positive neighborhood effects on adult labor market outcomes using the Moving to Opportunity (MTO) housing mobility experiment. Our results stand in such sharp contrast to the current literature because our analysis focuses on outcomes of the subpopulation induced by the program to move to a higher quality neighborhood, while previous analyses have focused on outcomes of either the entire population or the subpopulation induced by the program to move. We propose and implement a new strategy for identifying heterogeneous transition-specific effects that exploits the identification of the idiosyncratic, unobserved component of a neighborhood choice model. We estimate Local Average Treatment Effects (LATEs) of the change in quality most commonly induced by MTO vouchers, between the first and second deciles of the national distribution of neighborhood quality. Although MTO vouchers induced much larger changes in neighborhood quality than standard Section 8 vouchers, these LATEs only pertain to a subpopulation representing about nine percent of program participants.

Truancy prevention in the District of Columbia was an issue taken up after a tragic event among teenagers that resulted in multiple deaths and due to behavior related to truancy. The law was finally enacted in D.C. in 2013. Truancy, or an unexcused absence, was rampant with over 4,000 D.C. students missing 10-20 school days in 2012, without having a valid excuse. The law places accountability with the home of the student, with consequences resulting in fines and referrals to a Student Support Team or Court Social Services. This gives schools alternative tools in keeping students in the class for instruction and deter youth violence as a result. However, students who are chronically absent and chronically disruptive maybe more inclined to receive school administered suspensions. As such, those students would receive little classroom instruction or school time. Using pooled cross sectional data collected from oversight hearings from the Office of the State Superintendent of Education, and Ordinary Least Square (OLS) regression models, this paper gives insight on how the truancy prevention law in D.C. has impacted suspensions subsequently, before and after the law was enacted. The findings of this analysis suggest that the law has none or minimal impact on suspensions, but has reduced the rate of unexcused absences occurring since the laws implementation. Thus, D.C. policymakers would be advised to consider further studies, including consistent data collection, to reform the law to better assist schools in reducing suspensions for those students who are both chronically disruptive and chronically absent and thereby maximize class time for those students.

Background: Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental pollutants, known human lung carcinogens, and potent mammary carcinogens in laboratory animals. However, the association between PAHs and breast cancer in women is unclear. Vehicular traffic is a major ambient source of PAH exposure. Objectives: Our study aim was to evaluate the association between residential exposure to vehicular traffic and breast cancer incidence. Methods: Residential histories of 1,508 participants with breast cancer (case participants) and 1,556 particpants with no breast cancer (control participants) were assessed in a population-based investigation conducted in 19961997. Traffic exposure estimates of benzo[a]pyrene (B[a]P), as a proxy for traffic-related PAHs, for the years 1960-1995 were reconstructed using a model previously shown to generate estimates consistent with measured soil PAHs, PAHDNA adducts, and CO readings. Associations between vehicular traffic exposure estimates and breast cancer incidence were evaluated using unconditional logistic regression. Results: The odds ratio (95% CI) was modestly elevated by 1.44 (0.78, 2.68) for the association between breast cancer and long-term 1960-1990 vehicular traffic estimates in the top 5%, compared with below the median. The association with recent 1995 traffic exposure was elevated by 1.14 (0.80, 1.64) for the top 5%, compared with below the median, which was stronger among women with low fruit/vegetable intake [1.46 (0.89, 2.40)], but not among those with high fruit/vegetable intake [0.92 (0.53, 1.60)]. Among the subset of women with information regarding traffic exposure and tumor hormone receptor subtype, the trafficbreast cancer association was higher for those with estrogen/progesterone-negative tumors [1.67 (0.91, 3.05) relative to control participants], but lower among all other tumor subtypes [0.80 (0.50, 1.27) compared with control participants]. Conclusions: In our population-based study, we observed positive associations between vehicular traffic-related B[a]P exposure and breast cancer incidence among women with comparatively high long-term traffic B[a]P exposures, although effect estimates were imprecise.

This dissertation focuses on how transportation and information networks change the geographic distribution of economic activity. The first and second chapters examine the geographic distribution of patenting in the nineteenth century United States. The third explores the impact of the rollout of Rural Free Delivery (RFD) in the early twentieth century on voting behavior. In Chapter One, I examine the relationship between patenting activity and transportation access, using a newly collected panel dataset at the county level spanning the nineteenth century United State. I find a robust, statistically significant, positive effect of increases in local transportation access on patents per capita. The effect is large patents per capita double over the twenty years following introduction of the railroad. I ask if this increase is due to inventors responding to larger markets afforded by transportation improvements. I find modest evidence that market access explains the increase in patent activity, but most of the relationship seems to be explained by other variables correlated with transportation access. The second chapter proposes a novel way to study technology diffusion, investigating how transportation changes information absorption. Using digitized patent texts, I measure whether any given patent mentions previous, novel technologies within a particular window of time. The arrival speed of these new ideas is only weakly related transportation improvements; expansions of the transportation network disproportionately benefit the most develop places. Together, these two chapters suggest that the positive effect of transportation access on patenting is due to transportation forming a nexus that encourages local agglomerations, but leave the question of the overall impact of lager transportation networks on innovation unclear. Chapter Three focuses on the how mail delivery spread new information, studying the rollout of Rural Free Delivery (RFD) in the early twentieth century. Using a newly constructed panel data set, the analysis shows that voters in communities receiving more RFD routes distributed their votes to more parties; however, there is no evidence of an effect on turnout. RFD shifted positions taken by Representatives in line with their rural constituents, including increased support for pro-temperance and anti-immigration policies. The results only occur in counties with local newspapers, suggesting that the main channel is a lowered cost to voters of acquiring information relevant to political choices.

The United States federal government devotes around $40 billion each year to means-tested housing programs, plus another $6 billion or so each year in tax expenditures on the Low-Income Housing Tax Credit (LIHTC). This is well over twice the level of federal spending on either cash welfare or the Title I compensatory program in education, four times what is spent on the children’s health insurance fund (Falk 2012), and five times what is spent on Head Start.1 What exactly do we spend this money on, why, and what does it accomplish? Those are the overarching questions at the heart of our chapter. We should note these programs are just a modest share of the total subsidies government provides to subsidize housing for American . . .

In this paper, we document the importance of high-skilled immigration for U.S. employment in STEM fields. To begin, we review patterns of U.S. employment in STEM occupations among workers with at least a college degree. These patterns mirror the cycle of boom and bust in the U.S. technology industry. Among younger workers, the share of hours worked in STEM jobs peaked around the year 2000, at the height of the dot-com bubble. STEM employment shares are just now approaching these previous highs. Next, we consider the importance of immigrant labor to STEM employment. Immigrants account for a disproportionate share of jobs in STEM occupations, in particular among younger workers and among workers with a master's degree or PhD. Foreign-born presence is most pronounced in computer-related occupations, such as software programming. The majority of foreign-born workers in STEM jobs arrived in the U.S. at age 21 or older. Although we do not know the visa history of these individuals, their age at arrival is consistent with the H-1B visa being an important mode of entry for highly trained STEM workers into the U.S. Finally, we examine wage differences between native and foreign-born labor. Whereas foreign-born workers earn substantially less than native-born workers in non-STEM occupations, the native-foreign born earnings difference in STEM jobs is much smaller. Further, foreign-born workers in STEM fields reach earnings parity with native workers much more quickly than they do in non-STEM fields. In non-STEM jobs, foreign-born workers require 20 years or more in the U.S. to reach earnings parity with natives; in STEM fields, they achieve parity in less than a decade.

This dissertation is a compilation of three essays that investigate how increasing women's access to political and economics resources in the United States influences investments in the human capital of children and helps shape decisions around family formation in the country. In doing so, it documents the evolution of decision making of women in the U.S. over the last century, and shows how key shifts in policy and wage-enhancing technological change facilitated this transition. The essays pair cutting-edge econometric techniques with novel empirical designs to estimate causal impacts of women's increasing access to these resources. The first chapter examines the effect of the enfranchisement of women in early 20th century United States on the long term educational outcomes of children growing up during and after the passage of suffrage laws, and is co-authored with Esra Kose and Elira Kuka. This essay contributes to a growing literature which provides evidence that increasing the political power of women leads . . .

In the last 40 years, social scientists have provided important insights into the different characteristics of mass public shootings: their prevalence, types, patterns, and individual risk factors. However, we still lack a fundamental understanding of the processes that shape its incidence and spatial distribution. Our failure to tap into these dynamics is rooted in our inability to escape the dominant paradigm in which this phenomenon has been examined. Literature on mass murders, and most recently on mass public shootings, has been trapped by an analytical framework that cares only for individual risk factors. This paradigm is myopic because it assumes that only the proximate causes (i.e., factors and events closest to the attack) shape the prevalence and distribution of such attacks. The goal of this study is to step away from this paradigm and recast these shootings as a social phenomenon, shaped by social forces. This investigation is couched on three major Sociological/Criminological theoretical perspectives: social integration, social disorganization, and imitation/diffusion theories. Under social integration/social disorganization theory, I posit that certain ecological characteristics (primarily low social cohesion) make certain populations more at risk or vulnerable to these types of massacres. Similarly, I argue that an imitation or diffusion process, driven primarily by media exposure, also shapes the incidence and spatial distribution of these attacks. A Continuous-time Event History Model (or Hazard/Survival Model) is used to test the influence of social integration and imitation/diffusion forces on the prevalence of mass public shootings in the contiguous United States for the 1970-2014 time period. The results paint a mixed, but rather interesting picture. From the theoretical perspective findings are mixed. Imitation/diffusion and social disorganization theory were not supported by the results. Durkheims social integration theory was the most successful, but also partially supported. Despite these mixed findings, the results provide unexpected and interesting insights into the social causes of mass public shootings. The findings show that (contrary to expectations) the occurrence of a mass public shooting was found to depress the odds of future attacks. We also learned that mass public shootings tend occur in states that are more rural, with greater levels of marriage stability, and social-economic status. These are quite unique findings, as these relationships tend to be reversed for regular homicide. The results suggest that mass public shootings behave more like suicide, than regular homicide. This study is the first to provide insights into the sociological roots of mass public shootings. As such, the results provide a springboard for the future literature.

This paper employs commuter flow data from the 1990 and 2000 Decennial Censuses, and the 20062010 American Community Survey to replicate, evaluate, and extend the delineation of commuting zones first proposed by Tolbert and Killian (Labor Market Areas for the United States, 1987). Commuting zones offer a valuable tool for research on regional economies and have long served rural sociologists, economists, and geographers interested in a representation of the economy that acknowledges a connection between urban and rural areas and the capacity of economic systems to cross state lines. Our delineations provide both an update in the form of new delineations for 2010 and a revised set of 1990 and 2000 delineations that benefit from a consistent methodology across decades. We also provide a set of tools for comparing delineations across methods and over time. In presenting our revised delineations, we shed light on the role of expert opinion in the original delineations, the strengths and weaknesses of the original method, and offer suggestions for further revision of this tool that may better reflect the theoretical conception of commuting zones.

I develop a discrete choice dynamic migration model to examine the importance of amenity values in immigrants' migration decisions. The model accounts for differentials in both wages and location-specific amenities as determinants of migration decisions, and the size of migrants' networks is allowed to influence the value of the US location choice as well. By estimating the model using panel data from the Mexican Migration Project, I find that Mexican migrants place substantial value on amenities in the United States, which are shown to fall precipitously with migrants' age. Simulation results from policy experiments indicate that Mexican immigrants are more responsive to a policy that reduces the amenity values related to unauthorized US residence than to an increase in the number of border patrol officers.

The rollout of Rural Free Delivery (RFD) in the early twentieth century dramatically increased the frequency with which rural voters received information. This article examines the effect of RFD on voters' and Representatives' behavior using a panel dataset and instrumental variables. Communities receiving more routes spread their votes to more parties; there is no evidence it changed turnout. RFD shifted positions taken by Representatives in line with rural constituents, including increased support for pro-temperance and anti-immigration policies. These results appear only in counties with newspapers, supporting the hypothesis that information flows play a crucial role in the political process.

Using recent data from the American Community Survey, the author investigated how the dynamics of immigration influence our understanding of the adoptionschooling relationship. The results suggest that implications of immigrant and adoption statuses could be understood within specific familial contexts. Thus, no statistical differences were found in the outcomes of foreign-born adoptees in U.S. native families and their peers with immigrant parents. Instead, the most favorable patterns of schooling progress were found among U.S.-born adoptees living in immigrant families. Among immigrants, the analysis indicated similar patterns of achievement among Hispanic and White adoptees that are inconsistent with the predictions of segmented assimilation theory. However, there was a Hispanic disadvantage relative to Whites among immigrant children living with biological and stepparents. The article concludes with a discussion of the implications of these findings for kinship selection and assimilation processes and the contention that alternative theoretical frameworks should be used to understand the implications of adoption status.

Do workers in more physically demanding jobs have different worklives than those in more sedentary occupations? To answer this question, we link individual data from the Current Population Survey with occupation data from the Occupational Information Network. Individuals are categorized into more physically demanding and less physically demanding occupations. Analysis shows that even when controlling for sex, age and education, there is a significant difference in worklife between the two occupation groups. However, these results are in the realm of basic research and may not be applicable at this time for economic loss cases.

A System for Wearable Audio Navigation (SWAN) has been developed that aids a user in navigation, orientation, and situation awareness. SWAN provides support to persons with temporary or permanent visual impairment. SWAN has undergone many iterations, with the common requirement for mobility via wearable computing platforms, spatialized audio output, and robust position/orientation tracking of the user.

This paper analyzes the determinants of bilingualism (i.e., speaks a language other than English at home) among children age 518 years in the American Community Survey, 20052011. Two groups of children are considered: those born in the US (native born) and foreign-born children who immigrated prior to age 14 (the 1.5 generation). The analyses are conducted overall, within genders, and within racial and ethnic groups. Bilingualism is more prevalent if the parents are foreign born, less proficient in English, of the same ancestry (linguistic) group, and if the child lives in an ethnic (linguistic) concentration area. Although the effects are relatively smaller, a foreign-born grandparent living in the household increases child bilingualism, while a higher level of parental education tends to decrease it. Children of Asian and Hispanic origin are more likely to be bilingual than their white, non-Hispanic counterparts.

Objective: This study aims to provide demographic data on the 5.4% of U.S. RNs who are Latino in order to assist nursing educators in planning more effective engagement with the growing U.S. Latino population. Methods: Detailed data from the U.S. Census for the years 1980 to 2010 were used to identify the total U.S. population and the total number of RNs in four standard U.S. Census racial and ethnic groups: non-Latino white (NLW), Latino, African American, and Asian/Pacific Islander. Results: The number of RNs in each racial or ethnic group per 100,000 persons of that same group is reported for all four groups. Spanish-language ability and nativity were derived only for the NLW and Latino groups. Data are reported for the United States as a whole and for the five states with the largest Latino populations: California, Florida, Illinois, New York, and Texas. Of the four racial and ethnic groups, Latinos had the fewest number of RNs per 100,000 population in the period from 1980 to 2010. Compared with NLW RNs, Latino RNs were more likely to speak Spanish and to have been born abroad. State-by-state variations from the national patterns are provided. Conclusions: While major nursing organizations have expressed a desire to increase the diversity of the nursing workforce, the data show that Latinos lag far behind all other racial and ethnic groups in representation among RNs. Nursing education programs and institutions need to improve their efforts to increase the number of Latino nurses relative to the Latino population.

This quarterly update of the Housing Impact of Shale Drilling Study and Dashboard (Appendix 1) includes lead indicators measuring oil and gas shale development activities in the third quarter and lagged indicators measuring the housing market in second quarter of 2016. As with the first report and dashboard, the companion documents were prepared by a team of researchers from Cleveland State Universitys Levin College of Urban Affairs (CSU) for the Ohio Housing Finance Agency (OHFA) to monitor the impact of the Utica shale development industry on housing affordability and availability in eight counties of eastern Ohio where the core upstream and midstream activities of shale development are concentrated. The eight counties include Belmont, Carroll, Columbiana, Guernsey, Harrison, Jefferson, Monroe, and Noble.