Relative to other affluent countries, the United States devotes disproportionate resources to health care with disappointing results. Complex insurance rules and distorted market signals create massive inefficiencies, frustrated patients, and providers burdened by excessive paperwork. Recognizing these problems, entrepreneurs are increasingly applying information technology to health care equipment, monitoring, treatment, and service delivery, creating a sector known as digital health. These technologies, once embedded and distributed around the country, hold the potential to substantially alter the efficiency and quality of health care through the better generation, processing, and use of information; the reduction of overhead costs; and the empowerment of patients.

В статье представлен краткий историографический обзор историко-биографических исследований, осуществленных в отечественной и зарубежной исторической науке в рамках трех вспомогательных исторических дисциплин - генеалогии, просопографии и исторической демографии; проводится сравнительный анализ объектов исследования, источниковой базы и методов исследования этих дисциплин. Впервые в отечественной историографии рассматривается практический опыт реализации междисциплинарных исследований (с применением компьютерных технологий), основанных на информации номинативных документов, документов по личному составу, а также личного происхождения в государственных архивах Российской Федерации и за рубежом; анализируются крупнейшие био-информационные ресурсы, представленные в Интернет; делаются выводы о перспективах развития историко-демографических, генеалогических и просопографических исследований в условиях электронной среды.

In these essays, I develop and estimate life-cycle models aimed at explaining various patterns in labor supply behavior at older ages. The first study measures the extent to which later-life differences in health and disability risks across occupations affect retirement behavior and how these risks influence initial career choice. In the second essay, I look at the degree to which the changing composition of occupations over time—from more to less physically demanding—has contributed to the increase in labor force participation at older ages. The final study examines the effects of wage and health transition processes as well as the role of accrued work-related strain on the labor force participation decisions of older males, aimed particularly at accounting for the high rates of "reverse retirement" seen in the data.

The amount of data in our world has been exploding, and analyzing large data setsso called big datawill become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.

A host of recent research has used reweighting methods to analyze the extent to which observable characteristics predict between-group differences in the distribution of an outcome. Less attention has been paid to using reweighting methods to isolate the roles of individual covariates. We analyze two approaches that have been used in previous studies, and we propose a new approach that examines the role of one covariate while holding the marginal distribution of the other covariates constant. We illustrate the differences between the methods with a numerical example and an empirical analysis of blackwhite wage differentials among males.

Proposals for an earned income tax credit (EITC) expansion for childless workers vary in terms of the size of the credit, the earnings limits for eligibility, and eligibility exclusions. These variations have important implications for who benefits and the associated costs. An expansion of the EITC for childless workers could reach 814 million workers and cost $58 billion in new spending, depending on whether students are excluded and work requirements are adopted. A more generous option could reach 21 million workers but would require as much as $22 billion in new spending. Young people (ages 2124) are the primary beneficiaries of proposed expansions, as are men, who would receive approximately 5560 percent of benefits from any expansion. Women, older workers, and married couples also benefit, but to a lesser extent. Student exclusions and work requirements would lower costs but may be difficult to administer

Large American cities have disproportionately large shares of highly educated workers, a growing trend in recent decades.1 What’s the draw? Money for one thing, naturally. Not only do big-city firms generally pay higher wages; there is also evidence that the differential is greater for those with more education. These higher wages raise interesting questions: Why do firms in big cities find it profitable to pay more? That is, what makes a well-educated city worker more valuable than a comparably educated worker in a small town? And it’s not just about money: Evidence suggests that amenities are increasingly important factors in where people choose to live, and big cities appear to provide greater amenities for higher-income workers than small cities do. But which is the bigger draw — higher wages or better amenities? As this article will show, cities may have a stake in the answer. This article will focus on two channels through which . . .

The purpose of the present study was to (a) examine how acculturation and social support inform Latinos' parenting behaviors, controlling for gender and education; (b) describe parenting styles among Latino immigrants while accounting for cultural elements; and (c) test how these parenting styles are associated with family conflict. A 3 step latent profile analysis with the sample (N = 489) revealed best fit with a 4 profile model (n = 410) of parenting: family parenting (n = 268, 65%), child-centered parenting (n = 68, 17%), moderate parenting (n = 60, 15%), and disciplinarian parenting (n = 14, 3%). Parents' gender, acculturation, and social support significantly predicted profile membership. Disciplinarian and moderate parenting were associated with more family conflict. Recommendations include integrating culturally based parenting practices as a critical element to family interventions to minimize conflict and promote positive youth development.

Socio-ecological Conditions (SECs) are important to include in clinical research models as they have been known to impact the health of patients. However, current clinical research models account for these factors only in an unsatisfyingly rudimentary way. In this study, we developed an SEC Index that captured the latent and direct effects of social stress, one of the many kinds of SEC, on patients general health as measured by the Charlson Comorbidity Index. We demonstrated that the above SEC Index had a significant effect in a clinical model, a patient-level model with the specific clinical outcome of breast cancer prevalence. Further, we demonstrated that including the SEC Index of social stress into the clinical models significantly increased their performance. Our study demonstrated a viable approach that is interchangeable to include any SEC of interest, to more appropriately account for SECs in clinical research models.

Statistical agencies and other institutions collect data under the promise to protect the confidentiality of respondents. When releasing microdata samples, the risk that records can be identified must be assessed. To this aim, a widely adopted approach is to isolate categorical variables key to the identification and analyze multi-way contingency tables of such variables. Common disclosure risk measures focus on sample unique cells in these tables and adopt parametric log-linear models as the standard statistical tools for the problem. Such models often have to deal with large and extremely sparse tables that pose a number of challenges to risk estimation. This paper proposes to overcome these problems by studying nonparametric alternatives based on Dirichlet process random effects. The main finding is that the inclusion of such random effects allows us to reduce considerably the number of fixed effects required to achieve reliable risk estimates. This is studied on applications to real data, suggesting, in particular, that our mixed models with main effects only produce roughly equivalent estimates compared to the all two-way interactions models, and are effective in defusing potential shortcomings of traditional log-linear models. This paper adopts a fully Bayesian approach that accounts for all sources of uncertainty, including that about the population frequencies, and supplies unconditional (posterior) variances and credible intervals.

Were black ghettos a product of white reaction to the Great Migration in the 1920s and 1930s, or did the ghettoization process have earlier roots? This article takes advantage of recently available data on black and white residential patterns in several major northern cities in the period 18801940. Using geographic areas smaller than contemporary census tracts, we trace the growth of black populations in each city and trends in the level of isolation and segregation. In addition we analyze the determinants of location: which blacks lived in neighborhoods with higher black concentrations, and what does this tell us about the ghettoization process? We find that the development of ghettos in an embryonic form was well underway in 1880, that segregation became intense prior to the Great Migration, and that in this whole period blacks were segregated based on race rather than class or southern origin.

In the wake of the Great Recession, policymakers and academics have expressed concerns about rising employer skill requirements. Using a large database of online job postings for middle-skill occupations, we demonstrate that employers opportunistically raise education and experience requirements, within occupations, in response to increases in the supply of relevant job seekers. This relationship is robust to numerous tests for potentially confounding factors, is present even within firm-job title pairs, and is consistent with the predictions of a standard employer search model. We further identify this effect by exploiting the natural experiment arising from troop-withdrawals in Iraq and Afghanistan as an exogenous shock to local, occupation-specific labor supply. Our results imply that increases in the number of people looking for work can account for roughly 30 percent of the total increase in employer skill requirements observed between 2007 and 2010.

This paper investigates the effects of a large-scale paid maternity leave program on birth outcomes in the United States. In 1978, states with Temporary Disability Insurance (TDI) programs were required to start providing wage replacement benefits to pregnant women, substantially increasing access to antenatal and postnatal paid leave for working mothers. Using natality data, I find that TDI paid maternity leave reduces the share of low birth weight births by 3.2 percent, and the estimated treatment-on-the-treated effect is over 10 percent. It also decreases the likelihood of early term birth by 6.6 percent. Paid maternity leave has particularly large impacts on the children of unmarried and black mothers.

Children’s ability to engage in prosocial behavior develops in the toddler and preschool years, and research has shown that children’s early growth in prosocial behavior is important in promoting social competence and positive social relationships later in life (Eisenberg, Fabes, & Spinrad, 2006; Ensor, Spencer, & Hughes, 2011; Hay, Hudson, & Liang, 2010). Occurring first within the family context, children’s early development of prosocial behavior is potentially influenced by multiple family dynamics including marital, coparenting, and sibling relationships (Dunn & Munn, 1986; Eisenberg et al., 2006; Hastings, Utendale, & Sullivan, 2007; McCoy, Cummings, & Davies, 2009; Scrimgeour, Blandon, Stifter, & Buss, 2013; Svetlova, Nichols, & Brownell, 2010). These three family subsystems have each been implicated in children’s prosocial behavior, but have not been examined together. In order to provide a more comprehensive picture of family processes supporting children’s development of prosocial behavior, this study took a process-oriented approach to examine direct effects of positive marital relationship quality, supportive coparenting, and sibling positive involvement on older and younger siblings’ development of helping and sharing behaviors. This study also investigated indirect effects of positive marital relationship quality and supportive coparenting on older and younger siblings’ helping and sharing behaviors through sibling positive involvement. Supporting extant findings on the development of prosocial behavior, results revealed that older siblings engaged in more helping behavior during a sibling task than younger siblings. Additionally, older and younger siblings did not differ in their engagement in sharing during the sibling task. Results also provide support for continuing to examine prosocial behavior as a multidimensional construct. Finally, results from actor-partner interdependence models showed that positive marital relationship quality was positively associated with older and younger siblings’ positive involvement. Overall, this study underscores the importance of continuing to examine whole-family dynamics in order to more fully understand socialization processes influencing children’s development of prosocial behaviors across early childhood.

This report presents preliminary results from the Vermont Roots Migration Project, conducted by researchers at the University of Vermont and several other institutions in 2014. The project used social media and online data collection tools to conduct an online survey of people who attended high school while residents of Vermont. The survey questions centered on their residential choices and the factors that led them to reside permanently in, migrate out of, or return to live in the state. The survey was distributed through social media networks during a 3-week period in March and April. It yielded 3,692 completed surveys from people ranging in age from 15 to 91 years. The survey captured demographic information, geographic data, and open text responses, as well as quantitative data on key factors that influence residential choice. Over half of the respondents were people who permanently left the state (51.5%), nearly one-third were people who have remained in the state (30.5%) and the remainder (18%) were people who lived outside of the state for at least one year and returned to Vermont to live.

Sprawl versus compactness has been one of the biggest debates of our time in urban planning. Is sprawl good or bad for us? How does it affect people’s quality of life, such as transportation, housing affordability, and access to healthy food? The first step to answer these questions is to develop a valid and reliable measure of urban sprawl and then relate it to several quality-of-life outcomes. This is one of the main contributions of this dissertation. I developed a multidimensional measure of urban sprawl for 221 medium and large metropolitan areas and divisions in the U.S. This index places metropolitan sprawl at one end of a continuous scale and compact development at the other end. Having compactness scores for 221 metropolitan areas and divisions, I examined the relationship between urban sprawl and the availability and/or affordability of the three major components in a typical household’s budget: housing, transportation, and food. I found that, in agreement with more than 200 studies on travel and the built environment, metropolitan sprawl is associated with lower walk and transit shares of commute trips, longer drive times, and higher vehicle ownership rates. I also found that housing costs are higher in compact metropolitan areas, but these higher costs are more than offset by lower transportation costs, and the net effect is a just barely significant relationship between compactness and overall housing affordability. These findings are novel and interesting particularly because increasing housing affordability in sprawling areas has been one of the main arguments of pro-sprawl parties. Finally, I examined the relationship between metropolitan sprawl and the emergence of food deserts and found that urban sprawl, at both neighborhood and regional levels, increases the likelihood of a census tract being a food desert. Neighborhoods with a greater compactness index are likely to have population and potential customers to support grocery stores. At the regional level, more compact regions reduce racial and income segregation and do not allow older downtown neighborhoods to be filtered to lower socioeconomic status.

Income inequality across neighborhoods more than doubled in the U.S. between 1970 and 2010. This spatial reallocation of household income may affect public schools through changes to the distribution of peers and provision of local tax revenues. I find that rising income inequality across neighborhoods within a school district increases local public school funding, suggesting that the median voter substitutes a higher property tax rate for declines in neighborhood peer quality. But this income sorting also depresses human capital investment, primarily due to a widening enrollment gap between low- and high-income neighborhoods. These results are robust to instrumenting for changes in neighborhood incomes with the initial allocation of households interacted with differential national trends in household income growth by percentile.

This paper discusses the problem of calibrating survey weights to data at different levels of aggregation, such as households and individuals. We present and compare three different methods. The first does the weighting in two stages, using only the household data, and then only the individual data. The second redefines targets at the individual level, if possible, and uses these targets to calibrate only the individual level weights. The third uses multipliers of household size to produce household level weights that simultaneously calibrate to the individual level totals. We discuss advantages and disadvantages of these approaches, including their requirements in terms of access to the control total data and software. We conclude by outlining directions for further research.

Segmented assimilation theory predicts that contemporary non-white groups follow three patterns of assimilation: mainstream, downward, or delayed. Yet, the homogenous treatment and primacy of ethnicity resigns all group members to a similar fate. Whereas few studies of ethnic incorporation consider both the classed and gendered nature of the labor market, this study investigates the extent to which intersectional group differences within the highly stratified American economy shape segmented assimilation trajectories. This study introduces an intersectional approach to segmented assimilation theory. Using the 2000 census, this study examines how within group differences in skill and gender condition the hourly earnings, joblessness and self-employment participation outcomes of five ethnic minority groups from the first to the second generation, compared against US-born, non-Hispanic whites. Findings generally support the mainstream assimilation hypothesis for all groups; a downward assimilation trajectory among Chinese men only; and a delayed assimilation trajectory for low-skilled Filipinas and high-skilled Cuban men and women. This study reveals that intra-group differences in skill and gender shape divergent segmented assimilation trajectories among members of the same ethnic group. This study challenges the emphasis on and primacy of ethnicity in predicting segmented assimilation in favor of an intersectional approach that considers how multiple, interdependent, and intersecting dimensions of identity and not only ethnicity shape the process of economic incorporation among ethnic groups.