In this work we propose a dynamic Bayesian approach to modeling the population's density; predictors of different nature are used, e.g. economics and geographic indices. The model is applied to the evaluation of the location of population in the state of Massachusetts over a period of 50 years, from 1970 to 2010. The aim of this work is to introduce into the analysis both spatial and time correlation among data. We deal with AutoRegressive models, that provide the most common way to explore time dependence. In order to explore spatial correlation, we propose two different generalized regression mixed models: one with spatial independent random effects and one that includes spatial random effects evolving as a Conditionally AutoRegressive model (CAR). Both are compared with a baseline linear model. For the CAR model, we derive the analytical expression of the full conditional distributions necessary to build a MCMC algorithm efficiently coded in Julia language, and to sample from a posterior distribution. The implementation of the other two models were made in Stan.

The Long Island Sound Watersheds (LISW) are experiencing significant land use/cover change (LUCC), which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management. This paper modeled the LUCCs between 1996, 2001 and 2006 in the LISW in the New England region, which experienced an increase in developed area and a decrease of forest. The low-density development pattern played an important role in the loss of forest and the expansion of urban areas. The key driving forces were distance to developed areas, distance to roads, and social-economic drivers, such as nighttime light intensity and population density. In addition, this paper compared and evaluated two integrated LUCC models- the logistic regression - Markov chain model and the multi-layer perceptionMarkov chain (MLPMC) model. Both models achieved high accuracy in prediction, but the MLPMC model performed slightly better. Finally, a land use map for 2026 was predicted by using the MLPMC model, and it indicates the continued loss of forest and increase of developed area.

Population aging is widely assumed to have detrimental effects on economic growth yet there is little empirical evidence about the magnitude of its effects. This paper starts from the observation that many U.S. states have already experienced substantial growth in the size of their older population and much of this growth was predetermined by historical trends in fertility. We use predicted variation in the rate of population aging across U.S. states over the period 1980-2010 to estimate the economic impact of aging on state output per capita. We find that a 10% increase in the fraction of the population ages 60+ decreases the growth rate of GDP per capita by 5.5%. Two-thirds of the reduction is due to slower growth in the labor productivity of workers across the age distribution, while one-third arises from slower labor force growth. Our results imply annual GDP growth will slow by 1.2 percentage points this decade and 0.6 percentage points next decade due to population aging.

Rival schools of thought disagree on the impact increased mobility has on metropolitan economic performance. New Urbanist contributions to the discussion typically downplay the supposed benefits, emphasising the drawbacks of autodependency that often accompany increases in mobility. The current study adds to this debate by demonstrating that increased mobility inflates metropolitan median income, while imposing negative consequences for several measures of metropolitan workforce performance, and no clear impact in terms of economic growth. Findings suggest that the benefit to society of marginal mobility investment may well be negative. Prior to this paper, a metropolitan level estimate of mobility’s causal effect on economic and labor market outcomes had not been attempted. Future research should explore the apparent workforce outcomes more deeply and at the neighborhood or individual level in order to identify which subpopulations are impacted most strongly by increases in urban mobility. In spite of the potential for further research there is now strong evidence in the literature demonstrating that capital investment in the pursuit of urban mobility is above the efficient level. The imagined economic benefits of mobility investment have no clear empirical basis.

Over the past half century, American children have experienced increasingly unequal childhoods. The goal of this article is to begin to understand the implications of recent trends in social and economic inequalities among children for the future of inequalities in health among adults. The relative importance of many of the causal pathways linking childhood social and economic circumstances to adult health remains underexplored, and we know even less about how these causal pathways have changed over time. I combine a series of original analyses with reviews of relevant literature in a number of fields to inform a discussion of what growing childhood inequalities might mean for future inequalities in adult health. In the end, I argue that there is good reason to suppose that growing inequalities in childrens social and economic circumstances will lead to greater heterogeneity in adults morbidity and mortality.

We study the impact of the introduction of a form of bankruptcy protection on household investment in the U.S. South in the 1840s, which predated modern bankruptcy laws. During this period, certain southern states passed laws that protected married women's property from seizure in the case of insolvency, amending the common law default which vested a wife's property in her husband and thus allowed it to be seized for the repayment of his debts. Importantly, these laws only applied to newlyweds. We compare couples married after the passage of a law with couples from the same state who married before the passage of a law. Since states passed laws at different points in time, we can exploit variation in protection conditional on state and year of marriage. We find that the effect on household investment was heterogeneous: if most household wealth came from the husband (wife), the law led to an increase (decrease) in investment. This is consistent with a simple model where downside protection leads to both an increase in the demand for credit and a reduction in supply. Demand effects will only dominate if a modest fraction of total wealth is protected.

Since the early 2000s, after a long period of wide and persistent gaps, Latin America has experienced a steady decline in income inequality. This paper presents evidence of a trend reversal in labor income inequality, which is considered the main factor behind such a decline in income inequality across the region. Our analysis shows that, while labor income inequality increased during the 1990s, with heterogeneous experiences across countries, it fell in a synchronized way across countries beginning in the early 2000s. This systematic decline was supported by an expansion in real hourly earnings among the bottom of the wage distribution and, to a lesser extent, the middle part of the earnings distribution, thus reducing both upper and lower tail inequality. This trend reversal is explained by a lower dispersion of earnings among workers with observable different attributes and by a much less extensive dispersion of residual labor inequality. Regarding the earnings differentials among workers with observable different attributes, our analysis concludes that the decline in labor inequality in Latin America has been closely associated with a reduction in the college/primary education premium and in the urban-rural earnings gap, coupled with a steady drop in the high school/primary education premium, which accelerated markedly since the 2000s, as well as a reduction in the experience premium across all age-groups.

Over the past decade, Latinos have been buffeted by two major forces: a record number of immigrant deportations and the housing foreclosure crisis. Yet, prior work has not assessed the link between the two. We hypothesize that deportations exacerbate rates of foreclosure among Latinos by removing income earners from owner-occupied households. We employ a quasi-experimental approach that leverages variation in county applications for 287(g) immigration enforcement agreements with Immigration and Customs Enforcement and data on foreclosure filings from 2005-2012. These models uncover a substantial association of enforcement with Hispanic foreclosure rates. The association is stronger in counties with more immigrant detentions and a larger share of undocumented persons in owner-occupied homes. The results imply that local immigration enforcement plays an important role in understanding why Latinos experienced foreclosures most often. The reduced home ownership and wealth that result illustrate how legal status and deportation perpetuate the racial stratification of Latinos.

Since the 1940s, the black unemployment rate has consistently trended twice that of the white unemployment rate. This disparity contributes to lost income, fewer resources, and poorer health outcomes in the black community. In my thesis, I study black-white housing segregation, one of the many factors that could contribute to systematically higher black unemployment levels. Previous literature from the 1990s found a negative relationship between segregation and black employment. Using 2009 and 2010 data from the US2010 Project and the Integrated Public Use Microdata Series, Current Population Survey, I tested to see if this relationship still existed 20 years later. With the newer data, I found no statistically or substantively significant association between segregation and black employment.

The economic status of women in Georgia is a key factor in the overall health and future of the state’s economy. Women represent a majority of Georgia’s adult population1 and nearly half of the workforce. 2 In more than half of all Georgia households with children, women are primary or co-breadwinners.3 Despite their importance, women face a host of barriers keeping them, and Georgia’s economy, from reaching their full potential. Women working full-time in Georgia earn, on average, 70 cents for every dollar white men earn.4 The gender wage gap is even wider once part-time workers are taken into account. Georgia stands to gain a lot by removing these barriers to equal earnings for working women and their families. The state’s economy could add a staggering $14.4 billion if all working women in Georgia earned the same amount as men living in similar population areas, of the same age, education level and working the same number of hours. 5 Even more money could be added to Georgia’s economy if women who are now not working got more support, including child care and health care, which can allow them to rejoin the workforce or work more hours. . . .

Postnatal depression (PND) impacts an estimated 13% of women of childbearing age. PND impacts the mother’s offspring evidenced by increased risk of developmental delays, alcohol dependence, anxiety, and depression. Many investigators have examined the individual risk factors associated with PND but only a few studies outside of the U.S. have delved into the maternal neighborhood characteristics for PND. The aim of this study was to investigate the association between postnatal depression potential and structural neighborhood characteristics among at-risk women in a home visitation program in Hamilton County, Ohio. The archival data sources - eECS (individual level) and U.S. 2010 census tract (neighborhood level) were utilized for this study. The sample included 295 mothers enrolled in a home visitation program between 2006 and 2011 who were at risk for developing PND, observed as three-month Edinburgh Postnatal Depression Scale (EPDS) scores ≥ 10. After a principal component analysis of the structural characteristics, two components were maintained: Social Disadvantage and Stability. These two components were the neighborhood predicators analyzed in a generalized estimating equation (GEE) method using clustered standard errors. Stability was negatively associated with PND potential. Social Disadvantage was not found to be statistically significantly associated with PND potential. The findings suggest that women in home visitation programs who have high EPDS scores and live in unstable neighborhoods are at special risk of developing PND. This finding is significant in that it is possible for the counseling profession to intervene with at-risk women not only at the individual level, through differing therapeutic approaches (individual to group), but also at the neighborhood level (e.g., advocating for policy to increase stability).

Over the past two decades immigration enforcement has grown exponentially in the United States. We exploit the geographical and temporal variation in a novel index of the intensity of immigration enforcement between 2005 and 2011 to show how the average yearly increase in interior immigration enforcement over that time period raised the likelihood of living in poverty of households with U.S. citizen children by 4 percent. The effect is robust to a number of identification tests accounting for the potential endogeneity of enforcement policies, and is primarily driven by police-based immigration enforcement measures adopted at the local level such as 287(g) agreements.

Previous editions of the Navigator have presented national-level data about people with vision loss for the entire U.S. population, [school-aged children], and [infants and toddlers]. Now, we will focus on one of the largest demographic concentrations of people who are blind/visually impaired: older Americans. Various agencies and studies have focused on the aging population, and (if you are a regular reader of the Navigator) you won’t be surprised to learn that no single age range “defines” the senior population. For the purposes of this Navigator, we will focus on people ages . . .

Climate change is expected to worsen the negative effects of natural disasters like floods. The negative impacts, however, can be mitigated by individuals’ adjustments through migration and relocation behaviors. Previous literature has identified flood risk as one significant driver in relocation decisions, but no prior study examines the effect of the National Flood Insurance Program's voluntary program—the Community Rating System (CRS)—on residential location choice. This article fills this gap and tests the hypothesis that flood risk and the CRS‐creditable flood control activities affect residential location choices. We employ a two‐stage sorting model to empirically estimate the effects. In the first stage, individuals’ risk perception and preference heterogeneity for the CRS activities are considered, while mean effects of flood risk and the CRS activities are estimated in the second stage. We then estimate heterogeneous marginal willingness to pay (WTP) for the CRS activities by category. Results show that age, ethnicity and race, educational attainment, and prior exposure to risk explain risk perception. We find significant values for the CRS‐creditable mitigation activities, which provides empirical evidence for the benefits associated with the program. The marginal WTP for an additional credit point earned for public information activities, including hazard disclosure, is found to be the highest. Results also suggest that water amenities dominate flood risk. Thus, high amenity values may increase exposure to flood risk, and flood mitigation projects should be strategized in coastal regions accordingly.

Racial conflict has been at the center of US society since its inception. Various theories have tried to explain why racial conflict arises and what the motivating factors are. The aim of this article is to examine one of these theories––ethnic competition––by reviewing the sociological literature from the 1970s to present that focuses on racial interest, ethnic competition, and racial threat.

Using the farm tractor as a case study, I show that lags in technology diffusion arise along two distinct margins: scale and scope. Though tractors are now used in nearly every agricultural field operation and in the production of nearly all crops, they first developed with much more limited application, and early diffusion was accordingly limited in scope until tractor technology generalized. The results are consistent with theory and other historical examples, suggesting that the key to understanding technology diffusion lies not only in explaining the number of different users, but also in explaining the number of different uses.

Despite decades of work in environmental science and ecology, estimating human influences on ecosystems remains challenging. This is partly due to complex chains of causation among ecosystem elements, exacerbated by the difficulty of collecting biological data at sufficient spatial, temporal, and taxonomic scales. Here, we demonstrate the utility of environmental DNA (eDNA) for quantifying associations between human land use and changes in an adjacent ecosystem. We analyze metazoan eDNA sequences from water sampled in nearshore marine eelgrass communities and assess the relationship between these ecological communities and the degree of urbanization in the surrounding watershed. Counter to conventional wisdom, we find strongly increasing richness and decreasing beta diversity with greater urbanization, and similar trends in the diversity of life histories with urbanization. We also find evidence that urbanization influences nearshore communities at local (hundreds of meters) rather than regional (tens of km) scales. Given that different survey methods sample different components of an ecosystem, we then discuss the advantages of eDNAwhich we use here to detect hundreds of taxa simultaneouslyas a complement to traditional ecological sampling, particularly in the context of broad ecological assessments where exhaustive manual sampling is impractical. Genetic data are a powerful means of uncovering human-ecosystem interactions that might otherwise remain hidden; nevertheless, no sampling method reveals the whole of a biological community.

In several countries, girls are more likely than boys to be aborted, to die in infancy, or to have younger siblings, all of which signal that parents want sons. However, standard techniques for measuring sex preferences fail to detect more subtle forms of sex preferences, especially when preferences are heterogeneous within a population. The first chapter of this dissertation introduces a new framework for estimating heterogeneity in sex preferences using birth history records. The framework selects among many possible combinations of preferences over the sex and number of children to best match observed childbearing. Empirical estimates indicate that sex preferences are more widespread than previously reported and exhibit substantial heterogeneity within regions. In Africa, this heterogeneity is associated with agricultural traditions that favor men or women. During the apartheid era, all South Africans were formally classified as white, African, coloured, or Asian. Starting in 1970, the government directly provided free family planning services to residents of townships and white-owned farms. The second chapter of this dissertation demonstrates that, relative to African residents of other regions of the country, the share of African women that gave birth in these townships and white-owned farms declined by nearly one-third during the 1970s. Deferral of childbearing into the 1980s partially explains this decline, but lifetime fertility fell by one child per woman. The third chapter of this dissertation provides new evidence that family planning programs are associated with a decrease in the share of children and adults living in poverty. The chapter uses publicly-available census data to study the relationship between U.S. family planning programs in the late 1960s and early 1970s and short and longer-term poverty rates. Cohorts born after federal family planning programs began were less likely to live in poverty in childhood and in adulthood.

Background: Studies of mental health care received by persons with disabilities who make up a significant group of the U.S. popu- lation are limited. Objective: This cross-sectional study examined the relationship between disability and non-receipt of past year visits to a mental health professional among individuals with moderate to severe psychological distress. Methods: Study participants included a nationally representative sample of 5,566 people with moderate to severe psychological distress, extracted from 2011 to 2013 Integrated Health Interview using the 6-item Kessler Psychological Distress Scale. Self-reported disability domains included vision, hearing, mobility, upper body self-care difficulty, learning difficulty, communication difficulty, and cognition difficulty. Results: Sixty-four percent of participants reported a disability. Logistic regression analyses showed that (adjusting for nativity, other mental health conditions, and chronic pain) people aged 18e64 years old with disabilities have significantly lower odds (OR 5 0.52, p ! 0.001) of unmet mental health care services than people without disabilities. However, foreign-born respondents have significantly higher odds (OR 5 2.91; p ! 0.001) of unmet mental health care services than U.S. born Americans. After controlling for gender, other mental health conditions and chronic pain, people aged 65 and above with disabilities have higher non-significant odds (OR 5 1.34, p 5 0.361) of unmet mental health care services than people without disabilities. Additionally, females have significantly higher odds (OR 5 1.63, p 5 0.039) than males. Conclusions: Findings indicate the importance of identifying demographic characteristics associated with an increased risk for psycho- logical distress and increased unmet mental health care services among people with and without disabilities. ! 2016 Elsevier Inc. All rights reserved.

As private tour buses pulled up in a designated space in front of Little Havana’s Domino Park on Calle Ocho (Southwest 8th street), I awaited the arrival of a local resident, anthroplogy doctoral student and walking tour guide who agreed to accompany me alongside mixed strip of art galleries, tobacco and souvenir shops, and exilic-Cuban-owned (and increasingly pan-Latinx managed and frequented) retailers and restaurants. That I was born not far away yet felt so removed and disconnected from this space felt bittersweet, if not accentuated by the accompaniment of a resident-informant. My own primos (cousins), familial friends, and distant relatives, equally distant in the suburban Miami-Dade County and Broward County geographic spaces they now occupy, rarely if ever came to Little Havana, save for the occasional after-church meal at La Caretta or Ayestaran restaurant or to take a familial visitor (like me) to pasear (stroll) as the Abuelos once did with them (and with me and my siblings). Like I remember it, the park is full of mostly white, aging Cuban and other Latinx men, save for a few women who play dominoes (or chess) if not more seriously than their male counterparts, meanwhile tourists gaze through the fence, waiting to board their charter bus back to Miami’s cruise port.