Cities have traditionally been thought of as “growth machines”, while many suburban towns were notorious for exclusionary and growth-limiting not-in-my-backyard (NIMBY) policies aimed at protecting the property values of their “homevoters.” Increasingly, cities are experiencing substantial opposition to proposed new development, driven, in substantial part, by renters who fear that the development will make their homes less affordable and either cause them to have to leave the neighborhood or change the neighborhood to something less familiar and appealing . . .

While increasing evidence suggests an association between physical infrastructure in neighborhoods and health outcomes, relatively little research examines how neighborhoods change physically over time and how these physical improvements are spatially distributed across populations. This paper describes the change over 25 years (1985–2010) in bicycle lanes, off-road trails, bus transit service and parks, and spatial clusters of changes in these domains relative to neighborhood sociodemographics in four US cities that are diverse in terms of geography, size, and population. Across all four cities we identified increases in bicycle lanes, off-road trails, and bus transit service, with spatial clustering in these changes that related to neighborhood sociodemographics. Overall, we found evidence of positive changes in physical infrastructure commonly identified as supportive of physical activity. However, the patterning of infrastructure change by sociodemographic change encourages attention to the equity in infrastructure improvements across neighborhoods.

I estimate demand for health insurance using consumer-level data from the California and Washington ACA marketplaces. I use the demand estimates to simulate the impact of policies targeting adverse selection, including subsidies and the individual mandate. I find (1) high own-premium elasticities of -6.9 to -7.8, but low insurance coverage elasticities of -0.5 to -0.6; (2) minimal response to the mandate penalty amount, but significant response to the penaltys existence, suggesting consumers have a taste for compliance; (3) mandate repeal has minimal effect on consumer surplus because ACA subsidies already mitigate adverse selection by shielding most consumers from premium increases; and (4) mandate repeal reduces average annual consumer surplus by up to $1, 500 if consumers were exposed to premium increases under voucher-type systems, instead of ACA subsidies. The economic rationale for the mandate depends on the extent of adverse selection and the presence of other policies targeting selection.

In 2016, Hispanic unemployment rates fell to their lowest levels before the Great Recession started (5.6% in the first quarter, and 5.8% in the second and third quarters). The decline continued a general pattern, as seen in Figure 1. After reaching its high during the past decade of 12.8% in the first quarter of 2010, Hispanic unemployment rates generally fell and then stabilized between the third quarter of 2014 and the fourth quarter of 2015. Still, despite this decline, Hispanic unemployment in 2016 had yet to return to the rates observed in 2006.

This study examined the significance of three macro social determinants (i.e., family, neighborhood, and school factors) on the educational aspirations and integration of social work minority undergraduate students using a qualitative study of 40 interviews. Two research questions were raised: (1) how did family, neighborhood, and school contextual factors account for the participants’ postsecondary education in social work, a study that places more emphasis on the attainment of humanitarian goals over future economic outlook? and (2) what roles did family, neighborhood, and school play in shaping these participants’ postsecondary educational aspirations and integration? Overall, educationally resilient participants received strong family support but also encountered social roadblocks, stigmatization, and racial discrimination in the mainstream culture. Ironically, these social challenges also served as the major driving forces that inspired them to pursue their postsecondary education and major in social work. The findings of this study urge the general public and higher educational settings to develop more cultural sensitivity, validate unique contribution, and promote equality of cultural diversity among minority social work students.

We investigate the effect of higher house prices or rental costs on family size. We provide a static model of a household's choice of family size assuming constant elasticity of substitution preferences between children, leisure, and other goods, and Cobb–Douglas household production of children using parental time and housing. We then explore the wealth and substitution effects that changing house prices or rental costs have on desired family size. Renters are predicted to have fewer children in response to higher rents. Home owners are predicted to have more children in response to higher house prices only if they have sufficient initial housing and low substitution between family size and other consumption, and fewer children otherwise. Finally, we provide exploratory correlations between the change in lagged house prices or rental costs and the change in number of children born to women using aggregated census units in New Zealand. We find weak negative correlations in both cases.

In the United States, the lack of health insurance coverage among Hispanics is striking; about 27 percent of the Hispanics age 19-64 were not covered in 2015 by either private or public insurance as compared to 17 percent of blacks and 11 percent of whites (Barnett & Vornovitsky, 2016). Mexican Americans are the largest group in the Hispanic population and account for about 2 in every 3 Hispanics residing in the U.S. (Lopez, 2015). Mexican Americans have the most unfavorable health insurance coverage of any population group in the nation; one in every 3 Mexican Americans age 64 years and under did not have health insurance coverage in 2012 (Centers for Disease Control and Prevention, 2012). Nearly a fourth of the nation's 46.7 million uninsured population in 2013 were Mexican Americans (Lopez, 2015).

Consequences of historic redlining—the once federally sanctioned denial of services to residents of predominantly non-White neighborhoods—are often measured in terms of structural decay and economic stagnation. However, the effects of redlining are also evident in the health disparities observed between maligned neighborhoods and surrounding communities (Gee, 2008). With this fact in mind, in this article I juxtapose selected historic maps and data in an effort to examine the correlation between redlining and incidence of tuberculosis in 1950s Austin, Texas. The impetus for this article was a 1952 fundraising flyer for a campaign sponsored by the Travis County Tuberculosis Association. On the back of the flyer was a supplemental map of reported cases and deaths resulting from the disease in the Austin area for the previous year (exhibit 1). On examining the map, I was struck by a clear concentration of reported cases and deaths from the disease in the southeast area of the city, north of the Colorado River between East 1st and East 11th Streets. The high density of cases reported for that area suggested higher rates of the disease in those communities when compared with the rest of the map. Certainly, maps drawn on the back of antique fundraising flyers found in used bookstores hardly constitute vetted data. However, the high density of cases shown for that part of the city was consistent with both the historic characteristics of the area and the behavior of the disease. . .

In the United States, the lack of health insurance coverage among Hispanics is striking; about 23 percent of the Hispanics age 19-64 were not covered in 2015 by either private or public insurance as compared to 17 percent of blacks and 11 percent of whites (Barnett & Vornovitsky, 2016). Mexican Americans are the largest group in the Hispanic population and account for about 2 in every 3 Hispanics residing in the U.S. (Lopez, 2015). Mexican Americans have the most unfavorable health insurance coverage of any population group in the nation; one in every 3 Mexican Americans age 64 years and under did not have health insurance coverage in 2012 (Centers for Disease Control and Prevention, 2012).

There is strong evidence that raising the level of attainment of higher education degrees has historically yielded long-run economic and social benefits in the United States. Yet investing in greater educational success is costly, because it involves sending more students to college for longer periods of time, and because further investment may be needed to improve attainment rates. In this report, we present a simple model of the long-run economic costs and benefits of improving attainment by increasing completion rates. Given the assumptions of our model, costs exceed benefits over a number of years, but economic returns later begin to kick in and eventually the program of investment yields a positive net economic return. Currently, only 61 percent of first-time, full-time students at four-year colleges complete their college degree within eight years, which is twice the normal time. As a result of these low completion rates, one-quarter of thirty- to fortyyear-olds who have attended some college, including both two- and four-year . . .

Although research has established economic disadvantage as one of the strongest, most robust predictors of urban violence, the conditions under which this relation holds need further elaboration. This study examines the disadvantage–violence link across age-specific transitional periods from adolescence to adulthood and provides theoretical arguments for why the strength of this relation should decline with age. Using 90 of the largest cities in the United States, the present study analyzes the impact of economic disadvantage and other urban conditions (residential instability, family disruption, and population heterogeneity) on age-specific homicide counts from 1984 to 2006. The analytical strategy incorporates temporal trends by using negative binomial fixed-effects regression models. The results reveal a consistent decline from adolescence to adulthood in the strength of the estimated effects of economic disadvantage, residential instability, and family disruption on homicide trends. The findings are discussed in terms of the implications for future research and public policy.

The Great Lakes region has become a significant focal point in our national political discourse. Beyond its political influence, the region holds a critical position in debates about the future of the United States and fostering broad-based prosperity nationwide. Many of the countrys social, economic, and political challenges are playing out in this region, home to 50 million people.

Although several studies suggest foreign manufacturers in the United States may provide access to good quality employment opportunities with fair compensation and stable benefits, the question of who benefits more from the location of manufacturing foreign direct investment (FDI) remains open. Using the National Establishment Time Series data set and individual earnings data from the American Community Survey Public Use Microdata Sample files, this research conducts a quantile regression to estimate the earnings distribution effects that a concentration of manufacturing FDI may have on different earnings groups in Georgia between 2004 and 2010. The research does not measure inequality directly, but the findings both from place-ofwork and place-of-residence earnings analyses suggest strong implications relating to the issue of inequality among people. The concentration of manufacturing FDI in a certain area shows the largest distribution effects on area workers in the lower earnings group and residents in the middle earnings group.

No region of the United States fared worse over the postwar period than the Rust Belt, the heavy manufacturing region bordering the Great Lakes. This paper hypothesizes that the Rust Belt declined in large part due to the persistent labor market conflict which was prevalent throughout the Rust Belts main industries. We formalize this thesis in a two-region dynamic general equilibrium model in which labor market conflict leads to a hold-up problem in the Rust Belt that reduces investment and productivity growth and leads employment to move from the Rust Belt to the rest of the country. Quantitatively, the model accounts for much of the large secular decline in the Rust Belts employment share before the 1980s, and its relative stabilization since then, once labor conflict decreased. The model also includes a foreign sector to assess the alternative hypothesis that higher imports were behind the Rust Belts decline. This hypothesis is inconsistent with the timing of the Rust Belts decline.

The desire to understand household location decisions has dominated the use of revealed preference models, whereby hedonic price modeling has allowed researchers to identify the implicit prices that households pay for desirable amenities such as good weather and good schools. This research contributes to the limited work on identifying the implicit valuation that firms place on these same amenities as well as other local characteristics of the business environment. Specifically, firm’s implicit payment for urban agglomeration amenities is assessed, and it is found that firms place a high value on industry diversity, but consider both competition and industry specialization to be disamenities. The findings presented here also show that firms and households have very similar preferences for amenities that have previously been shown to be important to households.

The growing disconnect between humans and nature has implications for human well-being. Research has linked exposure to nature with various benefits including improved focus, vitality, productivity, and reduced stress, factors that may enhance the academic performance of individual students. In intensively-urbanized landscapes with few natural elements this effect could, via aggregated population-level impacts, influence the academic performance of entire populations, negatively affecting educational attainment and propagating urban poverty. Designing urban environments to provide increased interaction with natural landscape elements such as vegetation could mitigate this effect, benefiting the academic growth and future success of urban students. Recent studies support this idea; however, this effect is poorly understood, hindering the management of urban environments to improve educational outcomes. This study explores relationships between urban nature and the academic performance of urban schools using the Twin Cities Metropolitan Area of Minnesota, USA as a case study area. We used regression analysis to identify relationships among environmental variables on and around school campuses (i.e., tree cover, vegetated land covers, water) and four measures of population-level third-grade reading and mathematics success, accounting for school socioeconomic and demographic characteristics. Contrary to expectations, we found a positive relationship between impervious surfaces and reading performance, while relationships between two vegetated land covers (grass, shrub) and water bodies and both mathematics and reading academic success were non-significant. We found a significant, positive relationship between tree cover and reading performance, suggesting that initiatives aimed at increasing tree cover in student environments could support academic success.

In this paper, we consider the problem of predicting demographics of geographic units given geotagged Tweets that are composed within these units. Traditional survey methods that offer demographics estimates are usually limited in terms of geographic resolution, geographic boundaries, and time intervals. Thus, it would be highly useful to develop computational methods that can complement traditional survey methods by offering demographics estimates at finer geographic resolutions, with flexible geographic boundaries (i.e. not confined to administrative boundaries), and at different time intervals. While prior work has focused on predicting demographics and health statistics at relatively coarse geographic resolutions such as the county-level or state-level, we introduce an approach to predict demographics at finer geographic resolutions such as the blockgroup-level. For the task of predicting gender and race/ethnicity counts at the blockgroup-level, an approach adapted from prior work to our problem achieves an average correlation of 0.389 (gender) and 0.569 (race) on a held-out test dataset. Our approach outperforms this prior approach with an average correlation of 0.671 (gender) and 0.692 (race).

We examine the impact of sibling gender composition on women’s adult earnings. Using data from Add Health, we find that women with any brothers earn roughly 10 percent less than women with no brothers in their late 20s and early 30s. This effect is primarily due to lower earnings within broadly defined education and occupation groups. We then explore mechanisms that may explain this result. We do not find strong evidence that differences in parental investment, cognitive ability, self-reported personality traits, or parental expectations drive our results. However, we find that more family-centered behavior (including family responsibilities, being in a committed relationship, and intention to have children) among those with brothers partially explains the result. We then confirm our results with data from the NLSY-CYA.

The macroeconomic consequences of large-scale early childhood development policies depend on intergenerational dynamics, general equilibrium (GE) e ects on labor and capital markets, and the deadweight loss of raising taxes to nance the policies. To study these policies, this paper ex- tends a standard GE heterogeneous-agent overlapping-generations macro model with earnings risk and credit constraints to incorporate early childhood investments (parental time and money) and estimates it using US data. We validate the model by performing an RCT evaluation of a short-run small-scale government program that funds early childhood investments and showing that the ef- fects on children’s education and adult income in the model are similar to the empirical evidence. We then evaluate a permanent large-scale version of this early childhood program, taking into account GE and taxation e ects, and nd that it yields a 10% welfare increase (in consumption equivalence terms), reduces inequality by 7%, and increases intergenerational mobility of income by 32%—approximately enough for the US to achieve Canadian or Australian levels of inequality and mobility. Welfare gains are twice the ones obtained by a program that uses the same revenue to fund a lump- sum transfer. ey are also twice the ones obtained by introducing the same early childhood program as a short-run partial-equilibrium policy—similar to an RCT. Although GE and taxation e ects re- duce the gains by one-tenth each, the long-run change in the distribution of parental characteristics more than compensates for those reductions. Key to this welfare gain is that investing in a child not only improves her skills but also creates a be er parent for the next generation. Although earlier generations gain less, welfare gains are positive for every new generation and grow rapidly during the transition.

An exogenous increase in the density of bank branches reduces the share of unbanked households among low-income households. This finding is established using US interstate branching deregulation between 1994 and 2010 as an exogenous shock to the entry of new branches in poor counties. We exploit household level data, and show that the effect is stronger for populations that are more likely to be rationed by banks, such as black households living in "high racially-bias" states, or for households living in rural areas where branch density is initially low. We then use deregulation to instrument the likelihood of holding a bank account and subsequently explore the effect on wealth accumulation. Holding a bank account helps poor household to accumulate wealth.