The Brazilian official statistics show that the country is mainly urban, while authors including Veiga (2002) and Miranda and Silva (2013) present a more rural Brazil. The absence of a uniform way to define the rural areas in Bra-zil has led to diffused data about rural Brazil's size. Therefore, are Brazilian regions predominantly urban, rural or intermediate? This paper applies the rural definition methodologies from Eurostat/European Union to the municipalities of Brazil. The results show the predominance of the intermediary category in Brazilian territory, while the population mostly lives in urban areas. However, due to methodological characteristics, this paper reinforces the necessity of developing other methodologies which would be able to identify rurality and urbanity, considering socioeconomic dimensions.

Agricultural patterns could have diverse impact on long-run economic development. In the context of the US South, this paper examines the legacy of cotton on economic development focusing on a novel channel of structural change. Exploiting variation in cotton production along with agro-climatic conditions, I show that the legacy of cotton has impeded local economic development exclusively as of the mid-twentieth century. The structural break is found to be a consequence of cotton mechanization. Evidence from exogenous variation in the boll weevil infestation shows that cotton farming was strongly dependent on tenant farmers with little human capital. Following cotton mechanization, cotton tenants were largely displaced and absorbed by the manufacturing sector. I then find that the inflow of cotton tenants has reduced labor productivity in the manufacturing sector. Beyond the composition effect, the negative impact on manufacturing productivity has persisted in the . . .

Historical studies of labor markets frequently suffer from a lack of data on individual income. The occupational income score (OCCSCORE) is often used as an alternative measure of labor market outcomes. Using modern Census data, we find that the use of OCCSCORE biases results towards zero and can frequently result in statistically signif- icant coefficients of the wrong sign. We use a machine learning approach to construct a new adjusted score based on industry, occupation, and individual demographics. Our alternative score substantially outperforms OCCSCORE in both modern and historical contexts. We illustrate our approach by estimating racial and gender earnings gaps in the 1915 Iowa State Census and intergenerational mobility elasticities using linked data from the 1850-1910 Censuses.

In 1971 economist Barbara Bergmann’s developed the “occupational crowding model,” which posited that black men are “crowded into” low-wage occupations and “crowded out” of high-wage occupations due to employer discrimination. In quantitative analysis I’ve conducted for the years 2010 through 2011 the results have yielded a different picture from what Bergmann’s model predicts; while African American men are underrepresented in high-wage occupations, consistent with her model, this group does not appear to be overrepresented in low-wage occupations. I attribute this to demographic changes in the U.S. labor force, and conclude by suggesting that the model now requires further specification.

One of the main political debates in today's society is equal rights for everyone, and that includes equal pay for both men and women. Currently there is a wage gap between men and women due to differences in the industries that they work in, differences in human capital, and discrimination (McLay, 2017). Since the senior class at Illinois Wesleyan is about to graduate and go into the work force, I wanted to see how a female's wages throughout her career are affected by whether or not she had children. Starting and having a family has long been an important part of society, so it is good to know the extent to which wages are affected by children. In this paper, I am going to look at the differences in wages between four groups: men with children, men without children, women with children, and women without children, in order to analyze how having children influences the gender wage gap for women.

Republican candidates often receive between 30% and 40% of the two-way vote share in statewide elections in Massachusetts. For the last three Census cycles, MA has held 9-10 seats in the House of Representatives, which means that a district can be won with as little as 6% of the statewide vote. Putting these two facts together, one may be surprised to learn that a Massachusetts Republican has not won a seat in the U.S. House of Representatives since 1994. We argue that the underperformance of Republicans in Massachusetts is not attributable to gerrymandering, nor to the failure of Republicans to field House candidates, but is a structural mathematical feature of the distribution of votes. For several of the elections studied here, there are more ways of building a valid districting plan than there are particles in the galaxy, and every one of them will produce a 9-0 Democratic delegation.

It is well documented by demographers that there is a long and persistent under-coverage of adult black males in the US Census. Despite this, the census undercount has been largely ignored in research using census data. Similar omission patterns also exist in other household based surveys, such as the Current Population Survey and the Survey of Income and Program Participation. I demonstrate that estimates of the undercount that rely on counts from vital statistics data are understated and provide estimates of the undercount of prime age black men in household-based survey data that are robust to under-coverage in vital statistics data. Because the incarcerated are automatically included in the Census, the population at risk of becoming incarcerated provides a unique opportunity for the identification of non-reporter characteristics. I use variation in incarceration by state and year to estimate the impact of increases in incarceration on non-reporting. I find that 90 percent of the incarcerated population would have been non-reporting had they not been incarcerated. Applying reasonable estimates of the size of the population at risk of incarceration, I conclude that non-reporting is almost entirely driven by the population at risk of incarceration. I then use data from the Survey of Inmates on labor market outcomes of inmates prior to incarceration to impute outcomes for the non-reporting population. Accounting for non-reporting meaningfully increases estimated gaps in black-white educational attainment , unemployment rates, and annual earnings.

This paper provides new evidence regarding the economic effects of a high national minimum wage in the United States. We examine the short and longer-term economic effects of the 1966 Amendments to the Fair Labor Standards Act (FLSA) which increased the U.S. minimum wage to its highest level of the 20 th Century and extended coverage to an additional 9.1 million of the lowest paid workers. Our research design is a dynamic extension of Card's (1992) methodology that exploits state-level differences in the "bite" of a national minimum wage due to differences in the standard-of-living and industry composition. The results show that the 1966 FLSA increased wages dramatically and reduced aggregate employment modestly, implying a demand elasticity with respect to wages of-0.16. The disemployment effects, however, were significantly larger among African-American men, roughly half of whom would have earned below the new minimum wage in 1966.

The Affordable Care Act’s (ACA) Medicaid expansion is unique in terms of expanding coverage to adults without dependent children (“childless adults”) and increasing community-based outreach to raise awareness about coverage options. This dissertation explores the labor market and outreach effects of the ACA’s Medicaid expansion on childless adults and parents, respectively. First chapter of the dissertation investigates the pre/post labor market implications of the ACA’s Medicaid expansion for a population near the income eligibility cutoff. Using an arguably exogenous variation at this cutoff, I find that Medicaid enrollment increases for childless adults. This leads to an employment transition from full-time (≥35 Hrs) to part-time employment (<35 Hrs) after the expansion. The employment transition is mainly driven by the increase in employment for working less than 20 hours. These findings support the presence of employment lock – individuals who are employed primarily to retain health benefits. Replication of existing studies that used difference-in-differences (DD) models with expansion states as the treatment yield no employment effects. The treatment group in these models, however, is large and heterogeneous. In the second chapter, I assess the effect of the ACA’s Medicaid expansion on the retirement decision of low-income adults aged 55 to 64 years. This chapter also focuses on childless adults, a group that gained access to Medicaid coverage after the ACA. Using an instrumental variables (IV) model that exploits both the expansion decision of states and timing, I find that the probability of retirement increases by 14.8 percentage points for childless adults with Medicaid. The probability of retirement increases by 13.4 and 16.1 percentage points for men and women, respectively. In the last chapter, I show the effect of information on Medicaid enrollment of previously-eligible parents (“woodwork effect”). Previous studies that analyze the changes in Medicaid take-up often ignore potential outreach effects. After controlling for the change in income eligibility limits, I find that woodwork effects are stronger in hard-to-reach communities that consist of low-educated, Hispanic, and non-white parent groups. In addition, woodwork effects increase enrollment in non-expansion states, particularly in states that have high search volume of Medicaid. Overall, the findings support the presence of information spillovers under the ACA’s Medicaid expansion.

Son preference and female genital cutting – two of the most extreme forms of gender discrimination – exhibit large variation across the globe, often within narrowly defined geographical regions. This paper studies the historical origins of this variation by testing the anthropological theory that pre-industrial subsistence on pastoralism – herding animals – (i) induced a preference for sons over daughters because herding was by far the most male-dominated form of subsistence and (ii) generated larger payoffs to controlling female sexuality, e.g., through invasive forms of genital cutting, due to extended periods of male absenteeism. The analysis exploits within-country variation across 500,000 women in 43 countries who exhibit heterogeneity in the extent to which their ethnic group’s ancestors subsisted on pastoralism. The results document that women from historically pastoral societies (i) exhibit a higher preference for sons, as reflected both in desired and actual ratios of sons at birth; (ii) are more likely to have been infibulated, the most invasive form of female genital cutting; and (iii) report to have less control over their sexuality in general. These results suggest that contemporary variation in the extent to which sons are more valued than daughters and how self-determined women are in their sexuality can be traced back to a functional relationship between historical environmental conditions and societal norms which have persisted until today

Innovation has increased dramatically since the advent of the 1765 steam machine. Today, we possess technology that can process millions of instructions in a matter of seconds. Endogenous growth theory has stressed the importance of technological change and education as a source of economic growth. Thanks to technological innovation and the related economic growth, many people are better off today than before. However, computers cannot mimic human capacity in creativity and the ability to envision new solutions to existing problems. The rate at which workers use these unique capabilities is industry related. Therefore, in this study I relate the proportion of workers in each industry to known industry level innovation rates to predict economic growth rates at the local level. This study is especially important, as it guides policy makers as to what incentives they might use to attract new industries to bolster their future economic well being. Specifically, this study analyzes how innovation and other factors impact growth in the United States through the years 2005-2015 at the Metropolitan Statistical Area (MSA) using a lagged first-difference quantitative statistical model. This model is well matched to the structure of the data in revealing causality between the independent variables and the dependent. Results indicate no significant relationship between innovation, as measured . . .

We define many useful existing compactness measures, and other geometric features of legislative districts we introduce. We use all of these quantities in Section 3.2. We begin with basic notation used in many of the measures and then define the measures. Notation Denote a generic legislative district as D, and define it as a non-self-intersecting closed polygon with n vertices, each labeled (xi , yi) and numbered i in clockwise order (for i = 1, . . . , n). We choose an arbitrary starting vertex for label i = 1 and (using clock or modular algebra) define i = n + 1 = 1. The length of . . .

Many young people nationwide are undereducated, jobless, and living in poverty with no job prospects; in urban areas particularly, they face a continuing cycle of unemployment, in addition to substandard and often dangerous neighborhood conditions. Using greater Chicagoland (including the city and Cook County) as a case study, this article will highlight how capital and resources from the private sector, namely loans, investments, and services from regulated financial institutions (e.g., banks) could foster greater economic and community development, especially for underserved and at-risk youth. One way for banks to help promote and support programs that support youth employment is by aligning targeted investments with provisions of (and compliance with) the Community Reinvestment Act (CRA). Congress enacted the CRA in 1977 to encourage banks and thrift institutions to “serve the convenience and needs of the communities in which they are chartered to do business,” including low- and moderate-income (LMI) communities. The CRA requires each federal bank regulator, including the Federal Reserve, to evaluate the extent to which banks address the credit needs of LMI neighborhoods in their geographic market. On July 25, 2016, the Board of Governors of the Federal Reserve System (FRS), the Federal Deposit Insurance . . .

A long-standing debate is concerned over how long premigration socioeconomic differences persisted for immigrants and their descendants who entered at the turn-of-thetwentieth century. Some researchers argue that differences exist today, over 100 years after first arrival, while others argue that most differences disappeared after the third generation. However, none of this research has directly measured pre-migration socioeconomic status nor has it directly linked immigrants to their children. I create a new panel dataset that follows immigrants and their children from the sending country through settlement. Specifically, I link ship manifest records to census records to track how long premigration socioeconomic differences persist across generations. Passenger records provide a wealth of information of individuals including the occupation before arrival. I analyze how long premigration differences persist within and between groups. Whereas premigration socioeconomic status is associated with the first generation’s economic outcomes after settlement, many of these differences disappear by the second generation. These results suggest that background is not destiny for immigrant descendants. As scholars and politicians debate about whether countries should admit primarily high-skilled or low-skilled immigrants, the results from this article tell us whether such selection policies are necessary to ensure strong migrants’ performance in a period of open borders.

Introduction: Physical activity (PA) and sleep are associated with cerebrovascular disease and events like stroke. Though the interrelationships between PA, sleep, and other stroke risk factors have been studied, we are unclear about the associations of different types, frequency and duration of PA, sleep behavioral patterns (short, average and long sleep durations), within the context of stroke-related clinical, behavioral, and socio-demographic risk factors. The current study utilized Bayesian Belief Network analysis (BBN), a type of machine learning analysis, to develop profiles of physical activity (duration, intensity, and frequency) and sleep duration associated with or no history of stroke, given the influence of multiple stroke predictors and correlates. Such a model allowed us to develop a predictive classification model of stroke which can be used in post-stroke risk stratification and developing targeted stroke rehabilitation care based on an individual's profile. Method: Analysis was based on the 2004–2013 National Health Interview Survey (n = 288,888). Bayesian BBN was used to model the omnidirectional relationships of sleep duration and physical activity to history of stroke. Demographic, behavioral, health/medical, and psychosocial factors were considered as well as sleep duration [defined as short < 7 h. and long ≥ 9 h, referenced to healthy sleep (7–8 h)], and intensity (moderate and vigorous) and frequency (times/week) of physical activity. Results: Of the sample, 48.1% were ≤ 45 years; 55.7% female; 77.4% were White; 15.9%, Black/African American; and 45.3% reported an annual income < $35 K. Overall, the model had a precision index of 95.84%. We found that adults who reported 31–60 min of vigorous physical activity six times for the week and average sleep duration (7–8 h) had the lowest stroke prevalence. Of the 36 sleep (short, average, and long sleep) and physical activity profiles we tested, 30 profiles had a self-reported stroke prevalence lower than the US national average of approximately 3.07%. Women, compared to men with the same sleep and physical activity profile, appeared to have higher self-reported stroke prevalence. We also report age differences across three groups 18–45, 46–65, and 66+. Conclusion: Our findings indicate that several profiles of sleep duration and physical activity are associated with low prevalence of self-reported stroke and that there may be sex differences. Overall, our findings indicate that more than 10 min of moderate or vigorous physical activity, about 5–6 times per week and 7–8 h of sleep is associated with lower self-reported stroke prevalence. Results from the current study could lead to more tailored and personalized behavioral secondary stroke prevention strategies.

Building communities that are both functional and provide for our needs over time is no easy endeavor. There is no recipe for success that fits every community, and there are no magic bullets. Developing a fitting and sustainable economy is a challenge all communities face, but some are more equipped to manage. This guide provides an overview of Economic Development (ED) methods and strategies with the intention of beginning the conversation about how and why we do economic development. Goals and strategies change over time, and while we study and learn more about what our efforts do, and do not do, there will always be new challenges. Economic Development 101 is a guide that covers several topics related to the basics of economic development. While this guide can serve as an introduction to ED, the field changes constantly and the ability to innovate and adapt to change are useful skills. The guide is broken into three parts: ...

Coal and oil power plant retirements reduce air pollution nearby, but few studies have leveraged these natural experiments for public health research. We used California Department of Public Health birth records and Energy Information Administration data from 2001-2011 to evaluate the relationship between 8 coal and oil power plant retirements and nearby preterm births ( < 37 weeks gestational age). We conducted a difference-in-differences analysis using adjusted linear mixed models that included 57,005 births–6.5% of which were preterm–to compare the probability of preterm birth before and after power plant retirement among mothers residing within 0-5 km and 5-10 km of the 8 power plants. We found that power plant retirements were associated with a decrease in the proportion of preterm birth within 5 km (-0.019, 95% CI: -0.031, -0.008) and 5-10 km (-0.015, 95% CI: -0.024, -0.007) controlling for secular trends with mothers living 10-20 km away. For the 0-5 km area, this corresponds to a reduction in preterm birth from 7.0% to 5.1%. Subgroup analyses indicated a potentially larger association among non-Hispanic Black and Asian mothers compared to non-Hispanic White and Hispanic mothers and no differences in educational attainment. Future coal and oil power plant retirements may reduce preterm birth among nearby populations.

The quality and dynamics of mother-father couple relationships shape the experiences and well-being of the entire family.1,2 A large body of research, for example, suggests that children thrive when their parents are in stable, high-quality, low-conflict relationships.3-6 Despite the size and growth of the Latinoa population in the United States, little is known about the relationship dynamics of Hispanic couples or how they might differ from other racial and ethnic groups. Few studies have examined how Hispanic couples interact and communicate with one another, how they resolve arguments or disagreements, or the relevance of these factors for their family’s well-being. One reason that research on this topic is lacking is that data on these issues are scarce for the U.S. Hispanic population. A recent review of more than 20 (primarily national) data sets revealed that only one—the Supporting Healthy Marriage (SHM) evaluation data set—includes both a large enough sample of Latinos and information on an array of domains of family life. This data set therefore has the potential to address critical gaps in knowledge about Hispanic family life. Still, the SHM evaluation data set, while rich in information on married couplesb,c and their children, is a convenience sample of couples that may not represent the general population of Hispanic couples in the United States. This brief assesses the extent to which Hispanic participants in the SHM evaluation data set represent the broader U.S. population of Hispanic couples. Specifically, we examine how representative the study’s Latino couples are of low-income Hispanic couples with children (under age 18) in the general . . .

The 1990s were a glorious time for the Chicago Bulls, an age of historic championships and all-time basketball greats like Scottie Pippen and Michael Jordan. It seemed only fitting that city, county, and state officials would assist the team owners in constructing a sparkling new venue to house this incredible team that was identified worldwide with Chicago. That arena, the United Center, is the focus of Bulls Markets, an unvarnished look at the economic and political choices that forever reshaped one of America’s largest cities—arguably for the worse. Sean Dinces shows how the construction of the United Center reveals the fundamental problems with neoliberal urban development. The pitch for building the arena was fueled by promises of private funding and equitable revitalization in a long blighted neighborhood. However, the effort was funded in large part by municipal tax breaks that few ordinary Chicagoans knew about, and that wound up exacerbating the rising problems of gentrification and wealth stratification. In this portrait of the construction of the United Center and the urban life that developed around it, Dinces starkly depicts a pattern of inequity that has become emblematic of contemporary American cities: governments and sports franchises collude to provide amenities for the wealthy at the expense of poorer citizens, diminishing their experiences as fan and—far worse—creating an urban environment that is regulated and surveilled for the comfort and protection of that same moneyed elite.

A fundamental problem in education policy is how much educational outcomes are affected by government interventions on the supply side of the market. This paper is a response to this policy debate using a natural experiment setting in one of the most under-studied countries, Iran. It measures the effect of Iranian Cultural Revolution during which institutions of higher education were closed and supply of higher education was completely eliminated for 30 months. Using a regression discontinuity design, this paper documents the causal effect of this temporary elimination of supply of higher education on college attainment rates of affected cohorts. The results show that there is a small impact on men’s college attainment rate (about 10% or 1.5 percentage points) and no evidence of impact on women’s. This corroborates the argument that government interventions have little impact on educational outcomes when demand for education is high. It has important implications for higher education policy in both developing and developed countries. The Cultural Revolution is then used as an instrument to estimate return to college education for men.