This article examines the extent to which recent increases in intergenerational coresidence and financial dependency among young Black and White women are associated with declines in marriage and increases in nonmarital parenthood. We use U.S. Census and American Community Survey data for the period 1970 to 2010 to examine how changing family patterns by race have contributed to changes in intergenerational support. We find that compositional shifts in marriage and, to a lesser extent, nonmarital childbearing contribute to rises in coresidence and financial dependency over time, as well as to the growing gap between White and Black women. Controlling for marital and parental status reduces the temporal increase in coresidence and greatly reduces the race difference. Race differences in financial dependency are reversed after controlling for marital and family status, showing that coresiding young Black women are less, not more, likely than similar White women to be financially dependent on their parents.

Drawing on my own research in branding and global marketing over the last 25 years, the work of my academic peers, interviews with senior executives, trade publications, and my consulting work, I analyze brand strategies in a global economy where the forces of globalization are strong but not friction free: national and cultural differences cause turbulence, even resistance. I lay out actionable strategies for executives to launch and fly strong global brands, no matter the headwinds. My book contains many examples, visuals, and tools for you to use in analyzing your situation and discussing your aspirations with fellow executives, board members, and direct reports. My goal is to enable heads of business units and managers to navigate effectively and profitably in todays global marketscape.

The early 20th Century saw advances in U.S. public health infrastructure and policy. The 1916 poliomyelitis pandemic, the largest in U.S. history, tested these new advancements. While over 23,000 cases were diagnosed, public health quarantines expanded the social disruptions caused by the pandemic. The pandemic occurred during the start of the 1916 school year and schools were systematically closed in response to the viral outbreak. This paper uses state level 1916 polio morbidity as a proxy for schooling disruptions. We find that persons who were high school age during the pandemic had less educational attainment to their slightly older peers in 1940. These effects suggest that social disruptions caused by disease can be magnified by policies meant to mitigate the outbreak.

I argue that better educated workers are more mobile geographically because of larger wage offer dispersion, independent of geography. In a thin labor market, this generates larger wage rents (in excess of workers’ reservations) in new job matches, particularly for younger workers who are just beginning their careers. If an offer happens to arrive from a distant location, these larger rents are more likely to justify the cost of moving - even if the offer distribution is invariant geographically. I offer evidence based on the wage returns to both local and cross-state job matches and also on subjective migration costs.

We examine the relationship between local public goods, prices, wages, and population in an equilibrium inter-city model. Non-traded production, federal taxes, and imperfect mobility all affect how public goods (or “amenities” more broadly) should be valued from data. Reinterpreting the estimated effects of public infrastructure on prices and wages in Haughwout (2002), we find infrastructure over twice as valuable with our more general model. New estimates based on more years, cities, and data-sets indicate stronger wage and positive population effects of infrastructure. These imply higher values of infrastructure to firms, and also to households if moving costs are substantial.

Government spending shocks have substantially different effects on consumers across the income distribution: consumption increases for the poor whereas it decreases for the rich in response to a rise in government expenditure. I shed light on this issue by incorporating a progressive tax scheme and productive public expenditure into a heterogeneous agent model economy with indivisible labor. The model economy is able to successfully match aggregate and disaggregate effects of government spending shocks on consumption. When the government increases its spending and accompanies it by a rise in tax progressivity, the poor are employed and increase their consumption since after‐tax wage rates increase while the rich decrease their consumption because of a fall in after‐tax wage rates.

Especially in the central cities of the Northeast, neighborhoods that were once identified with black politics and culture are growing more ethnically diverse, and wealthier. John Mollenkopf examines demographic data from New York City's Harlem and Bedford-Stuyvesant and reflects on their implications for electoral politics and the fates of economically vulnerable black households.

Industry concentration has been rising in the US since 1980. Firm operating margins have also been rising. Are these signs of declining competition that call for a new antitrust policy? This paper explores the role of proprietary information technology systems (IT), which could increase industry concentration and margins by raising the productivity of top firms relative to others. Using instrumental variable estimates, this paper finds that IT system use is strongly associated with the level and growth of industry concentration and firm operating margins. The paper also finds that IT system use is associated with relatively larger establishment size and labor productivity for the top four firms in each industry. Successful IT systems appear to play a major role in the recent increases in industry concentration and in profit margins, moreso than a general decline in competition.

In the context of interactive query sessions, it is common to issue a succession of queries, transforming a dataset to the desired result. It is often difficult to comprehend a suc- cession of transformations, especially for complex queries. Thus, to facilitate understanding of each data transforma- tion and to provide continuous feedback, we introduce the concept of “data tweening”, i.e., interpolating between re- sultsets, presenting to the user a series of incremental visual representations of a resultset transformation. We present tweening methods that consider not just the changes in the result, but also the changes in the query. Through user stud- ies, we show that data tweening allows users to efficiently comprehend data transforms, and also enables them to gain a better understanding of the underlying query operations.

We examine the golden age of US innovation by undertaking a major data collection exercise linking US patents to state and county-level aggregates and matching inventors to Federal Censuses between 1880 and 1940. We identify a causal relationship between patented inventions and long run economic growth and outline a basic framework for analyzing key macro and micro-level determinants. We explore drivers of regional performance including population density, financial development, geographic connectedness and social structure. We then profile the characteristics of inventors and their life cycle, measure the returns to technological development, and document the relationship between innovation, inequality and social mobility. Our new data help to address important questions related to innovation and long-run growth dynamics.

The theoretical and empirical links between public health insurance access and fertility in the United States remain unclear. Utilizing a demographic cell-based estimation approach with panel data (1987-1997), we revisit the large-scale Medicaid expansions to pregnant women during the 1980s to estimate the heterogeneous impacts of public health insurance access on childbirth. While the decision to become a parent (i.e., the extensive margin) appears to be unaffected by increased access to Medicaid, we find that increased access to public health insurance positively influenced the number of high parity births (i.e., the intensive margin) for select groups of women. In particular, we find a robust, positive birth effect for unmarried women with a high school education, a result which is consistent across the two racial groups examined in our analysis: African American and white women. This result suggests that investigating effects along both the intensive and extensive margin is important for scholars who study the natalist effects of social welfare policies, and our evidence provides a more nuanced understanding of the influence of public health insurance on fertility.

Objectives: Policy-making related to immigrant populations is increasingly conducted at the state-level. State policy contexts may influence health insurance coverage by determining noncitizens’ access to social and economic resources and shaping social environments. Using nationally representative data, we investigate the relationship between level of inclusion of state immigrant policies and health insurance coverage and its variation by citizenship and race/ethnicity. Methods: Data included a measure of level of inclusion of the state policy context from a scan of 10 policies enacted prior to 2014 and data for adults ages 18–64 from the 2014 American Community Survey. A fixed-effects logistic regression model tested the association between having health insurance and the interaction of level of inclusiveness, citizenship, and race/ethnicity, controlling for state- and individual-level characteristics. Results: Latino noncitizens experienced higher rates of being insured in states with higher levels of inclusion, while Asian/Pacific Islander noncitizens experienced lower levels. The level of inclusion was not associated with differences in insurance coverage among noncitizen Whites and Blacks. Conclusions: Contexts with more inclusive immigrant policies may have the most benefit for Latino noncitizens.

Who files for bankruptcy in the United States is not well understood. Previous research relied on small samples from national surveys or a small number of states from administrative records. I use over 10 million administrative bankruptcy records linked to the 2000 Decennial Census and the 2001-2009 American Community Surveys to understand who files for personal bankruptcy. Bankruptcy filers are middle income, more likely to be divorced, more likely to be black, more likely to have terminal high school degree or some college, and more likely to be middle-aged. Bankruptcy filers are more likely to be employed than the U.S. as a whole, and they are more likely to be employed 50-52 weeks. The bankruptcy population is aging faster than the U.S. population as a whole. Lastly, using the pseudo-panels I study what happens in the years around bankruptcy. Individuals are likely to get divorced in the years before bankruptcy and then remarry. Income falls before bankruptcy and then rises after bankruptcy.

Many studies seek to understand the social and biological determinants of the sex ratio at birth, but the literature has neglected to explore how rates of fetal loss might affect a population’s sex ratio at birth due to a difficulty in measuring early fetal loss at a population level. Fetal loss is important for understanding sex ratios at birth because it occurs more often for male than female fetuses (Pelletier 1998; Caselli et al. 2006; Kraemer 2000, Carlo di Renzo et al. 2007; Byrne and Warburton 1987), and poor maternal wellbeing is linked to higher levels of fetal loss (Kim et al. 2012; Nepomnaschy et al. 2006; Agarwal et al. 1998; Norsker et al. 2012). To address this gap in the literature, I use birth intervals as a proxy of fetal loss after controlling for other determinants of birth intervals such as contraceptive use. Using data from the Demographic and Health Surveys (DHS) in sub-Saharan Africa (SSA), I find a negative relationship between the length of birth interval and the odds of a male birth. I suggest that this relationship can be explained by repeated early fetal loss which both decreases the odds of a male birth and lengthens the birth interval.

This paper uses Census IPUMS data from 1970 to 2000 and ACS data from 2010 to estimate the impact of oil booms and busts on wages and human capital formation in the USA. The paper finds that the oil boom between 1970 and 1980 was associated with a slower growth in the relative demand for skills in the oil and gas sector and regions where the sector had a large presence. The oil boom led to a sharp rise in real wages and a modest decline in college wage premium in oil-rich regions in the USA. Using a synthetic cohort approach, the paper finds that relative to cohorts who went to high school in the pre-oil boom period, the cohort reaching high school age during the oil boom was about 1-2% points less likely to have a college degree by 2000 and 2010.

Background Asian-Americans are a rapidly growing and diverse population. Prior research on dementia among Asian-Americans focused on Japanese-Americans or Asian-Americans overall, although marked differences in cardiometabolic conditions between subgroups have been documented. Methods We compared dementia incidence among four Asian-American subgroups (n=8,384 Chinese; n=4,478 Japanese; n=6,210 Filipino; n=197 South Asian) and whites (n=206,490) who were Kaiser Permanente Northern California members aged ≥64 years with no dementia diagnoses as of 1/1/2000. Dementia diagnoses were collected from medical records 1/1/2000–12/31/2013. Baseline medical utilization and comorbidities (diabetes, depression, hypertension, stroke, cardiovascular disease) were abstracted from medical records 1/1/1996–12/31/1999. We calculated age-standardized dementia incidence rates and Cox models adjusted for age, sex, medical utilization, and comorbidities. Results Mean baseline age was 71.7 years; mean follow-up was 9.6 years. Age-adjusted dementia incidence rates were higher among whites than “All Asian-Americans” or any subgroup. Compared with Chinese (13.7/1,000 person-years), dementia incidence was slightly higher among Japanese (14.8/1,000 person-years; covariate-adjusted-hazard ratio (adjusted-HR)=1.08; 95% CI=0.99–1.18) and Filipinos (17.3/1,000 person-years; adjusted-HR=1.20; 95% CI=1.11–1.31), and lower among South Asians (12.1/1,000 person-years; adjusted-HR=0.81; 95% CI=0.53–1.25). Conclusions Future studies are needed to understand how immigration history, social, environmental, and genetic factors contribute to dementia risk in the growing and diverse Asian-American population.

During the early decades of the twentieth century, a complex social trend developed in America. Sometimes referred to as the “Great Migration,” this time period saw more than six million African Americans leave their homes in the South and migrate to cities in the North and the West of the United States. While there were many reasons for African Americans leaving the South (e.g., searching for higher wages and employment rates, searching for greater tolerance), not all African Americans chose to leave their homes. This project intends to explore different variables that influenced individuals’ propensity to migrate. What factors played the greatest role in determining if an individual left his home in the South to migrate to the North or the West? For example, was the migrant’s home community or city size a significant contributor, or did other variables – such as the individual’s level of education and literacy status – play a more prominent role? At first glance, this research question may seem to be of little more importance than historical relevance. However, mass migration should not be something we only think of in our history textbooks, and it is certainly not limited to America – it is an intrinsic part of human nature across all cultures. As the author Jim Rohn once said, “If you do not like where you are, change it. You are not a tree.” The mass migration of groups of people has occurred for centuries and will continue to foster the globalization of culture, politics, and economics for years to come. Thus, by examining factors that contribute to an individual’s propensity to migrate through the lens of the Great Migration, this project intends to reveal prevalent truths that will allow policymakers and economists to better understand the phenomenon of mass migration. The first half of this project features a quantitative focus on the numbers themselves. Econometric analysis is used to test hypotheses on different variables in order to better understand individuals’ migration tendencies. However, the numbers alone can only tell part of the story. The second half of this project has a qualitative focus on personal accounts of persons who participated in the “Great Migration” in the early twentieth century. Interviews with two reverse migrants – individuals who left the South during the Great Migration and have since returned to the South – were conducted to see how the quantitative findings line up with qualitative research.

This paper builds on the analysis in Akcigit et al. (2017) by using US patent and Census data to examine macro and micro-level aspects of the relationship between immigration and innovation. We construct a measure of foreign born expertise and show that technology areas where immigrant inventors were prevalent between 1880 and 1940 experienced more patenting and citations between 1940 and 2000. We also show that immigrant inventors were more productive during their life cycle than native born inventors, although they received significantly lower levels of labor income than their native born counterparts. Overall, the contribution of foreign born inventors to US innovation was substantial, but we also find evidence of an immigrant inventor wage-gap that cannot be explained by differentials in productivity.

Differential privacy has been established as the primary framework for privacy preserving data-sharing. In the context of query answering through histograms, most of the datadependent solutions are composed of two steps: a partitioning phase that splits the histogram into bins and a finalizing step that approximates each bin with its average frequency or other similar statistics. Solutions that sort the histograms’ values prior to the partitioning phase can improve the utility of the final output. In this paper, we build SORTaki, a framework that integrates sorting with any partitioning and finalizing mechanism. Using SORTaki, we modify existing partitioning and finalizing solutions, as well as propose new ones, that mitigate the error of the final approximation up to 70% over existing sorting or nonsorting based algorithms. Additionally, we perform a principled and thorough empirical evaluation of current and proposed techniques, that highlights the right settings to use sorting and when to avoid it.

This paper examines the relationship between primary turnout and candidate ideology with a dataset of U.S. House candidates from 1980 to 2014. The findings are not fully consistent with either previous research or the conventional wisdom. I find that increased primary turnout is associated with the election of less extreme legislators on the Democratic side, but a similar relationship does not emerge for Republicans. In addition, the negative relationship between turnout and legislator extremism among Democrats is mainly apparent in closed primaries, where reformers would least expect this pattern to emerge. The results suggest that reformers should consider differences in the coalitions of political parties when adopting policies that are intended to mitigate legislative polarization.