When doing data science, it’s important to know what you’re building. This paper describes an idealized final product of a data science project, called a Continuously Updated Data-Analysis System (CUDAS). The CUDAS concept synthesizes ideas from a range of successful data science projects, such as Nate Silver’s FiveThirtyEight. A CUDAS can be built for any context, such as the state of the economy, the state of the climate, and so on. To demonstrate, we build two CUDAS systems. The first provides continuously-updated ratings for soccer players, based on the newly developed Augmented Adjusted Plus-Minus statistic. The second creates a large dataset of synthetic ecosystems, which is used for agent-based modeling of infectious diseases.

This report was created for the Organisation for Economic Co-operation and Development (OECD) for the following purposes: (1) to assess children’s material deprivation in the United States in a comparative perspective; (2) to examine the extent to which children from income-poor families are more often exposed to material deprivation compared to children from non-incomepoor families; (3) to identify the most common forms of material deprivation and the extent to which multiple deprivations exist; (4) to identify common forms of deprivation and the characteristics of children and families that increase the risk of multiple deprivations; and (5) to discuss the extent to which current social policies in the United States address these challenges.

Background and Objectives The encore years, or later life stages when adults enjoy health and free time, are the prime opportunity for leisure to maximize the overall quality of life. Physically active leisure is widely known to be linked to overall subjective well-being (SWB). However, experienced SWB or momentary emotion during active leisure as well as passive leisure has yet to be examined. Research Design and Methods Data were derived from the 2012/2013 American Time Use Survey Well-being modules. Propensity score matching (PSM) was used to identify comparable matched samples of older adults. Results The PSM identified 211 older adults who reported a series of emotions (i.e., happy, meaningful, tired, sad, stressed, pain) during active leisure, and the comparable counterpart (n = 211) during passive leisure. Results from the Wilcoxon Rank Sum tests showed that active leisure was associated with greater levels of experienced happiness and meaningfulness, as well as with lower levels of sadness (p < .05). Discussion and Implications Physically active leisure is linked to greater levels of experienced SWB among older adults. Although more detailed roles of active and passive leisure for experienced SWB are yet to be verified, choices that older adults make in their free time may significantly impact their experienced SWB and, in turn, their overall quality of life. Aging and public health policies should enhance accessibility to active leisure to promote older adults’ SWB.

I compare the strengths and weaknesses of five historical patent datasets and compare the suitability of each for use in innovation research. I first show that a number of historical sources exist that are nearly as complete as data on contemporary patenting. Second, I describe in detail differences across the datasets in terms of patent and inventor information included, reliability of provided information, and potential sample selection issues. Third, I show that while the datasets paint a remarkably consistent picture of aggregate invention through U.S. history, they contain important differences. In particular, differences in how patents are assigned to a location can produce statistically significant differences in estimates of the importance of agglomeration for invention. I discuss ways in which the different datasets can be used in conjunction with one another to improve inference.

Technological change has deeply shaped the U.S. labor market over the past four decades. It has been biased towards replacing routine labor through automation. We document business cycle features exhibited by routine-biased technological change. We ask if shifts in the task composition of labor demand away from routine labor account for the recessionary e ect of technology shocks on hours worked initially documented by Gali (1999). We show that such shifts in labor demand are able to generate a fall in hours worked within a Real Business Cycle model with capital-routine substitutability. We then bridge the gap between theory and data by building quarterly time series on hours worked and task premiums from the Current Population Survey. We assess the e ects of routine-biased technological change in the data by estimating a VAR model. Structural shocks are then identi ed by combining long-run exclusion and sign restrictions grounded in economic theory. Our results highlight that most of the decline in total hours worked is driven by routine-biased technology shocks through a decline in routine hours. This shock accounts for a signi cant amount of hours worked uctuations pointing out its relevance over the business cycle.

I examine whether the expansion of Medicaid eligibility under the Affordable Care Act increases the supply of entrepreneurs as measured by self-employment. Using the 2003–2017 Current Population Survey and focusing on childless adults in low-income households, I apply difference-in-differences, propensity score weighting, and instrumental variable (IV) methods. I find that expanding Medicaid eligibility raises the self-employment rate by 0.8 to 1.6 percentage points, without increasing self-employment exit. IV estimates imply that covered individuals have 8 to 11 percentage points higher probability to become self-employed. In the analysis of policy heterogeneity, I find evidence that the underlying mechanism of the effect was through the reduction of entrepreneurship lock. The results suggest that limited access to health insurance may be a barrier to entrepreneurship.

Migration has long been considered one of the key mechanisms through which labor markets adjust to economic shocks. In this paper, we analyze the migration response of American workers to two of the most important shocks that have hit Western economies since the late 1990s-import competition from China and the introduction of industrial robots. Exploiting plausibly exogenous variation in ex

Objective The goal of this study was to analyze differences in the employment and wage trajectories of college-educated young workers in the United States, as distinguished by the timing of their entry into the labor market relative to the onset of the 2008–09 recession. Methods and findings Using annual American Community Survey microdata, we analyzed the first six years of employment and wage outcomes for cohorts of young workers on traditional-student pathways entering the market (1) in 2006, shortly before recession onset; (2) in 2009, during the recession; and (3) in 2012, three years after the recession officially ended. We found evidence for negative effects on outcomes and outcome trajectories differentiated by the recession’s proximity to workers’ labor market entry, including lower wages for the cohort entering in 2009. However, recession effects tended to be smaller for workers at the high end of the education gradient or with no direct exposure to the recession and were outweighed by gendered labor outcome disparities. We also observed a possibly enduring, recession-induced rise in the number of idle young males and the proportion of male and female high school graduates enrolled in college and not working. Conclusions Cohort differences in labor outcomes show that the disadvantages of entering the labor market during an economic downturn appear lasting. However, the subordinate role of timing effects in sorting young workers’ employment and wage rates, when compared to the stark stratification of employment and wage outcomes by education or sex, is a useful reminder that these latter social structures remain key determinants of labor outcomes.

We use the Theil index and data from the 2012–2016, American Community Survey 5-Year Sample to document and analyze gender wage inequality for American Indian and Alaska Native (AIAN) women across single, multiracial and ethnic identity groups. Mean differences in hourly wages by gender contribute little to measured wage inequality when individuals are separated based upon their proximity to tribal homeland areas. Instead, we find between-group wage inequality is a function of glass-ceiling effects that differ by AIAN identification and homeland area. Differences in glass-ceiling effects across AIAN identity groups suggest the need to disaggregate data by AIAN ethnic identity. Furthermore, under certain circumstances, it may be appropriate to combine some racial AIAN identity groups into a single population even if the focus is to study policy impacts on citizens of federally recognized AIAN nations for those using government survey data.

This guide is an overview of best practices in the design and administration of beneficiary surveys for use in evaluations of section 1115 Medicaid demonstrations. Beneficiary surveys are particularly important data sources for evaluating demonstrations with eligibility and coverage provisions. Recent section 1115 policies of this type include community engagement requirements, premiums or monthly beneficiary account contributions, non-eligibility periods as a consequence of noncompliance with program requirements, healthy behavior incentives, and waivers of retroactive eligibility. 1 Surveys can yield rich information on beneficiaries’ understanding of and experiences with each of these policies. They can also help states assess changes in beneficiary outcomes over time, including for those who disenroll or transition to other coverage.

Over the past several decades the U.S. economy has undergone tremendous shifts with the precipitous decline of manufacturing, the rapid growth of digital and automation technologies, and the polarization of job growth between high- and low-wage occupations with middle-wage job growth trailing behind. These changes have predominantly benefitted educated workers, fueling widening inequality and calling into question the future of good jobs for the majority of workers who do not have college degrees. To better understand the relationships between these industry-level changes and their implications for building solid pathways into the middle class, PolicyLink and the University of Southern California Program for Environmental and Regional Equity (PERE) examine these economic changes in the nation’s largest metropolitan areas between 2005 and 2015. This analysis is described in Regional Economies in Transition: Analyzing Trends in Advanced Industries, Manufacturing, and the Service Sector to Inform Inclusive Growth Strategies, which presents a typology that classifies the 150 largest metros into seven types based on: (1) the growth of advanced industries, such as computer systems design and chemical manufacturing; (2) the decline of traditional manufacturing jobs; and (3) the quality of jobs in service-sector industries that generally do not require a bachelor’s degree and are therefore more accessible to economically insecure workers (defined as those with incomes below 200 percent of the federal poverty level).1 The table below presents a summary of the seven regional types.

This paper examines mortality differentials in Brazil and states between 1980 and 2010,using the Brazilian Ministry of Health Database. We use Modal age at death and measures of mortality compression to analyze regional and gender differences. We estimate age-specific mortality rates by single ages using two approaches: Wilmoth and colleagues (2012) Log-Quad approaches and Topal ́s method proposed by Gonzaga and Schmertmann (2016). Our results show that provincial disparities in mortality in general across regions of the country. Moreover, based on the modal age at death and the interquartile range (IQR) of ages at death. We find that there is a process of compression of mortality with increasing modal age at death.

Climatic variability has been shown to affect many underlying determinants of child malnutrition, including food availability, access, and utilization. Evidence of the effects of changing temperatures and precipitation on children’s nutritional status nonetheless remains limited. Research addressing this knowledge gap is merited given the short- and long-run consequences of malnutrition. We contribute to the literature on this issue by estimating the effects of temperature and precipitation anomalies on the weight of children ages 0-59 months across 16 countries in sub-Saharan Africa. Results from fixed-effects linear regression models show that precipitation anomalies have significant and non-linear effects on child weight, with sharp increases in thinness under dry conditions and minimal benefits to above-average precipitation. The negative effects of dry spells on acute malnutrition are significantly amplified by concurrent exposure to above-average temperatures. Tests for differences in the effects of climatic variability across sub-populations show statistically significant differences according to maternal education and children’s residence in rural or urban areas. Substantively, however, these differences are a matter of degree rather than kind. Our results underscore the vulnerability of young children to climatic variability and its second-order economic and epidemiological effects. The study also highlights the corresponding need to design and assess interventions to effectively mitigate these impacts.

This paper studies how access to financial services among a previously unbanked group affects human capital, labor market, and wealth outcomes. We use novel data from the Freedman's Savings Bank-created following the American Civil War to serve free Blacks-employing an instrumental variables strategy exploiting the staggered rollout of bank branches. Families with accounts are more likely to have children in school, be literate, work, and have higher occupational income, business ownership and real estate wealth. Placebo effects are not present using planned but unbuilt branches, or for Whites, suggesting significant positive effects of financial inclusion.

The recent decade witnessed a worsening of the affordable housing crisis across the country. Inclusionary zoning (IZ) has been a popular municipal remedy for the crisis. However, it is unclear whether IZ actually adds to the affordable housing stock, and whether it achieves its goal at the expense of average homeowners. Through a case study of New Jersey and North Carolina, this paper aims to address these two questions. The results suggest that there is no statistically significant positive relationship between the presence of IZ and the housing price in the two states, but its beneficiary effects are also debatable.

We investigate the impact of computerization of white collar jobs on wages and employment. Using online job postings from 2007 and 2010–2016 for office and administrative support (OAS) jobs, we show that when firms adopt new software at the job-title-level they increase the skills required of job applicants. Further, firms change the task content of such jobs, broadening them to include tasks associated with higherskill office functions. We aggregate these patterns to the local labor market level, instrumenting for local technology adoption with national measures. We find that a one standard deviation increase in OAS technology usage reduces employment in OAS occupations by about one percentage point and increases wages for college graduates in OAS jobs by over three percent. We find negative wage spillovers, with wages falling for both workers with no college experience and college graduates. These losses are in part driven by high-skill office occupations. These results are consistent with technological adoption inducing a realignment in task assignment across occupations, leading office support occupations to become higher-skill and hence less at risk from further automation. In addition, we find total employment increases with computerization, despite the direct job losses in OAS employment.

The labor force participation rate is a key measure of economic health. While the decline in prime-age workers’ labor force participation receives much attention from policymakers, it is far outpaced by the decline in participation among younger workers. In this analysis we show how changing employment and school enrollment patterns have contributed to declining labor force participation among youth, aged 16 to 24. Youth today are not disengaged; rather, declines in youth labor force participation primarily reflect a long-term but accelerating shift toward schooling and spending more time on education-related activities.

After decades of decline and political indifference, U.S. manufacturing is getting fresh attention, in national elections and in research about economic disparities between communities and America’s technological leadership. For the past two years, the authors of this report have worked on two-year project, sponsored by The Century Foundation (TCF) and its Bernard L. Schwartz Rediscovering Government Initiative (RGI), to elaborate on the contours of a policy that will not only revitalize the manufacturing industry, but lift the fortunes of struggling communities (urban, rural, and suburban) that have long looked to manufacturing as a source of good paying jobs and economic growth. The two-year project included three major research reports and interactions with nearly 500 stakeholders at community events throughout the industrial Midwest. The paper summarizes the research and (i) discusses why manufacturing remains important, (ii) presents a comprehensive framework for regional industrial policies best practices, and (iii) suggests the key state and federal policies and actions needed to revitalize manufacturing communities. The comprehensive framework identifies two major national policy drivers (trade and government purchasing) and four regional drivers (innovation, industrial retention, workforce and capital) that are all needed for U.S. manufacturing to recapture its economic promise.

With the rapid increase in educational attainment, technological change, and greater job specialization, decisions regarding human capital investment are no longer exclusively about the quantity of education, but rather the type of education to obtain. The skills and knowledge acquired in specific fields of study are more valuable for some jobs compared to others, which suggests the existence of differences in the quality of the education- occupation match in the labor market. With this premise in mind, this paper aims to estimate the effect of the quality of this education-occupation job match on workers’ wages and to explore the factors that contribute to the existence of such mismatch among workers with higher education (college or more). Using data from the American Community Survey 2010–16, we construct two indices that measure the quality of the education-occupation match: based on the predicted and observed distribution of workers using their fields of education and their jobs’ occupation classification. Results suggest there is a wage gap of around 3–4 percent when comparing workers that have good job matches to those who have bad matches. Given the importance of the penalty for mismatched jobs, we find that structural characteristics such as unemployment, and individual characteristics such as gender, race, immigration status, and even homeownership affect the quality of horizontal mismatch as well as.

This paper uses harmonized collections of national labor force datasets to compare the size and shape of the paid care sector around the globe. Paid care workers make up three of the four points of the “care diamond” organizing care provision in any national context: markets, the not-for-profit sector, and the state (the fourth point is families/households).* After explaining our definition of paid care – focused on health care, education, child care, and social services – we examine the size and characteristics of the paid care sector, finding enormous variation across countries. We then explore the relationship between the size of the care sector and various measures of need for care, finding very little evidence of relationship. Finally, we explore wages and working conditions for paid care workers in a subset of countries for which data is available.