I exploit variation in the job composition of US local labor markets to determine how automation affects familial outcomes from 1980 to 2019 and look at employment, marriage, divorce, and fertility rates as outcomes. Following previous work, I use historical prevalence of routine jobs to measure exposure to automation. I find that individuals susceptible to automation are more likely to become unemployed from 2000 to 2010; however, from 2010 to 2019 these individuals are more likely to become employed and work comparatively more hours. Fertility rates correlate with marriage rates; the results show higher fertility and marriage rates from 1990 to 2000 in local labor markets susceptible to automation, but this trend shifts from 2000 to 2019 as fertility and marriage rates become relatively lower. Moreover, I find that women in areas most susceptible to female-specific automation are more likely to experience lower marriage rates and are simultaneously are more likely to leave the labor force. This finding is correlated with higher fertility rates for women but is not correlated with the fertility rates of men, which may suggest that many women susceptible to automation are becoming single mothers and dropping out of the labor force.

This paper estimates the long-run effects of childhood Medicaid eligibility on adult health and economic outcomes using the program's original introduction (1966-1970) and its mandated coverage of welfare recipients. The design compares cohorts born in different years relative to Medicaid implementation, in states with different preexisting welfare-based eligibility. Early childhood Medicaid eligibility reduces mortality and disability, increases employment, and reduces receipt of disability transfer programs up to 50 years later. Medicaid has saved the government more than its original cost and saved more than 10 million quality adjusted life years.

Source Data Article Overview These secondary data originate from a study on the pre-pandemic association between high school dropout rates and internet access in the home, while controlling for several other demographic, economic, and social factors affecting the high school dropout rate. As the coronavirus (COVID-19) forced many students into remote learning, our work sought to identify counties across the United States where dropout rates were already high – and could be exacerbated as vulnerable students lack a critical tool to help them complete their diplomas in an online world: reliable internet access. In this source data article, we seek to foster a community of like-minded researchers interested in the links between high school dropout rates, local economic conditions, and socioeconomic factors. To help establish this community within the Data and Analytics for Good Journal, we provide data and source code, and share underlying methodologies in the hope that other researchers join our quest to better understand how the COVID-19 pandemic will impact vulnerable students across the United States. Internet access in the home will be just one of the factors affecting student performance, and we hope that others will provide data which can help us better understand our potential looming educational crisis. Data Value This project strives to start an empirical conversation about vulnerable populations and equal access to education with the Data and Analytics for Good Journal. These data support U.N. Sustainability (UNSDG) Goal #4 – Quality Education and UNSDG #10 Reduce Inequality. The goal of this secondary data compilation is to help academics, decision makers, and citizen data scientists to think more critically about where remote learning stemming from the COVID-19 pandemic could exacerbate achievement gaps in education. Moreover, these data can be used to identify geographic regions that may need additional resources to help remediate youth returning to school. Data Description Our data provide demographic, economic, and socioeconomic data for 3,133 counties all across the United States. This secondary data compilation primarily uses several public resources produced by the U.S. government, for all counties reporting data. Most of the variables in the data are derived from individual survey response data from the 2019 American Community Survey, which is collected by the U.S. Census Bureau. We also use economic data from the Local Area Unemployment Statistics (LAUS) from the U.S. Bureau of Labor Statistics, Small Area Income and Poverty Estimates (SAIPE) data from the U.S. Census Bureau, and the Social Vulnerability Index from the U.S. Center for Disease Control and Prevention. Data Application The final data set contains a host of county-level factors related to educational attainment, socioeconomic status, access to technology, and social vulnerability. Data can be used for simple descriptive analyses – including geospatial analysis – as well as more complex modeling such as decision trees and regressions. Possible research questions include, but are not limited, to: Indexing Table What is the relationship between high school dropout rates and internet access in the home – before COVID19? How do local employment opportunities – as proxied by Census occupation classifications1 – affect high school dropout rates? And do these opportunities differ by race/ethnicity and gender? How do dropout rates by race and ethnicity vary across counties in the United States? How do they differ by race/ethnicity and gender? How are socioeconomic variables, such as median household income and poverty rates, related to high school dropout rates?

The 2013 Home Care Rule narrowed the companionship exemption to cover home care workers employed by private agencies under the minimum wage and overtime payment rules of the Fair Labor Standards Act. Applying the Difference-in-Difference-in-Difference analyses to the Outgoing Rotation Group datafiles of the Current Population Survey, this study found that, contrary to the existing skepticism, the Home Care Rule was associated with higher hourly wage rates and weekly earnings among agency-employed home care workers.

BACKGROUND This study examines trends in affluence ‒ as indicated by high household income ‒ by household structure over the 1959 to 2017 period. I contrast the experiences of married couple households, whose share of all households declined substantially over time, with those of single-parent households, cohabiting couples, individuals living alone, and people living with non-relatives. METHODS I use data from multiple censuses and the American Community Survey and logistic regression. RESULTS Levels of absolute affluence rose substantially for all household types, reflecting rising living standards. Married-couple households were the most likely to be affluent and single-parent households were the least. Moreover, the affluence gap between married couple households and all others widened. Married couples fared better because they experienced larger increases in wages and other important sources of income, such as from investments and retirement. CONCLUSIONS The findings suggest that married-couple households benefit from a collective work strategy and economies of scale that increase their likelihood of affluence. Positive selectivity into marriage may also have increased over time. CONTRIBUTION This study provides timely new information on changing gaps in affluence by household structure during a period of substantial change in household living arrangements and economic well-being.

Homestead exemptions for senior and disabled homeowners disproportionally erode rural tax bases but may still stimulate local educational spending. This article examines one such exemption in Kentucky. Two-stage generalized method of moments is used to estimate the demand for local education spending, then spending in the absence of the exemption is simulated to estimate effects on school district expenditure and academic performance. We combine Census and National Center of Education Statistics data with detailed exemption and academic performance data from Kentucky’s Departments of Revenue and Education into a panel spanning 1999–2013. Results suggest the exemption provides relatively generous tax relief without increasing resource and academic achievement gaps between rural and nonrural districts. This is largely attributable to Kentucky’s strong school finance equalization effort. Our findings can help states with a similarly targeted exemption consider such impacts in relation to their own demography and funding systems.

A definition and equity-minded framework for understanding postsecondary value must consider students’ investment in college, in addition to their returns. Student investment includes costs beyond tuition and fees. In order to be successful in school, students must be able to cover the cost of books, supplies, and transportation to and from class. Additionally, having sufficient resources for housing and food are crucial for allowing students to focus on their coursework without needing to work long hours to cover those expenses. Furthermore, student investment should include costs incurred over the entire length of a student’s enrollment, rather than looking only at costs in one year. There are a number of ways that student investment can be measured, including full cost of attendance (COA, also known as sticker price), net price (COA minus grant aid), and opportunity costs in the form of forgone earnings. This paper explores those options and makes recommendations for how student investment should be measured with ideal data and with data that are currently available, including U.S. Department of Education (ED) data that are available for all colleges and nonpublic data that institutions may be able to access for their own students. The recommendations in this paper are based on an extensive review of research and analyses of publicly available data, as well as discussion with staff members at the Institute for Higher Education Policy (IHEP), the Bill & Melinda Gates Foundation, and members of the Postsecondary Value Commission Research Task Force. The paper also identifies issues that require more research and includes recommendations for improving publicly available data to allow colleges and policymakers to better measure student investment.

The influx of immigrants from Asia to the United States (U.S.) has expanded the pool of co-ethnic marriageable partners, strengthened racial identity, and contributed to the decline in interracial marriage with whites among Asian Americans. Yet, retreat from interracial marriage with whites may well vary by immigrant generation, an important factor in marital assimilation. Using data from the March Current Population Survey (1994–2015), we examine generational differences in intergenerational marriage and interracial marriage with whites among Asian Americans. The results reveal that over time third-plus-generation Asians show no significant change in interracial marriage with whites but declines in intergenerational marriage with first- or second-generation Asians. Second-generation Asians, on the other hand, have become more likely to marry first-generation Asians and less likely to marry whites. In addition, education provides different opportunities for intermarriage, with highly-educated Asian Americans more likely than their less-educated counterparts to marry whites and less likely to marry other Asians. Notably, highly-educated second-generation Asians tend to marry third-plus-generation Asians and whites while their less-educated counterparts marry first-generation Asians. These findings highlight the importance of generation and education in integration of Asian Americans.

The 20th century beheld a dramatic transformation of the family. Some Kuznets style facts regarding structural change in the family are presented. Over the course of the 20th century in the United States fertility declined, educational attainment waxed, housework fell, leisure increased, jobs shifted from blue to white collar, and marriage waned. These trends are also observed in the cross-country data. A model is developed, and then calibrated, to address the trends in the US data. The calibration procedure is closely connected to the underlying economic logic. Three drivers of the great transition are considered: neutral technological progress, skilled-biased technological change, and drops in the price of labor-saving household durables.

This paper documents that mortgage market deregulation helps mitigate the risk of population aging by affecting a foundational family-level decision: the choice to have children. Using a U.S. federal regulator ruling, I show that young households fully exposed to mortgage market deregulation increase their probability of purchasing a home and having a child by 6 percentage points. Supplemental tests reject alternative hypotheses based on income or housing wealth growth and, instead, suggest that access to space is the relevant economic mechanism. Collectively, the evidence indicates that increased access to mortgage credit affects the total number of children in the economy.

This paper applies quantitative spatial analysis to the long-term impact of Western gold rushes, studying the effect of 19th century US mineral districts on modern (2010) population density, as a proxy for long-term economic growth. OLS regression estimates show positive effects for areas adjacent to historic mining districts. Census tracts within 15 miles of a mineral district but not containing one are 29.8% more dense than other tracts. Additionally, capital-intensive/large-scale mining was more persistent than labor-intensive/small-scale methods, and path dependence is achieved mainly through agglomeration. This research corroborates historical arguments focusing on the development of Western infrastructure for long term growth. It also contributes to the growing economic literature on the persistence of place.

Kees Mandemakers has been a leader in the study of linked population data, but not every society has the sources or resources to create linked data. This essay is about one approach that derives from a source that does not offer all that is possible with linked longitudinal data, but that nonetheless has significant value. Migration to California is one of the persistent refrains encountered in both popular and academic works about the history of the 1930s. The reason for this is simple. In literature and the arts, images of that migration are well known, but while those themes are accurate, they have not been sufficiently studied. My approach is to study migration using census data that ask a retrospective question about where each respondent lived five years earlier, in this case tracking migration from 1935 to 1940. Focusing on migrants to California and the paths that they took, I show that there was migration from much of the U.S. especially metropolitan areas across the country, from states near to California, and from places subject to the severe environmental shocks of the 1930s. I also show that while much of the general view of migration to California focuses on agricultural workers who left their homes in search of farm work further west, the large majority of migrants to California went to metropolitan destinations and worked as much in industry and commerce as in agriculture.

Objectives: This study explores the heterogeneity in effects of the 2014 Affordable Care Act (ACA) Medicaid expansions on insurance coverage, health care access, and health status of low-income women with dependent children by pre-expansion state-level income eligibility. Materials and Methods: We employ a quasiexperimental difference-in-differences design comparing outcome changes in Medicaid expansion states to nonexpansion states. We estimate effects separately for three groups of expansion states based on pre-expansion (2013) parent income eligibility: low pre-expansion eligibility (<90% of federal poverty level [FPL]), high eligibility (90% to <138% FPL), and full eligibility (≥138% FPL). Study samples include women with dependent children below 138% FPL from the 2011 to 2018 American Community Survey for the insurance outcomes, and from the 2011 to 2018 Behavioral Risk Surveillance System for the access and health outcomes. Results: There is stark heterogeneity in changes of health insurance and health care access by pre-expansion income eligibility levels. In comparison to Medicaid non-expansion states, there are large increases in insured rate (9 percentage-points) and Medicaid coverage (16 percentage-points) in expansion states with low pre-expansion eligibility. Insurance changes are much smaller in states with high or full pre-expansion eligibility. Changes in access largely mirror those in coverage. There are no significant changes in health status regardless of pre-expansion eligibility. Conclusions: The ACA Medicaid expansions increased coverage and access for low-income women with dependent children primarily in states with low pre-expansion parent eligibility, and therefore, reduced differences in these outcomes between expansion states.

This study evaluates the impact of transit-oriented development (TOD) on household transportation expenditures in California by comparing TOD households with two groups of control households that are identified by propensity score matching. When controlling for household demographics, TOD households own fewer and more fuel-efficient cars, drive fewer miles, and use transit more. On average, they save $1232 per year on transportation expenditures than non-TOD households with similar demographics, accounting for 18% of their total annual transportation expenditures. When controlling for both demographics and neighborhood environment, TOD households still own slightly fewer and more fuel-efficient cars and use transit more. But they drive similar amount of miles as non-TOD households do. TOD households save $429 per year on transportation expenditures than non-TOD households with similar demographics and neighborhood environment, accounting for about 6% of their total annual transportation expenditures. TOD households save money on transportation costs mainly because they own fewer cars than non-TOD households. About two thirds of the savings can be attributed to transit-friendly neighborhood environment and one third to their access to rail transit, suggesting the importance of integrating a rail transit system with supportive land use planning and neighborhood design.

Though referrals are ubiquitous in the hiring process, it remains unclear exactly what they do. We exploit a novel data set to shed light on this question. Importantly, the data enables us to distinguish between different types of referrals-namely, those from family and friends and those from business contacts-and different types of jobs, as measured by the skill requirements of the occupation. Using these distinctions, we document clear patterns with respect to the frequency with which different types of referrals are used by workers in different occupations and subsequent labor market outcomes. Then we develop a structural framework to interpret our empirical findings and quantify the effects of social and business networks on employment rates, earnings, and job turnover across workers with different skills. For example, we find that referrals from family and friends contribute up to 20% of earnings for a subset of workers who struggle to generate offers through more traditional channels, and hence this type of referral is an important force for reducing earnings inequality. Referrals from business contacts, in contrast, have a more muted impact on earnings, as such referrals are most commonly used by workers who generate offers from other sources more readily.

While obesity across rural India has doubled in the last decade, research explaining such an unprecedented change is sparse. This paper shows that the rise in the incidence of rural obesity is associated with the process of structural transformation, especially within rural spaces. As the distance to nearby towns from the villages has reduced, urban proximity not only leads to improved livelihoods but also a change in dietary practices and access to processed food. Combining the rural sample of India's latest National Family Health Survey (2015–16) with the estimates for town distance from the village clusters, we show that an additional kilometer of reduction in rural–urban distance increases the risk of obesity among women by 0.06 percent. Our estimates imply that for every kilometer of reduction in rural–urban proximity 3000 rural women become at-risk for obesity. Heterogeneity analysis shows that this burden is higher in towns with a population of over 50,000. We also find that the risk has increased disproportionately among the lower socio-economic classes. Similarly, states at a more mature stage of structural transformation face higher risk of obesity. Finally, we find that higher dietary diversity reduces the influence of urban growth on rural obesity. Our findings underscore the looming dual burden of malnutrition among developing countries and suggest that nutrition policies that promote diet diversity could be a panacea.

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) nutritional program in the United States provides food-benefits to low income women and children. Children disqualify for WIC benefits when they turn 5. To study the effect of WIC on the maternal labour market and household food insecurity, we use age of the youngest child as a proxy for WIC participation to employ a fuzzy regression discontinuity design. Using data from the Current Population Survey (CPS), we study maternal employment and hourly wage as well whether a household is very food insecure. We find evidence that participation in WIC does not appear to have an effect on maternal employment, hourly wage, and whether a household is very food insecure and propose potential explanations.

In recent years, the goal of 60 percent of adults holding a postsecondary degree has been set as a key benchmark for the United States to build a skilled workforce and remain economically competitive. Engaging adults with some college credit but no degree is critical to reaching this goal. Efforts to increase adult degree attainment, however, have largely ignored the role of parenthood in adults’ ability to reengage with and complete college. This report builds on past IWPR research exploring the experiences and support needs of student parents, including those who have taken prolonged enrollment breaks, and the policy and practice reforms needed to improve their ability to thrive in and graduate from college. Using data from the American Community Survey, the report sheds light on gaps in educational attainment rates among parents by gender, marital status, and race and ethnicity. It then projects future attainment rates to highlight the integral role parents play in reaching a 60-percent attainment target nationally. The report also demonstrates how gaps in degree attainment by race and ethnicity may persist in the absence of more targeted support for adult learners who are parents of children under 18. This research was generously supported by Imaginable Futures.

Using a database on U.S. individuals and households, we examine whether rise in globalization and trade integration of product markets have contributed to the observed decline in US entrepreneurship in trade-exposed sectors. US trade policy that lowered tariffs on China dampens entrepreneurial dynamism through lower entry (especially by incorporated entrepreneurs) and higher exit in exposed sectors but increases entry by highly educated individuals in skill-intensive nontradable industries. The results are robust to secular trends, labor market specialization, local collateral and credit shocks, and long-run bank distress. They are also robust to aggregation at local, state, and national industry levels.

We evaluate how extractive capacity and migration respond to the introduction of the income tax, drawing on novel panel data on U.S. states from 1900 to 2010. States which introduced the income tax experienced a 15 percent increase in revenue per capita over the long run. However, there was no long-term increase in the absolute level of revenue. To explain this divergence, we document how the introduction of the income tax induced significant outmigration to non-income tax states. Our analysis suggests that migration responds more to tax introductions than to equivalent increases in existing taxes.