In Sickness and in Health: The Influence of State and Federal Health Insurance Coverage Mandates on Marriage of Young Adults in the USA

We study the effects of state and federal dependent health insurance mandates on marriage rates of young adults, ages 19 to 25. Motivated by low rates of coverage among this age group, state governments began mandating health insurers in the 1970s to allow adult children to stay on their parents’ insurance plans. These state level efforts successfully increased insurance coverage rates, but also came with unintended implications for the marriage decisions of young adults. Almost all state mandates explicitly prohibited marriage as a condition of eligibility, thereby directly discouraging marriage. Additionally, by making access to health insurance through parents easier, the mandates made access through spouses’ employers relatively less attractive. To the extent that young adults were altering their marriage plans to gain access through potential spouses, they no longer needed to do so under the mandates, thereby implicitly discouraging marriage. When the dependent coverage mandate of the Affordable Care Act (ACA) was enacted, it effectively ended the state-based marriage restrictions, thereby encouraging marriage among young adults previously eligible for state mandates. On the other hand, for those who were not eligible for state mandates, the ACA represented an attractive new path to obtain coverage, thereby discouraging marriage for these young adults, just as the state mandates had implicitly done previously for others. Thus, the separate efforts at the state and federal level to address low coverage rates for young adults ended up interacting and influencing incentives for marriage in opposite directions. We study these interaction effects on marriage empirically using a new dataset we compiled on state-level dependent coverage mandates. Consistent with theoretical arguments, we find that, before the implementation of the ACA, state mandates lowered marriage rates by about 2 percentage points, but this pattern reversed upon the passage of the ACA. We also find that state mandates increased the probability of out-of-wedlock births among state-mandate-eligible women as compared to ineligible ones, but the ACA reversed this trend as well. Our study provides an important example where fundamental understanding of the effects of the ACA dependent coverage mandate can only be had with full consideration of the pre-existing state laws

In Sickness and in Health: The Influence of State and Federal Health Insurance Coverage Mandates on Marriage of Young Adults in the USA

We study the effects of state and federal dependent health insurance mandates on marriage rates of young adults, ages 19 to 25. Motivated by low rates of coverage among this age group, state governments began mandating health insurers in the 1970s to allow adult children to stay on their parents’ insurance plans. These state level efforts successfully increased insurance coverage rates, but also came with unintended implications for the marriage decisions of young adults. Almost all state mandates explicitly prohibited marriage as a condition of eligibility, thereby directly discouraging marriage. Additionally, by making access to health insurance through parents easier, the mandates made access through spouses’ employers relatively less attractive. To the extent that young adults were altering their marriage plans to gain access through potential spouses, they no longer needed to do so under the mandates, thereby implicitly discouraging marriage. When the dependent coverage mandate of the Affordable Care Act (ACA) was enacted, it effectively ended the state-based marriage restrictions, thereby encouraging marriage among young adults previously eligible for state mandates. On the other hand, for those who were not eligible for state mandates, the ACA represented an attractive new path to obtain coverage, thereby discouraging marriage for these young adults, just as the state mandates had implicitly done previously for others. Thus, the separate efforts at the state and federal level to address low coverage rates for young adults ended up interacting and influencing incentives for marriage in opposite directions. We study these interaction effects on marriage empirically using a new dataset we compiled on state-level dependent coverage mandates. Consistent with theoretical arguments, we find that, before the implementation of the ACA, state mandates lowered marriage rates by about 2 percentage points, but this pattern reversed upon the passage of the ACA. We also find that state mandates increased the probability of out-of-wedlock births among state-mandate-eligible women as compared to ineligible ones, but the ACA reversed this trend as well. Our study provides an important example where fundamental understanding of the effects of the ACA dependent coverage mandate can only be had with full consideration of the pre-existing state laws

A Reevaluation of the Effects of State and Federal Dependent Coverage Mandates on Health Insurance Coverage

State governments have been passing laws mandating insurers to allow young adults to stay on their parents' health insurance plans past the age of 19 since the 1970s. These laws were intended to increase coverage, but research has been inconclusive on whether they were successful. We reconsider the issue with an improved approach featuring three key elements: a new, accurate dataset on state mandates; recognition that effects could differ greatly by age due to take up rate differences; and avoidance of endogenous characteristics when identifying mandate eligible young adults. We find the impact of the state mandates was concentrated among the 19 to 22 age group, for which dependent coverage increased sharply by about 6 percentage points. Overall coverage increased by almost 3 percentage points, with the difference explained by crowd out of public insurance. Crowd out of coverage through young adults own jobs was negligible. For those above age 22, we find little evidence of changes in coverage. We incorporate these insights into analysis of the Affordable Care Act (ACA) dependent coverage mandate, showing its effects were focused among those whom were previously ineligible for state mandates, or were eligible but older than 22. We argue the ACA's impact was broader because it had fewer eligibility conditions that implied parental dependence; young adults could be on their parents' insurance but still be relatively independent

Young Children and Parents' Labor Supply during COVID-19

We study the COVID-19 pandemic’s effects on the labor supply of parents with young children. Using the monthly Current Population Survey, and following a pre-analysis plan, we use three variations of difference-in-differences to compare workers with childcare needs to those without. The first compares parents with young children and those without young children, while the second and third rely on the presence of someone who could provide childcare in the household: a teenager in one and a grandparent in the other. We analyze three outcomes: whether parents were “at work” (not sick, on vacation, or otherwise away from his or her job); whether they were employed; and hours worked. Contrary to expectation, we find the labor supply of parents with young children was not negatively affected by the COVID-19 pandemic. Instead, some evidence suggests they were more likely to be working after the pandemic unfolded. For the outcomes of being at work and employed, our results are not systematically different for men and women, but some findings suggest women with young children worked almost an hour longer per week than those without. These results suggest that factors like employers allowing employees to work at home and informal sources of childcare aided parents in avoiding negative shocks to their labor supply during the pandemic

A Reevaluation of the Effects of State and Federal Dependent Coverage Mandates on Health Insurance Coverage

State governments have been passing laws mandating insurers to allow young adults to stay on their parents' health insurance plans past the age of 19 since the 1970s. These laws were intended to increase coverage, but research has been inconclusive on whether they were successful. We reconsider the issue with an improved approach featuring three key elements: a new, accurate dataset on state mandates; recognition that effects could differ greatly by age due to take up rate differences; and avoidance of endogenous characteristics when identifying mandate eligible young adults. We find the impact of the state mandates was concentrated among the 19 to 22 age group, for which dependent coverage increased sharply by about 6 percentage points. Overall coverage increased by almost 3 percentage points, with the difference explained by crowd out of public insurance. Crowd out of coverage through young adults own jobs was negligible. For those above age 22, we find little evidence of changes in coverage. We incorporate these insights into analysis of the Affordable Care Act (ACA) dependent coverage mandate, showing its effects were focused among those whom were previously ineligible for state mandates, or were eligible but older than 22. We argue the ACA's impact was broader because it had fewer eligibility conditions that implied parental dependence; young adults could be on their parents' insurance but still be relatively independent

Economics conference bingo

We describe a bingo-style game intended to be played at economics conferences. Early results from implementation of the game by economists at conferences suggest that fun increases more than a full standard deviation. Further study of the effects of the game are ongoing

Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Funder: Funding details are provided in the Supplementary MaterialAbstractPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.</jats:p

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Replication Materials for Barkowski/McLaughlin JHR 2020

Replication data, programs, and other materials for In Sickness and in Health: Interaction Effects of State and Federal Health Insurance Coverage Mandates on Marriage of Young Adults, by Scott Barkowski and Joanne Song McLaughlin, Journal of Human Resources, 2020

Replication Materials for Barkowski/McLaughlin JHR 2020

Replication data, programs, and other materials for In Sickness and in Health: Interaction Effects of State and Federal Health Insurance Coverage Mandates on Marriage of Young Adults, by Scott Barkowski and Joanne Song McLaughlin, Journal of Human Resources, 2020