The economic crisis caused by the COVID-19 pandemic has sharply reduced mobility and economic activity, disrupting the lives of people around the globe. This paper presents estimates on the early impact of the crisis on labor markets in 39 countries based on high-frequency phone survey data collected between April and July 2020. Workers in these countries experienced severe labor market disruptions following the COVID-19 outbreak. Based on simple averages across countries, 34 percent of the respondents reported stopping work, 20 percent of wage workers reported lack of payment for work performed, 9 percent reported job changes due to the pandemic, and 62 percent reported income loss in their household. Stopping work was more prevalent in the industrial and service sectors than in agriculture. Measures of work stoppage and income loss in the high-frequency phone survey are generally consistent with gross domestic product growth projections in Latin America and the Caribbean but not in Sub-Saharan Africa. This suggests that the survey data contribute new and important information on economic impacts in low-income countries.
We develop a framework to study optimal disability insurance when employers exhibit moral hazard and show that the optimal system takes into account employer-side moral hazard and selective hiring. We illustrate these insights using a reform in the Netherlands that extended experience rating to temporary workers. Using this reform, we document a 24% decrease in disability inflow. We also find an increase in worker selection, accounting for 14% of the overall decrease. Using our model, we evaluate the normative implications of the experience rating policy. We conclude that, given reasonable assumptions, the policy improved welfare and additional employer responsibility would further add to social welfare.
We merge the universe of 2000-2018 W-2 earnings records to the universe of 2000-2018 SSA-1099 forms to estimate the Social Security Disability Insurance (SSDI) claiming rate of each employer's employees. We document large variation across industries in claiming rates. We also show that SSDI claiming rates correlate with characteristics of firms that signal firm quality. There is a positive association between firm size and employee SSDI claiming, except for the largest firms, which have lower employee claiming rates. In addition, we document a negative association between employee wages and SSDI claiming. In future work, we will estimate the relationship between employer and employee wage premiums and SSDI claiming.
Can tax evasion justify high but taxed minimum wages? Exploiting a change in reporting defaults and the implied audit threat in Hungary, we demonstrate that a substantial portion of those who declare the minimum wage have much higher earnings in reality. This can be seen from their sharp but temporary jump to the new reporting default, a twofold increase in reported earnings. Consistent with misreporting, the response is concentrated both spatially and by employer, and the distribution of covariates around the threshold exhibits anomalies. Requiring minimum wage earners to pay higher taxes or ask for explicit exceptions increases reported earnings for some and decreases formal employment for others, suggesting a trade-off for taxation. In a model of labor demand and evasion with a linear tax and differential enforcement, raising the minimum wage generates a fiscal externality and can substitute for stricter enforcement by requiring tax evaders to report higher earnings. This goes towards rationalizing a prevalent international practice.
In this paper, we seek to unpack the variation in Medicaid spending across states using a novel empirical strategy. We leverage data describing demographics, fiscal spending, and mortality for the universe of Medicaid enrollees linked to similar data for the universe of Medicare enrollees. We use this data to allow us to compare fiscal spending and health effects of each state’s Medicaid program relative to a single, homogeneous alternative program: Medicare. By comparing each state’s Medicaid program to Medicare, we can effectively compare each state’s Medicaid program to each other state’s Medicaid program, allowing us to assess the extent to which program factors influence the variation in observed Medicaid spending across states.
Some consumers lack the cash needed to pay for medical care. As a result, they either delay care until they can pay for it or they forgo the care altogether. To test for such a possibility, we study the distribution of monthly Social Security checks among Medicare Part D enrollees. When Social Security checks are distributed, prescription fills increase by 6-12 percent. In that sense, drug consumption of low-income Medicare recipients is "liquidity sensitive." We then study recipients who transition onto a program that eliminates copayments. When those recipients do not face copayments, their drug consumption becomes less liquidity sensitive. That finding implies that, beyond risk protection, generous insurance also provides recipients with the ability to consume healthcare when they need it rather than when they have cash. Further, we find that recipients whose drug consumption is most liquidity sensitive exhibit price elasticities of demand that are twice the size of the average elasticity, suggesting that more-generous insurance causes recipients both to re-time prescription filling and also to start filling prescriptions that they otherwise would not fill. We present a stylized model that uses this finding to call into question the conventional interpretation of demand-response to price as solely inefficient moral hazard.
We study two mechanisms used by public health insurance programs for rationing healthcare: outsourcing to private managed care plans and quantity limits for prescription drugs. Leveraging a natural experiment in Texas's Medicaid program, we find that the shift to managed care and the relaxation of a strict drug cap increased access to high-value drugs and outpatient services and reduced avoidable hospitalizations. Program costs increased significantly, indicating a trade-off between cost and quality. We provide suggestive evidence attributing the reduction in hospitalizations to the relaxation of the drug cap and much of the spending increase to the shift to managed care.
Using mortality registers and administrative data on income and population, we develop new evidence on the magnitude of life expectancy inequality in Hungary and the scope for health policy in mitigating this. We document considerable inequalities in life expectancy at age 45 across settlement-level income groups, and show that these inequalities have increased between 1991–96 and 2011–16 for both men and women. We show that avoidable deaths play a large role in life expectancy inequality. Income-related inequalities in health behaviours, access to care, and healthcare use are all closely linked to the inequality in life expectancy.
We use high-frequency Google search data, combined with data on the announcement dates of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic in U.S. states, to disentangle the short-run direct impacts of multiple different state-level NPIs in an event study framework. Exploiting differential timing in the announcements of restaurant and bar limitations, non-essential business closures, stay-at-home orders, large-gatherings bans, school closures, and emergency declarations, we leverage the high-frequency search data to separately identify the effects of multiple NPIs that were introduced around the same time. We then describe a set of assumptions under which proxy outcomes can be used to estimate a causal parameter of interest when data on the outcome of interest are limited. Using this method, we quantify the share of overall growth in unemployment during the COVID-19 pandemic that was directly due to each of these state-level NPIs. We find that between March 14 and 28, restaurant and bar limitations and non-essential business closures can explain 6.0% and 6.4% of UI claims respectively, while the other NPIs did not directly increase own-state UI claims. This suggests that most of the short-run increase in UI claims during the pandemic was likely due to other factors, including declines in consumer demand, local policies, and policies implemented by private firms and institutions.
Using administrative data on a random 50% of the Hungarian population, including individual-level information on incomes, healthcare spending, and mortality for the 2003-2011 period, we develop new evidence on the distribution of healthcare spending and mortality in Hungary by income and geography. By linking detailed administrative data on employment, income, and geographic location with measures of healthcare spending and mortality we are able to provide a more complete picture than the existing literature which has relied on survey data. We compute mean spending and 5-year and 8-year mortality measures by geography and income quantiles, and also present gender and age adjusted results.
We document four patterns: (i) substantial geographic heterogeneity in healthcare spending; (ii) positive association between labor income and public healthcare spending; (iii) geographic variation in the strength of the association between labor income and healthcare spending; and (iv) negative association between labor income and mortality. In further exploratory analysis, we find no statistically significant correlation between simple county-level supply measures and healthcare spending. We argue that taken together, these patterns suggest that individuals with higher labor income are in better health but consume more healthcare because they have better access to services.
Our work suggests new directions for research on the relationship between health inequalities and healthcare spending inequalities and the role of subtler barriers to healthcare access.
We use data on enrollment in the Supplemental Security Income (SSI) and Social Security Disability Insurance (SSDI) program and data on health care spending by Medicaid beneficiaries to analyze the extent to which Medicaid spending is predictive of future disability insurance receipt among non-disabled teenagers and future disability insurance disenrollment among disabled teenagers. In our first set of analyses, we find that we currently do not have enough data to predict future SSI and SSDI enrollment among non-disabled teenagers. In our second set of analyses, we find that observed Medicaid spending among disabled teenagers can be used to predict SSI disenrollment. Our results indicate that machine learning models using information on healthcare spending may be useful for identifying current teenage SSI recipients who are more or less likely to be removed from SSI.
We study insurers’ use of prescription drug formularies to screen consumers in the ACA Health Insurance Exchanges. We begin by showing that Exchange risk adjustment and reinsurance succeed in neutralizing selection incentives for most, but not all, consumer types. A minority of consumers, identifiable by demand for particular classes of prescription drugs, are predictably unprofitable. We then show that contract features relating to these drugs are distorted in a manner consistent with multi-dimensional screening. The empirical findings support a long theoretical literature examining how insurance contracts offered in equilibrium can fail to optimally trade-off risk protection and moral hazard.
We systematically review the literature linking health to economic activity, particularly education and labor market outcomes, over the lifecycle. In the first part, we review studies that link childhood health to later-life outcomes. The main themes we focus on are in-utero exposures, birthweight, physical health and nutrition, mental health, and the environment. In the second part, we review studies of the impact of health on labor market success for adults. The main themes we focus on are the environment, disability, physical health shocks, within-household spillovers, cancer, and mental health.