Since 2014, overall life expectancy in the US has fallen for three years in a row, reversing a century-long trend of steadily declining mortality rates. This decrease in life expectancy reflects a dramatic increase in deaths from so-called “deaths of despair” – alcohol, drugs and suicide – among Americans without a college degree . Case and Deaton suggest that the increase in deaths from alcohol, drugs and suicide is largely attributable to stagnant living standards and long-term declines in economic opportunity among working class non-Hispanic whites. Other scholars have questioned the explanatory focus on distress and despair , especially for drug-related deaths. These researchers point instead to the role of new highly addictive and risky drugs. Case agrees with this revision. We contribute to this discussion by examining how two economic policies that increase after tax incomes of low-income Americans – the minimum wage and the earned income tax credit – causally affect deaths of despair. To do so, we use the CDC’s geocoded causes of death mortality data and leverage plausibly exogenous variation across states and time in these two policies. We employ the standard approach in the minimum wage – employment and EITC literatures to estimate panel models of cause-specific mortality over time, controlling for state and year fixed effects, testing the crucial parallel trends assumption and implementing a series of falsification and robustness tests. First, we estimate a set of placebo regressions, testing for effects in a sample of adults with a bachelor’s degree or higher. As this group is unlikely to work minimum wage jobs or to be eligible for the EITC, any effects on this group then are likely spurious, indicating a problem with the research design. Moreover, we implement event study models estimating changes in mortality around the time that states increase the minimum wage or implement state EITCs. Our models do not find a significant effect of either policy on drug mortality. However,vertical rack both higher minimum wages and EITCs significantly reduce non-drug suicides among lesseducated adults.
We find no significant effects in the more educated placebo sample, which is reassuring for our study design. We also find heterogeneous effects by gender: effects are larger and more statistically significant for women; for men, effects of the minimum wage are only marginally significant. Our estimated event study models establish parallel pre-trends — states that increase their minimum wages do not experience differential mortality trends in the years leading up to the implementation of the new higher wage. Moreover, the event study models show a discontinuous drop in suicide mortality at the time of minimum wage increases and implementation of state EITCs. Using auxiliary data from the Current Population Survey, we show that estimated effects significantly correlate with exposure to policies: sub-samples with larger exposure to minimum wages tend to have larger associated effects of minimum wages on suicides, while estimated effects of the EITC on average are larger for groups that have high rates of estimated EITC receipt. The findings of this paper contribute to the debate on the causes of deaths of despair. This discussion has taken place against a backdrop of a large body of literature that identifies socioeconomic status as a primary social determinant of health . However, the identification of causality remains a key issue within this literature: lower income may prevent individuals from engaging in health-enhancing behaviors or to access medical care, leading to poorer health outcomes. At the same time, sicker individuals may have more difficulty maintaining employment, leading to a negative association between health and income. To address this issue of causality, a number of recent papers have used quasi-experimental methods to isolate the effects of labor market shocks on mental health, all-cause mortality and deaths of despair . Carpenter, McLellan and Rees find that economic downturns lead to increased intensity of prescription pain reliever use and to increases in substance use disorders involving opioids. Moreover, they find that such effects are concentrated among working-age white males with low educational attainment. Autor, Dorn and Hanson find that labor demand shocks lead to premature mortality among young males.
These studies indicate that negative income shocks worsen health. More generally, a growing literature finds effects of economic policies on related health behaviors and outcomes. For example, using data from the Behavioral Risk Factor Surveillance System, Horn, MacLean and Strain find that minimum wage increases lead to reduced self-reported depression among women, but not among men. Sabia, Pitts and Argys find that minimum wages do not have harmful effects on teen alcoholism or drunk driving fatalities.While their findings are suggestive, the analysis stops short of credibly establishing a causal link . This partly results from limitations inherent to publicly available data: the authors are not able to explore heterogeneous effects by education and therefore cannot conduct placebo tests. Moreover, suppression of cells with few underlying observations complicate their analysis of effects by race and gender. Finally, their models make no attempt to analyze the credibility of the parallel trends assumption by examining time paths of effects around minimum wage increases. More generally, our methods improve in important respects upon the existing literature on minimum wages and health. Previous work on the employment effects of minimum wages highlighted some weak methods that characterize many of the studies that find negative employment effects . In our view, many of Leigh, Leigh and Du’s 15 “high quality” papers also use questionable methods that cast doubt on their validity as credible causal analyses of minimum wage effects on health outcomes. 2 The rest of the paper is organized as follows: Section 2 presents the data, while section 3 presents our empirical models in some detail. Results are presented in section 4, and section 5 concludes.In this paper, we study effects of two policies intended to raise incomes for low wage workers: the minimum wage and the EITC. During the sample period, many states implemented minimum wage policies exceeding the federal. Moreover, the sample period covers a significant federal minimum wage increase in 2007-2009; this increase was nonbinding for several high minimum wage states.
As a result, there is substantial variation in minimum wages within and between states in our sample. Eligibility for the EITC varies with household income and family characteristics: To qualify, households must have earned income; the credit phases in gradually up to a plateau, before phasing out at higher incomes. The phase-in and phase-out rates and maximum credit vary with family characteristics. The bulk of EITC credits go to low income families with children: Adults with no qualifying children are only eligible for relatively small benefits – in 2015, the maximum credit for people with no dependents was $503, compared to $5548 for a family with 2 dependents. This variation in eligibility and credit size has allowed researchers to study effects of the policy by comparing changes in outcomes for different family types around the time of federal EITC expansions. However, the mortality data do not include detailed family information to implement this kind of analysis. Instead, our empirical approach will exploit variation in state EITCs. These policies typically take the form of a proportional increase to the federal credit. 25 states plus DC had state EITCs at some time during the sample period. The policies vary significantly in magnitude,microgreen flood table with top-up rates ranging from 3.5% to 40%. We hypothesize that these two policies may affect deaths of despair by raising earnings at the low end of the income distribution. However, the model does not allow us to test this hypothesis directly. Rather, our estimates may reflect a combination of income and employment effects. Traditional economic theory predicts that higher minimum wages may induce job loss, as employers respond to higher labor costs by cutting back on employment. If this were the case, we might expect higher minimum wages to have negative effects on health in general, and on deaths of despair in particular. However, the large literature examining the effects of minimum wages on employment suggests that the disemployment effects have been small at most . Moreover, recent studies find that higher minimum wages raises earnings at the low end of the household earnings distribution, leading to significant reductions in poverty . Several studies have found that EITC expansions have positive employment effects for single mothers . To assess whether employment effects are quantitatively important in our sample, we have estimated simple panel models using the Current Population Survey. Results, shown in Appendix table 1, indicate that neither policy has any statistically significant effects on employment in either a pooled sample of workers with high school or less, or when separating samples by gender.3 However, these estimates could mask heterogeneous employment impacts across individuals. To the extent that employment in itself affects health, our estimates will then in part reflect these effects, together with any impacts of higher income. Note that we do not consider the impact of the Supplemental Nutrition Assistance Program . While this program is arguably a key safety net and antipoverty program, the lack of state level variation makes it difficult to estimate meaningful effects of this program on short term mortality.Sample Our primary data source consists of the restricted access geocoded CDC Multiple Causes of Death data for the years 1999 to 2015. The data is collapsed by state of residence, year and demographic cells, defined by age , education and gender. The analysis focuses on non-elderly adult mortality, excluding deaths at ages younger than 18 or older than 64. Observations with missing data are excluded from the sample.
We exclude four states – Georgia, Nevada, Rhode Island and South Dakota –from the sample because of missing and incomplete education data. In theremaining 46 states plus Washington, DC, 2.48 percent of the death records for the causes we study have missing data during the sample period. The term “deaths of despair” typically includes deaths from drug overdoses, suicides, and deaths from alcohol abuse . Some of these causes, such as deaths from alcoholic liver disease, reflect medical conditions that develop over time. As a consequence, alcohol-related mortality may be less responsive to minimum wage in the short run. We focus therefore on drug overdoses and suicides, which are more likely to be responsive to recent policy changes. For each cell, we calculate the number of deaths that are due to intentional and unintentional drug overdoses as well as the number of non-drug suicides.To take zeroes into account, we use the inverse hyperbolic sine transformation of the death count as our primary measure of mortality We obtained cell-level demographic characteristics and population counts using data from the Current Population Survey’s Annual Social and Economic Supplement . For each cell, we use the CPS survey responses to estimate the distribution of race and ethnicity , the share rural, the share uninsured, and the average age.5 We obtained the following state-level economic covariates from the University of Kentucky Center on Poverty Research : state GDP, population share receiving SSI, state population, the state unemployment rate and the state Earned Income Tax Credit. We obtained data on minimum wages from Vaghul and Zipperer . Since a number of studies have linked marijuana legalization to reductions in prescription opioid use , and the role of cannabis in helping treat opioid use disorder , we also include indicators for whether a state has legalized marijuana for medical or recreational use. Finally, we also include indicators for whether a state has implemented a Prescription Drug Monitoring Program ; based on evidence that such programs may reduce opioid misuse . We obtained state-level marijuana legalization and PDMP variables from the Prescription Drug Abuse Policy System.6 Table 1 shows summary statistics of the sample. The first three rows, which display average mortality rates, confirm a well-known socioeconomic gradient. All cause-specific mortality rates are noticeably higher among the lower-educated group than among the higher-educated group . The most striking differences are for drug non-suicide and non-drug suicide mortality rates. Within each education stratum, rates due to drug non-suicide and non-drug suicide are substantially higher among men than women, particularly among those with a high school diploma or less.