Research Project
10234143
Project Summary Opioid abuse is one of the most pressing public health challenges facing the United States today. It touches the lives of millions of people nationwide either directly or indirectly. In 2017, more than 11 million people misused some type of opioid, accounting for nearly 5% of the total population aged 12 or older. But the opioid epidemic also affects millions of other individuals indirectly by altering the lives of those living in the same households and communities. Despite a growing body of research examining the health and economic consequences of opioid misuse, we still know little about its effects on childbearing, family formation, and family reconfiguration patterns in the United States. Our study will be the first to examine the effect of the opioid epidemic on these important demographic outcomes using a nationally-representative dataset. Assessing the impact of the opioid epidemic on family formation and reconfiguration patterns is important because it can help inform policies to mitigate the detrimental consequences of the epidemic, and to reduce its negative repercussions for the health and wellbeing of women and children. To measure the intensity of the opioid epidemic at the local level each year we will use the opioid-overdose death rate computed from restricted vital statistics records, and prescribed grams of opioids per capita estimated from a database of all opioid medication sales nationwide. These two measures of the opioid epidemic will be linked with aggregate and individual-level indicators of marital and nonmarital fertility, marriage, and household structure. Our analysis will explore the mechanisms mediating the effect of the opioid epidemic on family formation and reconfiguration, such as employment conditions and barriers to marriage. We will also examine whether the effect of the epidemic varied by race and ethnicity. Finally, our study will compare the effect of different types of opioids, and specifically evaluate the impact of the introduction of fentanyl to the U.S. illicit drug market in recent years. Our proposed study incorporates two important methodological innovations to overcome estimation problems. First, to better isolate the causal effect of the increase in local opioid abuse on the outcomes of interest we will use an instrumental variables approach. The total annual payments to local doctors by pharmaceutical companies per thousand residents available from the Centers for Medicare and Medicaid Services will be used as an instrument. Second, our models will account for spatial autocorrelation in the estimation of the effect of local opioid abuse.
