The Impact of Staggered Benefit Disbursement on Opioid Use

A commonly recommended policy to alleviate the opioid burden is to distribute income benefits multiple times a month to a household instead of a single lump sum payment. This recommendation stems from two established bodies of literature that (1) establish the cyclical nature of the monthly opioid-mortality cycle and (2) document a relationship between benefit disbursement (income transfer) day and substance use. However, despite the national importance of the opioid epidemic, and the frequent intersection of opioid users with those who receive government benefits, no paper has empirically examined the relationship between the two. Our project overcomes prior data limitations to provide the first causal evidence on the relationship between income transfer schedules and opioid misuse, in a state that has been disproportionately impacted by the opioid epidemic.

West Virginia (WV) has the highest opioid-related death rate in the country. One of the poorest US states, WV relies heavily on government cash transfer programs, specifically Supplemental Nutrition Assistance Program (SNAP), which aims to alleviate food insecurity in low-income households, and Temporary Assistance for Needy Families (TANF), which aims to help families achieve self-sufficiency. Government income transfers, including SNAP and TANF, are disbursed to each household once monthly. Across the U.S., it is common to receive both SNAP and TANF benefits on the same day (i.e., one cash transfer from the government per month). However, WV distributes TANF to everyone on the 1^st of the month, but distributes SNAP during any one of the first nine days of the month, according to last name.

We take advantage of this novel and virtually random distribution schedule and WV’s willingness to provide linked Medicaid, SNAP and TANF data to estimate the causal impact of benefit disbursement schedules on opioid misuse. Our outcomes include licit and illicit opioid use, emergency department visits, hospitalizations, and mortality. We estimate the impact of multiple benefit distribution days across the month compared to a single distribution day. We then determine whether there are differential impacts by relative size of each transfer to total household income. Our results will provide evidence on not only the impact of multiple distribution dates, but also on the relative importance of longer versus shorter time intervals between payments. Next, we test for distributional changes to opioid overdose, mortality, and usage patterns. Then, we conduct a decomposition analysis to determine the proportion of the mortality/overdose spike due to benefits transfers (versus other factors). Finally, we offer a welfare calculation derived from the change in composition for days overdoses occur.

Preliminary data from the linked SNAP, TANF, and Medicaid dataset show that from 2014-2016, there were 4,767 opioid-related overdoses, 83% of which resulted in death. Of those who received SNAP benefits between 2014-2016, 3,281 also had an overdose. Among all overdoses, 20% occur in the first 5 days of the month; fewer than 2.5% occur during the last 5 days of the month, with declining rates in between. A paper and a full set of results will be available before ASHEcon this summer.