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Abstract

We estimate a fixed effects county level panel data model to relate socioeconomic variables to opioid-related drug overdoses, which cost the nation in excess of $430bn in 2015. In addition to demographic and labor market variables we include lagged employment shares by major industry and self-employment shares, as well as cumulative counts of presidentially declared disasters. We find that rurality, as measured by lower population density, is associated with higher overdose rates. Also, for each $10,000 reduction in net income per farm, opioids overdoses rose by 10% from a national average of 10.2 deaths per 100,000 people.

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