What Drives Risky Prescription Opioid Use? Evidence from Migration / Amy Finkelstein, Matthew Gentzkow, Dean Li, Heidi L. Williams.

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Finkelstein, Amy

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TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w30471.Publication details: Cambridge, Mass. National Bureau of Economic Research 2022.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: We investigate the role of person- and place-specific factors in the opioid epidemic by developing and estimating a dynamic model of risky prescription opioid use. We estimate the model using the relationship between cross-state migration and risky use among adults receiving federal disability insurance from 2006 to 2015. Event studies suggest that moving to a state with a 3.5 percentage point higher rate of risky use (roughly the difference between the 20th and 80th percentile states) increases the probability of risky use by 1.0 percentage point on-impact, followed by an additional increase of 0.30 percentage points per subsequent year. Model estimates imply large place effects in both the likelihood of transitioning to addiction and the availability of prescription opioids. A one standard deviation reduction in all place effects would have reduced risky use by two-thirds over our study period. Reductions in place effects on addiction have a larger cumulative effect than analogous reductions in place effects on availability. However, their relative efficacy is reversed in the first few years, suggesting a temporal tradeoff among policy options.

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September 2022.

We investigate the role of person- and place-specific factors in the opioid epidemic by developing and estimating a dynamic model of risky prescription opioid use. We estimate the model using the relationship between cross-state migration and risky use among adults receiving federal disability insurance from 2006 to 2015. Event studies suggest that moving to a state with a 3.5 percentage point higher rate of risky use (roughly the difference between the 20th and 80th percentile states) increases the probability of risky use by 1.0 percentage point on-impact, followed by an additional increase of 0.30 percentage points per subsequent year. Model estimates imply large place effects in both the likelihood of transitioning to addiction and the availability of prescription opioids. A one standard deviation reduction in all place effects would have reduced risky use by two-thirds over our study period. Reductions in place effects on addiction have a larger cumulative effect than analogous reductions in place effects on availability. However, their relative efficacy is reversed in the first few years, suggesting a temporal tradeoff among policy options.