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Thick Market Externalities and the Persistence of the Opioid Epidemic

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  • David M. Cutler
  • J. Travis Donahoe

Abstract

Opioid overdose death rates in the United States have risen continuously for over three decades, increasing 2,142 percent in total from 1990 to 2020. This is surprising. One might expect drug epidemics to be self-limiting, as policy and individual behavior reacts to observed deaths. We study why opioid deaths have risen so greatly and for so long. We consider three reasons for a prolonged epidemic: exogenous and continuing changes in demand or supply, and spillovers in demand for opioids across users, which we term “thick market externalities.” We show there is no evidence of sufficiently large exogenous changes in the demand or supply of opioids that could explain such a prolonged increase in death rates. We test for spillovers using county-level data on opioid deaths from 1991–2018 and opioid shipments from 2006–2009, combined with data on friendships and distance between counties. Estimating a model with addiction and spatial spillovers, we find large spillovers in opioid use and deaths across areas. A shock that increases opioid death rates by 1 in an index county causes 0.38 to 0.76 more deaths in other counties because of spillovers. Because opioids are addictive, this leads to even more deaths and spillovers in future years. In some specifications, these effects are large enough to generate a continuously increasing epidemic without any ongoing changes in demand or supply. We estimate spillovers explain 84 to 92 percent of opioid deaths from 1990 to 2018 and are the main reason deaths have increased for so long.

Suggested Citation

  • David M. Cutler & J. Travis Donahoe, 2024. "Thick Market Externalities and the Persistence of the Opioid Epidemic," NBER Working Papers 32055, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:32055
    Note: AG EH PE
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    1. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    2. Roland G. Fryer Jr. & Paul S. Heaton & Steven D. Levitt & Kevin M. Murphy, 2013. "Measuring Crack Cocaine And Its Impact," Economic Inquiry, Western Economic Association International, vol. 51(3), pages 1651-1681, July.
    3. Michael Kremer & Dan Levy, 2008. "Peer Effects and Alcohol Use among College Students," Journal of Economic Perspectives, American Economic Association, vol. 22(3), pages 189-206, Summer.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2004. "Estimation of simultaneous systems of spatially interrelated cross sectional equations," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 27-50.
    5. Esther Duflo & Emmanuel Saez, 2003. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 815-842.
    6. Case, A.C. & Katz, L.F., 1991. "The Company You Keep: The Effects Of Family And Neighborhood On Disadvantaged Younths," Harvard Institute of Economic Research Working Papers 1555, Harvard - Institute of Economic Research.
    7. Powell, Lisa M. & Tauras, John A. & Ross, Hana, 2005. "The importance of peer effects, cigarette prices and tobacco control policies for youth smoking behavior," Journal of Health Economics, Elsevier, vol. 24(5), pages 950-968, September.
    8. Eisenberg, Daniel & Golberstein, Ezra & Whitlock, Janis L., 2014. "Peer effects on risky behaviors: New evidence from college roommate assignments," Journal of Health Economics, Elsevier, vol. 33(C), pages 126-138.
    9. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    10. Olmstead, Todd A. & Alessi, Sheila M. & Kline, Brendan & Pacula, Rosalie Liccardo & Petry, Nancy M., 2015. "The price elasticity of demand for heroin: Matched longitudinal and experimental evidence," Journal of Health Economics, Elsevier, vol. 41(C), pages 59-71.
    11. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    12. Abby Alpert & David Powell & Rosalie Liccardo Pacula, 2018. "Supply-Side Drug Policy in the Presence of Substitutes: Evidence from the Introduction of Abuse-Deterrent Opioids," American Economic Journal: Economic Policy, American Economic Association, vol. 10(4), pages 1-35, November.
    13. Leila Agha & Dan Zeltzer, 2022. "Drug Diffusion through Peer Networks: The Influence of Industry Payments," American Economic Journal: Economic Policy, American Economic Association, vol. 14(2), pages 1-33, May.
    14. Diamond, Peter A, 1982. "Aggregate Demand Management in Search Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 90(5), pages 881-894, October.
    15. David M. Cutler & Edward L. Glaeser, 2021. "When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 171-196, Fall.
    16. Mireille Jacobson, 2004. "Baby Booms and Drug Busts: Trends in Youth Drug use in the United States, 1975–2000," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(4), pages 1481-1512.
    17. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances," Stata Journal, StataCorp LP, vol. 13(2), pages 221-241, June.
    18. David M. Cutler & Edward L. Glaeser, 2021. "When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic," NBER Working Papers 28873, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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