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Opioid Mortality in the US: Quantifying the Direct and Indirect Impact of Sociodemographic and Socioeconomic Factors

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  • Fischer, Manfred M.
  • Gopal, Sucharita

Abstract

This paper employs a spatial Durbin panel data model, an extension of the cross-sectional spatial Durbin model to a panel data framework, to quantify the impact of a set of sociodemographic and socioeconomic factors that influence opioid-related mortality in the US. The empirical model uses a pool of 49 US states over six years from 2014 to 2019, and a nearest-neighbor matrix that represents the topological structure between the states. Calculation of direct (own-state) and indirect (cross-state spillovers) effects estimates is based on Bayesian estimation and inference reflecting a proper interpretation of the marginal effects for the model that involves spatial lags of the dependent and independent variables. The study provides evidence that opioid mortality depends not only on the characteristics of the state itself (direct effects), but also on those of nearby states (indirect effects). Direct effects are important, but externalities (spatial spillovers) are more important. The sociodemographic structure (age and race) of a state is important whereas economic distress of a state is less so, as indicated by the total impact estimates. The methodology and the research findings provide a useful template for future empirical work using other geographic locations or shifting interest to other epidemics.

Suggested Citation

  • Fischer, Manfred M. & Gopal, Sucharita, 2023. "Opioid Mortality in the US: Quantifying the Direct and Indirect Impact of Sociodemographic and Socioeconomic Factors," Working Papers in Regional Science 2023/01, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus046:40256528
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    References listed on IDEAS

    as
    1. James Lesage & Manfred Fischer, 2008. "Spatial Growth Regressions: Model Specification, Estimation and Interpretation," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(3), pages 275-304.
    2. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    3. Manfred M. Fischer & Jinfeng Wang, 2011. "Spatial Data Analysis," SpringerBriefs in Regional Science, Springer, number 978-3-642-21720-3, March.
    4. Barbara Blake-Gonzalez & Richard J. Cebula & James V. Koch, 2021. "Drug-overdose death rates: the economic misery explanation and its alternatives," Applied Economics, Taylor & Francis Journals, vol. 53(6), pages 730-741, February.
    5. Baltagi, Badi H. & Heun Song, Seuck & Cheol Jung, Byoung & Koh, Won, 2007. "Testing for serial correlation, spatial autocorrelation and random effects using panel data," Journal of Econometrics, Elsevier, vol. 140(1), pages 5-51, September.
    6. King, N.B. & Fraser, V. & Boikos, C. & Richardson, R. & Harper, S., 2014. "Determinants of increased opioid-related mortality in the united states and canada, 1990-2013: A systematic review," American Journal of Public Health, American Public Health Association, vol. 104(8), pages 32-42.
    7. Manfred M. Fischer & James P. LeSage, 2020. "Network dependence in multi-indexed data on international trade flows," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-26, December.
    8. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    9. James Paul LeSage, 2020. "Fast MCMC estimation of multiple W-matrix spatial regression models and Metropolis–Hastings Monte Carlo log-marginal likelihoods," Journal of Geographical Systems, Springer, vol. 22(1), pages 47-75, January.
    10. Cheng Hsiao, 2007. "Rejoinder on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 56-57, May.
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    More about this item

    Keywords

    Spatial Durbin panel data model; Bayesian econometrics; Markov Chain Monte Carlo; direct (own state) effects; indirect (cross-state spatial spillover) effects; inferential statistics;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada

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