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Hierarchical forecasts of Diabetes mortality in Mexico by marginalization and sex to establish resource allocation

Author

Listed:
  • Eliud Silva

    (Universidad Anahuac Mexico)

  • Corey Sparks

    (The University of Texas at San Antonio)

Abstract

Objective The mexican population has experimented an astounding rise in type II Diabetes mortality as well as a growing trend for the economic burden in the recent years. The paper’s purpose is to propose an approach to establish a distribution of resource allocation objectively to face the future economic burden. Methodology Hierarchical forecasts of Diabetes mortality to 2030 by sub-domains of the population are estimated based on marginalization and sex. Results The forecasts confirm that differences related to sub-domains will be significant. In fact, the rates will increase most notably both in low and high marginalized. Limitations The hierarchical method just provide point forecast without prediction intervals. Originality There is not a similar application for Mexican data to do that objectively. Conclusions The most recommendable budget distribution should be mainly addressed among the low and high levels. Implications of these estimates should support unpostponable health policy in general and for the mentioned sub-domains in particular.

Suggested Citation

  • Eliud Silva & Corey Sparks, 2021. "Hierarchical forecasts of Diabetes mortality in Mexico by marginalization and sex to establish resource allocation," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 18(2), pages 82-98, Julio-Dic.
    • Handle: RePEc:qua:journl:v:18:y:2021:i:2:p:82-98
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    References listed on IDEAS

    as
    1. Armando Arredondo & Gabriela Reyes, 2013. "Health Disparities from Economic Burden of Diabetes in Middle-income Countries: Evidence from México," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-6, July.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    3. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Diabetes; mortality; hierarchical forecasts; marginalization; resource allocation.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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