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Education and medication use later in life and the role of intelligence

Author

Listed:
  • Gianmaria Niccodemi

    (VIDAS)

  • Govert Bijwaard

    (Netherlands Interdisciplinary Demographic Institute (NIDI-KNAW)/University of Groningen)

Abstract

We investigate the association between education and disease-specific medications in old age, prescribed by medical doctors, accounting for confounders and how this association is shaped by intelligence. We use administrative data on men including prescribed medication records. To account for endogeneity of education we estimate a structural model, consisting of (i) an ordered probit for educational attainment, (ii) a Gompertz mortality model for survival up to old age, (iii) a probit model for prescribed medications in old age, (iv) a measurement system using IQ tests to identify latent intelligence. The results suggest a strong effect of education on prescribed medications for most medications, except for prescribed medication for cardiac diseases and for depression and anxiety.

Suggested Citation

  • Gianmaria Niccodemi & Govert Bijwaard, 2024. "Education and medication use later in life and the role of intelligence," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(2), pages 333-361, March.
    • Handle: RePEc:spr:eujhec:v:25:y:2024:i:2:d:10.1007_s10198-023-01586-7
    DOI: 10.1007/s10198-023-01586-7
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    Keywords

    Educational inequality; Intelligence; Medication use; Structural equation model;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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