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Comparative Dynamics in Health Economics: Some Useful Results

Author

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  • Johansson, Per-Olov

    () (Dept. of Economics, Stockholm School of Economics)

  • Löfgren, Karl-Gustav

Abstract

In analysis of atemporal models, comparative statics experiments are typically carried out, often employing envelope properties, such as Roy's identity, Hotelling's lemma and Shephard's lemma, in order to simplify the analysis. In analysis of dynamic models, such experiments are seldom undertaken because of the complexity involved. In this note, we illustrate how to employ dynamic envelope properties in order to arrive at surprisingly simple comparative dynamics results in optimal control theory models. We also extend the envelope theorem to an infinite horizon problem with fundamental time dependency, and apply the result to parametric changes in death risks and health production functions.

Suggested Citation

  • Johansson, Per-Olov & Löfgren, Karl-Gustav, 1994. "Comparative Dynamics in Health Economics: Some Useful Results," SSE/EFI Working Paper Series in Economics and Finance 17, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0017
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    Citations

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    Cited by:

    1. Zethraeus, Niklas & Johansson, Per-Olov, 1997. "Willingness to Pay for Hormone Replacement Therapy," SSE/EFI Working Paper Series in Economics and Finance 214, Stockholm School of Economics.
    2. Thomas Aronsson & Kenneth Backlund & Karl-Gustaf Löfgren, 1998. "Nuclear Power, Externalities and Non-Standard Pigouvian Taxes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 11(2), pages 177-195, March.

    More about this item

    Keywords

    Dynamic envelope theorem; risk; health; comparative dynamics;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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