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The Timing of Uncertainty and the Intensity of Policy

Author

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  • P. Ruben Mercado

    (Department of Economics and Finance, U.A.D.E., Lima 717, Piso 1, 1073 Buenos Aires, Argentina)

Abstract

This article analyzes the trade-off between `caution' and `intensity' in the use of the control variable in a one-state one-control dynamic stochastic quadratic linear optimization problem with discount factor. It studies the effects that changes in uncertainty of the control parameter have on the optimal first period response of the control variable, showing that the trade-off between `caution' and `intensity' depends on the timing of the uncertainty. Given an increase in current uncertainty and an equal increase in future uncertainty, caution will always prevail over intensity. Moreover, the prevalence of caution will be enlarged as the increase in future uncertainty moves farther away into the future, while this prevalence will be reduced as the increase in future uncertainty expands into the future. Finally, for the infinite horizon case, caution is the optimal policy response.

Suggested Citation

  • P. Ruben Mercado, 2004. "The Timing of Uncertainty and the Intensity of Policy," Computational Economics, Springer;Society for Computational Economics, vol. 23(4), pages 303-313, June.
    • Handle: RePEc:kap:compec:v:23:y:2004:i:4:p:303-313
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    Cited by:

    1. Arnulfo Rodriguez, 2004. "Robust Control: A Note on the Timing of Model Uncertainty," Computing in Economics and Finance 2004 147, Society for Computational Economics.
    2. P. Mercado & David Kendrick, 2006. "Parameter Uncertainty and Policy Intensity: Some Extensions and Suggestions for Further Work," Computational Economics, Springer;Society for Computational Economics, vol. 27(4), pages 483-496, June.
    3. Arnulfo Rodriguez, 2004. "Robust Control: A Note on the Timing of Model Uncertainty," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 209-221, July.
    4. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.

    More about this item

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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