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Sensitivity Analysis of Normative Economic Models: Theoretical Framework and Practical Strategies

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  • Pannell, David J.

Abstract

The parameter values and assumptions of any economic model are subject to change and error. Sensitivity analysis (SA), broadly defined, is the investigation of these potential changes and errors and their impacts on conclusions to be drawn from the model. There is a very large literature on procedures and techniques for SA, but it includes almost nothing from economists. This paper is a selective review and overview of theoretical and methodological issues in SA. There are many possible uses of SA, described here within the categories of decision support, communication, increased understanding or quantification of the system, and model development. The paper focuses somewhat on decision support. It is argued that even the simplest approaches to SA can be theoretically respectable in decision support if they are applied and interpreted in a way consistent with Bayesian decision theory. This is not to say that SA results should be formally subjected to a Bayesian decision analysis, but that an understanding of Bayesian probability revision will help the modeller plan and interpret an SA. Many different approaches to SA are described, varying in the experimental design used and in the way results are processed. Possible overall strategies for conducting SA are suggested. It is proposed that when using SA for decision support, it can be very helpful to attempt to identify which of the following forms of recommendation is most appropriate: (a) do, V, (b) do either X or Y depending on the circumstances, (c) do either X or Y, whichever you like, (d) if in doubt, do X. A system for reporting and discussing SA results is recommended.
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Suggested Citation

  • Pannell, David J., 1996. "Sensitivity Analysis of Normative Economic Models: Theoretical Framework and Practical Strategies," 1996 Conference (40th), February 11-16, 1996, Melbourne, Australia 156444, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare96:156444
    DOI: 10.22004/ag.econ.156444
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    References listed on IDEAS

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    1. Kleijnen, J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments," Other publications TiSEM 87ee6ee0-592c-4204-ac50-6, Tilburg University, School of Economics and Management.
    2. Kleijnen, Jack P.C., 1992. "Sensitivity analysis of simulation experiments: regression analysis and statistical design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 34(3), pages 297-315.
    3. Morrison, David A. & Kingwell, Ross S. & Pannell, David J. & Ewing, Michael A., 1986. "A mathematical programming model of a crop-livestock farm system," Agricultural Systems, Elsevier, vol. 20(4), pages 243-268.
    4. Dungan, D. Peter & Wilson, Thomas A., 1991. "Macroeconomic effects and sensitivity analysis," Journal of Policy Modeling, Elsevier, vol. 13(3), pages 435-457.
    5. Bettonvil, Bert & Kleijnen, Jack P. C., 1997. "Searching for important factors in simulation models with many factors: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 96(1), pages 180-194, January.
    6. Canova, Fabio, 1995. "Sensitivity Analysis and Model Evaluation in Simulated Dynamic General Equilibrium Economies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 477-501, May.
    7. Nordblom, Thomas L. & Pannell, David J. & Christiansen, Scott & Nersoyan, Nerses & Bahhady, Faik, 1994. "From weed to wealth? Prospects for medic pastures in the Mediterranean farming system of north-west Syria," Agricultural Economics, Blackwell, vol. 11(1), pages 29-42, September.
    8. Harrison, Glenn W & Vinod, H D, 1992. "The Sensitivity Analysis of Applied General Equilibrium Models: Completely Randomized Factorial Sampling Designs," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 357-362, May.
    9. Hall, Nigel H. & Menz, Kenneth M., 1985. "Product Supply Elasticities for the Australian Broadacre Industries, Estimated with a Programming Model," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 53(01), pages 1-8, April.
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