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Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models

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  • Max E. Jerrell

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    (College of Business Administration, Northern Arizona University)

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    Abstract

    Fair and Jaffeen[Fair and Jaffee1972] considered the econometrics of models of markets which were not in equilibrium. The estimation of disequilibrium models has proved difficult. Because of this the model was chosen to be a member of a test suite of optimization problems by Dorsey and Mayern[Dorsey a nd Mayer1955] to compare various optimization techniques. Dorsey and Mayer were chiefly interested in evaluating newly developed global optimization techniques, particularly simulated annealing and genetic algorithms as applied to troubling problems. They find that the disequilibrium model also was a difficult estimation problem for both simulated annealing and genetic algorithms. They do not report success for either technique.

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    Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _028.

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    Handle: RePEc:sce:scecf6:_028

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    1. Jerrell, Max E, 1994. "Global Optimization Using Interval Arithmetic," Computational Economics, Society for Computational Economics, vol. 7(1), pages 55-62, February.
    2. Kalaba, Robert E. & Plum, Thomas & Tesfatsion, Leigh S., 1987. "Automation of Nested Matrix and Derivative Operations," Staff General Research Papers 11202, Iowa State University, Department of Economics.
    3. Goffe, William L & Ferrier, Gary D & Rogers, John, 1992. "Simulated Annealing: An Initial Application in Econometrics," Computer Science in Economics & Management, Society for Computational Economics, vol. 5(2), pages 133-46, May.
    4. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
    5. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-30, November.
    6. Tesfatsion, Leigh, 1991. "Automatic Evaluation of Higher-Order Partial Derivatives for Nonlocal Sensitivity Analysis," Staff General Research Papers 11183, Iowa State University, Department of Economics.
    7. Kalaba, Robert & Tishler, Asher, 1984. "Automatic Derivative Evaluation in the Optimization of Nonlinear Models," The Review of Economics and Statistics, MIT Press, vol. 66(4), pages 653-60, November.
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