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Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models

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  • Max E. Jerrell

    (College of Business Administration, Northern Arizona University)

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.

Suggested Citation

  • Max E. Jerrell, "undated". "Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models," Computing in Economics and Finance 1996 _028, Society for Computational Economics.
    • Handle: RePEc:sce:scecf6:_028
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    References listed on IDEAS

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    1. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
    2. Goffe, William L & Ferrier, Gary D & Rogers, John, 1992. "Simulated Annealing: An Initial Application in Econometrics," Computer Science in Economics & Management, Kluwer;Society for Computational Economics, vol. 5(2), pages 133-146, May.
    3. Kalaba, Robert E. & Plum, Thomas & Tesfatsion, Leigh S., 1987. "Automation of Nested Matrix and Derivative Operations," Staff General Research Papers Archive 11202, Iowa State University, Department of Economics.
    4. 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 653-660, November.
    5. Tesfatsion, Leigh, 1991. "Automatic Evaluation of Higher-Order Partial Derivatives for Nonlocal Sensitivity Analysis," Staff General Research Papers Archive 11183, Iowa State University, Department of Economics.
    6. Jerrell, Max E, 1994. "Global Optimization Using Interval Arithmetic," Computational Economics, Springer;Society for Computational Economics, vol. 7(1), pages 55-62, February.
    7. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
    8. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
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    Cited by:

    1. Zilinskas, Julius & Bogle, Ian David Lockhart, 2006. "Balanced random interval arithmetic in market model estimation," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1367-1378, December.
    2. Max E. Jerrell, 1999. "Environments for Global Optimization Using Interval Arithmetic and Computational (Automatic) Differentiation," Computing in Economics and Finance 1999 1321, Society for Computational Economics.
    3. Robert Cudeck, 2005. "Fitting Psychometric Models with Methods Based on Automatic Differentiation," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 599-617, December.

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