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Forward-looking variables in deterministic control

  • Game Theory and Market Games
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Abstract

In this paper, we adapt the Fair and Taylor [4] method for forward-looking variables in simulation models to control theory models. In particular, we develop a procedure for solving quadratic linear control models when there are forward-looking variables in the system equations. The simplest way to do this for deterministic problems would be to stack up the variables for all time periods using Theil's procedure [9], as suggested by Hughes-Hallet and Rees [5] for simulation models and done by Becker and Rustem [7] for perfect foresight problems. However, we plan to continue from the current paper and develop similar procedures for passive and active learning control problems, and the stacking procedure does not seem as natural for those problems. Therefore, we will use the Fair-Taylor approach here and adapt it for deterministic quadratic linear problems.

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References

  1. H.M. Amman and D.A. Kendrick, Forward-looking variables in stochastic control, The International Journal of Supercomputer Applications 7 (1993) 201–211.

    Google Scholar 

  2. H.M. Amman, D.A. Kendrick and S. Achath, Solving stochastic optimization models with learning and rational expectations, Economics Letters 48 (1995) 9–13.

    Google Scholar 

  3. R.C. Fair,Specification Estimation and Analysis of Macroeconometric Models, Harvard University Press, Cambridge, MA, 1984.

    Google Scholar 

  4. R.C. Fair and J.B. Taylor, Solution and maximum likelihood estimation of dynamic rational expectation models, Econometrica 51 (1983) 1169–1185.

    Google Scholar 

  5. A. Hughes-Hallet and H. Rees,Quantitative Economic Policies and Interactive Planning: A Reconsideration of the Theory of Economic Policy, Cambridge University Press, New York, 1983.

    Google Scholar 

  6. D.A. Kendrick,Stochastic Control for Economic Models, McGraw-Hill, New York, 1981.

    Google Scholar 

  7. R. Becker and B. Rustem, Algorithms for solving nonlinear models, Annals of Operations Research 44 (1993) 117–142.

    Google Scholar 

  8. T.J. Sargent and N. Wallace, “Rational” expectations, the optimal monetary instrument, and the optimal money supply rule, Journal of Political Economy 83 (1975) 241–254.

    Google Scholar 

  9. H. Theil,Optimal Decision Rules for Government and Industry, North-Holland, Amsterdam, 1964.

    Google Scholar 

  10. E.C. MacRae, Linear decisions with experimentation, Annals of Economic and Social Measurement 1 (1972) 437–447.

    Google Scholar 

  11. R.S. Pindyck,Optimal Planning for Economic Stabilization, North-Holland, Amsterdam, 1973.

    Google Scholar 

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Authors and Affiliations

  1. Department of Macroeconomics, University of Amsterdam, Amsterdam, The Netherlands

    Hans M. Amman

  2. Department of Economics, University of Texas, 78712, Austin, TX, USA

    David A. Kendrick

Authors
  1. Hans M. Amman
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  2. David A. Kendrick
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Amman, H.M., Kendrick, D.A. Forward-looking variables in deterministic control. Ann Oper Res 68, 141–159 (1996). https://doi.org/10.1007/BF02205452

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  • DOI: https://doi.org/10.1007/BF02205452

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