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Numerical methods for linear-quadratic models

In: Handbook of Computational Economics

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  • Amman, Hans

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This chapter was published in:

  • H. M. Amman & D. A. Kendrick & J. Rust (ed.), 1996. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 1, number 1.
    This item is provided by Elsevier in its series Handbook of Computational Economics with number 1-13.

    Handle: RePEc:eee:hecchp:1-13

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    Web page: http://www.elsevier.com/wps/find/bookseriesdescription.cws_home/BS_HE/description

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    Cited by:
    1. Blueschke-Nikolaeva, V. & Blueschke, D. & Neck, R., 2012. "Optimal control of nonlinear dynamic econometric models: An algorithm and an application," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3230-3240.
    2. Amman, Hans M. & Neudecker, Heinz, 1997. "Numerical solutions of the algebraic matrix Riccati equation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(2-3), pages 363-369.
    3. Pierpaolo Benigno & Michael Woodford, 2008. "Linear-Quadratic Approximation of Optimal Policy Problems," Discussion Papers 0809-01, Columbia University, Department of Economics.
    4. David A. Kendrick & Hans M. Amman & Marco P. Tucci, 2008. "Learning About Learning in Dynamic Economic Models," Working Papers 08-20, Utrecht School of Economics.
    5. Hans M. Amman & David A. Kendrick, 2008. "Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks," Working Papers 08-19, Utrecht School of Economics.
    6. Binder, Michael & Pesaran, Hashem, 2000. "Solution of finite-horizon multivariate linear rational expectations models and sparse linear systems," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 325-346, March.

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