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Reverse-Shooting versus Forward-Shooting over a Range of Dimensionalities

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Listed:
  • Ric D. Herbert
  • Peter J. Stemp

Abstract

This paper investigates the properties of dynamic solutions that have been derived using the well-known reverse-shooting and forwardshooting algorithms. Given an arbitrary large-scale model about which we have limited information, how successful are the algorithms likely to be in solving this model? We address this question using a range of investment models, both linear and non-linear. By extending the investment models to allow for multi-dimensional specifications of the capital stock, we are able to examine the computational efficiency of the competing algorithms as the dimensionality of the capital stock is allowed to increase. Our approach provides insights into how the complexity of the solutions to a broad range of macroeconomic models increases with the dimensionality of the models.

Suggested Citation

  • Ric D. Herbert & Peter J. Stemp, 2004. "Reverse-Shooting versus Forward-Shooting over a Range of Dimensionalities," Department of Economics - Working Papers Series 921, The University of Melbourne.
    • Handle: RePEc:mlb:wpaper:921
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    File URL: http://www.economics.unimelb.edu.au/downloads/wpapers-04/921.pdf
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    References listed on IDEAS

    as
    1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    2. Hayashi, Fumio, 1982. "Tobin's Marginal q and Average q: A Neoclassical Interpretation," Econometrica, Econometric Society, vol. 50(1), pages 213-224, January.
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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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