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Precision Performances of Terminal Conditions for Short Time Horizons Forward-Looking Systems

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  • Boucekkine, Raouf
  • Juillard, Michel
  • Malgrange, Pierre

Abstract

In this paper we investigate theoretically the numerical bias due to the truncation of structurally infinite time forward-looking models, by the means of various terminal conditions. On a general multivariate optimal growth model, we first analytically confirm some well-known heuristic properties for certain extreme spectral cases. However, we show that the heuristic findings stated in the literature, relying on intermediate spectral configurations, lack theoretical basis as that they omit, among other relevant features, the crucial role of initial conditions: in this case, comparison criteria exclusively based on spectral considerations lack theoretical sense. Numerical evidence is proposed to illustrate this point and other related empirical findings are presented. Citation Copyright 1997 by Kluwer Academic Publishers.

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  • Boucekkine, Raouf & Juillard, Michel & Malgrange, Pierre, 1997. "Precision Performances of Terminal Conditions for Short Time Horizons Forward-Looking Systems," Computational Economics, Springer;Society for Computational Economics, vol. 10(2), pages 169-186, May.
  • Handle: RePEc:kap:compec:v:10:y:1997:i:2:p:169-86
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    1. Laffargue, Jean-Pierre & Malgrange, Pierre & Pujol, Thierry, 1992. "Une maquette trimestrielle de l’économie française avec anticipations rationnelles et concurrence monopolistique," L'Actualité Economique, Société Canadienne de Science Economique, vol. 68(1), pages 225-261, mars et j.
    2. Boucekkine, Raouf, 1993. "Terminal conditions as efficent instruments for numerical detection of the saddlepoint paths: a linear algebra non-robustness argument," UC3M Working papers. Economics 2898, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Hall, S G, 1985. "On the Solution of Large Economic Models with Consistent Expectations," Bulletin of Economic Research, Wiley Blackwell, vol. 37(2), pages 157-161, May.
    4. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    5. Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(4), pages 711-734, May.
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