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Coherent optimal prediction with large nonlinear systems: an example based on a French model

Author

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  • Brillet, Jean-Louis
  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Abstract

The drawbacks of predictors obtained with the usual deterministic solution methods in nonlinear systems of stochastic equations have been widely investigated in the literature. Most of the proposed therapies are based on some estimation of the conditional mean of the endogenous variables in the forecast period. This however provides a solution to the problem which does not respect the internal coherency of the model, and in particular does not satisfy nonlinear identities. At the same time, for analogy with univariate skewed distributions, the conditional mean may be expected to lie on the wrong side of the deterministic solution, meaning that it moves towards values of the variables which are less likely to occur, rather than towards the most probable values. Estimation of the most likely joint value of all endogenous variables is proposed as an alternative optimal predictor. Experimentation is performed on a large scale macroeconomic model of the French economy, and some considerations are drawn from the results.

Suggested Citation

  • Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "Coherent optimal prediction with large nonlinear systems: an example based on a French model," MPRA Paper 29057, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:29057
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    References listed on IDEAS

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    7. Bianchi, Carlo & Brillet, Jean-Louis & Calzolari, Giorgio, 1984. "Analyse et mesure de l'incertitude en prevision d'un modele econometrique. Application au modele mini-DMS [Analysis and measurement of forecast uncertainty in an econometric model. Application to m," MPRA Paper 22565, University Library of Munich, Germany, revised 1984.
    8. Bianchi, Carlo & Calzolari, Giorgio, 1980. "The One-Period Forecast Errors in Nonlinear Econometric Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 201-208, February.
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    11. Fisher, Paul & Salmon, Mark, 1986. "On Evaluating the Importance of Nonlinearity in Large Macroeconometric Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 27(3), pages 625-646, October.
    12. Mariano, Roberto S & Brown, Bryan W, 1983. "Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 523-536, October.
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    Cited by:

    1. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    2. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    3. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.

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    More about this item

    Keywords

    Macroeconometric model; French economy; mean and mode; joint distribution; coherent prediction;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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