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Coherent Forecast with Nonlinear Econometric Models


  • Calzolari, Giorgio
  • Panattoni, Lorenzo


The drawbacks of forecasts 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. This paper proposes to estimate the mode of the joint distribution of the endogenous variables as an alternative optimal predictor.

Suggested Citation

  • Calzolari, Giorgio & Panattoni, Lorenzo, 1988. "Coherent Forecast with Nonlinear Econometric Models," MPRA Paper 28802, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:28802

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    References listed on IDEAS

    1. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389 Elsevier.
    2. 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.
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    More about this item


    Nonlinear econometric models; stochastic simulation; mean and mode; coherent solution;

    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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