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Coherent Forecast with Nonlinear Econometric Models

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  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Abstract

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

    as
    1. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
    2. Bianchi, Carlo & Calzolari, Giorgio & Sartori, Franco, 1982. "Stime 2SLS con componenti principali di un modello non lineare dell' economia italiana [2SLS with principal components: estimation of a nonlinear model of the Italian economy]," MPRA Paper 22665, University Library of Munich, Germany, revised 1982.
    3. Fair, Ray C, 1980. "Estimating the Expected Predictive Accuracy of Econometric Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 355-378, June.
    4. Hall, S G, 1986. "The Application of Stochastic Simulation Techniques to the National Institute's Model 7," The Manchester School of Economic & Social Studies, University of Manchester, vol. 54(2), pages 180-201, June.
    5. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1976. "Divergences in the results of stochastic and deterministic simulation of an Italian non linear econometric model," MPRA Paper 21287, University Library of Munich, Germany.
    6. 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.
    7. 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.
    8. Brundy, James M & Jorgenson, Dale W, 1971. "Efficient Estimation of Simultaneous Equations by Instrumental Variables," The Review of Economics and Statistics, MIT Press, vol. 53(3), pages 207-224, August.
    9. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-343, March.
    10. 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.
    11. Wallis, Kenneth F., 1982. "'Time-series' versus 'econometric' forecasts : A non-linear regression counterexample," Economics Letters, Elsevier, vol. 10(3-4), pages 309-315.
    12. 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.
    13. 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.
    14. 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.
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    Cited by:

    1. Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.

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    More about this item

    Keywords

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