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Il problema della coerenza delle previsioni nei modelli econometrici non lineari
[The coherency problem when forecasting with nonlinear econometric models]

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  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Abstract

Problems related to deterministic solution of nonlinear econometric models are well known in the literature. The use of mean (average) stochastic simulation results has been usually proposed to solve the problem of bias. This raises however other types of problems, like possible non-coherent solutions (and forecasts). In this paper we propose the use of the mode of the joint distribution of the endogenous variables, and apply the technique to a nonlinear macroeconometric model of the Italian economy.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 23904.

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Date of creation: 1988
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Handle: RePEc:pra:mprapa:23904

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Related research

Keywords: Nonlinear econometric model; stochastic simulation; mean; median; mode; Italian economy;

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References

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  1. 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 523-36, October.
  2. Fisher, Paul & Salmon, Mark, 1985. "On Evaluating the Importance of Non-Linearity in Large Macroeconometric Models," CEPR Discussion Papers 86, C.E.P.R. Discussion Papers.
  3. 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.
  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, 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 201-08, February.
  6. Wallis, Kenneth F., 1982. "'Time-series' versus 'econometric' forecasts : A non-linear regression counterexample," Economics Letters, Elsevier, vol. 10(3-4), pages 309-315.
  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 & 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.
  9. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
  10. 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 355-78, June.
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