Brillet, Jean-Louis and Calzolari, Giorgio and Panattoni, Lorenzo (1986): Coherent optimal prediction with large nonlinear systems: an example based on a French model.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Coherent optimal prediction with large nonlinear systems: an example based on a French model|
|Keywords:||Macroeconometric model; French economy; mean and mode; joint distribution; coherent prediction|
|Subjects:||C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling
C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables
|Depositing User:||Giorgio Calzolari|
|Date Deposited:||31. Mar 2011 18:55|
|Last Modified:||21. Feb 2013 06:46|
Amemiya, T. (1983), "Non-Linear Regression Models", in Handbook of Econometrics, ed. by Z.Griliches and M.D.lntriligator. Amsterdam: North-Holland, Vol.l, 333-389.
Anderson, T.W. (1958), An Introduction to Multivariate Statistical Analysis. New York: John Wiley.
Bianchi,C., J.L.Brillet et G.Calzolari (1984), "Analyse et Mesure de l'Incertitude en Prevision d'un Modele Econometrique. Application au Modele Mini-DMS", Annales de I'INSEE 54, 31-62.
Bianchi, C., and G. Calzolari (1980), "The One-Period Forecast Errors in Nonlinear Econometric Models", International Economic Review 21, 201-208.
Bianchi,C., G.Calzolari, and P.Corsi (1976), "Divergences in the Results of Stochastic and Deterministic Simulation of an Italian Non-Linear Econometric Model", in Simulation of Systems, ed. by L.Dekker. Amsterdam: North Holland, 653-661.
Brillet,J. L. (1981), Mini-DMS: Modele Macroeconomique de Simulation. Paris: INSEE, Archives & Documents No.35.
Brown,B.W., and R.S.Mariano (1984), "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System", Econometrica 52, 321-343.
Brown,B.W., and R.S.Mariano (1985), "Reduced Variance Prediction in Nonlinear Simultaneous Systems". Rice University, discussion paper presented at the World Congress of the Econometric Society, M.I.T, Cambridge MA, August 17-24.
Brundy, J. M., and D. W. Jorgenson (1971): "Efficient Estimation of Simultaneous Equations by Instrumental Variables", The Review of Economics and Statistics 53, 207-224.
Calzolari,G. (1979), "Antithetic Variates to Estimate the Simulation Bias in Non-Linear Models", Economics Letters 4, 323-328.
Dennis,J.E., and J.J. More' (1977), "Quasi-Newton Methods, Motivation and Theory", SIAM Review 19, 46-89.
Fair,R.C. (1980), "Estimating the Expected Predictive Accuracy of Econometric Models", International Economic Review 21, 355-378.
Fisher,P., and M.Salmon (1986), "On Evaluating the Importance of Nonlinearity in Large Macroeconometric Models", International Economic Review (forthcoming).
Fouquet,D., J.M.Charpin, H.Guillaume, P.A.Muet et D.Vallet (1978), DMS, Modele Dynamique Multisectoriel. Paris: Collections de l'INSEE, Serie C, No.64-65.
Hall,S.G. (1984), "The Application of Stochastic Simulation Techniques to the National Institute's Model 7". London: NIESR, discussion paper No.65.
Hall,S.G. (1985), "The Importance of Non-Linearities in Large Forecasting Models with Stochastic Error Processes". London: NIESR, discussion paper.
Howrey,E. P., and H.H.Kelejian (1971), "Simulation versus Analytical Solutions: the Case of Econometric Models", in Computer Simulation Experiments with Models of Economic Systems, ed. by T.H.Naylor. New York: John Wiley, 299-319.
Kendall,M.G., and A.Stuart (1969), The Advanced Theory of Statistics. Vol.l. London: Charles Griffin.
Mariano,R.S., and B.W.Brown (1983), "Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System", International Economic Review 24, 523-536.
McCarthy,M.D. (1972), "Some Notes on the Generation of Pseudo-Structural Errors for Use in Stochastic Simulation Studies", in Econometric Models of Cyclical Behavior, ed. by B.G.Hickman. New York: NBER, Studies in Income and Wealth No.36, 185-191.
Nagar,A.L. (1969), "Stochastic Simulation of the Brookings Econometric Model", in The Brookings Model: Some Further Results, ed. by J.S.Duesenberry, G.Fromm, L.R.Klein and E.Kuh. Amsterdam: North Holland, 425-456.
Oberhofer,W. (1971), "On the Treatment of Definition Equations in Likelihood Functions". University of Bonn: Institut fuer Gesellschafts-und Wirtschaftswissenschaften, Wirtschaftstheoretische Abteilung, discussion paper No. 14.
Rothenberg,T.J., and C.T.Leenders (1964), "Efficient Estimation of Simultaneous Equation Systems", Econometrica 32, 57-76.
Wallis,K.F. (1982), "Time Series versus Econometric Forecasts: A Non-Linear Regression Counter-Example", Economics Letters 10, 309-315.