Bianchi, Carlo and Brillet, JeanLouis and Calzolari, Giorgio and Panattoni, Lorenzo (1987): Forecast variance in simultaneous equation models: analytic and Monte Carlo methods. Published in: INSEE, Paris, France No. Paper presented at the Seminaire d'Econometrie de Malinvaud (February 1987): pp. 119.

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Abstract
Five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macromodel of the French economy, the MiniDMS developed at INSEE. They are bootstrap, analytic simulation on coefficients, Monte Carlo on coefficients, parametric stochastic simulation and reestimation, a residualbased procedure. Due to the complexity and the size of the model (nonlinear and with more than 200 equations), several associated technical problems had to be solved. The remarkable convergence of results which has been obtained for all the main endogenous variables suggests that forecast confidence intervals are likely to be quite reliable for this model.
Item Type:  MPRA Paper 

Original Title:  Forecast variance in simultaneous equation models: analytic and Monte Carlo methods 
Language:  English 
Keywords:  Bootstrap; analytic simulation; Monte Carlo; stochastic simulation; macroeconometric model; French economy 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63  Computational Techniques ; Simulation Modeling 
Item ID:  24541 
Depositing User:  Giorgio Calzolari 
Date Deposited:  08 Sep 2010 07:26 
Last Modified:  05 Oct 2019 14:06 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/24541 