Bianchi, Carlo and Calzolari, Giorgio and Weihs, Claus (1986): Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models.

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Abstract
In the econometric literature simulation techniques are suggested for estimating standard errors of forecasts, especially in case of nonlinear models, where explicit analytic formulae are not available. For this purpose analytic simulation on coefficients, Monte Carlo on coefficients, Monte Carlo simulation based on parametric estimate of the underlying error distribution have been proposed, and more recently a nonparametric procedure which uses the bootstrap technique is also suggested. Main purpose of this paper is to compare, in empirical applications for real world models, parametric and nonparametrlc estimates. Furthermore, in case of linear models, the same comparisons are performed with respect to the results obtained via analytic formulae. Additional results are obtained from an errorinvariables approach.
Item Type:  MPRA Paper 

Original Title:  Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models 
Language:  English 
Keywords:  Standard errors of forecasts; econometric models; parametric and nonparametric simulations 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C52  Model Evaluation, Validation, and Selection C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C30  General 
Item ID:  29120 
Depositing User:  Giorgio Calzolari 
Date Deposited:  09 Mar 2011 20:32 
Last Modified:  26 Sep 2019 22:13 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/29120 