Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models Reportar como inadecuado




Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

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 error-in-variables 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 MethodsC - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and SelectionC - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C30 - General-





Autor: Bianchi, Carlo

Fuente: https://mpra.ub.uni-muenchen.de/29120/







Documentos relacionados