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Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results

  • Bianchi, Carlo
  • Calzolari, Giorgio

In nonlinear econometric models, the evaluation of forecast errors is usually performed, completely or partially, by resorting to stochastic simulation. However, for evaluating the specific contribution of errors in estimated structural coefficients, several alternative methods have been proposed in the literature. Three of these methods will be compared empirically in this paper through experiments performed on a set of "real world" econometric models of small, medium and large size. This work extends to dynamic simulation of nonlinear econometric models, for which the authors have recently analysed the one-period (static) forecast errors empirically.

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File URL: http://mpra.ub.uni-muenchen.de/22657/1/MPRA_paper_22657.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 22657.

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Date of creation: 1983
Date of revision: 1983
Handle: RePEc:pra:mprapa:22657
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  1. Schmidt, Peter, 1974. "The Asymptotic Distribution of Forecasts in the Dynamic Simulation of an Econometric Model," Econometrica, Econometric Society, vol. 42(2), pages 303-09, March.
  2. Jerry A. Hausman, 1974. "Full Information Instrumental Variables Estimation of Simultaneous Equations Systems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 641-652 National Bureau of Economic Research, Inc.
  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. Feldstein, Martin S, 1971. "The Error of Forecast in Econometric Models when the Forecast-Period Exogenous Variables are Stochastic," Econometrica, Econometric Society, vol. 39(1), pages 55-60, January.
  5. Brundy, James M & Jorgenson, Dale W, 1971. "Efficient Estimation of Simultaneous Equations by Instrumental Variables," The Review of Economics and Statistics, MIT Press, vol. 53(3), pages 207-24, August.
  6. Mariano, Roberto S, 1982. "Analytical Small-Sample Distribution Theory in Econometrics: The Simultaneous-Equations Case," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(3), pages 503-33, October.
  7. Gallant, A. Ronald, 1977. "Three-stage least-squares estimation for a system of simultaneous, nonlinear, implicit equations," Journal of Econometrics, Elsevier, vol. 5(1), pages 71-88, January.
  8. Yoel Haitovsky & Neil Wallace, 1972. "A Study of Discretionary and Nondiscretionary Monetary and Fiscal Policies in the Context of Stochastic Macroeconometric Models," NBER Chapters, in: Economic Research: Retrospect and Prospect, Volume 1, The Business Cycle Today, pages 261-309 National Bureau of Economic Research, Inc.
  9. Hendry, David F. & Harrison, Robin W., 1974. "Monte Carlo methodology and the small sample behaviour of ordinary and two-stage least squares," Journal of Econometrics, Elsevier, vol. 2(2), pages 151-174, July.
  10. 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.
  11. Cooper, J Phillip & Fischer, Stanley, 1974. "Monetary and Fiscal Policy in the Fully Stochastic St. Louis Econometric Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 6(1), pages 1-22, February.
  12. 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.
  13. Bianchi, Carlo & Calzolari, Giorgio, 1982. "Evaluating forecast uncertainty due to errors in estimated coefficients: empirical comparison of alternative methods," MPRA Paper 22559, University Library of Munich, Germany.
  14. James M. Brundy & Dale W. Jorgenson, 1974. "The Relative Efficiency of Instrumental Variables Estimators of Systems of Simultaneous Equations," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 679-700 National Bureau of Economic Research, Inc.
  15. Dhrymes, Phoebus J, 1973. "Restricted and Unrestricted Reduced Forms: Asymptotic Distribution and Relative Efficiency," Econometrica, Econometric Society, vol. 41(1), pages 119-34, January.
  16. James M. Brundy & Dale W. Jorgenson, 1971. "Efficient estimation of simultaneous equations by instrumental variables," Working Papers in Applied Economic Theory 3, Federal Reserve Bank of San Francisco.
  17. 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.
  18. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
  19. Calzolari, Giorgio, 1981. "A Note on the Variance of Ex-Post Forecasts in Econometric Models," Econometrica, Econometric Society, vol. 49(6), pages 1593-95, November.
  20. 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.
  21. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1981. "Standard errors of multipliers and forecasts from structural coefficients with block-diagonal covariance matrix," MPRA Paper 22678, University Library of Munich, Germany, revised 1981.
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