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Evaluating forecast uncertainty due to errors in estimated coefficients: empirical comparison of alternative methods

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  • Bianchi, Carlo
  • Calzolari, Giorgio

Abstract

This paper is concerned with the contribution to forecast errors of errors in the estimated structural coefficients of a macro-econometric model (simultaneous equations). Its main purpose is to perform, on several "real-world" models, an empirical comparison of alternative techniques available in the literature for this purpose.

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File URL: http://mpra.ub.uni-muenchen.de/22559/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 22559.

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Date of creation: 1982
Date of revision:
Handle: RePEc:pra:mprapa:22559

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Related research

Keywords: Forecast errors; coefficient estimation errors; Monte Carlo; simultaneous equation models;

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References

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  1. 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.
  2. 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.
  3. Schmidt, Peter, 1973. "The Asymptotic Distribution of Dynamic Multipliers," Econometrica, Econometric Society, vol. 41(1), pages 161-64, January.
  4. 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.
  5. Ray C. Fair, 1978. "Estimating the Expected Predictive Accuracy of Econometric Models," Cowles Foundation Discussion Papers 480, Cowles Foundation for Research in Economics, Yale University.
  6. 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.
  7. 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 Vol 1: The Business Cycle Today, pages 261-310 National Bureau of Economic Research, Inc.
  8. 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.
  9. 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.
  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. Hatanaka, Michio, 1978. "On the efficient estimation methods for the macro-economic models nonlinear in variables," Journal of Econometrics, Elsevier, vol. 8(3), pages 323-356, December.
  12. Klein, Lawrence R, 1969. "Estimation on Interdependent Systems in Macroeconometrics," Econometrica, Econometric Society, vol. 37(2), pages 171-92, April.
  13. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1979. "A Monte Carlo approach to compute the asymptotic standard errors of dynamic multipliers," Economics Letters, Elsevier, vol. 2(2), pages 161-164.
  14. 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.
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Citations

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Cited by:
  1. McCarthy, Michael D., 1998. "Finite sample moments results for the quasi-FIML estimator of the reduced form: The linear case," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 239-262.
  2. Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "Evaluating Forecast Uncertainty in Econometric Models: The Effect of Alternative Estimators of Maximum Likelihood Covariance Matrix," MPRA Paper 28806, University Library of Munich, Germany.
  3. Calzolari, Giorgio & Bianchi, Carlo & Corsi, Paolo & Panattoni, Lorenzo, 1982. "Uncertainty of policy recommendations for nonlinear econometric models: some empirical results," MPRA Paper 28846, University Library of Munich, Germany.
  4. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
  5. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Paper 61, National Institute of Economic Research.
  6. Bianchi, Carlo & Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1987. "Forecast variance in simultaneous equation models: analytic and Monte Carlo methods," MPRA Paper 24541, University Library of Munich, Germany.
  7. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results," MPRA Paper 22657, University Library of Munich, Germany, revised 1983.
  8. Bianchi, Carlo & Calzolari, Giorgio & Weihs, Claus, 1986. "Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models," MPRA Paper 29120, University Library of Munich, Germany.
  9. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici
    [Forecast variance in econometric models]
    ," MPRA Paper 23866, University Library of Munich, Germany.

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