IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/22559.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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.

Suggested Citation

  • 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.
  • Handle: RePEc:pra:mprapa:22559
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/22559/1/MPRA_paper_22559.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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 355-378, June.
    2. 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 201-208, February.
    3. 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 503-533, October.
    4. 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 207-224, August.
    5. McCarthy, Michael D, 1972. "A Note on the Forecasting Properties of Two Stage Least Squares Restricted Reduced Forms-The Finite Sample Case," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 757-761, October.
    6. 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.
    7. Amemiya, Takeshi, 1977. "The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model," Econometrica, Econometric Society, vol. 45(4), pages 955-968, May.
    8. Klein, Lawrence R, 1969. "Estimation on Interdependent Systems in Macroeconometrics," Econometrica, Econometric Society, vol. 37(2), pages 171-192, April.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Schmidt, Peter, 1973. "The Asymptotic Distribution of Dynamic Multipliers," Econometrica, Econometric Society, vol. 41(1), pages 161-164, January.
    15. Schmidt, Peter, 1974. "The Asymptotic Distribution of Forecasts in the Dynamic Simulation of an Econometric Model," Econometrica, Econometric Society, vol. 42(2), pages 303-309, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    2. Giorgio Calzolari, 2015. "Indirect estimation and econometrics exams: how to live a round life," Econometrics Working Papers Archive 2015_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
    8. Simes, Richard M, 1988. "Macroeconometric Model Evaluation, with Special Reference to the NIF88 Model," Australian Economic Papers, Wiley Blackwell, vol. 27(0), pages 29-56, Supplemen.
    9. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    10. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
    11. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
    2. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
    8. Calzolari, Giorgio, 2012. "Econometric notes," MPRA Paper 71440, University Library of Munich, Germany.
    9. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    10. 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.
    11. Calzolari, Giorgio & Panattoni, Lorenzo, 1983. "Hessian and approximated Hessian matrices in maximum likelihood estimation: a Monte Carlo study," MPRA Paper 28847, University Library of Munich, Germany.
    12. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo & Panattoni, Lorenzo, 1985. "Asymptotic properties of dynamic multipliers in nonlinear econometric models," MPRA Paper 24401, University Library of Munich, Germany.
    13. Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "A Simulation Study on FIML Covariance Matrix," MPRA Paper 28804, University Library of Munich, Germany.
    14. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
    15. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1979. "A package for analytic simulation of econometric models," MPRA Paper 24134, University Library of Munich, Germany.
    16. Bianchi, Carlo & Brillet, Jean-Louis & Calzolari, Giorgio, 1983. "Analysis and measurement of the uncertainty in Mini-Dms model for the French economy," MPRA Paper 29056, University Library of Munich, Germany.
    17. Bianchi, Carlo & Brillet, Jean-Louis & Calzolari, Giorgio, 1984. "Analyse et mesure de l'incertitude en prevision d'un modele econometrique. Application au modele mini-DMS [Analysis and measurement of forecast uncertainty in an econometric model. Application to m," MPRA Paper 22565, University Library of Munich, Germany, revised 1984.
    18. Bianchi, Carlo & Calzolari, Giorgio, 1979. "Simulation of a nonlinear econometric model," MPRA Paper 24440, University Library of Munich, Germany, revised 1980.
    19. Calzolari, Giorgio, 1979. "Stochastic simulation experiments on Model 5 of Bonn University," MPRA Paper 24456, University Library of Munich, Germany.
    20. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.

    More about this item

    Keywords

    Forecast errors; coefficient estimation errors; Monte Carlo; simultaneous equation models;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:22559. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.