IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper

Forecast variance in simultaneous equation models: analytic and Monte Carlo methods

  • Bianchi, Carlo
  • Brillet, Jean-Louis
  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macro-model of the French economy, the Mini-DMS developed at INSEE. They are bootstrap, analytic simulation on coefficients, Monte Carlo on coefficients, parametric stochastic simulation and re-estimation, a residual-based procedure. Due to the complexity and the size of the model (nonlinear and with more than 200 equations), several associated technical problems had to be solved. The remarkable convergence of results which has been obtained for all the main endogenous variables suggests that forecast confidence intervals are likely to be quite reliable for this model.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: https://mpra.ub.uni-muenchen.de/24541/1/MPRA_paper_24541.pdf
File Function: original version
Download Restriction: no

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 24541.

as
in new window

Length:
Date of creation: Feb 1987
Date of revision:
Publication status: Published in INSEE, Paris, France Paper presented at the Seminaire d'Econometrie de Malinvaud (1987): pp. 1-19
Handle: RePEc:pra:mprapa:24541
Contact details of provider: Postal:
Ludwigstraße 33, D-80539 Munich, Germany

Phone: +49-(0)89-2180-2459
Fax: +49-(0)89-2180-992459
Web page: https://mpra.ub.uni-muenchen.de

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. 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.
  2. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
  3. Fisher, Paul & Salmon, Mark, 1985. "On Evaluating the Importance of Non-Linearity in Large Macroeconometric Models," CEPR Discussion Papers 86, C.E.P.R. Discussion Papers.
  4. 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.
  5. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
  6. 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.
  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. Corker, R. J. & Holly, S. & Ellis, R. G., 1986. "Uncertainty and forecast precision," International Journal of Forecasting, Elsevier, vol. 2(1), pages 53-53.
  9. 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.
  10. Schmidt, Peter, 1973. "The Asymptotic Distribution of Dynamic Multipliers," Econometrica, Econometric Society, vol. 41(1), pages 161-64, January.
  11. 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.
  12. 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.
  13. Calzolari, Giorgio & Sterbenz, Frederic P, 1986. "Control Variates to Estimate the Reduced Form Variances in Econometric Models," Econometrica, Econometric Society, vol. 54(6), pages 1483-90, November.
  14. Schmidt, Peter, 1977. "Some Small Evidence on the Distribution of Dynamic Simulation Forecasts," Econometrica, Econometric Society, vol. 45(4), pages 997-1005, May.
  15. 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.
  16. Calzolari, Giorgio, 1987. "Forecast Variance in Dynamic Simulation of Simultaneous Equation Models," Econometrica, Econometric Society, vol. 55(6), pages 1473-76, November.
  17. Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "Coherent optimal prediction with large nonlinear systems: an example based on a French model," MPRA Paper 29057, University Library of Munich, Germany.
  18. 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.
  19. 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.
  20. 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.
  21. Calzolari, Giorgio & Corsi, Paolo, 1977. "Stochastic simulation as a validation tool for econometric models," MPRA Paper 21226, University Library of Munich, Germany.
  22. 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.
  23. 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.
  24. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-43, March.
  25. Klein, Lawrence R, 1969. "Estimation on Interdependent Systems in Macroeconometrics," Econometrica, Econometric Society, vol. 37(2), pages 171-92, April.
  26. 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.
  27. Freedman, David A & Peters, Stephen C, 1984. "Bootstrapping an Econometric Model: Some Empirical Results," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(2), pages 150-58, April.
  28. 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.
  29. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:24541. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.