IDEAS home Printed from https://ideas.repec.org/a/prs/ecoprv/ecop_0249-4744_1999_num_140_4_5982.html
   My bibliography  Save this article

Une comparaison des prévisions des experts à celles issues des modèles B VAR

Author

Listed:
  • Sandrine Lardic
  • Auguste Mpacko Priso

Abstract

[eng] A Comparison of Expert Forecasts with BVAR Model Forecasts by Sandrine Lardic and Auguste Mpacko-Priso . This paper checks whether economic and financial experts forecast macroeconomic and financial variables «better» than alternative techniques and in particular the Bayesian method. The BVAR methodology, presented in detail in Lardic and Mpacko-Priso (1996) and summarised in this paper, is used to generate six-month and twelve-month forecasts of the Consumer Price Index, Industrial Production Index, Standard and Poors 425, and Standard and Poors 500 for two samples. These forecasts are then compared with economic and financial expert predictions as well as with forecasts derived from traditional techniques for the same periods of time. Statistical and economic criteria are used to gauge the different forecasts. We show that the BVAR forecasts are generally better than the individual expert forecasts. We conclude that the BVAR methodology merits being used more than it is at present. [fre] Une comparaison des prévisions des experts à celles issues des modèles BVAR par Sandrine Lardic et Auguste Mpacko-Priso . Cet article a pour objet de tester si les prévisions des variables macro-économiques et financières faites par des professionnels de l'économie et de la finance sont «meilleures» que celles issues de techniques alternatives, notamment bayésiennes. Suivant la méthodologie BVAR, les prévisions sur les horizons de six et douze mois des variables Indice des Prix à la Consommation, Indice de la Production Industrielle et Indice Standard and Pors 425 ou Standard and Poors 500 sont générées pour deux échantillons distincts. Ces prévisions sont ensuite comparées à celles des experts de l'économie et de la finance d'une part et à celles issues des techniques traditionnelles de prévision d'autre part. Cette comparaison repose à la fois sur des critères statistiques et économiques.

Suggested Citation

  • Sandrine Lardic & Auguste Mpacko Priso, 1999. "Une comparaison des prévisions des experts à celles issues des modèles B VAR," Économie et Prévision, Programme National Persée, vol. 140(4), pages 161-180.
    • Handle: RePEc:prs:ecoprv:ecop_0249-4744_1999_num_140_4_5982
    DOI: 10.3406/ecop.1999.5982
    Note: DOI:10.3406/ecop.1999.5982
    as

    Download full text from publisher

    File URL: https://doi.org/10.3406/ecop.1999.5982
    Download Restriction: no
    File URL: https://www.persee.fr/doc/ecop_0249-4744_1999_num_140_4_5982
    Download Restriction: no
    File URL: https://libkey.io/10.3406/ecop.1999.5982?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    2. Robert B. Litterman, 1984. "Forecasting and policy analysis with Bayesian vector autoregression models," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    3. Cumby, Robert E. & Modest, David M., 1987. "Testing for market timing ability : A framework for forecast evaluation," Journal of Financial Economics, Elsevier, vol. 19(1), pages 169-189, September.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Kunst, Robert & Neusser, Klaus, 1986. "A forecasting comparison of some var techniques," International Journal of Forecasting, Elsevier, vol. 2(4), pages 447-456.
    6. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    7. Holden, K. & Broomhead, A., 1990. "An examination of vector autoregressive forecasts for the U.K. economy," International Journal of Forecasting, Elsevier, vol. 6(1), pages 11-23.
    8. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    9. Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 53-67, January.
    10. Lakonishok, Josef, 1980. "Stock Market Return Expectations: Some General Properties," Journal of Finance, American Finance Association, vol. 35(4), pages 921-931, September.
    11. Merton, Robert C, 1981. "On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts," The Journal of Business, University of Chicago Press, vol. 54(3), pages 363-406, July.
    12. Lesage, James P., 1989. "Incorporating regional wage relations in local forecasting models with a Bayesian prior," International Journal of Forecasting, Elsevier, vol. 5(1), pages 37-47.
    13. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    14. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    15. David Ahlers & Josef Lakonishok, 1983. "A Study of Economists' Consensus Forecasts," Management Science, INFORMS, vol. 29(10), pages 1113-1125, October.
    16. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    17. Artis, M. J. & Zhang, W., 1990. "BVAR forecasts for the G-7," International Journal of Forecasting, Elsevier, vol. 6(3), pages 349-362, October.
    18. Robert B. Litterman & Thomas M. Supel, 1983. "Using vector autoregressions to measure the uncertainty in Minnesota's revenue forecasts," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 7(Spr).
    19. Hossain Amirizadeh & Richard M. Todd, 1984. "More growth ahead for Ninth District states," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    20. Pearce, Douglas K, 1984. "An Empirical Analysis of Expected Stock Price Movements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(3), pages 317-327, August.
    21. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    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. GRITLI, Mohamed Ilyes, 2018. "Quel avenir du dinar tunisien face à l'euro ? Prévision avec le modèle ARIMA [What future of the Tunisian dinar against the euro? Prediction with the ARIMA model]," MPRA Paper 83937, University Library of Munich, Germany.

    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. repec:lan:wpaper:413 is not listed on IDEAS
    2. repec:lan:wpaper:470 is not listed on IDEAS
    3. repec:lan:wpaper:425 is not listed on IDEAS
    4. repec:lan:wpaper:539557 is not listed on IDEAS
    5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    6. Peter C.B. Phillips, 1992. "Bayes Methods for Trending Multiple Time Series with an Empirical Application to the US Economy," Cowles Foundation Discussion Papers 1025, Cowles Foundation for Research in Economics, Yale University.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    8. Ford, Stephen A., 1986. "A Beginner'S Guide To Vector Autoregression," Staff Papers 13527, University of Minnesota, Department of Applied Economics.
    9. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    10. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    11. Kumar, V. & Leone, Robert P. & Gaskins, John N., 1995. "Aggregate and disaggregate sector forecasting using consumer confidence measures," International Journal of Forecasting, Elsevier, vol. 11(3), pages 361-377, September.
    12. Mark T. Leung & An-Sing Chen, 2005. "Performance evaluation of neural network architectures: the case of predicting foreign exchange correlations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 403-420.
    13. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
    14. Graham, John R. & Harvey, Campbell R., 1996. "Market timing ability and volatility implied in investment newsletters' asset allocation recommendations," Journal of Financial Economics, Elsevier, vol. 42(3), pages 397-421, November.
    15. Eicher, Theo S. & Kawai, Reina, 2023. "IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1615-1639.
    16. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.
    17. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    18. Gupta, Rangan & Kabundi, Alain, 2011. "A large factor model for forecasting macroeconomic variables in South Africa," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1076-1088, October.
    19. Mark T. Leung & An‐Sing Chen & Ruben Mancha, 2009. "Making trading decisions for financial‐engineered derivatives: a novel ensemble of neural networks using information content," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(4), pages 257-277, October.
    20. Pami Dua & Nishita Raje & Satyananda Sahoo, 2008. "Forecasting Interest Rates in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 2(1), pages 1-41, March.
    21. repec:zbw:bofrdp:1991_004 is not listed on IDEAS
    22. Tom Stark, 1998. "A Bayesian vector error corrections model of the U.S. economy," Working Papers 98-12, Federal Reserve Bank of Philadelphia.
    23. Victor Zarnowitz, 1991. "Has Macro-Forecasting Failed?," NBER Working Papers 3867, National Bureau of Economic Research, Inc.
    24. Fildes, Robert, 2006. "The forecasting journals and their contribution to forecasting research: Citation analysis and expert opinion," International Journal of Forecasting, Elsevier, vol. 22(3), pages 415-432.
    25. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.

    More about this item

    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:prs:ecoprv:ecop_0249-4744_1999_num_140_4_5982. 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: Equipe PERSEE (email available below). General contact details of provider: https://www.persee.fr/collection/ecop .

    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.