IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/121180.html

¿Son confiables las proyecciones del Relevamiento de Expectativas de Mercado del Banco Central de la República Argentina?
[Are the Projections of the Central Bank of the Argentina's Market Expectations Survey reliable?]

Author

Listed:
  • Frank, Luis

Abstract

The reliability of the REM as a predictor of key economic variables is evaluated 18 to 1 months before the publication of the final data. It is concluded that REM is not a reliable predictor beyond the 6-9 months prior to the month of publication, in general. This period, however, can be significantly shorter in financial variables. It would be advisable, however, to take these conclusions with caution given that the study covered only 3-8 years of REM's projections, depending on the variable, and one of those years is the one the COVID pandemic.

Suggested Citation

  • Frank, Luis, 2024. "¿Son confiables las proyecciones del Relevamiento de Expectativas de Mercado del Banco Central de la República Argentina? [Are the Projections of the Central Bank of the Argentina's Market Expectations Survey reliable?]," MPRA Paper 121180, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:121180
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/121180/1/MPRA_paper_121180.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stephen K. McNees, 1992. "How large are economic forecast errors?," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 25-42.
    Full references (including those not matched with items on IDEAS)

    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. Daniel M. Chin & John Geweke & Preston J. Miller, 2000. "Predicting turning points," Staff Report 267, Federal Reserve Bank of Minneapolis.
    2. Anderson, Richard G. & Hoffman, Dennis L. & Rasche, Robert H., 2002. "A vector error-correction forecasting model of the US economy," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 569-598, December.
    3. West, Carol Taylor, 2003. "Structural Regional Factors that Determine Absolute and Relative Accuracy of U.S. Regional Labor Market Forecasts," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 35(Supplemen), pages 1-15.
    4. Croushore, D., 2002. "Comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 483-489, December.
    5. Fullerton, Jr., Thomas M. & Taylor West, Carol A., 1998. "Regional Econometric Housing Start Forecast Accuracy in Florida," The Review of Regional Studies, Southern Regional Science Association, vol. 28(3), pages 15-42, Winter.
    6. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
    7. Fullerton, Thomas Jr. & Laaksonen, Mika M. & West, Carol T., 2001. "Regional multi-family housing start forecast accuracy," International Journal of Forecasting, Elsevier, vol. 17(2), pages 171-180.
    8. Joe Peek & Eric Rosengren & Geoffrey M. B. Tootell, 1998. "Does the Federal Reserve have an informational advantage? you can bank on it," Working Papers 98-2, Federal Reserve Bank of Boston.
    9. Paul Bennett & In Sun Geoum & David S. Laster, 1996. "Rational bias in macroeconomic forecasts," Research Paper 9617, Federal Reserve Bank of New York.
    10. William T. Gavin, 2003. "FOMC forecast: is all the information in the central tendency?," Review, Federal Reserve Bank of St. Louis, vol. 85(May), pages 27-46.
    11. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    12. Palle S. Andersen, 1997. "Forecast errors and financial developments," BIS Working Papers 51, Bank for International Settlements.
    13. Jones, Adam T. & Ogden, Richard E., 2017. "A day late and a dollar short: The effect of policy uncertainty on fed forecast errors," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 112-122.
    14. repec:rre:publsh:v:33:y:2003:i:1:p:85-103 is not listed on IDEAS
    15. Virén, Matti, 1998. "OECD Forecasts for the G7 Countries in 1969 - 1997," Discussion Papers 187, VATT Institute for Economic Research.
    16. João Valle e Azevedo, 2011. "Rational vs. professional forecasts," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    17. Oller, Lars-Erik & Barot, Bharat, 2000. "The accuracy of European growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 16(3), pages 293-315.
    18. O'Neill, Brian C. & Desai, Mausami, 2005. "Accuracy of past projections of US energy consumption," Energy Policy, Elsevier, vol. 33(8), pages 979-993, May.
    19. Dan Chin & John Geweke & Preston Miller, 2000. "Predicting Turning Points: Technical Paper 2000-3," Working Papers 13337, Congressional Budget Office.
    20. Joe Peek & Eric S. Rosengren & Geoffrey M. B. Tootell, 2001. "Synergies between Bank Supervision and Monetary Policy: Implications for the Design of Bank Regulatory Structure," NBER Chapters, in: Prudential Supervision: What Works and What Doesn't, pages 273-300, National Bureau of Economic Research, Inc.
    21. Jan Babecky & Jiri Podpiera, 2008. "Inflation Forecasts Errors in the Czech Republic: Evidence from a Panel of Institutions," Occasional Publications - Chapters in Edited Volumes, in: Katerina Smidkova (ed.), Evaluation of the Fulfilment of the CNB's Inflation Targets 1998-2007, chapter 6, pages 77-85, Czech National Bank, Research and Statistics Department.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

    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:121180. 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.