IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Evaluating FOMC forecast ranges: an interval data approach

Author Info

Listed author(s):
  • Henning Fischer

    ()

    (University of Giessen)

  • Marta García-Bárzana

    ()

    (University of Oviedo)

  • Peter Tillmann

    ()

    (University of Giessen)

  • Peter Winker

    ()

    (University of Giessen)

Abstract

The Federal Open Market Committee (FOMC) of the U.S. Federal Reserve publishes the range of members’ forecasts for key macroeconomic variables, but not the distribution of forecasts within this range. To evaluate these projections, previous papers compare the midpoint of the ranges with the realized outcome. This paper proposes a new approach to forecast evaluation that takes account of the interval nature of projections. It is shown that using the conventional Mincer-Zarnowitz approach to evaluate FOMC forecasts misses important information contained in the width of the forecast interval. This additional information plays a minor role at short forecast horizons but turns out to be of crucial importance for inflation and unemployment forecasts 18 months into the future. At long horizons the variation of members’ projections contains information which is more relevant for explaining future inflation than information embodied in the midpoint.

Download Info

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://www.uni-marburg.de/fb02/makro/forschung/magkspapers/13-2012_tillmann.pdf
File Function: First version, 2012
Download Restriction: no

Paper provided by Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung) in its series MAGKS Papers on Economics with number 201213.

as
in new window

Length: 16 pages
Date of creation: 2012
Publication status: Forthcoming in
Handle: RePEc:mar:magkse:201213
Contact details of provider: Postal:
Universitätsstraße 25, 35037 Marburg

Phone: 06421/28-1722
Fax: 06421/28-4858
Web page: http://www.uni-marburg.de/fb02/
Email:


More information through EDIRC

Keywords: Forecast evaluation; interval data; Federal Reserve; monetary policy;

Other versions of this item:

Find related papers by JEL classification:
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
  • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
  • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

This paper has been announced in the following NEP Reports:

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. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
  2. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, 03.
  3. Sinclair, Tara M. & Joutz, Fred & Stekler, H.O., 2010. "Can the Fed predict the state of the economy?," Economics Letters, Elsevier, vol. 108(1), pages 28-32, July.
  4. David Romer, 2010. "A New Data Set on Monetary Policy: The Economic Forecasts of Individual Members of the FOMC," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(5), pages 951-957, 08.
  5. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, 03.
  6. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, Elsevier.
  7. Blanco-Fernández, Angela & Corral, Norberto & González-Rodríguez, Gil, 2011. "Estimation of a flexible simple linear model for interval data based on set arithmetic," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2568-2578, September.
  8. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
  9. Glenn D. Rudebusch, 2008. "Publishing FOMC economic forecasts," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue jan18.
  10. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
  11. Capistrán, Carlos, 2008. "Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1415-1427, November.
  12. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
  13. Antonello D'Agostino & Karl Whelan, 2008. "Federal Reserve Information During the Great Moderation," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 609-620, 04-05.
  14. William T. Gavin, 2003. "FOMC forecast: is all the information in the central tendency?," Review, Federal Reserve Bank of St. Louis, issue May, pages 27-46.
  15. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
  16. Tillmann, Peter, 2011. "Strategic forecasting on the FOMC," European Journal of Political Economy, Elsevier, vol. 27(3), pages 547-553, September.
  17. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
  18. Gamber, Edward N. & Smith, Julie K., 2009. "Are the Fed's inflation forecasts still superior to the private sector's?," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 240-251, June.
  19. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  20. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
  21. William T. Gavin & Geetanjali Pande, 2008. "FOMC consensus forecasts," Review, Federal Reserve Bank of St. Louis, issue May, pages 149-164.
  22. Michael W. McCracken, 2010. "Using FOMC forecasts to forecast the economy," Economic Synopses, Federal Reserve Bank of St. Louis.
  23. David L. Reifschneider & Peter Tulip, 2007. "Gauging the uncertainty of the economic outlook from historical forecasting errors," Finance and Economics Discussion Series 2007-60, Board of Governors of the Federal Reserve System (U.S.).
  24. Chanont Banternghansa & Michael W. McCracken, 2009. "Forecast disagreement among FOMC members," Working Papers 2009-059, Federal Reserve Bank of St. Louis.
Full references (including those not matched with items on IDEAS)

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

as
in new window


Cited by:

  1. repec:ntu:ntugeo:vol2-iss1-14-054 is not listed on IDEAS
  2. Angela Blanco-Fernández & Peter Winker, 2016. "Data generation processes and statistical management of interval data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 475-494, October.
  3. Bratu, Mihaela, 2013. "The Assessment And Improvement Of The Accuracy For The Forecast Intervals," Working Papers of Macroeconomic Modelling Seminar 132602, Institute for Economic Forecasting.
  4. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, 03.
  5. Mihaela Simionescu, 2014. "M1 and M2 indicators- new proposed measures for the global accuracy of forecast intervals," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 54-59, June.
  6. Gamber, Edward N. & Liebner, Jeffrey P. & Smith, Julie K., 2015. "The distribution of inflation forecast errors," Journal of Policy Modeling, Elsevier, vol. 37(1), pages 47-64.

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

Access and download statistics

When requesting a correction, please mention this item's handle: RePEc:mar:magkse:201213. 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: (Bernd Hayo)

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.