IDEAS home Printed from https://ideas.repec.org/p/fip/fedpwp/06-19.html
   My bibliography  Save this paper

An evaluation of inflation forecasts from surveys using real-time data

Author

Listed:
  • Dean Croushore

Abstract

This paper carries out the task of evaluating inflation forecasts from the Livingston Survey and the Survey of Professional Forecasters, using the real-time data set for macroeconomists as a source of real-time data. The author examines the magnitude and patterns of revisions to the inflation rate based on the output price index and describe what data to use as ?actuals? in evaluating forecasts. The author then runs tests on the forecasts from the surveys to see how good they are, using a variety of actuals. The author finds that much of the empirical work from 20 years ago was a misleading guide to the quality of forecasts because of unique events during the earlier sample period. Repeating that empirical work over a longer sample period shows no bias or other problems in the forecasts. The use of real-time data also matters for some key tests on some variables. If a forecaster had used the empirical results from the late 1970s and early 1980s to adjust survey forecasts of inflation, forecast errors would have increased substantially.

Suggested Citation

  • Dean Croushore, 2006. "An evaluation of inflation forecasts from surveys using real-time data," Working Papers 06-19, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:06-19
    as

    Download full text from publisher

    File URL: https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2006/wp06-19.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dean Croushore, 1998. "Evaluating inflation forecasts," Working Papers 98-14, Federal Reserve Bank of Philadelphia.
    2. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, March.
    3. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-853, October.
    4. Davies, Antony, 2006. "A framework for decomposing shocks and measuring volatilities derived from multi-dimensional panel data of survey forecasts," International Journal of Forecasting, Elsevier, vol. 22(2), pages 373-393.
    5. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    6. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    7. Hafer, R W & Hein, Scott E, 1985. "On the Accuracy of Time-Series, Interest Rate, and Survey Forecasts of Inflation," The Journal of Business, University of Chicago Press, vol. 58(4), pages 377-398, October.
    8. Vanderhoff, James, 1984. "A `rational' explanation for `irrational' forecasts of inflation," Journal of Monetary Economics, Elsevier, vol. 13(3), pages 387-392, May.
    9. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    10. Ball, Laurence & Croushore, Dean, 2003. "Expectations and the Effects of Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 473-484, August.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Fildes, Robert & Stekler, Herman, 2002. "Reply to the comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 503-505, December.
    13. 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.
    14. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-735, September.
    15. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219, National Bureau of Economic Research, Inc.
    16. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    17. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    18. Dean Croushore, 1997. "The Livingston Survey: still useful after all these years," Business Review, Federal Reserve Bank of Philadelphia, issue Mar, pages 15-27.
    19. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    20. Brown, Bryan W & Maital, Shlomo, 1981. "What Do Economists Know? An Empirical Study of Experts' Expectations," Econometrica, Econometric Society, vol. 49(2), pages 491-504, March.
    21. Martin Evans & Paul Wachtel, 1993. "Inflation regimes and the sources of inflation uncertainty," Proceedings, Federal Reserve Bank of Cleveland, pages 475-520.
    22. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    23. Pearce, Douglas K, 1979. "Comparing Survey and Rational Measures of Expected Inflation: Forecast Performance and Interest Rate Effects," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 11(4), pages 447-456, November.
    24. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    25. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    26. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    27. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, Oxford University Press, vol. 118(1), pages 269-298.
    28. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    29. Lloyd B. Thomas, 1999. "Survey Measures of Expected U.S. Inflation," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 125-144, Fall.
    30. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    31. Roy H. Webb, 1987. "The irrelevance of tests for bias in series of macroeconomic forecasts," Economic Review, Federal Reserve Bank of Richmond, vol. 73(Nov), pages 3-9.
    32. Zarnowitz, Victor, 1985. "Rational Expectations and Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 293-311, October.
    33. Wallis, Kenneth F, 1989. "Macroeconomic Forecasting: A Survey," Economic Journal, Royal Economic Society, vol. 99(394), pages 28-61, March.
    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. Clements, Michael P., 2006. "Internal consistency of survey respondentsíforecasts: Evidence based on the Survey of Professional Forecasters," Economic Research Papers 269742, University of Warwick - Department of Economics.
    2. Dean Croushore, 1998. "Evaluating inflation forecasts," Working Papers 98-14, Federal Reserve Bank of Philadelphia.
    3. Paul Hubert, 2010. "Monetary Policy, Imperfect Information and the Expectations Channel," Sciences Po publications info:hdl:2441/f4rshpf3v1u, Sciences Po.
    4. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    5. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
    6. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    7. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    8. Ball, Laurence & Croushore, Dean, 2003. "Expectations and the Effects of Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 473-484, August.
    9. 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.
    10. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
    11. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. 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.
    13. Carlos Capistrán & Gabriel López-Moctezuma, 2008. "Experts´ Macroeconomics Expectations: An Evaluation of Mexican Short-Run Forecasts," Working Papers 2008-11, Banco de México.
    14. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    15. Elliott, Graham & Komunjer, Ivana & Timmermann, Allan G, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
    16. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
    17. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    18. Hossein Hassani & Abdol S. Soofi & Anatoly Zhigljavsky, 2013. "Predicting inflation dynamics with singular spectrum analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 743-760, June.
    19. Paul Hubert, 2015. "Revisiting the Greenbook’s relative forecasting performance," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 151-179.
    20. Dean Croushore, 2012. "Forecast bias in two dimensions," Working Papers 12-9, Federal Reserve Bank of Philadelphia.
    21. Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.

    More about this item

    Keywords

    Inflation (Finance);

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fip:fedpwp:06-19. 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: . General contact details of provider: https://edirc.repec.org/data/frbphus.html .

    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: (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.