IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_3671.html
   My bibliography  Save this paper

How Informative are the Subjective Density Forecasts of Macroeconomists?

Author

Listed:
  • Geoff Kenny
  • Thomas Kostka
  • Federico Masera

Abstract

In this paper, we propose a framework to evaluate the information content of subjective expert density forecasts using micro data from the ECB’s Survey of Professional Forecasters (SPF). A key aspect of our analysis is the use of scoring functions which evaluate the entire predictive densities, including an evaluation of the impact of density features such as their location, spread, skew and tail risk on density forecast performance. Overall, we find considerable heterogeneity in the performance of the surveyed densities at the individual level. Relative to a set of crude benchmark alternatives, this performance is somewhat better for GDP growth than for inflation, although in the former case it diminishes substantially with the forecast horizon. In addition, relative to the proposed benchmarks, we report evidence of some improvement in the performance of expert densities during the recent period of macroeconomic volatility. However, our analysis also reveals clear evidence of overconfidence or neglected risks in the expert probability assessments, as reflected also in frequent occurrences of events which are assigned a zero probability. Moreover, higher moment features of the expert densities, such as their skew or the degree of probability mass in their tails, are shown not to contribute significantly to improvements in individual density forecast performance.

Suggested Citation

  • Geoff Kenny & Thomas Kostka & Federico Masera, 2011. "How Informative are the Subjective Density Forecasts of Macroeconomists?," CESifo Working Paper Series 3671, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_3671
    as

    Download full text from publisher

    File URL: http://www.cesifo-group.de/DocDL/cesifo1_wp3671.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Victor Zarnowitz & Louis A. Lambros, 1983. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.
    2. Lahiri, Kajal & Teigland, Christie & Zaporowski, Mark, 1988. "Interest Rates and the Subjective Probability Distribution of Inflation Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 20(2), pages 233-248, May.
    3. Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
    4. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    5. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
    6. repec:nsr:niesrd:320 is not listed on IDEAS
    7. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    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. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    2. Oinonen, Sami & Paloviita, Maritta, 2014. "Analysis of aggregated inflation expectations based on the ECB SPF survey," Research Discussion Papers 29/2014, Bank of Finland.
    3. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    4. Maritta Paloviita and Matti Viren, 2012. "Are individual survey expectations internally consistent?," Discussion Papers 77, Aboa Centre for Economics.
    5. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    6. Łyziak, Tomasz & Paloviita, Maritta, 2017. "Formation of inflation expectations in turbulent times : Can ECB manage inflation expectations of professional forecasters?," Research Discussion Papers 13/2017, Bank of Finland.
    7. López Pérez, Víctor, 2015. "Does uncertainty affect participation in the European Central Bank's Survey of Professional Forecasters?," Working Paper Series 1807, European Central Bank.
    8. Sami Oinonen & Maritta Paloviita, 2017. "How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), pages 139-163.
    9. Rich, Robert W. & Tracy, Joseph, 2017. "The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis," Staff Reports 808, Federal Reserve Bank of New York.
    10. Tomasz Łyziak & Maritta Paloviita, 2017. "Formation of inflation expectations in turbulent times. Recent evidence from the European Survey of Professional Forecasters," NBP Working Papers 261, Narodowy Bank Polski, Economic Research Department.
    11. 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.
    12. Maritta Paloviita & Matti Viren, 2014. "Inflation and output growth uncertainty in individual survey expectations," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, pages 69-81.
    13. repec:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-017-1228-3 is not listed on IDEAS
    14. Paloviita, Maritta & Virén, Matti, 2014. "Analysis of forecast errors in micro-level survey data," Research Discussion Papers 8/2014, Bank of Finland.

    More about this item

    Keywords

    density forecasts; forecast evaluation; real-time data; Survey of Professional Forecasters;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:ces:ceswps:_3671. 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: (Klaus Wohlrabe). General contact details of provider: http://edirc.repec.org/data/cesifde.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 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.

    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.