IDEAS home Printed from https://ideas.repec.org/p/zbw/bubdp1/201114.html

Evaluating macroeconomic risk forecasts

Author

Listed:
  • Knüppel, Malte
  • Schultefrankenfeld, Guido

Abstract

Macroeconomic risk assessments play an important role in the forecasts of many institutions. A risk forecast is related to the potential asymmetry of the forecast density. In this work, we investigate how the optimality of such risk forecasts can be tested. We find that the Pearson mode skewness outperforms the standard third-moment-based skewness as a measure of asymmetry. We consider problems of the tests likely to be encountered in practice and try to offer remedies where possible. In general, tests for macroeconomic risk forecast optimality tend to have at best moderate power given the empirically available small sample sizes.

Suggested Citation

  • Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "Evaluating macroeconomic risk forecasts," Discussion Paper Series 1: Economic Studies 2011,14, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdp1:201114
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/47886/1/663650798.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
    3. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    4. Pesaran, M. Hashem & Timmermann, Allan, 2009. "Testing Dependence Among Serially Correlated Multicategory Variables," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 325-337.
    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. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    2. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.

    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. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    2. Knüppel, Malte & Schultefrankenfeld, Guido, 2008. "How informative are macroeconomic risk forecasts? An examination of the Bank of England's inflation forecasts," Discussion Paper Series 1: Economic Studies 2008,14, Deutsche Bundesbank.
    3. Jose A. Lopez & Christian Walter, 1997. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Research Paper 9730, Federal Reserve Bank of New York.
    4. Timmermann, Allan & Patton, Andrew, 2003. "Properties of Optimal Forecasts," CEPR Discussion Papers 4037, Centre for Economic Policy Research.
    5. Dean Croushore, 1998. "Evaluating inflation forecasts," Working Papers 98-14, Federal Reserve Bank of Philadelphia.
    6. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, Centre for Economic Policy Research.
    7. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    8. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    9. Ellwanger, Reinhard & Snudden, Stephen, 2025. "Putting VAR forecasts of the real price of crude oil to the test," Finance Research Letters, Elsevier, vol. 77(C).
    10. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    11. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    12. Ana-Maria Fuertes & Elena Kalotychou, 2004. "Forecasting sovereign default using panel models: A comparative analysis," Computing in Economics and Finance 2004 228, Society for Computational Economics.
    13. Christiane Baumeister & Lutz Kilian, 2014. "Do oil price increases cause higher food prices? [Biofuels, binding constraints, and agricultural commodity price volatility]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 29(80), pages 691-747.
    14. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    15. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    16. Artur C. B. Da Silva Lopes, 1998. "On the 'restricted cointegration test' as a test of the rational expectations hypothesis," Applied Economics, Taylor & Francis Journals, vol. 30(2), pages 269-278, February.
    17. Stefania D'Amico, 2004. "Density Estimation and Combination under Model Ambiguity," Computing in Economics and Finance 2004 273, Society for Computational Economics.
    18. Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
    19. Pär Österholm, 2009. "Incorporating Judgement in Fan Charts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 387-415, June.
    20. Rogelio Ladrón de Guevara Cortés & Salvador Torra Porras & Enric Monte Moreno, 2021. "Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(2), pages 513-543.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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:zbw:bubdp1:201114. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/dbbgvde.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.