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Central Bank Transparency and the consensus forecast: What does The Economist poll of forecasters tell us?

Author

Listed:
  • Emna Trabelsi

    (ISG - Institut Supérieur de Gestion de Tunis [Tunis] - Université de Tunis)

Abstract

We are interested, in this paper, in studying the effects that central banks exert on private sector forecasts by means of their transparency and communication measures. We analyze the impact of central bank transparency on the accuracy of the consensus forecasts (usually calculated as the mean or the median of the forecasts from a panel of individual forecasters) for a series of macroeconomic variables: inflation, Real output growth and the current account as a share of GDP for 7 advanced economies. Interestingly, while it is found of significance of central bank transparency and communication measures on forecasts themselves, there appear some limits of the same measures when we study their impact on forecast errors. Our findings, indeed, suggest that deviations of the economic forecast data from the realized ones (RGDP and the current account as a share of GDP) are a bit affected by the central bank transparency measures considered in the paper. Inflation forecast errors, especially, are not affected at all by those measures. A possible explanation (among others) could be attributed to the inefficiency of the mean forecasts. Inefficiency of the consensus forecasts is not a new issue from a theoretical point of view, but its empirical relevance is for the first time (to our knowledge) questioned on data extracted from the Economist poll of forecasters. More particularly, our paper extracts practical implications over the effectiveness of transparent announcements in forecast formation process. We rely on two noisy information models, though having different mechanisms (Kim et al, 2001; Morris and Shin, 2002) both of which are consistent with overweighting issue to explain the inefficiency of the consensus forecast.

Suggested Citation

  • Emna Trabelsi, 2016. "Central Bank Transparency and the consensus forecast: What does The Economist poll of forecasters tell us?," Post-Print hal-01121434, HAL.
  • Handle: RePEc:hal:journl:hal-01121434
    DOI: 10.1016/j.ribaf.2016.04.004
    Note: View the original document on HAL open archive server: https://hal.science/hal-01121434v3
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    References listed on IDEAS

    as
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    7. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
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    9. M. Middeldorp, 2011. "Central Bank Transparency, the Accuracy of Professional Forecasts, and Interest Rate Volatility," Working Papers 11-12, Utrecht School of Economics.
    10. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    11. Refet S Gürkaynak & Andrew Levin & Eric Swanson, 2010. "Does Inflation Targeting Anchor Long-Run Inflation Expectations? Evidence from the U.S., UK, and Sweden," Journal of the European Economic Association, MIT Press, vol. 8(6), pages 1208-1242, December.
    12. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
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    15. Pierre L. Siklos, 2003. "Assessing the Impact of Changes in Transparency and Accountability at the Bank of Canada," Canadian Public Policy, University of Toronto Press, vol. 29(3), pages 279-299, September.
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    22. Oliver Kim & Steve C. Lim & Kenneth W. Shaw, 2001. "The Inefficiency of the Mean Analyst Forecast as a Summary Forecast of Earnings," Journal of Accounting Research, Wiley Blackwell, vol. 39(2), pages 329-335, September.
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    24. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    25. Miah, Fazlul & Rahman, M. Saifur & Albinali, Khalid, 2016. "Rationality of survey based inflation expectations: A study of 18 emerging economies’ inflation forecasts," Research in International Business and Finance, Elsevier, vol. 36(C), pages 158-166.
    26. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    27. Petra M. Geraats, 2002. "Central Bank Transparency," Economic Journal, Royal Economic Society, vol. 112(483), pages 532-565, November.
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    Cited by:

    1. Zavyalova, Natalya, 2017. "BRICS money talks: Comparative socio-cultural communicative taxonomy of the New Development Bank," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 248-266.
    2. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
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    4. Barrera, Carlos, 2022. "Characterizing the Anchoring Effects of Official Forecasts on Private Expectations," MPRA Paper 114258, University Library of Munich, Germany.

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    More about this item

    Keywords

    Economist poll of forecasters; Inefficiency; Consensus forecasts; Communication; Transparency;
    All these keywords.

    JEL classification:

    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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