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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
    1. Michael Ehrmann & Sylvester Eijffinger & Marcel Fratzscher, 2012. "The Role of Central Bank Transparency for Guiding Private Sector Forecasts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 1018-1052, September.
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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.
    13. Crowe, Christopher & Meade, Ellen E., 2008. "Central bank independence and transparency: Evolution and effectiveness," European Journal of Political Economy, Elsevier, vol. 24(4), pages 763-777, December.
    14. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
    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.
    16. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    17. Pierre L. Siklos, 2010. "Sources of Disagreement in Inflation Forecasts: A Cross-Country Empirical Investigation," IMES Discussion Paper Series 10-E-26, Institute for Monetary and Economic Studies, Bank of Japan.
    18. Paul Hubert, 2015. "The Influence and Policy Signalling Role of FOMC Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(5), pages 655-680, October.
    19. Stephen Morris & Hyun Song Shin, 2008. "Coordinating Expectations in Monetary Policy," Chapters, in: Jean-Philippe Touffut (ed.), Central Banks as Economic Institutions, chapter 5, Edward Elgar Publishing.
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    21. Johnson, David R., 2002. "The effect of inflation targeting on the behavior of expected inflation: evidence from an 11 country panel," Journal of Monetary Economics, Elsevier, vol. 49(8), pages 1521-1538, November.
    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.
    23. Paul Hubert, 2015. "The Influence and Policy Signalling Role of FOMC Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(5), pages 655-680, October.
    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.
    28. Crowe, Christopher, 2010. "Testing the transparency benefits of inflation targeting: Evidence from private sector forecasts," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 226-232, March.
    29. Stephen Morris & Hyun Song Shin, 2002. "Social Value of Public Information," American Economic Review, American Economic Association, vol. 92(5), pages 1521-1534, December.
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    31. Carlos Capistr¡N & Manuel Ramos-Francia, 2010. "Does Inflation Targeting Affect the Dispersion of Inflation Expectations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 113-134, February.
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    33. Mr. Christopher W. Crowe, 2010. "Consensus Forecasts and Inefficient Information Aggregation," IMF Working Papers 2010/178, International Monetary Fund.
    34. Makoto Minegishi & Boris Cournède, 2009. "The Role of Transparency in the Conduct of Monetary Policy," OECD Economics Department Working Papers 724, OECD Publishing.
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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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