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Information rigidities: Comparing average and individual forecasts for a large international panel

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  • Dovern, Jonas
  • Fritsche, Ulrich
  • Loungani, Prakash
  • Tamirisa, Natalia

Abstract

We study forecasts of real GDP growth using a large panel of individual forecasts from 36 advanced and emerging economies over the period 1989–2010. We show that the degree of information rigidity in average forecasts is substantially higher than that in individual forecasts. Individual-level forecasts are updated quite frequently, a behavior which is more in line “noisy” information models (Woodford, 2002; Sims, 2003) than with the assumptions of the sticky information model (Mankiw & Reis, 2002). While there are cross-country variations in information rigidity, there are no systematic differences between advanced and emerging economies.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:intfor:v:31:y:2015:i:1:p:144-154 DOI: 10.1016/j.ijforecast.2014.06.002
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    Cited by:

    1. Trabelsi, Emna, 2016. "Central bank transparency and the consensus forecast: What does The Economist poll of forecasters tell us?," Research in International Business and Finance, Elsevier, pages 338-359.
    2. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, Research Program on Forecasting.
    3. Jonas Dovern & Matthias Hartmann, 2017. "Forecast performance, disagreement, and heterogeneous signal-to-noise ratios," Empirical Economics, Springer, pages 63-77.
    4. Melitz, Jacques, 2017. "Some doubts about the economic analysis of the flow of silver to China in 1550-1820," CEPR Discussion Papers 12427, C.E.P.R. Discussion Papers.
    5. Dovern, Jonas, 2014. "A Multivariate Analysis of Forecast Disagreement: Confronting Models of Disagreement with SPF Data," Working Papers 0571, University of Heidelberg, Department of Economics.
    6. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey among professional forecasters," Working Papers 2017-002, The George Washington University, Department of Economics, Research Program on Forecasting.
    7. repec:spr:portec:v:16:y:2017:i:3:d:10.1007_s10258-017-0129-x is not listed on IDEAS
    8. Niepmann, Friederike & Schmidt-Eisenlohr, Tim, 2017. "International trade, risk and the role of banks," Journal of International Economics, Elsevier, vol. 107(C), pages 111-126.
    9. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, pages 571-583.
    10. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, Department of Economics, Research Program on Forecasting.
    11. F. Bec & R. Boucekkine & C. Jardet, 2017. "Why are inflation forecasts sticky? Theory and application to France and Germany," Working papers 650, Banque de France.
    12. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, pages 154-167.
    13. Joao Tovar Jalles, 2015. "How Quickly is News Incorporated in Fiscal Forecasts?," Economics Bulletin, AccessEcon, vol. 35(4), pages 2802-2812.
    14. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, pages 102-120.
    15. Kenny, Geoff & Dovern, Jonas, 2017. "The long-term distribution of expected inflation in the euro area: what has changed since the great recession?," Working Paper Series 1999, European Central Bank.
    16. Ulrich Fritsche & Christian Pierdzioch, 2017. "Animal spirits, the stock market, and the unemployment rate: Some evidence for German data," Economics Bulletin, AccessEcon, pages 204-213.
    17. repec:eee:intfor:v:33:y:2017:i:4:p:760-769 is not listed on IDEAS
    18. Jalles, João Tovar & Karibzhanov, Iskander & Loungani, Prakash, 2015. "Cross-country evidence on the quality of private sector fiscal forecasts," Journal of Macroeconomics, Elsevier, pages 186-201.
    19. Rülke, Jan-Christoph & Silgoner, Maria & Wörz, Julia, 2016. "Herding behavior of business cycle forecasters," International Journal of Forecasting, Elsevier, pages 23-33.
    20. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, pages 760-769.

    More about this item

    Keywords

    Rational inattention; Aggregation bias; Growth forecasts; Information rigidity; Forecast behavior;

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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