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Differential Interpretation Of Information In Inflation Forecasts

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  • Eugene Kandel
  • Ben-Zion Zilberfarb

Abstract

We test the hypothesis associated with a standard assumption in the theoretical literature on learning: that economic agents interpret information identically. We use a data set based on a survey of Israeli business executives forecasting future inflation. One of the main advantages of using this data is that a major change in the inflation regime in 1985 can be treated as a natural experiment in new beliefs formation. We develop a methodology for testing this hypothesis and find evidence that is inconsistent with the identical-interpretation hypothesis, but is consistent with the proposed alternative. © 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Suggested Citation

  • Eugene Kandel & Ben-Zion Zilberfarb, 1999. "Differential Interpretation Of Information In Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 217-226, May.
  • Handle: RePEc:tpr:restat:v:81:y:1999:i:2:p:217-226
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    Citations

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    Cited by:

    1. Ottaviani, Marco & Sorensen, Peter Norman, 2006. "The strategy of professional forecasting," Journal of Financial Economics, Elsevier, vol. 81(2), pages 441-466, August.
    2. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
    3. Winkler, Bernhard, 2000. "Which kind of transparency? On the need for clarity in monetary policy-making," Working Paper Series 0026, European Central Bank.
    4. Xuguang Sheng & Maya Thevenot, 2013. "Differential Interpretation of Public Information: Estimation and Inference," Working Papers 2013-03, American University, Department of Economics.
    5. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2733-2746, October.
    6. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    7. Sheng, Xuguang (Simon) & Thevenot, Maya, 2015. "Quantifying differential interpretation of public information using financial analysts’ earnings forecasts," International Journal of Forecasting, Elsevier, vol. 31(2), pages 515-530.
    8. Jordi Pons-Novell, 2003. "Strategic bias, herding behaviour and economic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 67-77.
    9. Goldstein, Nathan & Zilberfarb, Ben-Zion, 2017. "Rationality and seasonality: Evidence from inflation forecasts," Economics Letters, Elsevier, vol. 150(C), pages 86-90.
    10. Granato, Jim & Guse, Eran A. & Wong, M. C. Sunny, 2008. "Learning From The Expectations Of Others," Macroeconomic Dynamics, Cambridge University Press, vol. 12(03), pages 345-377, June.
    11. Massa, Massimo & Simonov, Andrei, 2005. "Is learning a dimension of risk?," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2605-2632, October.
    12. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    13. Naohito Abe & Yuko Ueno, 2016. "The Mechanism of Inflation Expectation Formation among Consumers," UTokyo Price Project Working Paper Series 064, University of Tokyo, Graduate School of Economics.
    14. Hammad A. Siddiqi, 2006. "Is it Social Influence on Beliefs Under Ambiguity? A Possible Explanation for Volatility Clustering," Microeconomics Working Papers 22279, East Asian Bureau of Economic Research.
    15. 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.
    16. Abe, Naohito & Ueno, Yuko, 2016. "The Mechanism of Inflation Expectation Formation among Consumers," RCESR Discussion Paper Series DP16-1, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    17. Marinovic, Iván & Ottaviani, Marco & Sorensen, Peter, 2013. "Forecasters’ Objectives and Strategies," Handbook of Economic Forecasting, Elsevier.
    18. Siddiqi, Hammad, 2006. "Belief merging and revision under social influence: An explanation for the volatility clustering puzzle," MPRA Paper 657, University Library of Munich, Germany.

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