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Disagreement à la Taylor: Evidence from Survey Microdata

Author Info

Listed author(s):
  • Lena Draeger
  • Michael J. Lamla

Abstract

There is a growing interest in studying the disagreement of economic agents. Most studies, however, focus on the disagreement regarding one specific variable, hereby neglecting that disagreement may be comoving with disagreement on other variables. In this paper we explore to which extent disagreement regarding the interest rate is driven by disagreement on inflation and on unemployment. This relationship can be motivated by the existence of the Taylor rule. Using micro survey data for both professional forecasters and consumers, we provide evidence that disagreement on the future interest rate is mainly driven by disagreement on inflation. Exploring further determinants, we confirm that central bank transparency as well as news on money and credit conditions significantly influence disagreement.

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File URL: http://dx.doi.org/10.3929/ethz-a-010427317
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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 15-380.

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Length: 24 pages
Date of creation: Apr 2015
Handle: RePEc:kof:wpskof:15-380
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Keywords: Disagreement; Taylor rule; Interest rate expectations; Inflation expectations; Unemployment expectations; Microdata;

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Find related papers by JEL classification:
  • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
  • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
  • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
  • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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  1. Frieder Mokinski & Xuguang (Simon) Sheng & Jingyun Yang, 2015. "Measuring Disagreement in Qualitative Expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(5), pages 405-426, 08.
  2. Daron Acemoglu & Victor Chernozhukov & Muhamet Yildiz, 2006. "Learning and Disagreement in an Uncertain World," NBER Working Papers 12648, National Bureau of Economic Research, Inc.
  3. 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.
  4. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters,in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270 National Bureau of Economic Research, Inc.
  5. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
  6. Dräger, Lena & Lamla, Michael J., 2012. "Updating inflation expectations: Evidence from micro-data," Economics Letters, Elsevier, vol. 117(3), pages 807-810.
  7. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
  8. Michael Woodford, 2001. "Imperfect Common Knowledge and the Effects of Monetary Policy," NBER Working Papers 8673, National Bureau of Economic Research, Inc.
  9. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
  10. 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.
  11. Carvalho, Carlos & Nechio, Fernanda, 2014. "Do people understand monetary policy?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 108-123.
  12. Christopher A Sims, 2009. "Inflation expectations, uncertainty and monetary policy," BIS Working Papers 275, Bank for International Settlements.
  13. Thomas Maag, 2009. "On the accuracy of the probability method for quantifying beliefs about inflation," KOF Working papers 09-230, KOF Swiss Economic Institute, ETH Zurich.
  14. Michael J. Lamla & Thomas Maag, 2012. "The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1325-1350, October.
  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. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
  17. Badarinza, Cristian & Gross, Marco, 2012. "Information flows and disagreement," Working Paper Series 1475, European Central Bank.
  18. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
  19. 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.
  20. Badarinza, Cristian & Gross, Marco, 2009. "Inflation perceptions and expectations in the euro area: the role of news," Working Paper Series 1088, European Central Bank.
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Cited by:

  1. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.

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