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Heterogeneous expectations, learning and European inflation dynamics

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  • Weber, Anke

Abstract

This paper is the first attempt to investigate the performance of different learning rules in fitting survey data of household and expert inflation expectations in five core European economies (France, Germany, Italy, Netherlands and Spain). Overall it is found that constant gain learning performs well in out-of-sample forecasting. It is also shown that households in high inflation countries are using higher best fitting constant gain parameters than those in low inflation countries. They are hence able to pick up structural changes faster. Professional forecasters update their information sets more frequently than households. Furthermore, household expectations in the Euro Area have not converged to the inflation goal of the ECB, which is to keep inflation below to but close to 2% in the medium run. This contrasts the findings for professional experts, which seem to be more inclined to incorporate the implications of monetary union for the convergence in inflation rates into their expectations. --

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Bibliographic Info

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2007,16.

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Date of creation: 2007
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Handle: RePEc:zbw:bubdp1:6137

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Keywords: Monetary policy; heterogeneous expectations; adaptive learning; survey expectations;

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References

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  1. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre.
  2. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
  3. Marcet, Albert & Nicolini, Juan Pablo, 1998. "Recurrent Hyperinflations and Learning," CEPR Discussion Papers 1875, C.E.P.R. Discussion Papers.
  4. N. Gregory Mankiw & Ricardo Reis, 2006. "Sticky Information in General Equilibrium," NBER Working Papers 12605, National Bureau of Economic Research, Inc.
  5. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  6. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
  7. Holden, K & Peel, D A, 1990. "On Testing for Unbiasedness and Efficiency of Forecasts," The Manchester School of Economic & Social Studies, University of Manchester, vol. 58(2), pages 120-27, June.
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Cited by:
  1. Gilberto Tadeu Lima & Mark Setterfield, Jaylson Jair da Silveira, 2013. "Inflation Targeting and Macroeconomic Stability with Heterogeneous Inflation Expectations," Working Papers, Department of Economics 2013_11, University of São Paulo (FEA-USP).
  2. Steffen Henzel, 2008. "Learning Trend Inflation – Can Signal Extraction Explain Survey Forecasts?," Ifo Working Paper Series Ifo Working Paper No. 55, Ifo Institute for Economic Research at the University of Munich.

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