Skip to main content
Log in

Why Speed Doesn’t Kill: Learning to Believe in Disinflation

  • Published:
De Economist Aims and scope Submit manuscript

Summary

Central bankers generally prefer to reduce inflation gradually. We show that a central bank may try to convince the private sector of its commitment to price stability by choosing to reduce inflation quickly. We call this “teaching by doing”. We find that allowing for teaching by doing effects always speeds up the disinflation and leads to lower inflation persistence. So, we clarify why “speed” in the disinflation process does not necessarily “kill” in the sense of creating large output losses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ascari, G. and T. Ropele (2008), ‘Sacrifice Ratio or Welfare Gain Ratio? Disinflation in a DSGE Monetary Model’, Paper Presented at the 5th CDMA Conference, University of St. Andrews, 3–5 September.

  • Beck G., Wieland V. (2002) ‘Learning and Control in a Changing Economic Environment’. Journal of Economic Dynamics and Control 26: 1359–1377

    Article  Google Scholar 

  • Bomfimm A., Rudebusch G. (2000) ‘Opportunistic and Deliberate Disinflation Under Imperfect Credibility’. Journal of Money, Credit, and Banking 32: 707–721

    Article  Google Scholar 

  • Bomfim, A., R. Tetlow, P. von zur Muehlen and J. Williams (1997), ‘Expectations, Learning and the Costs of Disinflation: Experiments Using the FRB/US Model’, Board of Governors of the Federal Reserve System, Finance and Economics Discussion Series: No. 42, August.

  • Bullard J., Schaling E. (2001) ‘New Economy–New Policy Rules?’. Federal Reserve Bank of St. Louis Review 83(5): 57–66

    Google Scholar 

  • Bullard, J. and E. Schaling (2009), ‘Monetary Policy, Determinacy, and Learnability in the Open Economy’, Journal of Money, Credit and Banking, 41(8).

  • Chow G. (1997) ‘Dynamic Economics–Optimization by the Lagrange Method’. Oxford University Press, Oxford

    Google Scholar 

  • Cogley, T., R. Colacito and T. Sargent (2005), ‘Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas’, 2005 Meeting Papers, Society for Economic Dynamics.

  • Evans G., Honkapohja S. (2001) ‘Learning and Expectations in Macroeconomics’. Princeton University Press, Princeton, NJ

    Google Scholar 

  • Filardo, A. J. (1998), ‘New Evidence on the Output Cost of Fighting Inflation’, Economic Review Federal Reserve Bank of Kansas City, Third Quarter, pp. 31–61.

  • Gaspar V., Smets F., Vestin D. (2006) ‘Adaptive Learning, Persistence and Optimal Monetary Policy’. Journal of the European Economic Association 4(2–3): 376–385

    Article  Google Scholar 

  • Hoeberichts, M. and E. Schaling (2006), ‘Why Speed Doesn’t Kill: Learning to Believe in Disinflation’, Paper Presented at the South African Reserve Bank Conference ‘Macroeconomic Policy Challenges for South Africa’, 22–24 October.

  • Huh C.G., Lansing K.J. (2000) ‘Expectations, Credibility, and Disinflation in a Small Macroeconomic Model’. Journal of Economics and Business 52: 51–86

    Article  Google Scholar 

  • Kiley, M. (2008), ‘Monetary Policy Actions and Long-Run Inflation Expectations’, FEDS Working Paper, Board of Governors, No. 2008-03.

  • King, M. (1996), ‘How Should Central Banks Reduce Inflation?–Conceptual Issues’, Economic Review Federal Reserve Bank of Kansas City 81(4), Fourth Quarter, pp. 25–52. Can also be downloaded from www.kc.frb.org.

  • Milani, F. (2005), ‘Adaptive Learning and Inflation Persistence’, Working Paper, University of California, Irvine, November.

  • Molnár, K. and S. Santoro (2007), ‘Optimal Monetary Policy When Agents Are Learning’, NHH Working Paper, SAM 7, February.

  • Orphanides A., Williams J. (2003) ‘Imperfect Knowledge, Inflation Expectations and Monetary Policy’. In: Bernanke B., Woodford M. (eds) Inflation Targeting. University of Chicago Press, Chicago

    Google Scholar 

  • Roberts, J. (2007), ‘Learning, Sticky Inflation, and the Sacrifice Ratio’, Kiel Working Papers, No. 1365, June.

  • Sargent T. (1999) ‘The Conquest of American Inflation’. Princeton University Press, Princeton, NJ

    Google Scholar 

  • Schaling E. (2001) Programming versus Lagrange: Is there a Horse Race in Dynamic Optimization ?’. In: Klok H., van Schaik T., Smulders S. (eds) Economologues–Liber Amicorum for Theo van de Klundert. Tilburg University Press, The Netherlands, pp 334–349

    Google Scholar 

  • Schaling, E. (2004), ‘The Non-linear Phillips Curve and Inflation Forecast Targeting: Symmetric vs. Asymmetric Policy Rules’, Journal of Money, Credit, and Banking, Part 1 June, 36(3), pp. 361–386

    Google Scholar 

  • Svensson L. (1999) ‘Price Level Targeting vs. Inflation Targeting’. Journal of Money, Credit and Banking 31: 277–295

    Article  Google Scholar 

  • Tesfaselassie, M., E. Schaling, and S. Eijffinger (2006), ‘Learning About the Term Structure and Optimal Rules for Inflation Targeting’, CEPR Discussion Paper, no. 5896.

  • Vestin D. (2006) Vestin, ‘Price-level versus Inflation Targeting’. Journal of Monetary Economics 53: 1361–1376

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eric Schaling.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schaling, E., Hoeberichts, M. Why Speed Doesn’t Kill: Learning to Believe in Disinflation. De Economist 158, 23–42 (2010). https://doi.org/10.1007/s10645-010-9136-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10645-010-9136-3

Keywords

JEL Code(s)

Navigation