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Modeling Inflation After the Crisis

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  • James H. Stock
  • Mark W. Watson

Abstract

In the United States, the rate of price inflation falls in recessions. Turning this observation into a useful inflation forecasting equation is difficult because of multiple sources of time variation in the inflation process, including changes in Fed policy and credibility. We propose a tightly parameterized model in which the deviation of inflation from a stochastic trend (which we interpret as long-term expected inflation) reacts stably to a new gap measure, which we call the unemployment recession gap. The short-term response of inflation to an increase in this gap is stable, but the long-term response depends on the resilience, or anchoring, of trend inflation. Dynamic simulations (given the path of unemployment) match the paths of inflation during post-1960 downturns, including the current one.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16488.

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Date of creation: Oct 2010
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Publication status: published as James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
Handle: RePEc:nbr:nberwo:16488

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Cited by:
  1. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  2. Rochelle M. Edge & Refet S. Gurkaynak, 2011. "How useful are estimated DSGE model forecasts?," Finance and Economics Discussion Series 2011-11, Board of Governors of the Federal Reserve System (U.S.).
  3. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank, Research Department.
  4. Joseph S. Vavra, 2014. "Time-Varying Phillips Curves," NBER Working Papers 19790, National Bureau of Economic Research, Inc.
  5. 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.
  6. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
  7. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
  8. Hugo Gerard, 2012. "Co-movement in Inflation," RBA Research Discussion Papers rdp2012-01, Reserve Bank of Australia.
  9. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank, Research Centre.
  10. Steffen Henzel & Elisabeth Wieland, 2013. "Synchronization and Changes in International Inflation Uncertainty," CESifo Working Paper Series 4194, CESifo Group Munich.
  11. Troy Matheson & Emil Stavrev, 2013. "The Great Recession and the Inflation Puzzle," IMF Working Papers 13/124, International Monetary Fund.
  12. Gumbau-Brisa, Fabia & Olivei, Giovanni P., 2013. "An evaluation of the Federal Reserve estimates of the natural rate of unemployment in real time," Working Papers 13-24, Federal Reserve Bank of Boston.
  13. Muhammad Azmat Hayat & Etienne Farvaque, 2012. "Public Attitudes towards Central Bank Independence: Lessons From the Foundation of the ECB," Working Papers hal-00988169, HAL.
  14. Eva M. Köberl, 2011. "Kapazitätsauslastung, Produktionshemmnisse und Preisanpassungen unter dem Mikroskop," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 5(4), pages 43-54, December.
  15. Evan F. Koenig & Tyler Atkinson, 2012. "Inflation, slack, and Fed credibility," Staff Papers, Federal Reserve Bank of Dallas, issue Jan.

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