IDEAS home Printed from https://ideas.repec.org/a/fip/fedcec/00021.html
   My bibliography  Save this article

The Importance of Trend Inflation in the Search for Missing Disinflation

Author

Listed:
  • Todd E. Clark

Abstract

Some inflation-forecasting models based on the Phillips curve suggest that there should have been more disinflation since the Great Recession than has shown up in core PCE or core CPI data. One way researchers have found to make the disinflation disappear is to remove the long-term unemployed from the overall unemployment measure that is typically used in the models. This analysis shows that the disinflation arises in such models because of the way they account for the long-term trend in inflation. Under a different measurement of trend inflation, which historical forecast accuracy suggests should be preferable, the recent path of inflation can be reasonably well explained by an inflation-forecasting model that incorporates the overall unemployment rate.

Suggested Citation

  • Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.
    • Handle: RePEc:fip:fedcec:00021
    DOI: 10.26509/frbc-ec-201416
    as

    Download full text from publisher

    File URL: https://doi.org/10.26509/frbc-ec-201416
    File Function: Full Text
    Download Restriction: no
    File URL: https://libkey.io/10.26509/frbc-ec-201416?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Robert J. Gordon, 2013. "The Phillips Curve is Alive and Well: Inflation and the NAIRU During the Slow Recovery," NBER Working Papers 19390, National Bureau of Economic Research, Inc.
    2. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    3. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    2. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    3. Özer Karagedikli & C. John McDermott, 2018. "Inflation expectations and low inflation in New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 52(3), pages 277-288, September.
    4. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    5. Łukasz Rawdanowicz & Romain Bouis & Kei-Ichiro Inaba & Ane Kathrine Christensen, 2014. "Secular Stagnation: Evidence and Implications for Economic Policy," OECD Economics Department Working Papers 1169, OECD Publishing.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    2. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    3. Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What's Up with the Phillips Curve?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.
    4. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    5. Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
    6. Baxa Jaromír & Plašil Miroslav & Vašíček Bořek, 2017. "Inflation and the steeplechase between economic activity variables: evidence for G7 countries," The B.E. Journal of Macroeconomics, De Gruyter, vol. 17(1), pages 1-42, January.
    7. Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
    8. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    9. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    10. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    11. Kaihatsu, Sohei & Nakajima, Jouchi, 2018. "Has trend inflation shifted?: An empirical analysis with an equally-spaced regime-switching model," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 69-83.
    12. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    13. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    14. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    15. Jordan Roulleau-Pasdeloup, 2016. "The Government Spending Multiplier in a Deep Recession," Cahiers de Recherches Economiques du Département d'économie 16.22, Université de Lausanne, Faculté des HEC, Département d’économie.
    16. Kiley, Michael T., 2015. "An evaluation of the inflationary pressure associated with short- and long-term unemployment," Economics Letters, Elsevier, vol. 137(C), pages 5-9.
    17. Muellbauer, John, 2018. "The Future of Macroeconomics," INET Oxford Working Papers 2018-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    18. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    19. González-Astudillo, Manuel, 2019. "An output gap measure for the euro area: Exploiting country-level and cross-sectional data heterogeneity," European Economic Review, Elsevier, vol. 120(C).
    20. Angela Capolongo & Claudia Pacella, 2021. "Forecasting inflation in the euro area: countries matter!," Empirical Economics, Springer, vol. 61(5), pages 2477-2499, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedcec:00021. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: 4D Library (email available below). General contact details of provider: https://edirc.repec.org/data/frbclus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.