IDEAS home Printed from https://ideas.repec.org/p/boj/bojwps/wp16e18.html

TIPS: The Trend Inflation Projection System and Estimation Results

Author

Listed:
  • Koji Takahashi

    (Bank of Japan)

Abstract

In practice, trend inflation is often defined as a common factor extracted from observed inflation rates by removing cyclical effects from business cycles as well as other transitory distortions. Trend inflation can also be interpreted as the infinitely long-term inflation rate expected by private economic agents. If we assume that the central bank's inflation target policy is fully credible, trend inflation will converge to the target inflation rate in the long run. In the short run, however, trend inflation and the target rate can differ due to adaptive, or backward-looking, expectations and changes in the extent to which the inflation target is credible. Based on these considerations, this paper proposes a simple new methodology for projecting trend inflation, labelled the Trend Inflation Projection System (TIPS), where trend inflation is expressed as the weighted average of two components: an adaptive component, where a common trend is extracted from several core inflation measures, and a forward-looking component, namely the target inflation rate. In addition, the weights are allowed to vary over time to capture changes in the degree to which economic agents believe in the inflation target. The estimation results show that trend inflation in Japan increased dramatically in the first quarter of 2013, when the BOJ raised the target inflation rate, and has continued to rise gradually since then. However, since the second half of 2014, medium- to long-term inflation expectations have shifted downward, meaning that inflation expectations may be formed in a more adaptive manner than in the model. Furthermore, decomposition of the consumer price index (CPI, all items less fresh food) based on the estimated model indicates that although CPI inflation rose from the beginning of 2013 due to the increase in trend inflation, it has decreased again since the second half of 2014 due to transitory factors such as the decline in oil prices.

Suggested Citation

  • Koji Takahashi, 2016. "TIPS: The Trend Inflation Projection System and Estimation Results," Bank of Japan Working Paper Series 16-E-18, Bank of Japan.
    • Handle: RePEc:boj:bojwps:wp16e18
    as

    Download full text from publisher

    File URL: http://www.boj.or.jp/en/research/wps_rev/wps_2016/data/wp16e18.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    2. Yuto Iwasaki & Sohei Kaihatsu, 2016. "Measuring Underlying Inflation Using Dynamic Model Averaging," Bank of Japan Working Paper Series 16-E-8, Bank of Japan.
    3. Sohei Kaihatsu & Jouchi Nakajima, 2015. "Has Trend Inflation Shifted?: An Empirical Analysis with a Regime-Switching Model," Bank of Japan Working Paper Series 15-E-3, Bank of Japan.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. Mio, Hitoshi & Higo, Masahiro, 1999. "Underlying Inflation and the Distribution of Price Change: Evidence from the Japanese Trimmed-Mean CPI," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 17(1), pages 103-132, May.
    6. James C. Morley & Charles R. Nelson & Eric Zivot, 2003. "Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 235-243, May.
    7. Taisuke Nakata & Sebastian Schmidt & Timothy Hills, 2016. "The Risky Steady State and the Interest Rate Lower Bound," 2016 Meeting Papers 39, Society for Economic Dynamics.
    8. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    9. Yoshiyuki Nakazono, 2016. "Inflation expectations and monetary policy under disagreements," Bank of Japan Working Paper Series 16-E-1, Bank of Japan.
    10. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    11. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    12. Ichiro Fukunaga & Naoko Hara & Satoko Kojima & Yoichi Ueno & Shunichi Yoneyama, 2011. "The Quarterly Japanese Economic Model (Q-JEM): 2011 Version," Bank of Japan Working Paper Series 11-E-11, Bank of Japan.
    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. Tomiyuki Kitamura & Masaki Tanaka, 2019. "Firms' Inflation Expectations under Rational Inattention and Sticky Information: An Analysis with a Small-Scale Macroeconomic Model," Bank of Japan Working Paper Series 19-E-16, Bank of Japan.
    2. Juan Angel Garcia & Aubrey Poon, 2022. "Inflation trends in Asia: implications for central banks [Are Phillips curves useful for forecasting inflation?]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 671-700.
    3. Naohisa Hirakata & Kazutoshi Kan & Akihiro Kanafuji & Yosuke Kido & Yui Kishaba & Tomonori Murakoshi & Takeshi Shinohara, 2019. "The Quarterly Japanese Economic Model (Q-JEM): 2019 version," Bank of Japan Working Paper Series 19-E-7, Bank of Japan.

    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. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    2. Berger, Tino & Everaert, Gerdie & Vierke, Hauke, 2016. "Testing for time variation in an unobserved components model for the U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 179-208.
    3. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    4. Kuo‐Hsuan Chin, 2022. "Inflation persistence and monetary policy: DSGE‐VAR approach," Manchester School, University of Manchester, vol. 90(6), pages 715-729, December.
    5. Guido Ascari & Argia M. Sbordone, 2014. "The Macroeconomics of Trend Inflation," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 679-739, September.
    6. Giovanni Nicolò, 2025. "US Monetary Policy and Indeterminacy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(2), pages 195-213, March.
    7. Argia M. Sbordone, 2006. "U.S. Wage and Price Dynamics: A Limited-Information Approach," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
    8. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
    9. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    10. Alex, Dony, 2021. "Anchoring of inflation expectations in large emerging economies," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    11. James M. Nason & Gregor W. Smith, 2008. "The New Keynesian Phillips curve : lessons from single-equation econometric estimation," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 94(Fall), pages 361-395.
    12. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    13. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    14. Kevin Lansing, 2009. "Time Varying U.S. Inflation Dynamics and the New Keynesian Phillips Curve," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(2), pages 304-326, April.
    15. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    16. Ahmad, Yamin S. & Staveley-O’Carroll, Olena M., 2017. "Exploring international differences in inflation dynamics," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 115-135.
    17. Pooja Kapoor & Sujata Kar, 2023. "A review of inflation expectations and perceptions research in the past four decades: a bibliometric analysis," International Economics and Economic Policy, Springer, vol. 20(2), pages 279-302, May.
    18. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
    19. Kostas Mavromatis, 2020. "Finite Horizons and the Monetary/Fiscal Policy Mix," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 327-378, September.
    20. Blonigen, Bruce A. & Piger, Jeremy & Sly, Nicholas, 2014. "Comovement in GDP trends and cycles among trading partners," Journal of International Economics, Elsevier, vol. 94(2), pages 239-247.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:boj:bojwps:wp16e18. 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: Bank of Japan (email available below). General contact details of provider: https://edirc.repec.org/data/bojgvjp.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.