IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v57y2019i6d10.1007_s00181-018-1417-8.html
   My bibliography  Save this article

On inflation expectations in the NKPC model

Author

Listed:
  • Philip Hans Franses

    (Erasmus School of Economics)

Abstract

To create an estimable version for annual data of the hybrid new Keynesian Phillips curve, one needs an expression for the expectation of next year’s inflation. The rational expectations literature assumes that this expectation is equal to the realization in the next year and an associated forecast error. This paper argues that this assumption goes against the Wold decomposition theorem, and that it introduces correlation between the error and a regressor. A more appropriate approach resorts to a MIDAS type of model, where forecast updates for next year are created when for example monthly inflation rates come in. An illustration to annual USA inflation, 1956–2016, shows the merits of this MIDAS approach.

Suggested Citation

  • Philip Hans Franses, 2019. "On inflation expectations in the NKPC model," Empirical Economics, Springer, vol. 57(6), pages 1853-1864, December.
    • Handle: RePEc:spr:empeco:v:57:y:2019:i:6:d:10.1007_s00181-018-1417-8
    DOI: 10.1007/s00181-018-1417-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-018-1417-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-018-1417-8?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bart Frijns & Dimitris Margaritis, 2008. "Forecasting daily volatility with intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 14(6), pages 523-540.
    2. Galí, Jordi & Gertler, Mark, 1999. "Inflation Dynamics: A Structural Economic Analysis," CEPR Discussion Papers 2246, C.E.P.R. Discussion Papers.
    3. Jordi Galí, 2008. "Introduction to Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework," Introductory Chapters, in: Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework, Princeton University Press.
    4. Bruce Preston, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    5. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    6. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    7. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    8. Gali, Jordi & Gertler, Mark & David Lopez-Salido, J., 2005. "Robustness of the estimates of the hybrid New Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1107-1118, September.
    9. Lanne, Markku & Luoto, Jani, 2013. "Autoregression-based estimation of the new Keynesian Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 561-570.
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    11. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    12. Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
    13. JÖrg Breitung & Christoph Roling, 2015. "Forecasting Inflation Rates Using Daily Data: A Nonparametric MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 588-603, November.
    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. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. Choi, Yoonseok, 2021. "Inflation dynamics, the role of inflation at different horizons and inflation uncertainty," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 649-662.

    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. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. Yasufumi Gemma & Takushi Kurozumi & Mototsugu Shintani, 2023. "Trend Inflation and Evolving Inflation Dynamics:A Bayesian GMM Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 506-520, December.
    3. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    4. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    5. Oinonen, Sami & Vilmi, Lauri, 2021. "Analysing euro area inflation outlook with the Phillips curve," BoF Economics Review 5/2021, Bank of Finland.
    6. Toshihiro Okada, 2017. "Time to Innovate and Aggregate Fluctuations: a New Keynesian Model with Endogenous Technology," Discussion Paper Series 154, School of Economics, Kwansei Gakuin University, revised Dec 2018.
    7. Rareș-Petru MIHALACHE & Dumitru Alexandru BODISLAV, 2019. "The new Keynesian Phillips Curve. Implications. Strengths and weaknesses," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(621), W), pages 85-92, Winter.
    8. Medel, Carlos, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," MPRA Paper 62609, University Library of Munich, Germany.
    9. Syed Kanwar Abbas & Prasad Sankar Bhattacharya & Debdulal Mallick & Pasquale Sgro, 2016. "The New Keynesian Phillips Curve in a Small Open Economy: Empirical Evidence from Australia," The Economic Record, The Economic Society of Australia, vol. 92(298), pages 409-434, September.
    10. Zhang, Chengsi & Murasawa, Yasutomo, 2011. "Output gap measurement and the New Keynesian Phillips curve for China," Economic Modelling, Elsevier, vol. 28(6), pages 2462-2468.
    11. Johanna Amberger & Ralf Fendel, 2017. "Understanding inflation dynamics in the Euro Area: deviants and commonalities across member countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(2), pages 261-293, May.
    12. Kapur, Muneesh, 2018. "Macroeconomic Policies and Transmission Dynamics in India," MPRA Paper 88566, University Library of Munich, Germany.
    13. Abbas, Syed K. & Bhattacharya, Prasad Sankar & Sgro, Pasquale, 2016. "The new Keynesian Phillips curve: An update on recent empirical advances," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 378-403.
    14. repec:agr:journl:v:4(621):y:2019:i:4(621):p:85-92 is not listed on IDEAS
    15. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    16. 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.
    17. 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.
    18. Bec, Frédérique & Kanda, Patrick, 2020. "Is inflation driven by survey-based, VAR-based or myopic expectations? An empirical assessment from US real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    19. Jeremy Rudd & Karl Whelan, 2007. "Modeling Inflation Dynamics: A Critical Review of Recent Research," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 155-170, February.
    20. Adam Hale Shapiro, 2008. "Estimating the New Keynesian Phillips Curve: A Vertical Production Chain Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 627-666, June.
    21. Imen Kobbi & Foued-Badr Gabsi, 2017. "The Nonlinearity of the New Keynesian Phillips Curve: The Case of Tunisia," Economies, MDPI, vol. 5(3), pages 1-12, July.

    More about this item

    Keywords

    Inflation; New Keynesian Phillips curve; Rational expectations; MIDAS;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory

    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:spr:empeco:v:57:y:2019:i:6:d:10.1007_s00181-018-1417-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.