IDEAS home Printed from https://ideas.repec.org/p/hal/cesptp/halshs-00188309.html
   My bibliography  Save this paper

Which is the best model for the US inflation rate: a structural changes model or a long memory process?

Author

Listed:
  • Lanouar Charfeddine

    (OEP - UPEM - Université Paris-Est Marne-la-Vallée)

  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper analyzes the dynamics of the US inflation series using two classes of models: structural changes models and Long memory processes. For the first class, we use the Markov Switching (MS-AR) model of Hamilton (1989) and the Structural Change (SCH-AR) model using the sequential method proposed by Bai and Perron (1998, 2003). For the second class, we use the ARFIMA process developed by Granger and Joyeux (1980). Moreover, we investigate whether the observed long memory behavior is a true behavior or a spurious behavior created by the presence of breaks in time series. Our empirical results provide evidence for changes in mean, breaks dates coincide exactly with some economic and financial events such Vietnam War and the two oil price shocks. Moreover, we show that the observed long memory behavior is spurious and is due to the presence of breaks in data set.

Suggested Citation

  • Lanouar Charfeddine & Dominique Guegan, 2007. "Which is the best model for the US inflation rate: a structural changes model or a long memory process?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00188309, HAL.
    • Handle: RePEc:hal:cesptp:halshs-00188309
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00188309
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-00188309/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Charfeddine, Lanouar & Guégan, Dominique, 2012. "Breaks or long memory behavior: An empirical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5712-5726.
    2. Charfeddine, Lanouar & Khediri, Karim Ben, 2016. "Time varying market efficiency of the GCC stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 487-504.
    3. Dominique Guegan & Philippe de Peretti, 2011. "Tests of structural changes in conditional distributions with unknown changepoints," Post-Print halshs-00611932, HAL.
    4. Charfeddine, Lanouar, 2016. "Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis," Economic Modelling, Elsevier, vol. 53(C), pages 354-374.
    5. Dominique Guegan & Philippe de Peretti, 2011. "Tests of Structural Changes in Conditional Distributions with Unknown Changepoints," Documents de travail du Centre d'Economie de la Sorbonne 11042, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    7. Lanouar Charfeddine & Dominique Guegan, 2009. "Breaks or Long Memory Behaviour: An empirical Investigation," Post-Print halshs-00377485, HAL.
    8. Dominique Guégan & Philippe Peretti, 2013. "An omnibus test to detect time-heterogeneity in time series," Computational Statistics, Springer, vol. 28(3), pages 1225-1239, June.
    9. Slim Chaouachi & Zied Ftiti & Frederic Teulon, 2014. "Explaining the Tunisian Real Exchange: Long Memory versus Structural Breaks," Working Papers 2014-147, Department of Research, Ipag Business School.
    10. Peter Smith, 2010. "Discussion of the Fisher Effect Puzzle: A Case of Non-Linear Relationship," Open Economies Review, Springer, vol. 21(1), pages 105-108, February.
    11. Mimouni, Karim & Charfeddine, Lanouar & Al-Azzam, Moh'd, 2016. "Do oil producing countries offer international diversification benefits? Evidence from GCC countries," Economic Modelling, Elsevier, vol. 57(C), pages 263-280.
    12. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    13. Charfeddine, Lanouar & Khediri, Karim Ben & Mrabet, Zouhair, 2019. "The forward premium anomaly in the energy futures markets: A time-varying approach," Research in International Business and Finance, Elsevier, vol. 47(C), pages 600-615.
    14. repec:ipg:wpaper:2014-503 is not listed on IDEAS
    15. Charfeddine, Lanouar & Al Refai, Hisham, 2019. "Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    16. Dominique Guegan & Philippe de Peretti, 2012. "An Omnibus Test to Detect Time-Heterogeneity in Time Series," Working Papers halshs-00721327, HAL.
    17. Charfeddine, Lanouar, 2017. "The impact of energy consumption and economic development on Ecological Footprint and CO2 emissions: Evidence from a Markov Switching Equilibrium Correction Model," Energy Economics, Elsevier, vol. 65(C), pages 355-374.
    18. Mihaela SIMIONESCU, 2016. "The Identification Of Inflation Rate Determinants In The Usa Using The Stochastic Search Variable Selection," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 8(1), pages 171-181, March.
    19. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    20. Dominique Guegan & Philippe de Peretti, 2011. "An Omnibus Test to Detect Time-Heterogeneity in Time Series," Post-Print halshs-00560221, HAL.

    More about this item

    Keywords

    Structural breaks models; long range dependance; inflation series; Changements de régimes; longue mémoire; taux d'inflation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:hal:cesptp:halshs-00188309. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.