IDEAS home Printed from https://ideas.repec.org/p/acb/cbeeco/2010-524.html
   My bibliography  Save this paper

Bubbles or Volatility: A Markov-Switching Unit Root Test with Regime-Varying Error Variance

Author

Listed:
  • Shu-Ping Shi

Abstract

We demonstrate that the constant variance assumption in the Markov-switching Augmented Dickey-Fuller (ADF) test proposed by Hall, Psaradakis and Sola (1999) may result in the misjudgement of bubbles. Upon relaxing this assumption to allow for regime-varying error variances in the Markov-switching ADF test (referred to as the MSADF-RV test), we revisit the integration properties of the money base, consumer price and exchange rate in Argentina from January 1983 to November 1989. Based on the MSADF-RV test, we observe the occurrence of volatility switches in the exchange rate and the consumer price instead of observing bubbles in these two series as in Hall, Psaradakis and Sola (1999)

Suggested Citation

  • Shu-Ping Shi, 2010. "Bubbles or Volatility: A Markov-Switching Unit Root Test with Regime-Varying Error Variance," ANU Working Papers in Economics and Econometrics 2010-524, Australian National University, College of Business and Economics, School of Economics.
  • Handle: RePEc:acb:cbeeco:2010-524
    as

    Download full text from publisher

    File URL: https://www.cbe.anu.edu.au/researchpapers/econ/wp524.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Arora, Vipin & Gomis-Porqueras, Pedro & Shi, Shuping, 2013. "The divergence between core and headline inflation: Implications for consumers’ inflation expectations," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 497-504.
    2. Shu-Ping Shi & Yong Song, 2012. "Identifying Speculative Bubbles with an Infinite Hidden Markov Model," Working Paper series 26_12, Rimini Centre for Economic Analysis.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:acb:cbeeco:2010-524. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/feanuau.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.