English, Article edition: Unreal exchange rates: a simulation-based approach to adjust misleading PPP estimates Pär Sjölander

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Bookmark: http://trove.nla.gov.au/version/28728
Physical Description
  • article
Language
  • English

Edition details

Title
  • Unreal exchange rates: a simulation-based approach to adjust misleading PPP estimates
Author
  • Pär Sjölander
Physical Description
  • article
Notes
  • Purpose – In what seems as an infinitely ongoing debate regarding the purchasing power parity (PPP) theory, this paper seeks to question the strength of the scientific “evidence” put forward by the PPP revisionists Design/​methodology/​approach – In this paper, the validity of the PPP revisionists' scientific evidence supporting long-run PPP is questioned based on the replication of an influential review study that is considered by PPP revisionists to exhibit “some of the strongest evidence” in favour of the PPP theory. Findings – By simulation experiments it is demonstrated that the traditional PPP unit root tests are non-robust to the empirically identified (G)ARCH distortions. Due to (G)ARCH distortions, over-rejections for the traditional unit root tests are shown to be a problem that potentially misleads researchers to believe that long-run PPP holds under circumstances when it is in fact not valid. As a potential remedy to this problem, a new unit root test is introduced which is robust to conditional heteroscedasticity disturbances, and in contrast to traditional unit root tests, it exhibits no significant empirical support for the PPP theory. Originality/​value – The study illustrates that the PPP revisionists' unit root tests cannot reliably test the PPP hypothesis in the presence of (G)ARCH distortions, due to bad power and size properties. Perhaps it is time to conclude that, based on the currently existing research, it is virtually impossible to empirically come to a credible conclusion regarding whether long-run PPP holds or not.
  • Exchange rates, Purchasing power
  • RePEc:eme:jespps:v:34:y:2007:i:3:p:256-288
Language
  • English
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