Threshold Cointegration and the PPP Hypothesis
Pedro Gouveia and
Paulo Rodrigues ()
Journal of Applied Statistics, 2004, vol. 31, issue 1, 115-127
Self-Exciting Threshold Autoregressive (SETAR) models are a non-linear variant of conventional linear Autoregressive (AR) models. One advantage of SETAR models over conventional AR models lies in its flexible nature in dealing with possible asymmetric behaviour of economic variables. The concept of threshold cointegration implies that the Error Correction Mechanism (ECM) at a particular interval is inactive as a result of adjustment costs, and active when deviations from equilibrium exceed certain thresholds. For instance, the presence of adjustment costs can, in many circumstances, justify the fact that economic agents intervene to recalibrate back to a tolerable limit, as in the case when the benefits of adjustment are superior to its costs. We introduce an approach that accounts for potential asymmetry and we investigate the presence of the relative version of the purchasing power parity (PPP) hypothesis for 14 countries. Based on a threshold cointegration adaptation of the unit root test procedure suggested by Caner & Hansen (2001), we find evidence of an asymmetric adjustment for the relative version of PPP for eight pairs of countries.
Keywords: Nonlinearity; cointegration; Setar models (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:31:y:2004:i:1:p:115-127
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().