Regime switching with structural breaks in output convergence
Beylunioğlu Fuat C.,
Thanasis Stengos and
Ege Yazgan ()
Additional contact information
Beylunioğlu Fuat C.: Istanbul Bilgi University, Istanbul, Turkey
Studies in Nonlinear Dynamics & Econometrics, 2018, vol. 22, issue 3, 17
Abstract:
In this paper, we examine empirically GDP per capita convergence using an approach that explicitly allows for regime switching in the long memory parameter d within the context of a Markov Switching (MS)–ARFIMA framework. As existing methods used in the estimation of standard MS models, such as the EM algorithm are no longer appropriate, we will make use of the Viterbi algorithm to estimate the long memory MS model used by Tsay and Härdle (Tsay, W.-J., and W. K. Härdle. 2009. “A Generalized Arfima Process with Markov-Switching Fractional Differencing Parameter.” Journal of Statistical Computation and Simulation 79: 731–745.). We will classify the output gap series into two regimes, a high d and a low d regime, where a high d close to unity would imply persistence and lack of convergence. By examining the path of d parameter over time which enables us to observe non-convergent behavior in more detail, we find that converging behavior is diminishing over time and divergence is the dominant force.
Keywords: long memory; Markov switching; output convergence; structural breaks; Viterbi algorithm (search for similar items in EconPapers)
JEL-codes: C1 C2 O1 O4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1515/snde-2017-0043 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:22:y:2018:i:3:p:17:n:5
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html
DOI: 10.1515/snde-2017-0043
Access Statistics for this article
Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach
More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().