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A wavelet-based panel unit-root test in the presence of an unknown structural break and cross-sectional dependency, with an application of purchasing power parity theory in developing countries
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Karlstad Business School (from 2013).
Gothenburg Univ, Dept Econ & Stat, Gothenburg, Sweden.;Jonkoping Int Business Sch, Dept Econ Finance & Stat, Jonkoping, Sweden..
Jonkoping Int Business Sch, Dept Econ Finance & Stat, Jonkoping, Sweden..
Jonkoping Int Business Sch, Dept Econ Finance & Stat, Jonkoping, Sweden.;Linnaeus Univ, Dept Econ & Stat, Vaxjo, Sweden..
2017 (English)In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 49, no 21, p. 2096-2105Article in journal (Refereed) Published
Abstract [en]

This article introduces two different non-parametric wavelet-based panel unit-root tests in the presence of unknown structural breaks and cross-sectional dependencies in the data. These tests are compared with a previously suggested non-parametric wavelet test, the parameteric Im-Pesaran and Shin (IPS) test and a Wald type of test. The results from the Monte Carlo simulations clearly show that the new wavelet-ratio tests are superior to the traditional tests both in terms of size and power in panel unit-root tests because of its robustness to cross-section dependency and structural breaks. Based on an empirical Central American panel application, we can, in contrast to previous research (where bias due to structural breaks is simply disregarded), find strong, clear-cut support for purchasing power parity (PPP) in this developing region.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 49, no 21, p. 2096-2105
Keywords [en]
Panel unit-root test, cross-sectional dependency, structural break, wavelet
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Other Social Sciences not elsewhere specified
Research subject
Statistics
Identifiers
URN: urn:nbn:se:kau:diva-64325DOI: 10.1080/00036846.2016.1231908ISI: 000396793200005OAI: oai:DiVA.org:kau-64325DiVA, id: diva2:1145329
Available from: 2017-09-28 Created: 2017-09-28 Last updated: 2019-05-20Bibliographically approved

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Almasri, Abdullah

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