Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis

Abstract

This paper applies Monte Carlo simulations to evaluate the size and power properties in the presence of a structural break, for the standard Augmented Dickey‐Fuller (ADF) test versus nonlinear exponential smooth transition autoregressive unit root tests. The break causes the tests to be undersized, and the statistical power considerably decreases. Moreover, the effect is intensified in small samples and very much increased for more persistent nonlinear series. As a remedy, we modify the standard ADF and exponential smooth transition autoregressive unit root tests in order to adjust for a structural break. This improves both the power and the size considerably, even though the empirical size still is lower than the nominal one. More persistent series are more affected by structural breaks, and the new tests are most powerful under the existence of a rather persistent nonlinear data generating process (which is an empirically relevant and common type of data generating process). The proposed tests are applied to investigate mean reversion in the real effective exchange rates of 5 East and Southeast Asian countries, taking into account the structural change in exchange rate regime brought about by the 1997 Asian financial crisis. The empirical findings corroborate our simulation results; the modified more powerful tests are able to reject the unit root in all 5 countries, whereas the tests that do not consider the structural break could only reject in one of these cases.

OECD Ülkelerinde Satın Alma Gücü Paritesinin İncelenmesi: Doğrusal Olmayan Yapısal Kırılmalı Birim Kök Testinden Yeni Kanıtlar

“…Many studies also argue for investigating nonlinearity and structural break simultaneously for PPP because they are not mutually exclusive (Sollis, 2004;Christopoulos & León-Ledesma, 2010;Omay et al, 2018Omay et al, , 2020Nazlioglu et al, 2022) 7 Nonlinear unit root test of Kapetanios et al (2003) has been very popular among researchers and an increasing number of studies are devoted to test PPP using this testing procedure. Erlat (2004); Liew et al (2004); Bahmani-Oskooee et al (2007; Ozdemir (2008); Wu and Lee (2008); ; ; Telatar and Hasanov (2009); Su et al (2014); Yildirim (2017); Habimana et al (2018) are some of these studies, among others. But Choi and Moh (2007) argue that this test has serious problems in practice on large power loss and the source of this power loss is unknown and Li and Park (2018) For OECD countries, several studies are using various unit root tests, and the fastgrowing empirical methodology of unit root testing has also influenced the findings of these studies.…”

Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants

“…As an alternative to ADF and PP tests, BBC unit root test is also executed following the study of Pippenger and Goering [66]. Literature findings demonstrate that nonlinear unit root tests outperform their linear counterparts in terms of size and power properties [67,68]. Those studies suggest using nonlinear models since the standard unit root tests might yield misleading results in the presence of nonlinear dynamics.…”

Convergence in per capita carbon footprint and ecological footprint for G7 countries: Evidence from panel Fourier threshold unit root test

“…For instance, the results of Yavuz and Yilanci 14 showed that per capita CO 2 emissions of G7 countries are converging until reaching a threshold value but diverging after this value. As pointed out by Habimana et al., 15 the power of the nonlinear unit root tests, as well as the linear ones, are reduced if there are structural changes in the data generation process because nonlinear models are incapable of capturing changes. Therefore, it is necessary to use a unit root test that allows for both multiple smooth changes and nonlinearities in the series.…”