Abstract
PurposeThis paper aims to test purchasing power parity (PPP) hypothesis for Greece, Italy, Ireland, Portugal and Spain, which are known as the GIIPS countries.Design/methodology/approachThe authors conduct a comprehensive analysis by using unit root approaches without and with structural breaks and non-linearity.FindingsThe PPP is valid for the GIIPS countries. Considering structural breaks in non-linear framework plays a crucial role.Originality/valueThere is no empirical study testing PPP hypothesis by focusing on the GIIPS countries. This study further takes into account for structural breaks and non-linearity in the real exchange rates of these countries.
Highlights
Purchasing power parity (PPP) hypothesis implies that exchange rates adjust to their equilibrium values until purchasing power discrepancy disappears across countries
The results from the conventional tests indicate the random walk behavior of the real exchange rates, implying that PPP does not hold in the GIIPS countries
The conventional tests indicate that the real effective exchange rates during the 1970–2020 period have unit root, implying that PPP does not hold in the GIIPS countries
Summary
Purchasing power parity (PPP) hypothesis implies that exchange rates adjust to their equilibrium values until purchasing power discrepancy disappears across countries. One drawback of conventional unit root methods is that they exhibit size distortions and have low power in finite samples (Stock, 1994) To address this issue, scholars use historical data [1] which leads to substantial increase in power of tests (Lothian and Taylor, 1996) and is consistent with the view of that PPP holds in the long run (Christopoulos and Leon-Ledesma, 2010). Exchange rates may expose to structural breaks because of regime changes, unexpected crashes, shocks and shifts in inflation policy They may show non-linear behavior in the existence of market frictions (such as price rigidities, transactions costs and asymmetric information). Neglecting a break in a unit root (difference stationary) process can lead standard unit root tests to reach an incorrect conclusion of stationarity (Harvey et al, 2010). Taylor et al (2001) indicate that ADF unit root test has low power for the data generating process with nonlinear mean reversion
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