Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence
This paper generalises the monthly seasonal unit root tests of Franses (1991) for a heterogeneous panel following the work of Im, Pesaran, and Shin (2003), which we refer to as the F-IPS tests. The paper presents the mean and variance necessary to yield a standard normal distribution for the tests, for different number of time observations, T, and lag lengths. However, these tests are only applicable in the absence of cross-sectional dependence. Two alternative methods for modifying these F-IPS tests in the presence of cross-sectional dependency are presented : the first is the cross-sectionally augmented test,denoted CF-IPS, following Pesaran (2007), the other is a bootstap method, denoted BF-IPS. In general, the BF-IPS tests have greater power than the CF-IPS tests, although for large T and high degree of cross-sectional dependency the CF-IPS test dominates the BF-IPS test.
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