Disentangling the source of non-stationarity in a panel of seasonal data
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Abstract In dealing with a panel of seasonal data with cross-section dependence, this paper establishes a common factor model to investigate whether the seasonal and non-seasonal non-stationarity in a series is pervasive, or specific, or both. Without knowing a priori whether the data are seasonal stationary or not, we propose a procedure for consistently estimating the model; thus, the seasonal non-stationarity of common factors and idiosyncratic errors can be separately detected accordingly. We evaluate the methodology in a series of Monte Carlo simulations and apply it to test for non-stationarity and to disentangle their sources in panels of worldwide real exchange rates and of consumer price indexes for 37 advanced economies.
2020 ◽
pp. 1-14
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2016 ◽
Vol 33
(4)
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pp. 333-360
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2017 ◽
Vol 13
(1)
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pp. 1-9
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1996 ◽
Vol 20
(2)
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pp. 140-140
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2006 ◽
Vol 30
(3)
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pp. 233-246
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1991 ◽
Vol 109
(3)
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pp. 502-511
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