Abstract
This paper reviews various recent approaches to cointegration analysis of seasonal time series. In addition to the usual decisions concerning data transformations and univariate time series properties, it is necessary to decide how seasonal variation is included in the multivariate model and how standard cointegration methods should accordingly be modified. Seasonal cointegration and periodic cointegration methods are discussed, as are some of their recent refinements. An overview of further research topics is also provided.
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