Based on simple time series plots and periodic sample autocorrelations, we document that monthly river flow data displays long memory, in addition to pronounced seasonality. In fact, it appears that the long memory characteristics vary with the season. To describe these two properties jointly, we propose a seasonal periodic long memory model and fit it to the well-known Fraser river data (to be obtained from Statlib at http://lib.stat.cm.edu/datasets/). We provide a statistical analysis and provide impulse response functions to show that shocks in certain months of the year have a longer lasting impact than those in other months.

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doi.org/10.1016/S1364-8152(01)00025-1, hdl.handle.net/1765/13525
Environmental Modelling & Software
Erasmus Research Institute of Management

Ooms, M., & Franses, P. H. (2001). A seasonal periodic long memory model for monthly river flows. Environmental Modelling & Software, 16(6), 559–569. doi:10.1016/S1364-8152(01)00025-1