Summary
The problem of optimal forecast combination is considered in situations of structural change. We develop a rather general approach, which combines the time-varying-parameter models of Diebold and Pauly (1987a) with allowance for prediction-error serial correlation as in Diebold (1988). The methodology is based on the regression-based paradigm of Granger and Ramanathan (1984), so that many earlier results emerge as special (and often restrictive) cases. Both deterministic and stochastic parameter variations are considered, with and without allowance for serial correlation. The results are illustrated in a series of examples.
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Diebold, F.X., Pauly, P. (1989). Forecasting in Situations of Structural Change: A General Approach. In: Hackl, P. (eds) Statistical Analysis and Forecasting of Economic Structural Change. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-02571-0_19
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DOI: https://doi.org/10.1007/978-3-662-02571-0_19
Publisher Name: Springer, Berlin, Heidelberg
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