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- W2914337564 abstract "The Generalized Smooth Transition Auto-Regression (GSTAR) parametrizes the joint asymmetry in the duration and length of cycles in macroeconomic time series by using particular generalizations of the logistic function. The symmetric smooth transition and linear auto-regressions are peculiar cases of the new parametrization. A test for the null hypothesis of dynamic symmetry is discussed. Two case studies indicate that dynamic asymmetry is a key feature of the U.S. economy. Our model beats its competitors in point forecasting, but this superiority becomes less evident in density forecasting and in uncertain forecasting environments." @default.
- W2914337564 created "2019-02-21" @default.
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- W2914337564 date "2018-03-28" @default.
- W2914337564 modified "2023-09-27" @default.
- W2914337564 title "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle" @default.
- W2914337564 hasPublicationYear "2018" @default.
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