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• W2895749955 abstract "Abstract The literature of time series models with threshold effects makes the assumption of a constant threshold value over different periods. However, this time-homogeneity assumption tends to be too restrictive owing to the fact that the threshold value that triggers regime switching could possibly be time-varying. This study herein proposes a threshold model in which the threshold value is assumed to be a latent variable following an autoregressive (AR) process. The newly proposed model was estimated using a Markov Chain Monte Carlo (MCMC) algorithm under a Bayesian framework. The Monte Carlo simulations are presented to assess the effectiveness of the Bayesian approaches. An illustration of the model was made through an application to a regime-sensitive Taylor rule employing U.S. data." @default.
• W2895749955 created "2018-10-12" @default.
• W2895749955 creator A5024732735 @default.
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• W2895749955 date "2018-09-29" @default.
• W2895749955 modified "2023-09-23" @default.
• W2895749955 title "Threshold models with time-varying threshold values and their application in estimating regime-sensitive Taylor rules" @default.
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• W2895749955 doi "https://doi.org/10.1515/snde-2017-0114" @default.
• W2895749955 hasPublicationYear "2018" @default.
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