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This chapter explores nonlinear time-series models, focusing on Markov Switching Autoregressive (MSAR), Threshold Autoregressive (TAR), and Smooth Transition Autoregressive (STAR) models. MSAR models capture regime-dependent dynamics with probabilistic transitions governed by a Markov process, making them suitable for modeling phenomena such as economic cycles or stock market volatility. TAR models extend this framework by allowing deterministic regime shifts when a threshold variable crosses a certain level, enabling the modeling of systems with abrupt behavioral changes. STAR models further generalize TARs by introducing smooth transitions between regimes, capturing gradual changes in time-series behavior. Together, these models provide a flexible toolkit for analyzing complex, nonlinear dynamics in economics, finance, and other applied fields.

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Markov Switching Models, Threshold Auto Regressive Models, and Smooth Transition Models

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  • 发表日期：

    2025年

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  • Sarit Maitra

摘要

This chapter explores nonlinear time-series models, focusing on Markov Switching Autoregressive (MSAR), Threshold Autoregressive (TAR), and Smooth Transition Autoregressive (STAR) models. MSAR models capture regime-dependent dynamics with probabilistic transitions governed by a Markov process, making them suitable for modeling phenomena such as economic cycles or stock market volatility. TAR models extend this framework by allowing deterministic regime shifts when a threshold variable crosses a certain level, enabling the modeling of systems with abrupt behavioral changes. STAR models further generalize TARs by introducing smooth transitions between regimes, capturing gradual changes in time-series behavior. Together, these models provide a flexible toolkit for analyzing complex, nonlinear dynamics in economics, finance, and other applied fields.