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

In: Non-Linearity in Econometric Modeling, Vol. 1

Author

Listed:
  • Sarit Maitra

    (Alliance University—Central Campus, Chikkahadage Cross Chandapura-Anekal)

Abstract

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.

Suggested Citation

  • Sarit Maitra, 2025. "Markov Switching Models, Threshold Auto Regressive Models, and Smooth Transition Models," Dynamic Modeling and Econometrics in Economics and Finance, in: Non-Linearity in Econometric Modeling, Vol. 1, chapter 0, pages 159-188, Springer.
    • Handle: RePEc:spr:dymchp:978-3-032-06462-2_5
    DOI: 10.1007/978-3-032-06462-2_5
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