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Flexible markov-switching models with evolving regime-specific parameters: an application to Brazilian business cycles

Author

Listed:
  • Fábio A. R. Gomes
  • Lívia C. M. Melo
  • Gian Paulo Soave

Abstract

This article develops a flexible class of Markov-switching models in which the GDP growth rate is decomposed into a long-run growth trend and evolving regime-dependent means. The models can account for multiple regimes, breaks in the long-run trend, stochastic volatility, and time-varying transition probabilities. They can also handle data outliers that may arise from rare events, such as the COVID-19 crisis. We illustrate our methodology by modelling Brazilian GDP growth, which has exhibited complicated dynamics over the past four decades. Our results suggest two regimes, one long-run trend break, significant time variation in volatility, and the presence of outliers. Moreover, the selected model features time-varying transition probabilities driven by domestic variables (fiscal stance, reserves, and the real interest rate). Significantly, our findings indicate a marked decline in Brazil’s long-run growth in recent years.

Suggested Citation

  • Fábio A. R. Gomes & Lívia C. M. Melo & Gian Paulo Soave, 2024. "Flexible markov-switching models with evolving regime-specific parameters: an application to Brazilian business cycles," Applied Economics, Taylor & Francis Journals, vol. 56(14), pages 1705-1722, March.
    • Handle: RePEc:taf:applec:v:56:y:2024:i:14:p:1705-1722
    DOI: 10.1080/00036846.2024.2305621
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