Fiscal sustainability among Brazilian states: a Markov-switching, unsupervised learning approach

Castro, Hedmus and Alexandre, Michel and Costa Filho, João Ricardo (2026): Fiscal sustainability among Brazilian states: a Markov-switching, unsupervised learning approach.

Abstract

The purpose of this paper is to identify patterns of fiscal sustainability among Brazilian states, considering regime changes. To this end, we employ two distinct approaches: the Markov-switching autoregressive (MSAR) model and k-means clustering. Our dataset comprises quarterly data on the primary balance of Brazilian states. Our results show that Brazilian states transition between two fiscal regimes characterized by positive or negative fiscal results. Furthermore, Brazilian states can be grouped based on their shared characteristics. Finally, we demonstrate important correlations between fiscal sustainability variables, such as performance in a given fiscal regime and transition probabilities. These results will contribute to a more accurate assessment of the fiscal dynamics of Brazilian states.

• Item Type: MPRA Paper
• Language: English
• Keywords: fiscal sustainability, Brazilian states, Markov-switching, unsupervised learning
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C24 - Truncated and Censored Models ; Switching Regression Models ; Threshold Regression Models; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C38 - Classification Methods ; Cluster Analysis ; Principal Components ; Factor Models; E - Macroeconomics and Monetary Economics > E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook > E62 - Fiscal Policy; H - Public Economics > H7 - State and Local Government ; Intergovernmental Relations > H72 - State and Local Budget and Expenditures; H - Public Economics > H7 - State and Local Government ; Intergovernmental Relations > H74 - State and Local Borrowing

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