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

Hedmus Castro, Michel Alexandre and João Ricardo Costa Filho

MPRA Paper from University Library of Munich, Germany

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.

Keywords: fiscal sustainability; Brazilian states; Markov-switching; unsupervised learning (search for similar items in EconPapers)
JEL-codes: C24 C38 E62 H72 H74 (search for similar items in EconPapers)
Date: 2026-05-25
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