Governance and Currency Crises in Latin America Post-Nineties: A Machine Learning Approach

Karla Melissa Guzmán and Hongzhong Fan

Emerging Markets Finance and Trade, 2025, vol. 61, issue 7, 1938-1960

Abstract: The paper provides evidence of currency crises in 11 countries in Latin America from 2002 to 2020. The research compares four machine learning classifiers to identify which better classify a new observation as a currency crisis when considering governance and macroeconomic variables. The random forest model outperforms other models in the assessment, even in identifying imbalanced data within our interest class. The model yields a misclassification rate of 1.82%, a balanced accuracy of 99.04%, and a kappa value of 84.76. The results reveal the governance aspects associated with the likelihood of currency crises: poor perception of political stability, corruption, and government effectiveness. Moreover, it is confirmed that export growth, foreign reserves growth, and external debt remain relevant macroeconomic predictors of currency crises post-nineties.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/1540496X.2024.2438299 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mes:emfitr:v:61:y:2025:i:7:p:1938-1960

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/MREE20

DOI: 10.1080/1540496X.2024.2438299

Access Statistics for this article

More articles in Emerging Markets Finance and Trade from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().