Analysis of the influence of economic variables on the Selic Rate using logistic regression
DOI:
https://doi.org/10.22567/rep.v15i1.1176Keywords:
Logistic regression, selic rate, monetary policy, economic indicatorsAbstract
This study examines how domestic and external economic variables influence the probability of an increase in Brazil’s Selic rate using logistic regression. The analysis began with more than 30 macroeconomic indicators from the past decade, from which the final model retained the IBOV index, unemployment rate, international gasoline prices, and U.S. interest rates. Estimated in SPSS, the model demonstrated robust performance, with a Nagelkerke R² of 75.8%, an accuracy of 90.9% in predicting rate hikes, and statistically significant coefficients for all variables (p < 0.05). The results indicate that Copom’s decisions are shaped by a combination of domestic factors—such as economic activity and labor market conditions—and external pressures, especially related to the U.S. monetary cycle and international energy price shocks. These findings reinforce evidence that emerging economies operate under substantial global influence and highlight the usefulness of logistic regression as a predictive tool for understanding the determinants of Brazil’s monetary policy.
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