Financial crises are recurrent events with profound economic and social implications. Accurately predicting these crises is of paramount importance for policymakers, financial institutions, and investors. This abstract provides an overview of a study that explores the utility of Logit models in predicting financial crises and their ability to provide insights into the factors contributing to these crises and the value of Logit models in predicting financial crises and gaining insights into their underlying drivers. Such predictive models can enhance risk management strategies and help prevent or mitigate the devastating consequences of financial crises. Future research could focus on refining the model by incorporating additional data sources and improving predictive accuracy further.
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