This study develops an early warning signal (EWS) of government debt crisis using a panel data consisting of 43 developing countries over the period of 1960 to 2017. It employs two different methods: the noise to signal ratio to capture the signaling power of individual indicators; and the binomial logistic regression to construct a more general model. The binomial logistic regression offers a better predictive power relative to the noise to signal ratio. The binomial logistic regression can predict 61.5% of the government debt crisis 2 years in advance. An increase in inflation, government and private debt exposures, external debt to exports, ratio of short-term external debt to foreign exchange reserves, and the ratio of external interest payments to gross national income can signal an upcoming debt crisis. Similarly, a continuous decline in the gross domestic product (GDP) and government consumption also increase the likelihood of government debt crisis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.