An Early Warning Signal (EWS) Model for Predicting Financial Crisis in Emerging African Economies

Kehinde Damilola Ilesanmi,Devi Datt Tewari

doi:10.5430/ijfr.v12n1p101

Kehinde Damilola Ilesanmi, Devi Datt Tewari

Open Access

https://doi.org/10.5430/ijfr.v12n1p101

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Abstract

The devastating effects of the global financial crisis (GFC) have led to a renewed, global interest in the development of an early warning signal (EWS) model. The purpose of the EWS model is to alert policymakers and other stakeholders to the possibility of the occurrence of a crisis. This study estimates a EWS model for predicting the financial crisis in four emerging African economies using a multinomial logit model and a data set covering the period of January 1980 to December 2017. The result of the study suggests that emerging African economies are more likely to face financial crisis as debts continue to rise without a corresponding capacity to withstand capital flow reversal as well as excessive foreign exchange risk due to currency exposure. The result further indicates that rising debt exposure raises the likelihood of the economies remaining in a state of crisis. This result confirms the significance of a financial stability framework that addresses the issues confronting Africa’s emerging economies such as rising debt profile, liquidity and currency risk exposure.

Highlights

The 2007/08 global financial crisis (GFC) which emanated from the United States and spread to other developed and emerging countries resulted in large-scale losses in most economies around the globe (Cunningham and Friedrich, 2016; Ilesanmi and Tewari, 2019a)
This study investigated the possibility of creating an early warning signal model aimed at predicting the occurrence of a financial crisis in emerging African countries
The identification and prediction of the state of the financial system are very important for the design of appropriate policy such as countercyclical capital buffers which can help reduce large losses associated with financial crisis

Summary

Introduction

The 2007/08 global financial crisis (GFC) which emanated from the United States and spread to other developed and emerging countries resulted in large-scale losses in most economies around the globe (Cunningham and Friedrich, 2016; Ilesanmi and Tewari, 2019a). The multinomial logit model was used by Bussiere and Fratzscher (2006) within a currency crisis framework, while Oet et al (2013) and Caggiano et al, (2014) applied it within a banking crisis framework In these studies, the model was used to predict the probability of the occurrence of a crisis (which takes the value of 1 for the first crisis year, 2 for the other crisis years (Note 1) and 0 for non-crisis years), as a function of a vector of several independent variables. Mateju, Rusnak, Smidkova, and Vasicek, 2014; Barrell, Davis, Karim, and Liadze, 2010), a number of studies have been done on emerging economies and low-income countries (Caggiano, et al, 2014) None of these studies has focused on emerging African economies (EAEs).

Systemic Risk and EWS

Methodology and Data

Estimation Result and Discussion

Diagnostic Tests

Findings

Conclusion and Policy Recommendation