Abstract

Interest in the relationship between credit rating and economic growth is growing as emerging economies increasingly integrate into international financial markets. Without credit ratings, developing economies would not have been able to successfully issue their sovereign bonds to support economic growth. Therefore, this paper examines a causality relationship between Standard & Poor’s long-term foreign currency sovereign credit ratings and economic growth in 19 Sub-Saharan countries over the period from 2003 to 2018. The results of the Granger causality tests show a unidirectional causality from sovereign credit ratings to economic growth, not vice versa. This implies that economic growth is not significant in determining sovereign credit ratings. It can thus be concluded from these findings that sovereign credit ratings are proactive actions by rating agencies that are relevant in determining future economic growth. Thus, investors benefit from utilizing credit ratings to prevent inherent information asymmetry in fundamental economic factors. Therefore, it is important for policy makers to pay attention to sovereign credit ratings when formulating macroeconomic policies.

Highlights

  • Sovereign credit rating (SCR) has become one of the most topical subjects amongst African economic analysts, investors and ordinary citizens

  • To examine the causal relationship, the analysis roots or the existence of a stochastic trend is imconsiders SCRs announced by Standard & Poor’s portant in determining whether a statistical proon a total of 19 countries in Sub-Saharan Africa for cess is stationary or not

  • The general assumption underlying SCRs is that a change in credit rating affects the overall economy and the well-being of all its citizens

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Summary

INTRODUCTION

Sovereign credit rating (SCR) has become one of the most topical subjects amongst African economic analysts, investors and ordinary citizens. Credit rating agencies amplifies the financial cri- As in Mutize and Gossel (2018), a key literature ses by failing to predict the emergence of these cri- in the area of credit rating analysis in Africa, the ses and, in turn, the sudden downgrades of crisis Granger causality test in this analysis estimates countries more than their economic fundamen- the following two panel regression equations: tals can justify. Through IRF, both the negative and positive impact can be identified and evaluated

AND DISCUSSION
F-statistic
CONCLUSION
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