Inflation uncertainty, macroeconomic instability and the efficiency of financial institutions

Abstract

PurposeThe study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).Design/methodology/approachData for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.FindingsReported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.Practical implicationsFor policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.Originality/valueThe approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.

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“…To ensure the reliability of the latent variables, Cronbach's alpha testing and confirmatory factor analyses (CFAs) were concurrently performed before carrying out further analyses. First, CFAs was conducted to evaluate the measurement models' fitness and the convergent and discriminant validity of used constructs, as suggested by some prior studies (Astrachan et al, 2014;Idiana et al, 2022;Abaidoo and Agyapong, 2023). Specially, differences in chi-square and degree of freedom (Dx 2 [df]) were calculated to compare four measurement models that included items from four constructs, EEC, PEE, BIC and AUC, The skewness and kurtosis values of the items in the four constructs, namely, EEC, PEE, BIC and AUC, were found to be within an acceptable range, with all skewness values being less than j3j and all kurtosis values being less than j8j (Hu and Bentler, 1999) (Table 3).…”