Abstract

This study contributes to the current debate on the downsides and benefits of revenue diversification. Diversification may affect banks when they invest in riskier activities with lower returns, while they benefit from diversified activities that are less risky but have higher returns. The study offers extended implications in the empirical literature using a different measure of revenue diversification from an emerging market perspective. The study uses recent financial data from 26 Malaysian and Nigerian banks for the period 2009–2017, totaling 234 observations. The GMM estimation technique is employed to test the relationship. The results show that revenue diversification – non-interest income/gross revenue ratio (NII), fee and commission income/revenue ratio (NII1), and non-interest income/total assets ratio (NIITA) – significantly affect the firm value and stability of Nigerian banks. Liquidity, administrative expenses, net interest margin (NIM), non-performing loans (NPL), size, GDP growth rate and inflation also affect the firm value and stability of a bank. For Malaysian banks, diversification variables do not significantly affect firm value of a bank, while liquidity, administrative expenses, NIM and size significantly affect firm value. Diversification (NII and NIITA), liquidity, administrative expenses, NIM, NPL, size, GDP growth and inflation rate has a significant impact on the stability of Malaysian banks. The study concludes that revenue diversification affects both the firm value and stability of banks, and to achieve sound financial stability, banks that focus on interest-generating activities may diversify into non-interest-generating activities.

Highlights

  • MethodsThe study uses dynamic panel data (GMM) to tackle the problems of intrinsic endogeneity, heteroscedasticity, and autocorrelation

  • This study found that the first hypothesis (H1) indicates that revenue diversification has a significant impact on the firm value of banks

  • This study examines the influence of revenue diversification on the firm value and stability of banks

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Summary

Methods

The study uses dynamic panel data (GMM) to tackle the problems of intrinsic endogeneity, heteroscedasticity, and autocorrelation. This section details the data sources, highlights a two-step GMM estimator, the typical heterothe model specifications, and various measure- scedasticity issues are solved in the models. The ments of diversification, firm value, and stability. Lags of a dependent variable were incorporated in the model under the dynamic model estimation. Before the dynamic panel estimation is analyzed, the Sargan test and Arellano-Bond test were. The study uses data obtained from financial state- conducted to check for second order autocorrelaments that are used in various cross-country stud- tion. The study accepts the null hypothesis when ies.

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