Interest Rate Spread as the 'Power of Growth' on Financial Profitability of Banks in Africa
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Published:2021-04-14
Issue:
Volume:
Page:312-332
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ISSN:2395-602X
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Container-title:International Journal of Scientific Research in Science and Technology
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language:en
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Short-container-title:IJSRST
Author:
Manu Emmanuel Kwaku1, Xuezhou Wen2, Somuah Mary Akosuah3
Affiliation:
1. School of Management, Jiangsu University, Zhenjiang, Jiangsu Province, P. R. China 2. School of Business, Jiangnan University, Wuxi, Jiangsu Province, P. R. China 3. Valley View University, Ghana Techiman
Abstract
The high-interest rate has postured solemn distresses to the administration, managers, firms, and the masses. Commercial banks in Africa, principally, are exasperated to use the policy rate to bring down loaning charges. Interest rate charges though have sustained to persist gluey downwards. This study considered the impact of interest rate as the power of growth on financial profitability and examine the causal link amid the measurement variables (bank credit, savings, non-performing loans, and interest rate) between 2000 and 2016. The countries used in this study were investigated as a whole panel and individually per country. First, considering the results from homogeneity assessment and Pesaran CD's checks, we detect the presence of heterogeneity and cross-sectional correlations for the explored data. Second, the CADF and CIPS panel unit root tests report that the variables are non-stationary at their stages but become stationary at their first transformations. Third, the Westerlund-Edgerton panel bootstrap cointegration test shows that the variables are cointegrated and hence possess a structural long-run relationship. Forth, results from the PMG estimator through the panel ARDL model show that; (1) A two-way connectedness is verge by bank credit and FP in the long-period and short-run; (2) A positive and significant one-way cause running from NPLs to BC, a one-way cause amid interest rate and bank credit and lastly one-way causality only in the long-period for NPLs and SAV are evidenced; (3) The PMG estimator through the panel ARDL framework is evidenced to be very significantly effective to the application of Granger causatives test. Though different parameter estimates are evidenced, the results are generally consistent with that of the PMG in terms of connections.
Publisher
Technoscience Academy
Reference53 articles.
1. Al-Tamimi, H., & Hussein, A. (2010). Factors influencing performance of the UAE Islamic and conventional national banks. Global Journal of Business Research, 4(2), 1-9. 2. Asafu-Adjaye, J., Byrne, D., & Alvarez, M. (2016). Economic growth, fossil fuel and non-fossil consumption: A Pooled Mean Group analysis using proxies for capital. Energy economics, 60, 345-356. 3. Basher, S. A., Haug, A. A., & Sadorsky, P. (2012). Oil prices, exchange rates and emerging stock markets. Energy economics, 34(1), 227-240. 4. Bawumia, M., Belnye, F., & Ofori, M. E. (2005). The determination of bank interest spreads in Ghana: An empirical analysis of panel data. African Development Review, 20(3), 378-399. 5. Bragt, D. v., Francke, M., Kramer, B., & Pelsser, A. (2010). Risk-neutral valuation of real estate derivatives. ORTEC Technical Paper(2009-02).
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