Interest Rate Spread as the 'Power of Growth' on Financial Profitability of Banks in Africa

Authors

  • Emmanuel Kwaku Manu  School of Management, Jiangsu University, Zhenjiang, Jiangsu Province, P. R. China
  • Wen Xuezhou  School of Business, Jiangnan University, Wuxi, Jiangsu Province, P. R. China
  • Mary Akosuah Somuah  Valley View University, Ghana Techiman

DOI:

https://doi.org/10.32628/IJSRSET218154

Keywords:

Bank Credit, Savings, Non-Performing Loan, Financial Profitability, Interest Rate

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.

References

  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).
  6. Busch, R., & Memmel, C. (2016). Quantifying the components of the banks’ net interest margin. Financial Markets and Portfolio Management, 30(4), 371-396.
  7. Corb, H. (2012). Interest rate swaps and other derivatives: Columbia University Press.
  8. Dietrich, A., & Wanzenried, G. (2011). Determinants of bank profitability before and during the crisis: Evidence from Switzerland. Journal of International Financial Markets, Institutions and Money, 21(3), 307-327.
  9. Dogan, E., & Aslan, A. (2017). Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional dependence. Renewable and Sustainable Energy Reviews, 77, 239-245.
  10. Dogan, E., & Seker, F. (2016a). The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. Renewable and Sustainable Energy Reviews, 60, 1074-1085.
  11. Dogan, E., & Seker, F. (2016b). An investigation on the determinants of carbon emissions for OECD countries: empirical evidence from panel models robust to heterogeneity and cross-sectional dependence. Environmental Science and Pollution Research, 23(14), 14646-14655.
  12. Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., . . . Leitão, P. J. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27-46.
  13. Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460.
  14. Eggoh, J. C., Bangaké, C., & Rault, C. (2011). Energy consumption and economic growth revisited in African countries. Energy Policy, 39(11), 7408-7421.
  15. Gengenbach, C., Palm, F. C., & Urbain, J.-P. (2009). Panel unit root tests in the presence of cross-sectional dependencies: Comparison and implications for modelling. Econometric Reviews, 29(2), 111-145.
  16. Goodhart, C. (2009). The interest rate conditioning assumption. International Journal of Central Banking, 5(2), 85-108.
  17. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438.
  18. Gujarati, D. N. (2007). Sangeetha (2007) Basic Econometrics. Tata McGraw Hill Publishing Company Limited, New Delhi, 110(008), 451-452.
  19. Hainz, C., Horvath, R., & Hlavá?ek, M. (2014). The interest rate spreads in the Czech Republic: Different loans, different determinants? Economic Systems, 38(1), 43-54.
  20. Haron, S. (2004). Determinants of Islamic bank profitability. Global Journal of Finance and Economics, 1(1), 11-33.
  21. International Monetary Fund (2019). International Financial Statistics, Real Interest rate. Retrieved from World Bank, World Development Indicators,https://data.worldbank.org/indicator/FR.INR.RINR?view=chart , September 20, 2019
  22. Irungu, P. N. (2013). The effect of interest rate spread on financial performance of commercial banks in Kenya. Unpublished Master’s Thesis). University of Nairobi, Nairobi, Kenya.
  23. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1-44.
  24. Kodongo, O., & Ojah, K. (2012). The dynamic relation between foreign exchange rates and international portfolio flows: Evidence from Africa's capital markets. International Review of Economics & Finance, 24, 71-87.
  25. Koehn, M., & Santomero, A. M. (1980). Regulation of bank capital and portfolio risk. The journal of finance, 35(5), 1235-1244.
  26. Lopez, J. A., Rose, A. K., & Spiegel, M. M. (2018). Why have negative nominal interest rates had such a small effect on bank performance? cross country evidence: National Bureau of Economic Research.
  27. Lukas, B. A., & Ferrell, O. C. (2000). The effect of market orientation on product innovation. Journal of the academy of marketing science, 28(2), 239-247.
  28. Mang’eli, M. (2012). Relationship between interest rate spread and financial performance of the commercial banks in Kenya. Un-published MBA project, University of Nairobi, Kenya.
  29. Musah, A., Anokye, F. K., & Gakpetor, E. D. (2018). The Impact of Interest Rate Spread On Bank Profitability In Ghana. European Journal of.
  30. Nawaz, M., Shakoor, M. I., & Pirzada, S. S. (2013). The professional development of employees in banks of Pakistan: A comparative study of public and private banks in Punjab Pakistan. International Journal of Learning and Development, 3(5), 89-110.
  31. Ogbenjuwa, E. I. (2016). Implementation of International Financial Reporting Standards by listed companies in Nigeria.
  32. Ongore, V. O., & Kusa, G. B. (2013). Determinants of financial performance of commercial banks in Kenya. International journal of economics and financial issues, 3(1), 237-252.
  33. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics, 61(S1), 653-670.
  34. Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric theory, 20(3), 597-625.
  35. Peng-fei, W. C. Z. (2003). An Empirical Analysis on Economies of Scale and Scope in China Commercial Banks [J]. China Industrial Economy, 10.
  36. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels.
  37. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross?section dependence. Journal of applied econometrics, 22(2), 265-312.
  38. Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634.
  39. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
  40. Quah, C. H., & Crowley, P. M. (2010). Monetary integration in East Asia: A hierarchical clustering approach. International finance, 13(2), 283-309.
  41. Romer, C. D., & Romer, D. H. (2000). Federal Reserve information and the behavior of interest rates. American Economic Review, 90(3), 429-457.
  42. Roodman, D., & Morduch, J. (2014). The impact of microcredit on the poor in Bangladesh: Revisiting the evidence. Journal of Development Studies, 50(4), 583-604.
  43. Samahiya, M., & Kaakunga, E. (2014). Determinants of Commercial Banks’ Interest Rate Spread in Namibia: An Econometric Exploration. Botswana Journal of Economics, 12(1), 1-10.
  44. Saushini, E. M., & Sheefeni, J. P. S. An Analysis of the Banking Sector Interest Rate Spread in Namibia.
  45. Sheriff, I., & Amoako, G. (2014). Macroeconomic determinants of interest rate spread in Ghana: Evidence from ARDL modelling approach. Journal of Finance and Bank Management, 2(2), 115-132.
  46. Trivedi, S. R. (2015). Banking innovations and new income streams: impact on banks' performance. Vikalpa, 40(1), 28-41.
  47. Ugoani, J. (2016). Nonperforming loans portfolio and its effect on bank profitability in Nigeria. Independent Journal of Management & Production, 7(2).
  48. Westerlund, J., & Edgerton, D. L. (2007a). New improved tests for cointegration with structural breaks. Journal of time series Analysis, 28(2), 188-224.
  49. Westerlund, J., & Edgerton, D. L. (2007b). A panel bootstrap cointegration test. Economics letters, 97(3), 185-190.
  50. World Bank (2019). Adjusted savings: net national savings (% of GNI). Retrieved from World Bank, World Development Indicators, https://data.worldbank.org/indicator/NY.ADJ.NNAT.GN.ZS, September 20, 2019
  51. World Bank (2019). Bank Credit to Bank Deposits for all countries. Retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org /series/GFDD.SI.04, September 20, 2019.
  52. World Bank (2019). Bank Non-Performing Loans to Gross Loans for all countries. Retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/ GFDD.SI.02, September 20, 2019.
  53. World Bank (2019). Bank's Return on Assets for All countries. Retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/ [GFDD.EI.05], September 20, 2019.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2021-04-30

Issue

Volume 8, Issue 2, November-December-2021

Section

Research Articles

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How to Cite

[1]
Emmanuel Kwaku Manu, Wen Xuezhou, Mary Akosuah Somuah "Interest Rate Spread as the 'Power of Growth' on Financial Profitability of Banks in Africa" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 2, pp.312-332, November-December-2021. Available at doi : https://doi.org/10.32628/IJSRSET218154