Loan Growth, Loan Deposit Ratio and Prediction of Bank Fragility in Kenya Using Generalised Linear Model

  • Albert C. Bwire Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
  • Joel K. Tenai Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
  • Robert M. Odunga Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
Keywords: Loan Portfolio Growth. Loan Deposit Ratio & Generalised Linear Model

Abstract

The purpose of this study was to investigate the predictive ability of growth of loan portfolio and loan deposit ratio on bank fragility in Kenya using Generalised Linear Model. Bank systemic crisis arises when the level of non-performing loans to total assets is between 5% -10%, while bank fragility is said to arise when the level of non-performing loans to totals assets is above 10%. Bank crises have a social welfare consequence on various stakeholders and therefore there is need to find ways to minimize the negative effects. The study targeted 42 Commercial banks in operation at the end of 2015. Secondary data was collected from Central Bank of Kenya for period 2005 – 2015 for purposes of descriptive statistics; this was mainly to test the stability of study variables for a longer period. The generalised linear regression analysis was for period 2010-2014 considered close to bank distress events of 2015 and 2016. The study data was found to be non-normal and heteroscedastic the reason GLM was utilised. The credit creation and agency cost theories were used to explain the causal relationships. These theories expound on credit creation, lender behaviour and bank fragility. It has been established that most research on bank fragility have focused on Non-Performing loans, Loan loss provisions and Capital, Assets, Management, Earnings, Liquidity and sensitivity (CAMELS) indicators to detect bank instability. This study is a departure from CAMELS and tests if there are a few variables with distinctive ability to predict bank fragility. The findings of the study show, lagged dependent variable with powerful predictive ability. Besides, loan growth shows a negative significant relationship with bank fragility. Loan Deposit ratio (LDR) shows a positive significant relationship with bank fragility. This study is significant because it proves need to re-examine CAMELS indicators and identify new ratios which can predict bank fragility, distress and bank failure. Consequently, there is need for further studies to establish LDR percentage beyond which regulatory authorities should intervene in the Commercial banks’ operations. The growth of loan portfolio showed a negative significant relationship, therefore there is need to find how this variable can be modelled to timely identify fragile institutions.

References

Adams, J., Khan, H.T.A., Raeside, R., & White, D. (2007). Research Methods for Graduate Business and Social Students. Response Business Books, Sage Publications Ltd.

Almanidis, P., & Sickles, R.C. (2012). Banking Crises, early warning models, and efficiency. Rice University, Working Papers 15-006. https://doi: 10.1007/978-3-319-48461-7_14

Altunbas, Y., Manganelli, S., & Marques-Ibanez, D. (2015). Realized Bank Risk during the great recession. www.federalresrve.gov/econresdata/ifdp/2015/files/ifdp1140

Arnould, R. J. (1985). Agency Costs in Banking Firms: An Analysis of Expense Preference Behaviour. Journal of Economics and Business, 37(2), 103-112. https://doi.org/10.1016/0148-6195(85)90010-4

Berg, S. A. (2012). The declining deposit to loan ratio- what can the banks do? Norges Bank, Staff Memo, Financial stability.

Berger, A. N., Imbierowicz, B., & Rauch, C. (2016). The Roles of Corporate Governance in Bank Failures during the Recent Financial Crisis. Journal of Money, Credit and

Banking, 48(4), 729-770. https://doi.org/10.1111/jmcb.12316

Bhattacherjee, A. (2012). Social Science research: Principles, methods and practices, textbooks collection, Book 3, University of South Florida, Scholar Commons.

Bishara, A. J., & Hittner, J. B. (2015). Reducing Bias and Error in the Correlation Coefficient due to Non-normality. Educational and Psychological Measurement, 75(5), 785-804.

Bologna, P. (2011). Is there a role for funding in explaining recent U.S. banks failures? IMF Working Paper, WP/11/180

Bongini, P., Claessens, S., & Ferri, G. (2001). The Political Economy of Distress in East Asian Financial Institutions. Journal of Financial Services Research, 19, 5-25. https://doi.org/10.1023/A:1011174316191

Boudriga, A., Taktak, N.B., & Jellouli, S. (2009). Bank supervision and non-performing loans: a cross-country analysis. Journal of Financial Economic Policy, 1(4), 286-318. https://doi: 10.1108/17576380911050043

Brownbridge, M. (1996). Government Policies and the Development of Banking in Kenya. Institute of Development Studies at the University of Sussex, Working Paper 29.

Bryman, A. (2012). Social Research Methods (4th Ed.). Oxford University Press.

Caprio, G., & Klingebiel, D. (1997). Bank Insolvency: Bad Luck, Bad Policy or Bad Banking? Annual World Bank Conference on Development Economics, The International Bank for Reconstruction and development/The World Bank.

Cecchetti, S. G., King, M.R., & Yetman, J. (2011). “Weathering the Financial Crisis: Good policy or Good Luck?”. Bank for International Settlement. Working paper, 351.

Cleary, S., & Hebb, G. (2016). An efficient and functional model for predicting bank distress: In and out of sample evidence. Journal of Banking & Finance, 64(C), 101-111. https://

Cochran, J. P., Call, S. T., & Glahe, F.R. (1999). Credit Creation or Financial Intermediation?: Fractional Reserve Banking in a growing Economy. The Quarterly Journal of
Austrian Economics, 2(3), 53-64. https://doi: 10.1007/s12113-999-1020-0

Cucinelli, D. (2015). The impact of non-performing Loans on Bank Lending Behaviour: Evidence from the Italian Banking Sector. Eurasian Journal of Business &

Economics, 8(16), 59-71. https://doi: 10.17015/ejbe.2015.016.04

Daumont, R., Gall, F., & Leroux, F. (2004). Banking in Sub-Saharan Africa: What Went Wrong? IMF Working paper WP/04/55.

Demirguc-Kunt, A., & Detragiache, E. (1998). The Determinants of Banking Crises in Developing and Developed Counties. IMF Staff Paper, 45(1).

Disalvo, J., & Johnston, R. (2017). The Rise in Loan to Deposit Ratios: Is 80 the New 60?. Economic Insights, Federal Reserve Bank of Philadelphia, Research Department. 2(3), Third Quarter, 18-23.

End, J. W. D. (2016). A Macroprudential approach to address Liquidity risk with the loan to deposit ratio. The European Journal of Finance, 22(3), 237-253. https://doi.org/10.1080/1351847X.2014.983137

Fahlenbrach, R., Prilmeier, R., & Stulz, R.M. (2018). Why Does Fast Loan Growth Predict Poor Performance for Banks? Review of Financial Studies, 31(3), 1014-1063. https://doi.org/10.1093/rfs/hhx109

Fama, E.F., & Jensen, M. C. (1983). Agency Problems and Residual claims. Journal of Law & Economics, XXVI, 327-349.

Fofack, H. (2005). Non-performing loans in Sub-saharan Africa: Causal analysis and macroeconomic implications. World Bank Policy Research Paper 3769.

Foos, D., Norden, L., & Weber, M. (2010). Loan Growth and Riskiness of Banks. Journal of Banking & Finance, 34(12), 2929-2940. https://doi.org/10.1016/j.jbankfin.2010.06.007

Gorton, G., & Schmid, F. (1999). Corporate Governance, ownership dispersion and efficiency: Empirical evidence from Austrian cooperative banking. Journal of Corporate Finance, 5(2), 119-140.
Government of Kenya, The Banking Act, Chapter 488. Laws of Kenya.

Granja, J., Matvos, G., Seru, A. (2017). Selling Failed Banks, The Journal of Finance, LXXII (4),1723-1784. https://doi.org/10.1111/jofi.12512

Grodecka-Messi, A., Kenny, S., & Ogren, A. (2018). Predictors of Bank Distress: The 1907 Crisis in Sweden. Sveriges Riksbank Working Paper Series No. 358.

Gujarati, D.N., & Porter, D.C. (2009). Basic Econometrics. (5th Ed.). McGraw-Hill International Edition.

Heffernan, S. (2009). Modern Banking. John Wiley & Sons Ltd.

Ho, P., Huang, C., Lin, C., & Yen, J. (2016). CEO overconfidence and financial crisis: Evidence from bank lending and Leverage. Journal of Financial Economics, 120(1), 194-209.

Iftikhar, S. F. (2015). Financial Reforms and Financial Fragility: A Panel Data Analysis. International Journal of Financial Studies, 3(2), 1-18. https//doi:10.3390/ijfs3020084

Jensen, M. C. (1986). Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers. The American Economic Review, 76(2), 323-329. https://www.jstor.org/stable/1818789

Jin, J., Kanagaretnam, K., & Lobo, G.J. (2018). Discretion in bank loss allowance, risk taking and earnings management. Accounting and Finance, 58(1), 171-193. https://doi.org/10.1111/acfi.12210

Jones, J.S., Lee, W.Y., & Yeager, T.J. (2012). Opaque Banks, Price Discovery, and Financial Instability. Journal of Financial Intermediation, 21(3), 383-408. https://doi.org/10.1016/j.jfi.2012.01.004

Kazandjieva-Yordanova, I.P. (2017). Does the Too Big To Fail Doctrine Have a Future? Economic Alternatives, 1, 51-78.

Kedir, A. M., Iftikhar, S.F., Murinde, V., & Kamgnia, B. D. (2018). Bank fragility in Africa: GMM dynamic panel data evidence. Transnational Corporations Review. Http://doi.org/10.1080/19186444.2018.1475105.

Laeven, L. (2011) Banking Crises: A Review. Annual Review of Financial Economics, 3, 17-40. https://doi.org/10.1146/annurev-financial-102710-144816

Logan, A. (2001). The United Kingdom’s small banks’ crisis of the early 1990s: What were the leading indicators of failure? Bank of England Working paper No. 139.

Lu, W., & Whidbee, D.A. (2016). US bank failure and bailout during the financial crisis: Examining the determinants of regulatory intervention decisions. Journal of Financial Economic Policy, 8(3), 316-347. https://doi.org/10.1108/JFEP-02-2016-0011

McLeay, M., Radia, A., & Thomas, R. (2014). Money Creation in the Modern economy. Bank of England Quarterly Bulletin, Q1.

Meera, A. K. M., & Larbani, M. (2009). Ownership effects of fractional reserve banking: An Islamic Perspective. Humanomics, 25(2), 101-116. https://doi.org/10.1108/08288660910964175

Messai, A. S., & Gallali, M.I. (2015). Financial Leading indicators of Banking Distress: A Microprudential Approach. Evidence from Europe. Asian Social Science, 11(21), 78-90. https://doi.10.5539/ass.v11n21p78

Olivier, J., & Norberg, M.M. (2010). Positively Skewed Data: Revisiting the Box-Cox Power Transformation. International Journal of Psychological Research, 3(1), 68-75.

Oordt, M. V., & Zhou, C. (2018). Systemic risk and bank business models. Journal of Applied Econometrics, 34(3), 365-384. https://doi.org/10.1002/jae.2666

Osborne, J. (2010). Improving your data Transformation: Applying the Box-Cox Transformation. Practical Assessment, Research, and Evaluation, 15(15), 1-9

Rauch, C. (2010). Bank Fragility and The Financial Crisis: Evidence from the U.S. Dual Banking System, in International Banking in the New Era: Post Crisis Challenges and Opportunities. International Finance Review, 11, 33-86. https://doi.org/10.1108/S1569-3767(2010)0000011006

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students, (5th Edition.). FT Prentice Hall.

Schumpeter, J.A. (2016). Bank Credit and the creation of deposits. Journal of Accounting, Economics and Law: A Convivium, 6(2), 151-159. https://doi.org/10.1515/ael-2016-0012

Shen, C., & Chen, C. (2008). Causality Between Banking and Currency Fragility: A Dynamic Panel Model. Global Finance Journal, 19(2), 85-101. https://doi.org/10.1016/j.gfj.2007.11.003.

Turner, A. (2012). Credit creation and social optimality, International Review of Financial Analysis, 25, 142-153. https://doi.org/10.1016/j.irfa.2012.09.004

Werner, R.A. (2014). Can banks individually create money out of nothing? The theories and the empirical evidence. International Review of Financial Analysis, 36, 1-19. https://doi.10.1016/j.irfa.2014.07.015

Werner, R.A. (2016). A lost century in economics: Three theories of banking and the conclusive evidence. International Review of Financial Analysis, 46, 361-379. https://doi.org/10.1016/j.irfa.2015.08.014.
Published
2021-05-08
How to Cite
Bwire, A., Tenai, J., & Odunga, R. (2021, May 8). Loan Growth, Loan Deposit Ratio and Prediction of Bank Fragility in Kenya Using Generalised Linear Model. African Journal of Education,Science and Technology, 6(3), Pg 103-113. Retrieved from http://ajest.info/index.php/ajest/article/view/536
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