Nexus Between Insider Loans, Loan Quality and Fragility Among Banks in Kenya
##article.subject##:
Loan quality. Insider loans. Bank fragility. Early Warning System.
##article.abstract##
The aim of the study was to assess the ex-ante predictive ability of Insider loans and Loan quality on fragility among banks in Kenya. Methodology: The study utilised a sample of thirty (30) Commercial Banks with at least five (5) years data for period 2010-2014 before the fragility events of 2015-2016. Data was collected from Central Bank of Kenya. Findings: The lagged dependent variable had significant predictive ability on bank fragility. Insider loan’s ability was not statistically significant inconsistent with findings by Central Bank of Kenya Inspection reports. The loan quality variable was not statistically significant. Using Generalised Linear regression model, lagged dependent variable had b=0.91, z-statistics 8.46, p>z = 0.000; loan quality had b=-0.05, z-statistic -1.20 with p>z=0.229, while insider loans had b=0.39, z-statistics of 1.84, p>z=0.065. At 95% level the lagged dependent variable could explain bank fragility in Kenya. Implications for Research: Most studies in Kenya show ex-post that insider loans are a problem. The study did not however, find evidence that insider loans could predict fragility ex-ante. There is need for continued development of new matrix to identify how insider loans can be useful ex-ante in early warning studies. Due to sophistication of Commercial banking business, loan quality as a measure of dependence on loans had less predictive ability. Policy makers should focus more on additional metrics utilising the non-performing loans as lagged bank fragility variable had good predictive ability. Originality: The study contributes to early warning interventions in bank fragility predicated upon the notion that disruptive instability in banking is cyclic in nature and that bank fragility has negative impact on social-economic welfare of citizens.
References
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Baltagi, B. H. (2005). Econometric Analysis of Panel Data (3rd Ed.). John Wiley & Sons Ltd.
Bernanke, B.S. (1983). Non-monetary effects of the Financial Crisis in the Propagation of the Great Depression. The American Economic Review, 73(3), 257-276. https://www.jstor.org/stable/1808111
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.
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
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Frolov, M. (2006). Is Information Disclosure by Banks Useful for Predicting their Failure? The Case of Japan’s Banking Crisis. KEIO Business Review, 43, 1-22.
Galil, K., Samuel, M., & Shapir, O.M. (2018). Too-Big-To-Fail and the Modelling of Bank Distress. SSRN Electronic Journal. https://ssrn.com/abstracts=3308261.
Gujarati, D.N., & Porter, D.C. (2009). Basic Econometrics. (5th Ed.). McGraw-Hill International Edition.
Heffernan, S. (2009). Modern Banking. John Wiley & Sons Ltd.
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
Jing, Z., & Fang, Y. (2018). Predicting US ban failures: A comparison of Logit and Data mining models, Journal of Forecasting, 37(2), 235-256. https://doi.org/10.1002/for.2487
Kaufmann, G.G. (1988). Bank Runs: Causes, Benefits and Costs. Cato Journal, 7(3), 559-587.
Kenn-Ndubuisi, J. I., & Akani, H.W. (2015). Effects of Recapitalisation on Commercial Banks Survival in Nigeria: Pre and Post CAMEL Analysis. European Journal of Accounting, Auditing and Finance Research, 3(9), 12-30.
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.
Osborne, J. (2010). Improving your data Transformation: Applying the Box-Cox Transformation. Practical Assessment, Research, and Evaluation, 15(15), 1-9
Ott, R. L & Longnecker, M. (2010). An introduction to statistical Methods and Data Analysis. Brooks/Cole (6thEd.). Cengage Learning.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students, (5th Edition.). FT Prentice Hall.
Shaffer, S. (2012). Bank failure risk: Different now? Economic Letters, 116(3), 613-616. https://doi.org/10.1016/j.econlet.2012.06.016
Shehzad, C.T., Haan, J., & Scholtens, B. (2010). The Impact of bank ownership concentration on impaired loans and capital adequacy. Journal of Banking & Finance, 34(2), 399-408. https://doi.org/10.1016/j.jbankfin.2009.08.007
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.
Smith, M. E., Thorpe, R., & Jackson, P. (2012). Management Research (4th Ed.). Sage Publications Ltd.
Thomson, J.B. (1991). Predicting Bank failures in the 1980s. Federal Reserve Bank of Cleveland, Economic Review, 27(1), 9-20
Whalen, G. (1991). A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool. Federal Reserve Bank of Cleveland: Economic Review, 27(1), 21-31.
Wheelock, D.C., & Wilson, P.W. (2000). Why do Banks disappear? The determinants of U.S. Bank
Alston, L. J., Grove, W. A., & Wheelock, D. C. (1994). Why do Banks fail? Evidence from the 1920s. Explorations in Economic History, 31, 409-431. https://ssrn.com/abstract=2271698
Altman, E. I., Cizel, J., & Rijken, H.A. (2014). Anatomy of Bank Distress: The Information Content of Accounting Fundamentals within and Across Countries. Retrieved from https://dx.doi.org/10.2139/ssrn.2504926
Alvarez-Franco, P. B., & Restrepo-Tobon, D.A. (2016). Managerial Efficiency and Failure of U.S. Commercial Banks During the 2007-2009 Financial Crisis: Was this Time Different? Ecos de Economica: A Latin American Journal of Applied economics, 20(43), 5-22. http://dx.doi.org/10.17230/ecos.2016.43.1
Ang, J. S., Cole, R. A., & Lin, J. W. (2000). Agency Costs and Ownership Structure. The Journal of Finance, LV(1), 81-106. https://doi: 10.1111/0022-1082.00201
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
Babajide, A. A., Olokoyo, F.O., & Adegboye, F.B. (2015). Predicting Bank Failures in Nigeria Using Survival Analysis Approach. Journal of South African Business Research. https://doi: 10.5171/2015.965940
Baltagi, B. H. (2005). Econometric Analysis of Panel Data (3rd Ed.). John Wiley & Sons Ltd.
Bernanke, B.S. (1983). Non-monetary effects of the Financial Crisis in the Propagation of the Great Depression. The American Economic Review, 73(3), 257-276. https://www.jstor.org/stable/1808111
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.
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.
Brownbridge, M. (1998). Financial Distress in Local Banks in Kenya, Nigeria, Uganda and Zambia: Causes and Implications for Regulatory Policy. Development Policy Review, 16, 173-188.
Bryman, A. (2012). Social Research Methods (4th Ed.). Oxford University Press.
Calomiris, C.W., & Mason, J. R. (2003). Fundamentals, Panics, and Bank Distress during the Depression. The American Economic Review, 93(5), 1615-1647. https://doi:10.1257/000282803322655473
Central Bank of Kenya Act 1966. (September 2018). Retrieved from http://www.kenyalaw.org
Central Bank of Kenya. (2017). Central Bank of Kenya Bank Supervision Department Annual Report, 2017. http://www.centralbank.go.ke
Chijoriga, M. M. (1999). Political Interventions and Bank Failure in Pre-Liberalised Tanzania. The African Journal of Finance and Management, 9(1), 14-30.
Cihak, M., & Schaeck, K. (2010). How well do aggregate prudential ratios identify banking system problems? Journal of Financial Stability, 6, 130-144.
Clancy, D. K., & Zhao, R. (1999). A Bank Failure Prediction Model Based on Bank Operation Profile. Asia-Pacific Journal of Accounting, 6(2), 255-274. https://doi: 10.1080/10293574.1999.10510565
Daumont, R., Gall, F., & Leroux, F. (2004). Banking in Sub-Saharan Africa: What Went Wrong? IMF Working paper WP/04/55.
Demirguc-Kunt, A. (1989). Deposit institution failures: a review of the empirical literature. Economic Review, Federal Reserve Bank of Cleveland: Economic Review, 25(Q4), 2-18.
DeYoung, R., & Torna, G. (2013). Non-traditional banking activities and bank failures during the financial crisis. Journal of Financial Intermediation, 22(3), 397-421. https://doi.org/10.1016/j.jfi.2013.01.001
Dimitrios, A., Louri, H., & Tsionas, E.M. (2016). Determinants of non-performing loans: Evidence
Flannery, M.J., & Hankins, K. W. (2013). Estimating Dynamic Panel Models in Corporate Finance, Journal of Corporate Finance, 19(C), 1-19. https://doi.org/10.1016/j.jcorpfin.2012.09.004
Fofack, H. (2005). Non-performing loans in Sub-Saharan Africa: Causal analysis and macroeconomic implications. World Bank Policy Research Paper 3769.
Frolov, M. (2006). Is Information Disclosure by Banks Useful for Predicting their Failure? The Case of Japan’s Banking Crisis. KEIO Business Review, 43, 1-22.
Galil, K., Samuel, M., & Shapir, O.M. (2018). Too-Big-To-Fail and the Modelling of Bank Distress. SSRN Electronic Journal. https://ssrn.com/abstracts=3308261.
Gujarati, D.N., & Porter, D.C. (2009). Basic Econometrics. (5th Ed.). McGraw-Hill International Edition.
Heffernan, S. (2009). Modern Banking. John Wiley & Sons Ltd.
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
Jing, Z., & Fang, Y. (2018). Predicting US ban failures: A comparison of Logit and Data mining models, Journal of Forecasting, 37(2), 235-256. https://doi.org/10.1002/for.2487
Kaufmann, G.G. (1988). Bank Runs: Causes, Benefits and Costs. Cato Journal, 7(3), 559-587.
Kenn-Ndubuisi, J. I., & Akani, H.W. (2015). Effects of Recapitalisation on Commercial Banks Survival in Nigeria: Pre and Post CAMEL Analysis. European Journal of Accounting, Auditing and Finance Research, 3(9), 12-30.
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.
Osborne, J. (2010). Improving your data Transformation: Applying the Box-Cox Transformation. Practical Assessment, Research, and Evaluation, 15(15), 1-9
Ott, R. L & Longnecker, M. (2010). An introduction to statistical Methods and Data Analysis. Brooks/Cole (6thEd.). Cengage Learning.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students, (5th Edition.). FT Prentice Hall.
Shaffer, S. (2012). Bank failure risk: Different now? Economic Letters, 116(3), 613-616. https://doi.org/10.1016/j.econlet.2012.06.016
Shehzad, C.T., Haan, J., & Scholtens, B. (2010). The Impact of bank ownership concentration on impaired loans and capital adequacy. Journal of Banking & Finance, 34(2), 399-408. https://doi.org/10.1016/j.jbankfin.2009.08.007
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.
Smith, M. E., Thorpe, R., & Jackson, P. (2012). Management Research (4th Ed.). Sage Publications Ltd.
Thomson, J.B. (1991). Predicting Bank failures in the 1980s. Federal Reserve Bank of Cleveland, Economic Review, 27(1), 9-20
Whalen, G. (1991). A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool. Federal Reserve Bank of Cleveland: Economic Review, 27(1), 21-31.
Wheelock, D.C., & Wilson, P.W. (2000). Why do Banks disappear? The determinants of U.S. Bank
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2021-10-24
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Articles
