Loan Ratios, Information Asymmetry and Fragility among Banks in Kenya
Keywords:
Loan ratios. Information asymmetry. Adverse Selection. Bank fragility
Abstract
The goal of the research was to establish the mediating role of information asymmetry on loan ratios and fragility among commercial banks in Kenya. The study utilized explanatory research design. The population was forty-two commercial banks, however following exclusions number declined to thirty. Evidence highlights loan ratios have predictive abilities in identifying fragility among commercial banks in Kenya. Log total assets (logta) partially mediates the relationship between loan ratios and bank fragility. Information asymmetry therefore has a role in bank fragility. The study brings to the fore matters’ worth of future study. That the log of total assets partially mediates the relationship between loan ratios and fragility among commercial banks in Kenya. Size has implications on information disclosure by banks. The ability to predict fragility has socio-economic benefits to the country and other bank stakeholders. This research mainstreams the role of information asymmetry in bank fragility studies with bank’s asset side of the balance sheet as the focus
References
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Akerlof, G. A. (1970). The Market for ‘Lemons’: Quality uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), 488-500. https://www.jstor.org/stable/1879431
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
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Asongu, S., & Nwachukwu, J. (2018). Bank Size, Information Sharing and Financial Access in Africa. International. Journal of Managerial Finance, 24(4), 188-209. https://doi10.1108/IJMF-08-2017-0179
Baltagi, B. H. (2005). Econometric Analysis of Panel Data (3rd Ed.). John Wiley & Sons Ltd.
Baron, R. M., & Kenny, D. A. (1986). The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. The Journal of Personality and Social Psychology, 51(6), 1173-1182. https://doi: 10.1037//0022-3514.51.6.1173
Bartov, E., & Bodnar, G. M. (1996). Alternative Accounting Methods, Information Asymmetry and Liquidity: Theory and Evidence. The Accounting Review, 71(3), 397-418. https://www.jstor.org/stable/248295
Basu, S. (2003). Why do Banks Fail?, International Review of Applied Economics, 17(3), 231-248. https://doi.org/10.1080/0269217032000090469
Berger, A. N., & Davies, S. M. (1998). The Information Content of Bank Examination. Journal of Financial Services Research, 14(2), 117-144.
Bhattacharya, N., Ecker, F., Olsson, P.M., & Schipper, K. (2012). Direct and mediated associations among earnings quality, information asymmetry, and cost of equity. The Accounting Review, 87(2), 449-482. https://doi.org/10.2308/accr-10200
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.
Bleck, A. (2018). Regulating Bank Leverage. Journal of Financial Economic Policy, 10(2), 264-274. https://doi.org/10.1108/JFEP-12-2017-0122
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.
Central Bank of Kenya Act 1966. (September 2018). Retrieved from http://www.kenyalaw.org
Chae, J. (2005). Trading volume, information asymmetry and timing information, The Journal of Finance, LX(1), 413-442. https://www.jstor.org/stable/3694843
Claus, I., & Grimes, A. (2003). Asymmetric Information, Financial Intermediation and the Monetary Transmission Mechanism: A critical Review. New Zealand Treasury, Working Paper, 03/19.
Cressy, R., & Otto, T. (2001). Is there adverse selection in the credit market? Venture Capital: An International Journal of Entrepreneurial Finance, 3(3), 215-238.
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 from Euro area Countries. Finance Research Letters, 18, 116-119. https://doi: 10.1016/j.frl.2016.04.008
Federal Reserve Bank of Kansas City. (2016). Basics for Bank Directors. www.bankdirectorsdesktop.org.
Francis, J., LaFond, R., Olsson, P., & Schipper, K. (2005). The Market Pricing of Accruals Quality. Journal of Accounting and Economics, 39(2), 295-327. doi:10.1016/j.jacceco.2004.06.003
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.
Gonzalez-Hermosillo, B., Pazarbasioglu, C., Billings, R. (1997). Determinants of Banking System Fragility: A Case Study of Mexico. IMF Staff Papers, 44(3), 295-314.
Helwege, J., & Liang, N. (1996). Is there a pecking order? Evidence from a panel of IPO firms. Journal of Financial Economics, 40(3), 429-458.
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
James, C. (1991). The Losses Realised in Bank Failures. The Journal of Finance, XLVI(4), 1223-1242. https://doi.org/10.1111/j.1540-6261.1991.tb04616.x
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
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.
Keele, L., & Kelly, N.J. (2006). Dynamic Models for Dynamic Theories: The Ins and Outs of Lagged Dependent Variables. Political Analysis, 14(2), 186-205. https://doi.org/10.1093/pan/mpj006
Kerstein, J., & Kozberg, A. (2013). Using Accounting proxies of proprietary FDIC ratings to predict Bank failures and enforcement actions during the recent financial crisis, Journal of Accounting, Auditing & Finance, 28(2), 128-151. https//doi. 10.1177/2150129713478846
Krishnaswami, S., & Subramaniam, V. (1999). Information Asymmetry, valuation, and the Corporate Spin-off decision. Journal of Financial Economics, 53(1), 73-112. https://doi.org/10.1016/S0304-405X(99)00017-3
LaPorta, R., Lopez-De-Silanes, F., & Zamarripa, G. (2003). Related Lending. The Quarterly Journal of Economics, 118(1), 231-268.
Leary, M.T., & Roberts, M.R. (2010). The Pecking Order, Debt Capacity, and Information Asymmetry. Journal of Financial Economics, 95(3), 332-355. https://doi.org/10.1016/j.jfineco.2009.10.009
Lee, G., & Masulis, R.W. (2009). Seasoned Equity Offerings: Quality of Accounting Information and Expected Floatation Costs. Journal of Financial Economics, 92(3), 443-469. https://doi.org/10.1016/j.jfineco.2008.04.010
Lo, S., & Andrews, S. (2015). To transform or not to transform: Using generalised linear mixed models to analyse reaction time data. Frontiers in Psychology, 6.
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.
Mamonov, M. (2018). Bank’s Hiden Negative Capital Before and After the Senior Management Change at the Bank of Russia. Russia Journal of Money & Finance, 77(1), 51-70. DOI: 10.31477/rjmf.201801.51
Mannasoo, K., & Mayes, D. (2009). Explaining Bank Distress in Eastern European Transition Economies. Journal of Banking & Finance, 33(2), 244-253. https://doi.org/10.1016/j.jbankfin.2008.07.016
Mishkin, F.S. (1991). Asymmetric Information and Financial Crises: A Historical Perspective. National Bureau of Economic Research Working paper, 69-108.
Morris, S., & Shin, H.S. (2012). Contagious Adverse Selection. American Economic Journal: Macroeconomics, 4(1), 1-21. omics 2012, 4(1): 1–21 http://dx.doi.org/10.1257/mac.4.1.1
Murinde, V. (2012). Financial Development and Economic Growth: Global and African Evidence. Journal of African Economies, 21(2), i10-i56. https://doi.org/10.1093/jae/ejr042
Olivier, J., & Norberg, M.M. (2010). Positively Skewed Data: Revisiting the Box-Cox Power Transformation. International Journal of Psychological Research, 3(1), 68-75.
Osborne, J. (2010). Improving your data Transformation: Applying the Box-Cox Transformation. Practical Assessment, Research, and Evaluation, 15(15), 1-9
Preacher, K.J., & Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments & Computers, 36(4), 717-731.
Rothschild, M., & Stigliz, J. (1976). Equilibrium in competitive insurance markets: An essay on the economics of imperfect information. Quarterly Journal of Economics, 14, 259-280. https://doi.org/10.1007/978-94-015-7957-
5_18.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students, (5th Edition.). FT Prentice Hall.
Schluchter, M.D. (2008). Flexible Approaches to Computing Mediated Effects in Generalised Linear Models: Generalized Estimating Equations and Bootstrapping, Multivariate Behavioral Research, 43(2), 268-288.
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
Spence, M. (1973). Job market signalling. The Quarterly Journal of Economics, 87(3), 355-374
Thomson, J.B. (1991). Predicting Bank failures in the 1980s. Federal Reserve Bank of Cleveland, Economic Review, 27(1), 9-20
Yoon, H., Zo, H., & Ciganek, A.P. (2011). Does XBRL adoption reduce Information Asymmetry? Journal of Business Research, 64(2), 157-163. https://doi.org/10.1016/j.jbusres.2010.01.008
Zhang, D., Cai, J., Dickinson, D.G., & Kutan, A.M. (2016). Non-performing Loans, Moral Hazard and Regulation of the Chinese Commercial Banking System. Journal of Banking & Finance, 63, 48-60. https://doi.org/10.1016/j.jbankfin.2015.11.010
Zhao, X., Lynch, J.G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197-206. http://dx.doi.org/10.1086/651257
Akerlof, G. A. (1970). The Market for ‘Lemons’: Quality uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), 488-500. https://www.jstor.org/stable/1879431
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
Armstrong, C. S., Core, J.E., Taylor, D.J., & Verrecchia, R.E. (2011). When Does Information Asymmetry Affect the Cost of Capital? Journal of Accounting Research, 49(1), 1-40. https://doi.org/10.1111/j.1475-679X.2010.00391.x
Asongu, S., & Nwachukwu, J. (2018). Bank Size, Information Sharing and Financial Access in Africa. International. Journal of Managerial Finance, 24(4), 188-209. https://doi10.1108/IJMF-08-2017-0179
Baltagi, B. H. (2005). Econometric Analysis of Panel Data (3rd Ed.). John Wiley & Sons Ltd.
Baron, R. M., & Kenny, D. A. (1986). The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. The Journal of Personality and Social Psychology, 51(6), 1173-1182. https://doi: 10.1037//0022-3514.51.6.1173
Bartov, E., & Bodnar, G. M. (1996). Alternative Accounting Methods, Information Asymmetry and Liquidity: Theory and Evidence. The Accounting Review, 71(3), 397-418. https://www.jstor.org/stable/248295
Basu, S. (2003). Why do Banks Fail?, International Review of Applied Economics, 17(3), 231-248. https://doi.org/10.1080/0269217032000090469
Berger, A. N., & Davies, S. M. (1998). The Information Content of Bank Examination. Journal of Financial Services Research, 14(2), 117-144.
Bhattacharya, N., Ecker, F., Olsson, P.M., & Schipper, K. (2012). Direct and mediated associations among earnings quality, information asymmetry, and cost of equity. The Accounting Review, 87(2), 449-482. https://doi.org/10.2308/accr-10200
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.
Bleck, A. (2018). Regulating Bank Leverage. Journal of Financial Economic Policy, 10(2), 264-274. https://doi.org/10.1108/JFEP-12-2017-0122
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.
Central Bank of Kenya Act 1966. (September 2018). Retrieved from http://www.kenyalaw.org
Chae, J. (2005). Trading volume, information asymmetry and timing information, The Journal of Finance, LX(1), 413-442. https://www.jstor.org/stable/3694843
Claus, I., & Grimes, A. (2003). Asymmetric Information, Financial Intermediation and the Monetary Transmission Mechanism: A critical Review. New Zealand Treasury, Working Paper, 03/19.
Cressy, R., & Otto, T. (2001). Is there adverse selection in the credit market? Venture Capital: An International Journal of Entrepreneurial Finance, 3(3), 215-238.
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 from Euro area Countries. Finance Research Letters, 18, 116-119. https://doi: 10.1016/j.frl.2016.04.008
Federal Reserve Bank of Kansas City. (2016). Basics for Bank Directors. www.bankdirectorsdesktop.org.
Francis, J., LaFond, R., Olsson, P., & Schipper, K. (2005). The Market Pricing of Accruals Quality. Journal of Accounting and Economics, 39(2), 295-327. doi:10.1016/j.jacceco.2004.06.003
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.
Gonzalez-Hermosillo, B., Pazarbasioglu, C., Billings, R. (1997). Determinants of Banking System Fragility: A Case Study of Mexico. IMF Staff Papers, 44(3), 295-314.
Helwege, J., & Liang, N. (1996). Is there a pecking order? Evidence from a panel of IPO firms. Journal of Financial Economics, 40(3), 429-458.
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
James, C. (1991). The Losses Realised in Bank Failures. The Journal of Finance, XLVI(4), 1223-1242. https://doi.org/10.1111/j.1540-6261.1991.tb04616.x
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
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.
Keele, L., & Kelly, N.J. (2006). Dynamic Models for Dynamic Theories: The Ins and Outs of Lagged Dependent Variables. Political Analysis, 14(2), 186-205. https://doi.org/10.1093/pan/mpj006
Kerstein, J., & Kozberg, A. (2013). Using Accounting proxies of proprietary FDIC ratings to predict Bank failures and enforcement actions during the recent financial crisis, Journal of Accounting, Auditing & Finance, 28(2), 128-151. https//doi. 10.1177/2150129713478846
Krishnaswami, S., & Subramaniam, V. (1999). Information Asymmetry, valuation, and the Corporate Spin-off decision. Journal of Financial Economics, 53(1), 73-112. https://doi.org/10.1016/S0304-405X(99)00017-3
LaPorta, R., Lopez-De-Silanes, F., & Zamarripa, G. (2003). Related Lending. The Quarterly Journal of Economics, 118(1), 231-268.
Leary, M.T., & Roberts, M.R. (2010). The Pecking Order, Debt Capacity, and Information Asymmetry. Journal of Financial Economics, 95(3), 332-355. https://doi.org/10.1016/j.jfineco.2009.10.009
Lee, G., & Masulis, R.W. (2009). Seasoned Equity Offerings: Quality of Accounting Information and Expected Floatation Costs. Journal of Financial Economics, 92(3), 443-469. https://doi.org/10.1016/j.jfineco.2008.04.010
Lo, S., & Andrews, S. (2015). To transform or not to transform: Using generalised linear mixed models to analyse reaction time data. Frontiers in Psychology, 6.
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.
Mamonov, M. (2018). Bank’s Hiden Negative Capital Before and After the Senior Management Change at the Bank of Russia. Russia Journal of Money & Finance, 77(1), 51-70. DOI: 10.31477/rjmf.201801.51
Mannasoo, K., & Mayes, D. (2009). Explaining Bank Distress in Eastern European Transition Economies. Journal of Banking & Finance, 33(2), 244-253. https://doi.org/10.1016/j.jbankfin.2008.07.016
Mishkin, F.S. (1991). Asymmetric Information and Financial Crises: A Historical Perspective. National Bureau of Economic Research Working paper, 69-108.
Morris, S., & Shin, H.S. (2012). Contagious Adverse Selection. American Economic Journal: Macroeconomics, 4(1), 1-21. omics 2012, 4(1): 1–21 http://dx.doi.org/10.1257/mac.4.1.1
Murinde, V. (2012). Financial Development and Economic Growth: Global and African Evidence. Journal of African Economies, 21(2), i10-i56. https://doi.org/10.1093/jae/ejr042
Olivier, J., & Norberg, M.M. (2010). Positively Skewed Data: Revisiting the Box-Cox Power Transformation. International Journal of Psychological Research, 3(1), 68-75.
Osborne, J. (2010). Improving your data Transformation: Applying the Box-Cox Transformation. Practical Assessment, Research, and Evaluation, 15(15), 1-9
Preacher, K.J., & Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments & Computers, 36(4), 717-731.
Rothschild, M., & Stigliz, J. (1976). Equilibrium in competitive insurance markets: An essay on the economics of imperfect information. Quarterly Journal of Economics, 14, 259-280. https://doi.org/10.1007/978-94-015-7957-
5_18.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students, (5th Edition.). FT Prentice Hall.
Schluchter, M.D. (2008). Flexible Approaches to Computing Mediated Effects in Generalised Linear Models: Generalized Estimating Equations and Bootstrapping, Multivariate Behavioral Research, 43(2), 268-288.
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
Spence, M. (1973). Job market signalling. The Quarterly Journal of Economics, 87(3), 355-374
Thomson, J.B. (1991). Predicting Bank failures in the 1980s. Federal Reserve Bank of Cleveland, Economic Review, 27(1), 9-20
Yoon, H., Zo, H., & Ciganek, A.P. (2011). Does XBRL adoption reduce Information Asymmetry? Journal of Business Research, 64(2), 157-163. https://doi.org/10.1016/j.jbusres.2010.01.008
Zhang, D., Cai, J., Dickinson, D.G., & Kutan, A.M. (2016). Non-performing Loans, Moral Hazard and Regulation of the Chinese Commercial Banking System. Journal of Banking & Finance, 63, 48-60. https://doi.org/10.1016/j.jbankfin.2015.11.010
Zhao, X., Lynch, J.G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197-206. http://dx.doi.org/10.1086/651257
Published
2022-06-28
How to Cite
Bwire, A. (2022, June 28). Loan Ratios, Information Asymmetry and Fragility among Banks in Kenya. African Journal of Education,Science and Technology, 7(1), Pg 261-276. https://doi.org/https://doi.org/10.2022/ajest.v7i1.770
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