Credit Survey Information and Commercial Banks’ Lending to Non-Financial Corporate Sector in Kenya
Mwangi, Maina Samuel
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While Non-Financial Corporate Sector in Kenya finances most of its investment from borrowed funds particularly from commercial banks, the growth rate of lending by commercial banks to Non-Financial Corporate Sector in Kenya has been on a significant slowdown. It has declined from 30.5 percent in 2011 to 4.3 percent in 2018. This slowdown is a concern among both the government and Non-Financial Corporate Sector on the ability of commercial banks in Kenya to fund Kenya‟s overall investment needs.The slump of commercial banks‟ lending arises from both demand-side and supply-side factors. However, a gap that has remained unexplored in literature is whether commercial banks‟ lending to the Non-Financial Corporate Sector is penchant to the variations in the supply of credit by the commercial banks or the changes in demand of credit partly owing to the fact that credit demand and credit supply are not directly observable variables. This study sought to assess the relationship between credit survey information and commercial banks‟ lending to the Non-Financial Corporate Sector. The study used information contained in credit survey reports that enabled separation of the effect of credit demand, non-performing loans and the effect of credit standards on commercial banks‟ lending to Non-Financial Corporate Sector in Kenya. Additionally, the study tested the moderating effect of lending to the government by commercial banks on the link between credit survey information and commercial banks‟ lending to the non-financial corporate sectors in Kenya. Credit rationing theory and portfolio theory underpin this study. The study used secondary data extracted from reports prepared by the Central Bank of Kenya and Kenya National Bureau of Statistics. Data was collected only after the issue of authorization letter by Kenyatta University as well as a research permit by the National Commission for Science, Technology and Innovation. The data obtained was analyzed using a random effects panel model as supported by Hausman test using gretl software. Prior to the model estimation, various diagnostic tests such as unit-root tests and normality test were conducted to avoid model mis-specification. The descriptive statistics revealed that on average, commercial banks always tightens their lending standards. However, based on the regression results, credit standards do not significantly influence commercial banks‟ lending to Non-Financial Corporate Sector in Kenya. In respect to credit demand, the regression results indicate that increase in the percentage of commercial banks reporting a net increase in credit demand results in an increase in the growth rate of total lending by commercial banks to the Non-Financial Corporate Sector in Kenya. The regression results further indicated that non-performing loans in respect to loans issued by commercial banks in the second immediate past quarter negatively influence the growth of commercial banks‟ lending to the Non-Financial Corporate Sector in the current quarter. Considering the effects of commercial banks‟ lending to the government, the study established that it has no moderating effect on the relationship between credit survey information and commercial banks‟ lending to the non-financial corporate sectors in Kenya. Based on the study‟s empirical results, the study recommends that the government should play a role in assisting the Non-Financial Corporate Sector in Kenya increase their credit demand from commercial banks. This should involve focusing on the factors influencing credit demand such as employment rate, public investment, and exchange rates. In addition, the study recommends that when commercial banks are lending to the Non-Financial Corporate Sector, they should focus on the repayment plan of the loan including the expected future cash flows to repay the principal amount and the interest as and when they fall due. The study further recommends that the Central Bank of Kenya adjust its credit survey to cover quantitative data. This will enable researchers conduct a more detailed study on the extent to which credit demand influence commercial banks‟ lending.