The Influence of Green Bonds on Financial Performance of Banks and Investment Firms Listed In the Nairobi Securities Exchange in Kenya

Abstract

In the recent years, a high number of firms listed within the Nairobi Securities exchange have registered a decline within the firm’s financial performance. This has resulted to financial difficulties which is contrary to the shareholders’ expectations and adversely affecting the economic process of the Kenyan economy. The selection of a firm’s financial structure and its impact on financial performance remains an excellent dilemma to all or any stakeholders. The Nairobi securities exchange stock market has transitioned the investment sector with an aim of “greening” the mainstream financial market using green bonds. This study investigated the influence of green bonds on financial performance of banks and investment firms listed in the NSE in Kenya. Specifically, the study investigated four major components of green bonds namely; Green Revenue Bonds (GRB), Green Project Bonds (GPB), Securitized Bonds (SB) and Proceed Bonds (PB) as per the green bond principles GBP (2016) on firms’ financial performance. In addition to this, the study evaluated the moderating role of interest rate on financial performance of banks and investment firms listed in the NSE. The study adopted a positivist research philosophical paradigm, which is epistemological and characterized by a theoretical belief that the independent variable affects the level of the dependent variable, from empirically testable hypotheses. An ex-post facto form design was adopted in this study due to the nature of research problem and the quantitative data available. The target population of comprised of all the 17 firms in the banking and investment sector of the NSE from 2012 to 2019 since the first green bond was issued in Kenya. The study employed both primary and secondary data. A census was conducted on the 17 firms which had issued green bonds either directly or indirectly for the period 2012 – 2019. The study used secondary panel data found in the audited financial reports of the companies. Diagnostic tests carried out included Auto-correlation test, Test for normality, Heteroscedasticity test and Unit Root Test. In order to determine the most appropriate model for the study, a Hausman test was conducted. The study used descriptive statistics to determine the spread of data over time, correlation analysis and panel linear multiple regression analysis. Further, the regression coefficients were used for a significance test using F-statistic at 5% level of significance and conclusions drawn. The probability value of the F-test was employed to examine the null hypothesis Finally, the coefficient of determination (R2) was used to rank independent variables’ contribution to the dependent variable. The study found out that green revenue bonds, green proceeds bonds and project had a significant and positive effect on banks and investment firms listed in the NSE in Kenya. Securitized bonds had a negative relationship with banks and investments firm’s financial position and the effect was significant. The overall moderating effect of interest rate on firms’ financial performance increased by 5% after introducing the moderator which explained 12% of changes in firms financial position compared to 7.7% without the moderator. The study concludes that green revenue bonds, green proceeds bonds and project had a significant and positive effect on banks and investment firms listed in the NSE and that the inclusion of green bonds in the financial structure jointly enhanced the financial structure’s power to explain the variations in firms’ financial performance. This study recommends that the Capital markets should boost green bonds investments by improving public awareness and by enacting policies that ensures full disclosure of all green bonds invested by adopting Africa’s 2063 Agenda eight which requires that all Member States strictly follows the new areas of statistical development such as data revolution, big data, and Statistical Data and Metadata exchange (SDMX).