Temporal Dynamics of Internal Financing on Financial Performance within a Corporate Governance-Sustainability Framework. Evidence from Listed Real Sector Non-Financial Firms at the Nairobi Securities Exchange(NSE)

There is growing recognition of the central role corporate governance plays in providing specialized services that align firms towards accountable and transparent financial practices. What is not clear, however, is the conditional effect of corporate governance on the causal link involving internal financing and financial performance. Therefore, this study exploits the principles underlying the Agency and Pecking Order Theories to probe how corporate governance conditions the effect of retained earnings, a popular internal financing source, on the financial performance of real-sector non-financial firms listed at the Nairobi Securities Exchange (NSE). The study employs a causal-explanatory design that targets 51 real-sector non-financial firms listed at the NSE. A sampling frame defined for the period 2016 to 2022 inclusive is used to identify 42 firms with complete and suitable financial records that constituted the secondary data. After running the relevant diagnostic tests, retained earnings had a positive and significant direct effect on financial performance (b=0.653, p<0.001). This effect, however, diminishes on introducing corporate governance. The interaction between retained earnings and corporate governance was positive and significant (b=0.263, p<0.05), an indication that corporate governance strengthened the dynamics of internal financing on financial performance. However, on its own, corporate governance impacted financial performance negatively, showing that embracing corporate governance may be counterproductive in the short term, depending on the firm’s context. This study concludes that sustainable financial performance among real-sector firms is conditional on strong corporate practices infused within internal financing mechanisms. For long-term causality, future research should endeavor to use dynamic panel models.