LONG TERM LIABILITIES AND FINANCIAL PERFORMANCE OF NON-FINANCIAL FIRMS LISTED AT NAIROBI SECURITIES EXCHANGE, KENYA
LONG TERM LIABILITIES AND FINANCIAL PERFORMANCE OF NON-FINANCIAL FIRMS LISTED AT NAIROBI SECURITIES EXCHANGE, KENYA
Timothy Cheruiyot Bett - Student, Department of Economics, Accounting and Finance, School of Business and Economics, Jomo-Kenyatta University of Agriculture and Technology, Kenya
Oluoch Oluoch - Lecturer, Department of Economics, Accounting and Finance, School of Business and Economics, Jomo-Kenyatta University of Agriculture and Technology, Kenya
Tumaini Mwikamba - Lecturer, Department of Economics, Accounting and Finance, School of Business and Economics, Jomo-Kenyatta University of Agriculture and Technology, Kenya
Cythia Waga - Lecturer, Department of Economics, Accounting and Finance, School of Business and Economics, Jomo-Kenyatta University of Agriculture and Technology, Kenya
ABSTRACT
Despite the fact that in Kenya, many firms have tried to undertake their operations prudently using cost-effective strategies, those firms have ended up liquidated or exiting the market due to inappropriately stretching their financial brawns and wrong credit management schemes which in essence is lack of knowledge on suitable financing. Non-financial firms have not been performing well for the last decade the entire period of this study as per the literature for this study hence the purpose of this study. As a general objective, this study sought to evaluate the effects of long term liabilities on financial performance of non-financial firms listed at Nairobi Securities Exchange, Kenya. The 44 non-financial firms listed at the NSE, Kenya for period of a period 12 years between 2012 to 2023 was a target population of interest for this study. This study employed positivism philosophy and ex-post facto research design. The study used secondary data that was obtained from the respective firms’ historical financial reports. The Data was entered into the data collection sheets and later it was entered into EVIEWS v 10.0 for further analysis. Data was then quantitatively analysed using descriptive statistics which included means, standard deviation, maximum values and minimum values. The study further employed the diagnostic tests; stationary, Hausman test, normality, homoscedasticity, serial correlation and multicollinearity was tested. This ensured that the assumptions hold to avoid any misspecifications.
