Financial Structure on Liquidity of Manufacturing Firms Listed in Nairobi Securities Exchange, Kenya
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Date
2023-05
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Kenyatta University
Abstract
Liquidity of a manufacturing firm means a lot for it providesi ai cushioni thati wouldi enablei thei companyi toi survivei ai periodi ofi lowi earningsi duringi whichi thei companyi mighti bei unablei toi accessi capitali markets. Studies, both theoretical and empirical, demonstrate that a firm's financial structure affects the firm's liquidity. However, as a corporation`s liquidity desires are mainly impacted through the character of its operations, a corporation`s liquidity call for will range relying on its unique circumstances. Specifically, the look at was looking to; discover the impact of brief time period debt, long time debt capital and equity capital on liquidity of manufucturing corporations indexed in Nairobi Security Exchange, Kenya.The usage of corporation size forms the moderating factor/ variable. The look at can be pegged on 5 major theories which encompass the Working Capital theory, Modigliani-Miller theorem, the Pecking Order Theory, the Bird in Hand Theory, and the Theory of Optimal Firm Size. The positivist philosophy was used in the current investigation. Explanatory research design was used in the investigation. Nine Firms listed under the Manufacturing and allied sector of the Nairobi Securities Excjange were used as the study population There was no sample frame used in the investigation. Census was utilized because the target population Was below the central limit theorem threshold of normal population. Using a data extraction tool, information on accruals, leases, debentures, preference shares, retained earnings, reserves, cash balances, bank balances, and account payables was gathered. The researcher took care at some stage in records amassing and evaluation to make certain that the cloth given withinside the thesis represents the real records received from the monetary statements of the diverse manufacturing establishments and NSE reports. Diagnostic test for the best linear unbiased estimator was conducted through Multicollinearity test, heteroscedasticity test, normality test and stationarity test was done to reduce data ‘noise’. Data was analyzed by the use of inferential statistics which included bivariate analysis using Pearson correlation and multivariate analysis using static panel regression. Robust Static Panel selection was done using Hausman test, in addition to descriptive statistics, inclusive of mean, mode, general deviation. Finally, the data analysis output were presented by the use of tables as was deemed appropriate. The study concluded that financial structure affects liquidity of listed manufacturing firms in Kenya. Short-term debt is the main factor of financial structure that affects the liquidity of listed manufacturing firms in Kenya. The study further concludes that short-term debt significantly affects liquidity of listed manufacturing firms in Kenya. From the regression analysis, short-term debt showed a strong significant negative effect on cash ratio of the listed manufacturing firms in Kenya. The study concludes that long-term debt has a positive effect on liquidity of listed manufacturing firms in Kenya. Thus, increased long-term debt increases the liquidity of listed manufacturing firms in Kenya. The study concludes that Equity have a significant effect on liquidity of listed manufacturing firms in Kenya. The study threfore concludes that firm size has a significant effect on liquidity of listed manufacturing firms in Kenya. In accordance to the findings in the regression analysis, the study concludes that firm size has a positive effect on the liquidity of listed manufacturing firms in NSE, Kenya. Thus, increased assets base improves the liquidity of manufacturing firms listed in Kenya.
Description
A Research Thesis Report Submitted to Kenyatta University's Department of Accounting and Finance in the School of Business, Economics, and Tourism in Partial Completion of the Requirements for the Award of the Master Degree of Science in Finance, May 2023