Asset and Liability Management, Quality of Financial Reporting and Financial Performance of Manufacturing Firms in the Building and Construction Sector in Kenya

Abstract

All business organizations including those in the building and construction sector are always concerned about their financial performance. Despite the concern for financial performance in general and profitability in particular, it is still not clear how the management of assets and liabilities affects the financial performance of manufacturing companies in the building and construction sector in Kenya. The variations in the asset and liability management policies across the industry is reflected in the variations in the asset and liability structures. There is lack of empirical and theoretical clarity as to how the asset and liability management influences profitability of these companies. Empirically, extant research arrives at conflicting findings as to how asset management is related to financial performance. Theoretically, whereas the portfolio theory of Markowtz (1952) recommend optimal asset and liability structuring to minimize risk and therefore boost performance, the agency theory of Jensen and Meckling (1976) on the other hand fail to pinpoint a clear association between the asset and liability structures and financial performance. The trade-off theory of Gitman (1974) and asset finance matching theory of Sagan (1955) imply an inverse relationship between asset and liability structures and profitability. This study is designed as a causal exploratory survey using a census of manufacturing companies in the building and construction sector in Kenya as listed by the Kenya Association of Manufacturers subject to their reporting dates and data availability which translates to a sample of 44 companies. It pursues five objectives relating to establishing the effect of management of current assets, current liabilities, fixed assets and long term liabilities on the financial performance of the study companies. Further it aims to check how the quality of financial reporting moderates this established ex-ante relationship between the management of assets and liabilities on one hand and financial performance on the other. It is carried over a 5 year period covering 2016 to 2020 and is rooted in the positivism philosophy of research. This forms 220 firm-year observations. Bivariate and multivariate linear panel regression models are adopted after conducting model specification tests. The indicators used in the study are current asset structure (CAS) for current asset management; current liability structure (CLS) for current liability management; fixed assets turnover (FAT) for non-current asset management; long term liabilities turnover (TLT) for long term liability management and return on equity (ROE) for financial performance. The tests of hypotheses were conducted using the t-statistic at 95% confidence interval. At the descriptive level, the firms are shown to have a moderate to high quality of financial reporting but moderate to poor levels of financial performance. At the inferential level, the findings reveal that at the bivariate level current asset structure has a positive effect on financial performance and that both current liability structure and fixed assets turnover have positive effects on financial performance. Long term liability turnover is found to have no effect on such performance. At the multivariate level, CAS and TLT have a negative effect while CLS and FAT have a positive effect on financial performance of manufacturing companies in the building and construction sector in Kenya. At the joint level, the quality of financial reporting has a positive moderation influence on the effect of asset and liability management on financial performance except for current assets management, where the moderating influence is negative. The findings support the trade-off theory with respect to asset management and the agency theory with respect to liability management. The study was limited to the firms listed by the Kenya Association of Manufacturers in the building and construction sector and recommends an enhanced sample for all company sizes to check out if the findings are generalizable to other sets of companies outside of the manufacturing ones.