Asset structure, leverage, and value of listed firms: Evidence from Kenya


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Firm value shows the performance of a firm while reflecting the present value of the firm’s future cashflows, hence affecting investment decisions. Therefore, this paper explores the relationship between asset structure, leverage, and firm value of 51 listed companies between 2010 and 2019 using secondary data collected from audited financial statements. The study applies panel data regression models and the causal-comparative research design. The quantitative data are analyzed using multiple regression. The result shows that plant, equipment, property, current, and financial assets influence the firm value positively. Nonetheless, the quotient of current to total assets was reported to yield the highest beta coefficient, implying that significant firm value creation is realized for every additional current asset held, weighed against the quotient of additional equipment, property, and plant to the value of total assets. Leverage had an insignificant influence on the value of firms, implying that no maximization of value is attainable in manufacturing firms through the astute use of borrowed funds. The study recommends that finance pundits consider firms’ asset structure and the use of borrowed funds when formulating financial and investment policies. The study enriches the scholarly world by developing a model for establishing the value of listed firms.

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    • Table 1. Measurement of variables
    • Table 2. Stationarity test results
    • Table 3. Normality test results
    • Table 4. Heteroscedasticity test: Breusch-Pagan-Godfrey
    • Table 5. Variance inflation factor test results
    • Table 6. Autocorrelation test derives
    • Table 7. Model specification test results
    • Table 8. Data characteristics
    • Table 9. Correlation matrix
    • Table 10. Goodness of fit of the model
    • Table 11. Independent variables and dependent variables: Individual level of significance of the variables
    • Conceptualization
      Barine Nkonge Habakkuk
    • Data curation
      Barine Nkonge Habakkuk
    • Formal Analysis
      Barine Nkonge Habakkuk
    • Funding acquisition
      Barine Nkonge Habakkuk
    • Investigation
      Barine Nkonge Habakkuk
    • Methodology
      Barine Nkonge Habakkuk
    • Project administration
      Barine Nkonge Habakkuk
    • Resources
      Barine Nkonge Habakkuk
    • Software
      Barine Nkonge Habakkuk, Kariuki Samuel Nduati, Kariuki Peter Wang’ombe
    • Validation
      Barine Nkonge Habakkuk, Kariuki Samuel Nduati, Kariuki Peter Wang’ombe
    • Visualization
      Barine Nkonge Habakkuk, Kariuki Samuel Nduati, Kariuki Peter Wang’ombe
    • Writing – original draft
      Barine Nkonge Habakkuk
    • Writing – review & editing
      Barine Nkonge Habakkuk
    • Supervision
      Kariuki Samuel Nduati, Kariuki Peter Wang’ombe