Human Capital Efficiency and Firm Value of Listed Manufacturing Firms in Nigeria
Onovayen Erus Evelyn, Okolie Agustine Oke, Okoro Edesiri Godsday
Asian Journal of Economics, Business and Accounting · pp. 122–131 · Published 1 Sep 2026
10.9734/ajeba/2026/v26i92373Abstract
This study examines how Human Capital Efficiency shapes the market value of listed manufacturing firms in Nigeria over the 2012–2024 period, a window selected to reflect the post-IFRS reporting era and ensure comparability across firm disclosures. Guided by six research objectives, the study disaggregates human capital efficiency into five measurable dimensions: Earnings per Employee, Value Added per Employee, Human Capital Return on Investment, Staff Compensation to Revenue Ratio, and Value Added to Staff Ratio. Each dimension is tested individually against Tobin’s Q before their joint effect is examined through a composite Human Capital Efficiency Index, with market capitalisation included as a control variable. An ex post facto design was adopted because the underlying data were historical and drawn entirely from firms’ audited annual reports rather than from any experimental intervention. The population comprised all forty-six manufacturing firms listed on the Nigerian Exchange Group; a purposive sampling strategy based on data adequacy yielded an unbalanced panel of 556 firm-year observations. Descriptive statistics and correlation analysis preceded diagnostic checks for multicollinearity, heteroskedasticity, and model specification, the results of which determined the appropriate estimation technique. Because the Breusch-Pagan test confirmed heteroskedasticity in both models, Panel-Corrected Standard Error regression was selected to correct the standard errors without distorting the coefficient estimates. The findings provide limited support for the individual efficiency proxies, with the Staff Compensation to Revenue Ratio showing the clearest association with market value, suggesting that investors may respond more to tangible workforce investment than to computed efficiency measures alone.
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