Effect of Financial Leverage on Firm Value: Evidence From Selected Firms Quoted on the Nigerian Stock Exchange
Umar Abbas Ibrahim; Abdulqudus Isiaka · 2020 · European Journal of Business and Management
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
This study examined the effect of financial leverage on firm value with evidence from a sample of selected companies quoted on the Nigerian Stock Exchange. The study adopts a panel data analysis using secondary data obtained from the financial statements of the selected companies over the period 2014-2018. The sample of 18 firms studied was selected through the convenient sampling technique. The level of financial leverage was denominated by long term debt to equity ratio. This work is the first Nigerian study to utilize the Tobin’s q ratio as a proxy of firm value. Other variables proven in l
Abstract by Umar Abbas Ibrahim; Abdulqudus Isiaka, European Journal of Business and Management (2020) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
The influence of relational competencies on supply chain resilience: a relational view
Negative / Null Result ReportJob satisfaction and organizational commitment effect in the transformational leadership towards employee performance
Negative / Null Result ReportDynamic capabilities and their indirect impact on firm performance
Negative / Null Result ReportDo Socially Responsible Firms Pay More Taxes?
Negative / Null Result ReportThe Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance
Negative / Null Result ReportPine and Gilmore's Concept of Experience Economy and Its Dimensions: An Empirical Examination in Tourism
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.7176/ejbm/12-3-16
