Evaluating the influence of leverage and liquidity on the financial performance of general insurance companies in Sub-Saharan Africa
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DOIhttp://dx.doi.org/10.21511/ins.13(1).2022.04
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Article InfoVolume 13 2022, Issue #1, pp. 36-46
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The factors of the insurance industry’s business performance are of concern to a variety of participants in any economy, such as the government, politicians, policyholders, and speculators. There has been very little research on this issue in Sub-Saharan Africa, with the majority focusing on specific factors that influence the performance of insurance businesses. The purpose of this paper was to evaluate the influence of leverage and liquidity on financial performance of general insurance companies in Sub-Saharan Africa. The study used descriptive correlational techniques to obtain panel data across 113 general insurers operating in Sub-Saharan Africa as of December 31, 2019, for 11 years (2008–2019). The pooled OLS, fixed effects and random effects models were estimated with the financial performance measures (proxied by ROA) as the dependent variables where the Hausman test was employed to test the hypothesis. The study found that there is a negative negligible link between leverage and financial performance, whereas there is a positive association between liquidity and financial performance. The study suggested that proper liquidity management is critical for insurance businesses to enhance a company’s value as well as financial success. The focus should be on establishing a proper asset-liability mix, in which a company’s total liabilities do not exceed its total assets. Furthermore, organizations require cash flow policy recommendations to optimize profit potential while limiting liquidity risk in the financial statement.
- Keywords
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JEL Classification (Paper profile tab)C23, G3, L25
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References27
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Tables4
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Figures1
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- Figure 1. Sub-Saharan African countries insurance penetration in 2017
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- Table 1. Panel results for the main objective
- Table 2. Unit root test
- Table 3. Pearson’s correlation between variables
- Table 4. Descriptive statistics
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