Debt Financing and Financial Performance: Evidence from Listed Non-Financial Firms in East Africa Community

Debt Financing and Financial Performance: Evidence from Listed Non-Financial Firms in East Africa Community

John Kanji¹, Duncan Elly Ochieng², Herick Ondigo³, Helen Kinyua⁴

¹Department of Finance and Accounting, Faculty of Business and Management Science, University of Nairobi, Kenya

^2,3Senior Lecturer, Department of Finance and Accounting, Faculty of Business and Management Science, University of Nairobi, Kenya

⁴Lecturer, Department of Finance and Accounting, Faculty of Business and Management Science, University of Nairobi, Kenya.

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000378

Received: 04 August 2025; Accepted: 11 August 2025; Published: 12 September 2025

ABSTRACT

The purpose of this study was to investigate the influence of debt financing on financial performance among East African Community-listed non-financial enterprises. To achieve this goal, secondary data was collected from four East African nations. Throughout the 2011–2020 study periods, the research employed an explanatory research design. The study operationalized debt financing by debt/assets ratio and debt/equity ratio. Financial performance was operationalized by return on assets (ROA) and earnings per share (EPS). Results showed that debt/assets proportion significantly influences financial performance in Kenya, Rwanda, Tanzania, and Uganda. It was also revealed that in Rwanda debt to assets influences earnings per share while it does not influence in Kenya, Tanzania, and Uganda. Thus, the hypothesis that there exists no substantial link amongst debt/asset ratio and financial performance among listed non-financial firms in the East Africa Community was rejected in terms of debt/assets ratio but supported in terms of earnings per share. The study’s findings have expanded our understanding of previously uncharted territory. It validates theories of financial management that suggest concepts related to debt financing and financial performance. It is suggested that future study concentrate on non-East African Community nations. By doing so, it will be possible to ascertain whether the study’s conclusions apply to other parts of Africa.

Keywords: Debt Financing, Financial Performance, Non-Financial Firms in East Africa Community

INTRODUCTION

Background

Debt financing is an essential capital earning source for the company because the retaining of earnings may not be available or may not be sufficient to support business operations (Kose et al., 2020). Debt financing is a significant component affecting working capital (WC), which can affect a company’s financial performance. This happens especially through short-term debt which is a current liability to a firm. Increased short-term debt may reduce working capital which may reduce financial metrics. In order to minimize risks and assure appropriate investment in short-term assets for optimal financial performance, managers strive to manage working capital properly.

According to La Rosa et al, (2018) debt financing offers both benefits, and drawbacks in terms of corporate growth and strategic initiatives. Debt financing has advantages according to Cole and Sokolyk (2018), include the ability to deduct interest from taxes as well as free cash flow limitation; in the same vein, the drawbacks include the possibility of insolvency costs and agency disputes between debt holders and owners. When undertaking debt financing determinations, the management has to find a favorable neutrality amongst the advantages of corporate tax debt financing and financial distress costs resulting from insolvency risks (Altman, Hotchkiss & Wang, 2019), and agency costs (Lucky & Michael, 2019). The fundamental component of debt is the borrower’s obligation to refund with interest money secured from borrowing, together with additional costs for services like origination and any other fees (Harelimana, 2017).

Debt ratios are used to assess debt financing. Debt financing is mainly measured through the debt-to-equity ratio with other ratios like debt ratio assumed by researchers. By dividing an institutions entire total debt by its total assets, debt ratios are computed. According to Margitis and Psillaki (2007), a lower ratio indicates that a corporation has little dependency on debt, while a high percentage indicates an institution is greatly dependent on debt funding. Debt financing can also be operationalized in terms of the nature of the debt; that is, either long-term or short-term debt. In this study, debt financing was operationalized as debt/assets ratio and debt/equity ratio.

Problem Statement

Important concepts for businesses include debt financing and financial performance. This is due to the fact that they are essential to a business’ capacity to grow and increase shareholder value that continues to be a primary objective of the company. Firm managers have acknowledged this and implemented a number of initiatives to remedy the shortcomings in the working capital and debt financing of listed companies (Noreen, 2013). Businesses still struggle to reach their financial performance goals, even with the greatest debt financing arrangements and adequate working capital. Because of this, managers of the company are unable to determine how debt financing affect the company’s financial performance. The inability of firm managers to establish optimal debt financing is related to the challenge of precisely figuring out the best financing arrangement for their businesses to boost financial performance (Noreen, 2013).

Publicly listed firms in East Africa source for funds to finance their operations from diverse sources. The two primary forms of funding that these companies have on file are long-term and short-term debt. The majority of businesses will have a combination of both kinds of debt, so it’s important to determine which source is better than the other one in terms of influencing financial performance (Kaushik & Shauhan, 2019). In regards to financial performance, firms listed in the various securities exchanges in East Africa Community performance has been differently with improved financial performance being recorded though others have been recording losses (Doan, 2020). The publicly listed non-financial institutions have reported experiencing financial performance issues in the past times. Thus, depicting the need to find out how debt financing influence financial performance. Because of their poor working capital foundation, East African securities markets have not yet drawn a sizable share of global capital inflows (Irving, 2015).

Globally, Vamishan (2014) examined how debt ratios affected Tehran stock market performance and concluded that there is a negative correlation between debt ratios and interest per share, there was also a significant positive correlation with firms’ success. Different research by Burakat (2014) came to the conclusion that there exists an association that is inverse amongst financial performance and leverage. Doan (2020) focused on how financial performance is influenced by debt financing in 102 Ho Chi Minh Exchange listed firms, Vietnam. Debt financing had a significant impact on performance, as per the research.

In Africa, Solaboni (2013) examined how working capital and leverage affected the financial performance of 35 manufacturing companies listed on the Nigerian Stock Exchange, coming to the conclusion that both working capital and debt financing possess a favorable influence towards economic success. Ogobe, Orinya, and Kemi (2013) examined the influence by debt financing towards the profitability of Ghanaian listed companies and came to the conclusion that debt financing increases return on assets (ROA). Similar research was done in Tunisia by Hasan et al. (2014), coming to a determination that financial leverage has a detrimental effect on economic performance. The investigation used pooled panel regression analysis.

There are conceptual gaps in the aforementioned studies. For instance, Kaushik and Shauhan (2019); Doan (2020); and Mutisya and Otieno (2015) operationalized debt financing just as capital structure, while the current study operationalized debt financing as debt to assets ratio and debt to equity ratio. Other gaps in the area were contextual where the researches focused on other sectors other than banking in East Africa. Doan (2020), for example, undertook the study on Ho Chi Minh Exchange listed firms with the current study focused on East African Community listed non-financial firms. This research answers the question: What is the effect of debt financing on financial performance of listed non-financial firms in East Africa Community?

LITERATURE REVIEW

Theoretical Review

According to trade off theory hypothesis, every business has an ideal equity-debt ratio that maximizes firm value. The idea asserts that a business’s financial configurations are ideal, and thus it may be established by weighing the risks and advantages of employing both borrowing and equities. As a consequence, the benefits of debt shielding from financial trouble have been adjusted. Agency expenses and asymmetric information are two additional expenditures that should be reduced. The ideal level is reached whenever the advantages of dealing with debt problems precisely offset any increase in costing those results from the issuing of additional debt, current value (Myers, 2001).

Businesses permit a variance in the percentage of capital amounts between their genuine leverage ratio and the goal rate. According to the findings, if the expenses of making adjustments outweigh the value lost due to a less-than-ideal capital structure, businesses do not change their pace towards the goal. The majority of empirical research must focus on analyzing capital structure determinants, which theories identify as crucial to drawing conclusions about the role that theories of capital structure have played in the development of corporate finance (Fischer et al. 1989).

An ideal capital structure ratio for businesses, according to a number of research that bolster the trade-off argument. However, they might try to modify their capital structure to more closely resemble this goal (Marsh, 1982). According to Jalilv and and Harris (1984) and certain documented literature, the rate of progress towards the desired ratio is extremely slow (Huang & Ritter, 2009).

Trade off theory must have an anticipation of picking a targeted capital configuration which contributes to business worth maximization by minimizing the current costs of imperfect markets, are writers who support such theory (Sheikh & Wang, 2010). The mean reversion of corporate earnings may be one explanation for this disparity. The presumption, according to researchers, is because every financial stream does have a yield and costs unique to itself. Such relate to a corporation’s earning potential, bankruptcy, operations, and hazards (Awan & Amin, 2014). Welch (2004) argues that the bulk of the variance in capital structure may be demonstrated by the structural variability in asset prices.

The trade-off theory has drawn criticism for its prediction of a positive correlation between leverage and earnings, which runs counter to substantial empirical data. However, the mean-reverting nature of corporate profitability could be one explanation for this mismatch. This idea has significant significance for decisions borrowed funds company management makes when running the business. Business management could utilize the trade-off concept in determining the best debt/equity ratio for utilizing to maximum returns. It is appropriate to this present investigation since it connects debt financing and financial performance.

Empirical Review

Impact of debt financing on dividend payment ratio among NSE-listed companies was studied by (Mudeizi, 2017). For five years, secondary data was collected annually (2012 – 2016). The findings demonstrate that debt financing made a statistically significant contribution. There is a concept gap as this study concentrated on dividend payout ratio which is distinct from financial outcomes (Mudeizi, 2017). Research involving 66 NSE-listed companies was conducted on the effect of borrowing on the state of the finances (Muiruri & Wepukhulu, 2018). The analysis revealed that while capital structure did not significantly or favorably affect ROA, it did possess a positive and significant influence towards ROE. Additionally, the choices made regarding liquidity as influenced by the funding source had a noteworthy and advantageous impact.

The goal of Surbhi and Sharma (2023) was to ascertain how debt financing affects the financial performance of an organization, and their conclusions are solely based on the findings of earlier research in this area. The Web of Science and SCOPUS databases have been used as a foundation to gather the necessary data for this purpose; the databases contain documents spanning the whole time period available, from 1985 to 2022. Following data collection, a thorough literature analysis was conducted, and it was discovered that debt indicators significantly deteriorate financial performance metrics. In Vietnam, a rising market, Doan (2020) conducted longitudinal study followed 102 companies that were traded on the Ho Chi Minh Market. As ROA is used as a financial indicator, financial leverage is done using debt level as total assets percentage. This investigation identified a link between around debt financing and company performance. A discovery has been made that increased debt use negatively affects institutional performance.

Conceptual Framework

Figure 1 presents the conceptual framework describing how the concepts as well as the variables being studied are related (Ravitch & Riggan, 2012). “From the review of literature, it was hypothesized that debt financing had an effect on financial performance Figure 1 shows this hypothesized relationship.

METHODOLOGY

Data

The research utilized secondary annual information in the form of listed East African companies’ annual audited financial statements between 2011 and 2020. Debt financing data pertained to the value of long-term amortizing loan and fixed income debt. Financial performance data pertained to net income and total assets. The information was gathered from the listed financial companies in East Africa’s annual financial reports. The reports were extracted from the NSE database, USE database, RSE database and DSE database and companies’ websites. The data collected were in absolute figures and in millions. This data enabled the researcher to calculate the ratios for analysis.

Data Analysis

Descriptive statistics were utilized to assess the data collected on debt financing, working capital, capital structure, and financial performance (mean, standard deviation, skewness, and kurtosis). Regression analysis was used to test the proposed relationships. Specifically, simple regression analysis was used to test the relationship between Financial Performance (ROA) on Debt/Asset Ratio and Financial Performance (EPS) on Debt to Asset Ratio in Kenya, Rwanda, Tanzania and Uganda. To analyze how the predictors affect the financial performance of the banks in the various East African Community countries Kenya, Uganda, Tanzania, and Rwanda comparative analysis was conducted. A comparative analysis examines and contrasts the links between data or processes. This provided context for the study and facilitated the understanding of how the relationships between the various data sets differed and overlapped. The analysis was based on ratios calculated from the absolute figures of data gathered from East African listed companies’ annual reports.

RESULTS AND DISCUSSION

Descriptive Results

The study examined the significant factors present in each of the countries analyzed. It employed descriptive statistical techniques, including means, standard deviation, and coefficient of variation. The mean, representing the central tendency, identified the most typical value within the set of scored employed in the estimating process. The standard deviation quantified the extent to which the values deviate from the mean. Additionally, the coefficient of variation assessed the variability of responses from each surveyed country.

Table 1: Descriptive Results

The finding based on mean indicated that Kenya had the highest average debt ratio, quick ratio. Firm size and dividend payout in comparison to Rwanda, Uganda, and Tanzania. Tanzania possessed the highest ROA, efficiency of management, and debt/equity ratio. In terms of earnings on each share and current ratio, Rwanda led the pack. In terms of variability, the findings indicated that Kenya had high variability in most of the indicators used in the analysis, that is, very high values of coefficient of variation (CV).

Hypothesis Testing

The goal of the investigation was to investigate the relationship between debt financing and financial performance within listed non-financial firms in East Africa Community. The study operationalized debt financing by debt/assets ratio and debt/equity ratio. Financial performance was operationalized by return on assets (ROA) and earnings per share (EPS). This objective was guided by the following null hypothesis and sub null hypotheses.

H₀₁:   There exists no substantial relationship amongst debt financing and financial performance within listed non-financial firms in East Africa Community

H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance within listed non-financial firms in the East Africa Community

H_01b: There exists no substantial relationship amongst debt/equity ratio and financial performance within listed non-financial firms in the East Africa Community

Table 2: Financial Performance (ROA) on Debt/Asset Ratio (Kenya)

As can be seen in Table 2 above, changes in the debt/asset ratio were responsible for 65.3% of the variation in ROA, whereas 34.7% of the variation was caused by independent factors that were left out of the model. The null hypothesis was rejected (p=0.000 being less than α-value of 0.05), indicating that the debt-to-asset ratio significantly influenced financial performance (ROA) within companies listed on the Kenyan Stock Exchange (NSE). This suggests that the entire model was significant. The equation for prediction was;

ROA = 0.145 – 0.509 Debt to Asset Ratio.

This implied that if there is an extra uni­t increase in debt/assets ratio, ROA will, on average decrease by 0.509 units, respectively. Then sub hypothesis that H_01a: It point to the inexistence of a significant connection amongst debt to asset ratio and monetary outcomes of the listed non-financial firms in East African community was rejected in the Kenyan case.

Table 3: Financial Performance (EPS) on Debt/Asset Ratio (Kenya)

Basing on table 3 above shows that although other independent factors not present accounted for 100% of the variation, changes in the debt/asset ratio only explained 0.000% variation in financial performance (EPS). With the p= 0.946 being higher than the α= 0.05, the model as a whole was not significant. This suggested that the alternative hypothesis, according to which the debt/asset ratio possessed no significant impact on financial performance (EPS) among Kenyan enterprises listed on the NSE, was supported. The predictive equation was; EPS = -]46.925 + 40.029 Debt/Asset Ratio. This implied that if there is an extra unit increase in debt/assets ratio, EPS will, on average go up by 0.509 units, respectively. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance (EPS) within listed non-financial firms in East Africa Community was supported in the Kenyan case.

Table 4: Financial Performance (ROA) on Debt/Asset Ratio (Rwanda)

According to Table 4 above, variations in the debt/asset ratio was responsible for 74.5 percent of financial performance variation (ROA), leaving 25.5 percent unexplained. Regarding significance, the entire model was significant because the debt/asset ratio significantly influenced financial performance (ROA) among companies listed at the Rwanda Stock Exchange (RSE), as indicated by the null hypothesis being rejected (p= 0.000 being less than α= 0.05). The equation for prediction was;

ROA = 0.232 – 0.751 Debt to Asset Ratio.

This implied that if there is an extra unit increase in debt to assets ratio, ROA will, on average decrease by 0.751 units, respectively. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance.

Table 5: Financial Performance (EPS) on Debt to Asset Ratio (Rwanda)

Outcomes basing on table 5 above shows that variations in the debt/asset ratio was responsible for 77% financial performance variation in (EPS), leaving 23% unexplained. Regarding significance, the entire model was significant since the debt/asset ratio significantly influenced financial performance (EPS) among companies listed at the Rwanda Stock Exchange (RSE) and the p= 0.000 was less than the α-value of 0.05, implying that the null hypothesis rejection. The equation for prediction was;

EPS = 0.6 – 1.884 Debt/Asset Ratio.

This implied that if there is an extra unit increase in debt/assets ratio, EPS will, on average decrease by 1.884 units, respectively. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance.

Table 6: Financial Performance (ROA) on Debt to Asset Ratio (Tanzania)

Table 6 above demonstrates that changes in the debt/asset ratio were responsible for 22.1 percent of financial performance (ROA) variation, leaving 77.9 percent unexplained. Regarding significance, the entire model was significant because the debt/asset ratio significantly influenced financial performance (ROA) among companies listed on the Tanzania Stock Exchange (TSE), as indicated by the null hypothesis being rejected (p= 0.000 being less than α-value of 0.05). The predictive equation was;

 ROA = 0.194 – 0.42 Debt/Asset Ratio.

This implied that if there is an extra unit increase in debt/assets ratio, ROA will, on average decrease by 0.42 units, respectively. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance.

Table 7: Financial Performance (EPS) on Debt/Asset Ratio (Tanzania)

Outcomes based on table 7 above points to variations in the debt/asset ratio was responsible for 13.4% financial performance (EPS) variation in, leaving 86.6 percent unexplained. Regarding significance, the p= 0.163>0.05 indicated that the model as a whole was significant, which implied that the null hypothesis was supported, thus, debt/asset ratio had no significant influence on financial performance (EPS) amongst firms listed at TSE, Tanzania. The predictive equation was;

 EPS = 0.06 + 0.014 Debt/Asset Ratio.

This implied that if there is an extra unit increase in debt/assets ratio, EPS will, on average go up by 0.014 units, respectively. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance among listed non-financial firms in East Africa Community was supported in the Tanzania case.

Table 8: Financial Performance (ROA) on Debt/Asset Ratio (Uganda)

Outcomes basing on table 8 above demonstrate that variations in the debt/asset ratio being responsible for 16.1% of the financial performance (ROA)variation, leaving 83.9 percent unexplained. In terms of significance, the model as a whole was significant because the debt/asset ratio significantly impacted financial performance (ROA) among companies listed at USE, Uganda, as indicated by the null hypothesis being rejected (p=0.008 being less than the α-value of 0.05). The predictive equation was;

ROA = 0.104 – 0.176 Debt/Asset Ratio.

This implied that if there is an extra unit increase in debt/assets ratio, ROA will, on average decrease by 0.176 units. Then sub hypothesis that H_01a: There exists no substantial relationship amongst debt/asset ratio and financial performance among listed non-financial firms in East Africa Community was rejected in the Uganda case.

Table 9: Financial Performance (EPS) on Debt/Asset Ratio (Uganda)

Outcomes basing on table 9 above point to variations in the debt/asset ratio was responsible for 0.8 percent financial performance (EPS) variation in, leaving 99.2 percent unexplained. As for significance, a p= 0.558 indicated that the model as a whole was significant, which implied that the null hypothesis was supported, thus, debt/asset ratio had no significant influence EPS amongst USE firms. The predictive equation was;

EPS = 0.158 – 0.148 Debt/Asset Ratio.

This implied that if there is an extra unit increase in debt/assets ratio, EPS will, on average decrease by 0.148 units, respectively. Then sub hypothesis that H_01a: There is no significant relationship between debt to asset ratio0and financial performance among listed non-financial firms0in East Africa Community was supported in the Uganda case.

The findings showed that among listed non-financial enterprises in the East Africa Community, the debt to asset ratio affects return on assets. The impact of debt to assets on earnings per share, however, was inconclusive, that is, Kenya, Tanzania and Uganda results indicated that debt to assets ratio does not influence earnings per share while in Rwanda, the inverse was true. The findings could be explained by the variation in number of firms that were included in this study per country, Rwanda had the smallest sample size wit best performing firms.

We can infer from the literature above that profitable businesses typically issue more debt in order to lower their taxable revenue, in accordance with trade-off theory. Since trade-off theory has provided a thorough explanation of the capital structure, the situation becomes intriguing.

Businesses can achieve the ideal capital structure by weighing the advantages of debt and equity against their costs. The debt tax shield is a significant benefit of using debt. On the other hand, the drawbacks of debt, especially when a company takes on excessive debt, could be the price of possible financial crisis. The primary advantage of debt is that interest payments are tax deductible, which encourages the use of debt.

CONCLUSION AND RECOMMENDATIONS

It is recommended that the listed non-financial firms in the East African community seek out tactics that boost their assets in light of the study’s conclusions. The study’s findings demonstrated that non-financial firms in the East Africa Community would considerably increase their working capital financing as their firm size (total assets) increased. Large businesses, characterized by their firm size, should be less likely to borrow money because they are generally more financially stable and have more investments. Because there are fewer or manageable current obligations as a result of the balanced borrowing, working capital is higher because there are more current assets than current liabilities.

The success of the listed non-financial enterprises in the East African Community and the economy as a whole continues to depend on the issue of finance for these firms. Therefore, regulators in the Ministry of Finance, Ministry of Small and Medium Enterprises, Capital Market Authorities, and other government agencies should make sure that laws  are implemented to allow listed non-financial companies in the East Africa Community to obtain both short- and long-term loans. The policies should ensure that the credit market is robust, flexible, and not skewed to disadvantage the borrowers. Additionally, to support the listed non-financial enterprises in the East Africa Community with their financial needs, policymakers should also establish courses in financial acumen and continuous development programs for practitioners in the finance departments. Policies must also be implemented to guarantee that listed non-financial companies in the East Africa Community have access to trade credit.

The more profitable the company is, the more resilient it will be. Since they may use retained earnings to fund ongoing operations, profitable businesses are less likely to take out expensive debt. Retained revenues from profitable operations are a vital source of funding because they allow institutions to create robust loss-absorbing buffers and reduce the need for urgent, expensive external borrowing. It is also advised that non-financial companies listed on the NSE seek out tactics that lower their levels of relative leverage. This will help in keeping a healthy working capital, which is vital for the operations that fund the profit centers. The balance ensures that firms are not forced to prioritize debt repayments over their strategic objectives.

The study concludes that by concentrating on the cost and benefit analysis of debt, trade-off theory forecasts the ideal debt ratio that contributes to maximizing a company’s value. When the advantages of issuing debt outweigh the rising present value of the expenses associated with issuing more debt, the optimal point can be reached. One of the main advantages of debt is that interest payments are tax-deductible outflows. These advantages encourage businesses to take on debt, as it boosts earnings available to the shareholders.

LIMITATIONS

The primary goal of the research was to determine how listed non-financial enterprises in the East Africa Community’s financial performance relates to debt-to-financing. The study did, however, have a few drawbacks. The study employed an explanatory research design approach, and data were gathered from listed East African companies’ annual audited financials between 2011 and 2020. This may have biased the conclusions, as the study was conducted within a specific collection of countries with unique characteristics. This contextual limitation was mitigated by a broad approach of incorporating all listed non-financial enterprises in the East Africa Community.

The study concentrated on three characteristics in particular. However, FDI and Foreign Portfolio Investments between these nations is likely to be influenced by a number of other factors, some of which are domestic and include economic growth and the macroeconomic climate in place. Others, on the other hand, are external and include governmental meddling and the performance of international businesses. However, the study concentrated on the endogenous factors that are controllable within the listed non-financial enterprises in the East Africa Community.

SUGGESTIONS FOR FURTHER RESEARCH

In the investigation, debt financing formed the independent component, and financial performance was the dependent variable. This is anticipated to offer greater insights into the dynamic features of debt financing and financial performance of listed non-financial firms in the East Africa Community, despite the fact that it is expensive, complex, and time-consuming.

Future studies ought to concentrate on nations that are not members of the East Africa Community. By doing so, it will be possible to ascertain whether the study’s conclusions apply to other parts of Africa. Future studies ought to categorize nations based on their geographical locations, including the Common Market for Eastern and Southern Africa (COMESA), among other classification schemes.

To better explore how local financial conditions impact capital structure decisions, future iterations could benefit from including firm-level interviews or case studies. Furthermore, a clear comparison of the regulatory or economic circumstances in the East African countries under study will provide insightful background.

CONFLICT OF INTEREST

The authors declare that they do not have any conflict of interest.

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