Abstract
Orientation: Coronavirus disease 2019 (COVID-19) and the subsequent lockdown regulations restricted ongoing trade for most retail firms. Business strategies had to be adjusted to avoid a grand challenge of insolvency.
Research purpose: This paper provides previously unavailable empirical evidence of firm-level capital structure and determinants in relation to the COVID-19 pandemic for the firms in the retail sector in an emerging market.
Motivation for the study: Capital structure decisions, as influenced by the pandemic, provide novel value because such decisions are usually long-term, yet the volatile uncertainty of the pandemic negated the long-term cycle.
Research design, approach and method: A correlational design was followed to identify and interpret how retail firms reacted during the initial lockdown period. This was completed using a quantitative method, doing statistical analysis to describe and interpret possible relationships. The secondary data ranged from 2009 to 2021 for 11 South African listed retail firms was collected from EquityRT® and INET BFA. Data were analysed using descriptive statistics and panel data analysis by Eviews 12 software.
Main findings: The pandemic, measured using a dummy variable, was found to have a significant effect on capital structure together with risk, profitability, size and age. Liquidity, tangibility and growth were insignificant. Overall, capital structure proxied by the debt-equity ratio was reduced timeously without exhibiting dependence on short-term funds.
Practical/managerial implications: The retail firms exhibited exemplary capital structure decision-making behaviour during the COVID-19 pandemic.
Contribution/value-add: The empirical evidence of the effect of the COVID-19 pandemic on the capital structures and its determinants of retail firms in South Africa is the contribution of this study. Based on the findings, two conflicting capital structure theories (pecking order and trade-off theories) were part of the decision-making process, creating the cautious behaviour for these retail firms.
Keywords: COVID-19; pandemic; capital structure; determinants; panel data analysis.
Introduction
The coronavirus disease 2019 (COVID-19) pandemic gripped the world in early 2020. Countries implemented various national and regional shutdowns and limited the movement of people in order to reduce the spread of the COVID-19 virus. South Africa implemented a national lockdown at level 5, starting on 26 March 2020. This impacted the retail sector with limited retail allowed during the lockdown period. Level 5 restrictions were initially for 3 weeks and were subsequently extended, whereafter the lockdown restrictions were relaxed in a stepwise fashion where the lockdown levels were lowered, yet still creating trading uncertainty at the time. Table 1 indicates the lockdown levels and the restrictions on the retail industry, including the restrictions on manufacturing and trade. Lockdown levels were adjusted as the COVID-19 infection rates increased or decreased, creating volatile trading uncertainty. All restrictions related to COVID-19 were lifted on 23 June 2022 (McCain 2023).
TABLE 1: Lockdown regulations on retail, manufacturing and trade. |
The impact of the lockdown restrictions on the retail industry was vast with firms having to act quickly to adapt. Importantly, for the retail industry, a level 5 lockdown meant that only essential goods were allowed to be sold (Ecim et al. 2020). Additionally, many retail businesses shut down completely during the level 5 lockdown period. Consumers were also moving towards buying online, which meant less spending in the actual shops. Other consequences of the pandemic and lockdown measures included COVID-19 regulations such as surface and hand sanitation as well as social distancing in the workplace, which meant additional expenditure. On a business survival level, the most prevalent concerns and actions were towards the liquidity (LIQ) of a firm (OECD 2020), which only reflected a short-term response.
Financing is critical for the value creation and financial sustainability of a company (DeAngelo 2022; Mokhova & Zirecker 2014). Yet, long-term consequences were highlighted by Goodell (2020), who claims that the way firms structure their financing, using equity or leverage (LEV), is at a critical point given the influence of the COVID-19 pandemic. This is because of debt financing likely to be disrupted by a drastic macro-economic shock (Huang, Gao & Chen 2020). The operation disruption caused by the pandemic is expected to tighten financial flexibility and increase the cost of capital (Goodell 2020). Companies will therefore attempt to increase their debt levels to mitigate reduced liquidity. Additionally, it is expected to be more rapidly during a time of crisis (Vo, Mazur & Thai 2022). However, companies that were already financially constrained before the pandemic will have difficulty to secure more debt during the pandemic (Moyo & Markou 2022), facing liquidation risk, which was the case in the previous 2008 financial crisis (Campello, Graham & Harvey 2010; Hossain 2021).
Capital structure and changes in the equity and leverage ratios are even more critical for the retail sector, which was severely impacted by the national lockdown. Customers have had to change their habits, and thereto, the long-term effects of changed consumer behaviour are still to be seen, which, in turn, has a domino effect on capital structure and the ways a retail company may fund its activities (Opute et al. 2020).
The various effects of the COVID-19 pandemic on capital structure could not be investigated previously because of the lack of available data. However, now, after the 2021 annual financial reports have been published, data are available for the effects to be investigated. This then prompts the following research question: What was the immediate impact of the COVID-19 pandemic on capital structure of retail firms? This investigation, within an emerging market context, will be supported by providing the common determinants of capital structure, as informed by the existing, comprehensive body of knowledge.
Notwithstanding these knowledge bases, the findings of this article provide a novel contribution of capital structure during a pandemic, which is under-theorised, at this point. It provides novelty value on the reaction of a retail sector in response to the pandemic when profit-constraining lockdown measures had been implemented. Fresh insights include the use of a dummy variable, as a proxy to distinguish between the pre-pandemic and the ‘during-pandemic’-period, which then showed significance, when the panel data analysis indicated that the pandemic impacted the capital structure. Other significant determinants were profitability (PROF), business risk (RISK), size and age. The comparison of the pre- and during COVID-19 descriptive statistics showed that the retail firms reacted quickly and re-adjusted their capital structure, suggesting proactive management and sound decision making while heeding warnings highlighted by the likes of the OECD (2020), Huang and Ye (2021) and Goodell (2020) and other capital market advisories.
The results are indicative of the resilience of an emerging market’s (South Africa: [SA]) retail sector and provide a level of comfort to investors regarding the responsiveness of the retail industry during a grand challenge such as the pandemic. Emerging economies may use these findings as a guide to capital structure decision-making during times of crises.
Capital structure
The seminal work of Modigliani and Miller (1958) sparked the debate on the importance of capital structure; the authors initially suggested that different combinations of debt and equity will be irrelevant to the value of a company. This notion was criticised because of the perfect-market condition assumptions of the authors. Later, Modigliani and Miller (1963) accepted that the inclusion of debt in the capital structure will lead to enhanced value creation for a firm. This is because of the tax deductibility of the interest associated with debt.
The debate continued and two opposing capital structure theories were proposed namely the pecking order theory (initially by Donalson 1962, expanded by Myers & Mailuf in 1984) and the static trade-off theory of Kraus and Litzenberg (1973). More theories emerged such as the agency theory by Jensen and Meckling (1976) and market timing theory by Baker and Wurgler (2002). Interestingly, the static trade-off theory was extended to a dynamic version (Strebulaev 2007) as companies can deviate from their target capital structure. Once there is a deviation, companies will only adjust to their target capital structure if the perceived benefit of readjustment outweighs the cost. Despite the development of the different theories, the pecking order and the trade-off theories are still viewed as the most prominent theories (Culata & Gunarshih 2012; DeAngelo 2022). Myers (1984) rightfully referred to these contradictory theories not being fully able to explain actual financing decisions of companies as the capital structure puzzle.
Both the prominent theories suggest that capital structure consists of equity and debt as a financing combination but contradict each other in the way debt and equity should be used (Tazvivinga, Mouton & Pelcher 2021). According to the trade-off theory, the capital structure financing mix is established through a balancing act of the tax shield of increased debt and is weighted against the increased cost of financial distress. The pecking order theory suggests that financial managers should rather follow a prescribed order of options when financing is needed. The order of financing, according to the pecking order theory, is retained earnings, debt and lastly equity, which should be resorted to when all other options have been exhausted. In the first of its kind for capital structure determinants, a systematic review by Kumar, Colombage and Rao (2017), the authors investigated literature from 1972 to 2013 mainly in the Emerald and EBSCO databases, amongst others. At the time, only two articles were dedicated to the retail sector globally, indicating a clear gap in the academic literature for the retail sector.
Capital structure studies within emerging markets, specifically SA, are limited. Ramjee and Gwatdzo (2012) and Moyo, Wolmarans and Brummer (2013) both investigated the speed of adjustment, which informed on how quickly firms return to the target capital structure ratio after deviating from it. Both of these studies did not investigate capital structure determinants nor specifically the crises. Moyo et al. (2013) included retail, manufacturing and mining. De Vries and Erasmus (2010) investigated determinants of capital structure. Their sample was on industrial firms only, ranging from 1995 to 2008, thus excluding the financial crisis. Size and tangibility (TANG) were identified as the most important factors influencing capital structure. The methodology included a multiple regression, which excluded a panel data analysis. This means that differences between firms were automatically excluded, and the analysis was limited to time series data.
A study including the effects of the financial crisis on capital structure determinants (Mouton & Smith 2016) included the top 40 firms listed on the Johannesburg Securities Exchange (JSE); therefore, retail was included, however, not addressed specifically. A panel data analysis revealed incremental of the financial crisis, having risk and tangibility as significant determinants during and post-financial crisis. Tazvivinga et al. (2021) did a study on capital structure determinants on the retail sector in SA, which is a leading industry in Africa. A panel data analysis revealed size, firm age (AGE), profitability, growth (GROW) opportunities and tangibility as significant determinants of capital structure for the retailing industry. However, the effects of both the financial crisis and pandemic were excluded from the sample size, which was from 2009 to 2018. The summary of previous SA literature in capital structure shows that capital structure enquiries are lacking in the retail sector with the inclusion of crises.
In order to establish support for one or the other of opposing capital structure theories, the effect of the determinants of the capital structure on the financing mix needs to be established. In the literature review study of capital structure, the most accepted determinants over 40 years were identified by Kumar et al. (2017). Based on the authors’ findings, profitability, tangibility, liquidity, business risk, growth, size and age were selected as capital structure determinants for this study. While noting these established principles, it is the effect of the pandemic that is the focal point of this study; therefore, the theory support discussion will revolve on the expected crisis dynamics (Almeida 2021).
During a crisis such as the pandemic, it is expected for companies to experience increased business risk because of economic contraction (Mohammad & Khan 2021) causing a decline in profitability, growth and liquidity. It is also expected for older, bigger companies with more assets to raise debt easier, to support liquidity management and increase cash holdings (Almeida 2021; Bajaj, Kashiramka & Singh 2021; Kumar et al. 2017).
The retail companies in question are all listed on the Johannesburg Stock Exchange (JSE) and therefore by default have easier access to these benefits, as opposed to unlisted and smaller firms. To contextualise the findings, the general theoretical expectations for the contending theories are summarised in Table 2.
Global macro-economic change
The changing macro-economic conditions in which companies operate influence their capital structure (Auret, Chipeta & Krishna 2013; Kumar et al. 2017; Piaw & Jais 2014). The worldwide COVID-19 pandemic has posed major macro-economic pressure on companies because of the restriction or halting of trade because of lockdown conditions. The impact of the restrictions has a possible negative effect on profitability, one of the major determinants of the capital structure of a firm. The capital structure is therefore bound to change because of the restrictions on liquidity during the pandemic, with firms being forced to stop or limit trading (Huang & Ye 2021). Firms are expected to increase their debt in order to manage possible liquidity constraints and increase cash holdings.
Over the past 30 years, there were major grand challenge macroeconomic events that had a significant impact on companies’ capital structures of which the 2007/2008 financial crisis is the most recent one. Others are the Argentinian crisis that began in 2001, the 1997 Asian crisis and the 1994 Mexican crisis (De Wet 2020). It is important to note that these crises were all financial crises, whereas the COVID-19 pandemic is unique. It is different from previous crises as the pandemic is a health crisis of global proportions that grips the entire world with the globalised effect of socio-economic impacts, trade restrictions and value chain disruptions felt universally and across every sector. In this specific way, it is not similar to a financial crisis although the macro-economic conditions for all firms changed globally.
It is already accepted that no universal capital structure theory should be expected for all companies (Myers 2001), and literature predicts that the capital structure of companies should change during the COVID-19 period. Therefore, to inform the impact of the COVID-19 pandemic on the capital structures of SA retail firms, it is necessary also to establish which capital structure theory is followed in this industry amidst a pandemic. This investigation may be used as guidance to other retail firms to successfully navigate through such a volatile period.
Limited research is available on the effect of the pandemic on capital structure, and hence this study has relevance. Globally, Huang and Ye (2021) and Almeida (2021) found that firms expanded their leverage to bridge the liquidity problems that they faced during the pandemic. This move was risky for firms that were already highly leveraged before the pandemic, as they faced the risk of becoming insolvent because of the high cost of debt and constraints posed by the pandemic. The capital structure studies completed in SA were discussed in the previous section, and it was noted that there is a lack of literature for retail firms, capital structure and pandemics. The holistic effect of pandemic in SA pertaining to capital structure has not yet been researched and it is this gap to which this study provides a response.
Research methods and design
The methodology followed was quantitative in nature, using secondary data in a panel regression model. This methodology is consistent with other studies in capital structure (Moradi & Paulet 2019; Thiele & Wendt 2017). The internationally recognised INET BFA and EquityRT® databases for secondary data were used to collect the data for the South African firms in the retail sector from 2009 until 2021. The sample period includes pre-pandemic and during-pandemic years. The authors acknowledge the global financial crisis of 2007/2008. However, as it can be argued as to when the effects of the financial crisis were apparent, for the purpose of this study, 2009 will be considered as post-financial crisis. The years 2020 and 2021 are considered as the beginning of COVID-19 and will encapsulate the immediate effect of COVID-19 on retail company’s capital structure.
The population consists of 15 firms in the retail sector. Judgement sampling was applied, and firms that were not listed during the sample period were excluded. Four firms were excluded, resulting in a sample size of 11 companies. Ethical clearance was obtained with clearance code, SAREC20210510/06.
A panel regression model was used to capture the heterogeneity in the sample as well as the uniqueness of each company (Brooks 2014). The model is also appropriate as it captures cross-sectional and time-series data well, expanding the number of observations to 143. The statistical software EViews 12 was used to run the panel regression models. The equation below shows the regression equation with the variables chosen based on previous literature:
Leverage, the dependent variable, was the debt-to-equity (DE) ratio used as a proxy for capital structure. Firm-specific factors (independent variables) influencing capital structure are liquidity, profitability, business risk, firm size (SIZ), tangibility, firm age and growth. Liquidity was calculated as current assets divided by current liabilities. Profitability was included as the return of assets (ROA) ratio – (earnings before interest and tax [EBIT] divided by Total assets). Business risk was proxied by the standard deviation of ROA. Firm size was proxied by the natural logarithm of market capitalisation. Market capitalisation as proxy for size is not often used in capital structure studies; however, Cevheroglu-Acar (2018) mentions it as suitable when market conditions need to be considered. The size of a firm relates to the ease and availability of information in the market (Cevheroglur-Acar 2018), and in this case, the market was influenced by the macro-economic changes because of COVID-19. Therefore, market capitalisation as a measurement was deemed necessary to control for the change in the equity element of capital structure.
Tangibility was calculated as the fixed assets divided by total assets. Firm age was proxied using the natural logarithm of the number of years listed on the JSE. Firm growth was proxied by the natural logarithm of sales. The inclusion of these determinants and the proxies are recognised and used in studies by Moradi and Paulet (2019), Kieschnick and Moussawi (2018), Kumar et al. (2017), Thiele and Wendt (2017), Thippayana (2014), Moyo et al. (2013) and De Vries and Erasmus (2012).
To determine the effect of the pandemic on the capital structures of the South African retail firms, there must be a clear distinction between pre-pandemic and during-pandemic data. The pandemic’s proximate effect on the retail industry got underway on 26 March 2020 with the start of the national lockdown and subsequent trade restrictions. This watershed date is the distinction used to determine which data points will fall under the pre-pandemic sub-sample or not. A dummy variable (COVID_DUM) is included to indicate this distinction. A zero was allocated to pre-pandemic data and a one was allocated to the during-pandemic data points.
Ethical considerations
Ethical clearance to conduct this study was obtained from the University of Johannesburg School of Accounting Research Ethics Committee (SAREC) (No. SAREC20210510/06).
Results
This study is explicitly focused to determine the effect of the pandemic on capital structure; therefore, descriptive statistics are specifically presented as two subsets: ‘pre-COVID-19’ and ‘during COVID-19’ periods, which are presented in Tables 3 and 4, respectively.
TABLE 3: Pre-coronavirus disease 2019 descriptive statistics (2009–2019). |
TABLE 4: During coronavirus disease 2019 descriptive statistics (2020–2021). |
Table 3 and Table 4 show the descriptive statistics of pre- and during-COVID-19 periods. This provides critical information with regard to the variables important to capital structure, including leverage, which is the proxy for capital structure. When the two sub-sets were compared, it became apparent that the percentage change in the mean for each determinant, which is reported in Table 5, must be highlighted to show the substantial changes that took place immediately within the pandemic. Leverage decreased by 86%, showing that firms reduced their long-term liabilities during the COVID-19 period.
TABLE 5: Mean percentage change from pre-coronavirus disease 2019 to during coronavirus disease 2019. |
Profitability decreased by 47%, GROW by 55% and LIQ by 27% indicating the effect of the pandemic because of trading restrictions. Tangibility shows the least change with a decrease of 18%. This all indicated a downward trend of the variables during the COVID-19 period compared to pre-COVID-19. With such a major macro-economic event, it is understandable that RISK can and should increase. The South African retail sector’s risk increased by 72% during the pandemic. Firm size decreased slightly, indicating a possible contraction in the market, and AGE increased as the firms are getting older. The significance of these variables was established through the regression analysis. The correlation matrix, as shown in the Table 1-A1, indicates low correlation between the variables. The highest correlation between the variables is between profitability and liquidity, with a correlation of 0.3864. This is an indication that multicollinearity does not exist between the variables.
The panel regression estimation process started with the pooled ordinary least squared (OLS) model, which rendered an adjusted R-squared of 0.1497. The sequential fixed effects model (FE), accommodating the heterogeneity of the sample, showed an adjusted R-squared of 0.4331 (see Table 2-A1 and Table 3-A1). The results of the likelihood test (Table 6) indicated that the FE is preferred over the pooled OLS, with the significant p < 0.01.
TABLE 6: Results of the diagnostic tests. |
Following the acknowledgment of the accommodation of the cross sections in the sample, the random effects model (RE) was estimated and an adjusted R-squared of 0.2253 was documented (see Appendix 1). The diagnostic testing of the Hausman test, displayed in Table 6, was performed. The null hypothesis is that no correlation exists within the error term, which was rejected (p < 0.05), and the FE was determined as the overall preferred model. The final model FE, based on the diagnostic tests performed and is shown in Table 7.
TABLE 7: Final model: Fixed effects model. |
The F-stat of the FE is significant (p < 0.01) with the model having a 43.31% explanatory value (R-squared). The results of the FE show profitability, risk, size, age and importantly the COVID-19 dummy, as significant on the 99% confidence level (p < 0.01). Interestingly, liquidity, growth and tangibility were insignificant for the South African retail sector, an emerging market. The discussion on the findings follows in the next section.
Discussion
The effect of COVID-19 had a significant effect on the capital structure of the SA retail sector. This is evident from the significant result of the COVID-19 dummy variable. This finding is supplemented by the findings of the descriptive statistics, where a decrease in the average profitability, growth, liquidity and tangibility was identified and an average increase in risk.
The descriptive statistics indicated an average decrease of 46% in profitability when pre-COVID-19 and during-COVID-19 periods are compared. Profitability was found to be a significant, at the 99% confidence level and a negative determinant of capital structure. This is in support of the pecking order theory.
Importantly, average liquidity, measured by the current ratio, remained healthy with a ratio of 1.6773 during the pandemic period when compared to the rule of thumb of 2.0. This is an indication that the financial management in the retail sector overall was managed well, and short-term funds such as liquidity were not necessary to use during the COVID-19 period, proved by the insignificant finding of liquidity to capital structure. This insignificant and positive coefficient of liquidity with capital structure (leverage), also opposes the statement of Huang and Ye (2021), who warned of insolvency because of liquidity. Although the average liquidity decreased during COVID-19, the SA retail firms did well to avoid possibilities of insolvency, showing resilience during the COVID-19 pandemic. This is a clear indication of prudent behaviour of the South African retail companies who did not rely on liquidity to decrease the long-term debt.
Business risk was found significant at the 99% confidence level and negative. Thus, as risk increased, leverage decreased, ceteris paribus. The RISK coefficient of −0.403 indicated that as the business risk increased, the leverage will decrease. The descriptive statistics clearly indicate an increase in business risk during the COVID-19 period. The extent of the increased business risk is evident in the average increase of 72% during the pandemic. This is attributable to uncertainty and reduced trading. This conclusion then indicates that leverage decreased, which, in turn, implies that the capital structure decisions were positioned to reduce debt and caution was exercises, within the unchartered territory of a grand challenge global pandemic.
Growth and tangibility were both found statistically insignificant with leverage, with the average growth decreased by 55% and average tangibility decreased by 18%. Normally, tangibility is used to secure additional debt, but as leverage was reduced because of the economic contraction, tangibility and growth should not and could not have a significant impact on capital structure.
Age was significant at the 99% confidence level with a negative coefficient. Kumar et al. (2017) found that developed American and European countries show such a relationship with leverage, whereas developing countries normally show a positive relationship. The average age increased, which then mean that leverage decreases as firms grow older. Firms seem to reduce their leverage and continue to do so, as a strategic decision during the pre- and during-pandemic time. Profoundly, the South African retail companies’ capital structure shows a similar relationship with that of developed markets, positioning the SA retail market as a leader in Africa, following the developed markets’ trends.
Size was found to be statistically significant at the 99% confidence level with a positive coefficient. The average firm size decreased by 2%, showing a contraction in the market during the pandemic. The result for size is an indication of the prudent behaviour of the SA retail companies, by reducing debt in reaction to the decline in firm size. This finding is supported by the trade-off theory.
Linking the findings to the opposing capital structure theory predictions in Table 2, it is evident that the capital structure puzzle prevails for the SA-listed retail companies. The significant negative coefficient of business risk together with the positive coefficient of size support the trade-off theory. The significant negative coefficients of profitability and age support the pecking order predictions. Therefore, a mixture of financial flexibility supported by the pecking order theory, together with the balancing act of the trade-off theory, may usefully explain the capital structure strategy evident in the responsive re-alignment of decision-making of the listed SA retail companies as evident from the initial response during the pandemic (Table 5).
Conclusion
The global COVID-19 pandemic had far-reaching consequences for not only individuals but also the trading of companies. The international lockdown procedures were unprecedented on a global and local scale. The objective of this study was to investigate the immediate impact of COVID-19 on the capital structure of retail firms, an under-theorised area. The most common determinants of capital structure were included in the quantitative analysis. Descriptive statistics and panel regression analysis were used, with the inclusion of 11 firms over the sample period of 2009–2021.
From a financial perspective, the short-term and immediate effect of the pandemic on the capital structure of the retail sector was surprising. The study theorises that firms had to rebalance and went into what seems to be an iterative strategic re-alignment. Although capital structure is normally a long-term decision, caution towards solvency during a pandemic, or crisis alike, is needed. This influences the capital structure of a firm, creating potential managerial problems should a firm have to tap into their capital structure to maintain solvency. From an investor’s perspective, having knowledge of the general retail sector response to the pandemic, creates evidence that will assist in investment decision making.
To the authors’ knowledge, at the point of writing, this study is the first of its kind in South Africa and contributes towards the COVID-19 literature. It is valuable to note that the retail sector reacted quickly to the lockdown measures and constraints it faced during this unprecedented time. The results indicated that, although the COVID-19 period had a significant impact on capital structure, the retail sector sustained itself, reacted with prudence and showed financial flexibility. The theoretical finding, where the companies draw from both the trade-off and pecking order theories, provides evidence that these capital structure theories are used jointly to work towards sustainable capital structure strategies.
Although there are many calculations for the proxy of size within capital structure research, such as the natural logarithm of the book value of total assets, the natural logarithm of sales and the natural logarithm of market capitalisation (Cevheroglu-Acar 2018; De Vries & Erasmus 2012; Vo et al. 2022), the decision to use the natural logarithm of market capitalisation in this instance is suitable and provides novel insights. Using the natural logarithm of market capitalisation as a proxy had a dual purpose. Not only did it serve as a proxy for size, but it is also an indication of the change in equity, as an element of capital structure, providing novel insights in the global pandemic period.
The results of the mean percentage change of the determinants from pre-pandemic to during-pandemic were quite prominent. This warrants further research as to the changes of the determinants of other companies in different sectors, which could highlight the responsiveness of the other sectors towards capital structure during pandemic periods as well as the theoretical underpinnings of the capital structure decisions.
Although the decrease in profitability and growth can be seen as drastic, the effect on liquidity was less with an average decrease of 27%. Recent literature cautioned against the risk of insolvency because of the pandemic (Huang & Ye 2021; OECD 2020), but liquidity was found insignificant in relation to capital structure; therefore, the retail sector shows resilience and prudence in their capital structure decisions.
Displaying such cautious behaviour can serve as an example for other industries on how to deal with future pandemics and financial crises alike, providing important practical implications and confirmation of prudent decision-making during crises. This finding substantiates DeAngelo (2022), of the importance of these findings, and how it contributes towards the intuitive capital structure decision making. The capital structure decisions should be further researched using qualitative methods, to determine other strategic decisions and buffers within the retail sector. The results should inform on successful strategies and could be implemented in other emerging markets. Notwithstanding these under-studied areas, these results still provide immediate, and albeit bounded, information because of the limited timeframe of 2 years into the pandemic. A follow-up study will be required to determine the long-term effects of a global pandemic such as the COVID-19 pandemic. The retail firms exhibited exemplary capital structure decision-making behaviour during the COVID-19 pandemic.
Acknowledgements
The authors want to thank Dr’s M.C. de Wet for his consultations and guidance with the econometric models and C Williamson for her critical review and valuable input.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
M.M. and L.P. were responsible for conceptualisation, analysis and writing.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author, M.M., upon reasonable request.
Disclaimer
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.
References
Almeida, H., 2021, ‘Liquidity management during the Covid-19 pandemic’, Asia-Pacific Journal of Financial Studies 50(1), 7–24. https://doi.org/10.1080/10800379.2013.12097246
Auret, C., Chipeta, C. & Krishna, S., 2013, ‘Financial constraints and capital structure dynamics across the business cycle: Some evidence from the JSE’, Journal for Studies in Economics and Econometrics 37(1), 75–104. https://doi.org/10.1080/10800379.2013.12097246
Bajaj, Y., Kashiramka, S. & Singh, S., 2021, ‘Application of capital structure theories: A systematic review’, Journal of Advances in Management Research 18(2), 173–199. https://doi.org/10.1108/JAMR-01-2020-0017
Baker, M. & Wurgler, J., 2002, ‘Market timing and capital structure’, Journal of Finance LVII(1), 1–32. https://doi.org/10.1111/1540-6261.00414
Brooks, C., 2014, Introductory econometrics for finance, 3rd edn., Cambridge University Press, New York, NY.
Campello, M., Graham, J.R. & Harvey, C.R., 2010, ‘The real effects of financial constraints: Evidence from a financial crisis’, Journal of Financial Economics 97(3), 470–487. https://doi.org/10.1016/j.jfineco.2010.02.009
Cevheroglu-Acar, M. G., 2018, ‘Determinants of capital structure: Empirical evidence from Turkey’, Journal of Management and Sustainability 8(1), 31–45. https://www.doi.org/10.5539/jms.v8n1p31
Culata, P. & Gunarsih, T., 2012, ‘Pecking order theory and trade off theory of capital structure: Exchange from Indonesian Stock Exchange’, The Winners 13(1), 40–49. https://doi.org/10.21512/tw.v13i1.666
DeAngelo, H., 2022, ‘The capital structure puzzle: What are we missing?’, Journal of Financial and Quantitative Analysis 57(2), 413–454. https://doi.org/10.1017/S002210902100079X
De Vries, A. & Erasmus, P.D., 2010, ‘Determinants of capital structure: A South African study’, Corporate Ownership and Control 8(1), 590–599. https://doi.org/10.22495/cocv8i1c6p2
De Vries, A. & Erasmus, P.D., 2012, ‘The influence of firm characteristics and economic factors on capital structures: A comparison between book value and market value leverage’, Management Dynamics 21(3), 2–16.
De Wet, M.C., 2020, ‘Modelling the South African financial cycle’, Doctoral thesis, University of Johannesburg, Johannesburg, viewed 25 March 2021, from http://hdl.handle.net/102000/0002.
Donalson, G., 1962, ‘Corporate debt capacity: A study of corporate debt policy and the determination of corporate debt capacity’, The Journal of Finance 17(3), 554–555. https://doi.org/10.2307/2977084
Ecim, D., Lang, Y., Cerbone, D., Kok, M., Maroun, W. & Van Zijl, W., 2020, ‘Crisis communication initiatives between South African retailers and their stakeholders during COVID-19’, The Retail Marketing Review 16(3), 32–47.
Goodell, J.W., 2020, ‘COVID-19 and finance: Agendas for future research’, Finance Research Letters 35, 101512. https://doi.org/10.1016/J.FRL.2020.101512
Hossain, M. S., 2021, ‘A revisit of capital structure puzzle: Global evidence and analysis’, International Review of Economics & Finance 75(C), 657–678. https://doi.org/10.1016/j.iref.2021.05.001
Huang, Z., Gao, W. & Chen L., 2020, ‘Does the external environment matter for the persistence of firms’ debt policy?’, Finance Research Letters 32(127), 1–9. https://doi.org/10.1016/j.frl.2018.12.021
Huang, H. & Ye, Y., 2021, ‘Rethinking capital structure decision and corporate social responsibility in response to COVID-19’, Accounting and Finance 61(3), 4757–4788. https://doi.org/10.1111/acfi.12740
Jensen, C. & Meckling, H., 1976, ‘Theory of the firm: Managerial behaviour, agency costs and ownership structure’, Journal of Financial Economics 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X
Kieschnick, R. & Moussawi, R., 2018, ‘Firm age, corporate governance and capital structure choices’, Journal of Corporate Finance 48, 597–614. https://doi.org/10.1016/j.jcorpfin.2017.12.011
Kraus, A. & Litzenberger, R.H., 1973, ‘A state-preference model of optimal financial leverage’, The Journal of Finance 28(4), 911–922. https://doi.org/10.1111/j.1540-6261.1973.tb01415.x
Kumar, S., Colombage, S. & Rao, P., 2017, ‘Research on capital structure determinants: A review and future directions’, International Journal of Managerial Finance 13(2), 106–132. https://doi.org/10.1108/IJMF-09-2014-0135
McCain, N., 2023, COVID-19 regulations: Health minister to ‘unpack’ implications of repealing mask mandate, viewed June 2023, from https://www.news24.com/news24/southafrica/news/COVID-19-regulations-health-minister-to-unpack-implications-of-repealing-mask-mandate-20220623.
Modigliani, F. & Miller, M.H., 1958, ‘The cost of capital, corporation finance and the theory of investment’, The American Economic Review 48(3), 261–297.
Modigliani, F. & Miller, M.H.M., 1963, ‘Corporate income taxes and the cost of capital: A correction’, American Economic Review 53(3), 433–443.
Mohammad, K.U. & Khan, M.R., 2021, ‘Bank capital structure dynamics and Covid-19: Evidence from south’, iRASD Journal of Economics 3(3), 293–304. https://doi.org/10.52131/joe.2021.0302.0045
Mokhova, N. & Zinecker, M., 2014, ‘Macroeconomic factors and corporate capital structure’, Procedia – Social and Behavioral Sciences 110, 530–540. https://doi.org/10.1016/j.sbspro.2013.12.897
Moradi, A. & Paulet, E., 2019, ‘The firm-specific determinants of capital structure – An empirical analysis of firms before and during the Euro crisis’, Research in International Business and Finance 47, 150–161. https://doi.org/10.1016/j.ribaf.2018.07.007
Mouton, M. & Smith, N., 2016, ‘Company determinants of capital of capital structure on the JSE Limited and the influence of the 2008 financial crisis’, Journal of Economic and Financial Sciences 9(3), 789–806. https://doi.org/10.4102/jef.v9i3.71
Moyo, V. & Markou, D., 2022, ‘The global financial crisis and the speed of capital structure adjustment: Evidence from South Africa research purpose’, Journal of Economic and Financial Sciences 15(1), 754. https://doi.org/10.4102/jef.v15i1.754
Moyo, V., Wolmarans, H. & Brummer, L., 2013, ‘Dynamic capital structure determinants: Some evidence from South African firms’, Journal of Economic and Financial Science 6(3), 661–682. https://doi.org/10.4102/jef.v6i3.253
Myers, S.C., 1984, ‘Capital structure puzzle’, Journal of Finance 39: 574–592. https://doi.org/10.3386/w1393
Myers, S.C., 2001, ‘Capital structure’, The Journal of Economic Perspectives 15(2), 81–102. https://doi.org/10.1257/jep.15.2.81
Myers, S.C. & Majluf, N.S., 1984, ‘Corporate financing and investment decisions when firms have information that investors do not have’, Journal of Financial Economics 13(2), 187–221. https://doi.org/10.1016/0304-405X(84)90023-0
OECD, 2020, The impact of the corona virus (COVID-19) crisis on development finance, viewed 14 July 2021, from https://www.oecd.org/coronavirus/policy-responses/the-impact-of-the-coronavirus-COVID-19-crisis-on-development-finance-9de00b3b/.
Opute, A., Iwu, C., Adeola, O., Mugobo, V., Okeke-Uzodike, O., Fagbola, O. et al., 2020, ‘The COVID-19-pandemic and implications for businesses: Innovative retail marketing viewpoint’, The Retail and Marketing Review: Special Covid Edition 16(3), 90–98.
Piaw, L.L.T. & Jais, M., 2014, ‘The capital structure of Malaysian firms in the aftermath of Asian financial crisis 1997’, Journal of Global Business and Economics 8(1), 24–41.
Ramjee, A. & Gwatidzo, T., 2012, ‘Dynamics in capital structure determinants in South Africa’, Meditari Accounting Research 20(1), 52–67. https://doi.org/10.1108/10222521211234228
South African Department of Health, n.d., COVID-19 risk adjusted strategy, viewed 17 August 2021, from https://sacoronavirus.co.za/COVID-19-risk-adjusted-strategy.
Strebulaev, I.A., 2007, ‘Do tests of capital structure theory mean what they say?’, The Journal of Finance LXII(4), 1747–1787. https://doi.org/10.1111/j.1540-6261.2007.01256.x
Tazvivinga, J.E., Mouton, M.M. & Pelcher, L., 2021, ‘Determinants of capital structure for retailing firms on the JSE’, Retail and Marketing Review 14(1), 55–64.
Thiele, F. & Wendt, M., 2017, ‘Family firm identity and capital structure decisions’, Journal of Family Business Management 7(2), 221–239. https://doi.org/10.1108/JFBM-05-2017-0012
Thippayana, P., 2014, ‘Determinants of capital structure in Thailand’, Social and Behavioral Sciences 143, 1074–1077. https://doi.org/10.1016/j.sbspro.2014.07.558
Vo, T.A., Mazur, M. & Thai, A., 2022, ‘The impact of COVID-19 economic crisis on the speed of adjustment toward target leverage ratio: An international analysis’, Finance Research Letters 45, 102157. https://doi.org/10.1016/j.frl.2021.102157
Appendix 1
|