Do Liquidity and Capital Structure Predict Firms’ Financial Sustainability? A Panel Data Analysis on Quoted Non-Financial Establishments in Ghana

Abstract

This study examined the connection between liquidity, capital structure, and the financial sustainability of 28 quoted non-financial establishments in Ghana. Panel data for the period from 2008 to 2019 was used for the analysis. In the study, liquidity was proxied by the current ratio, while the debt ratio was used as a surrogate of capital structure. Additionally, return on equity (ROE) was employed as a measure of sustainability. This indicator was used because of its flexibility as it can be applied to any line of business or product. From the results, the studied panel was cross-sectionally independent. Furthermore, the series were first differenced stationary and cointegrated in the long-run. The elasticities of the predictors were determined through the generalized method of moments (GMM) estimator, and from the results, liquidity proxied by the current ratio improved the entities’ financial sustainability. In addition, capital structure surrogated by the debt ratio promoted the financial sustainability of the establishments. Moreover, the interaction between capital structure and liquidity advanced the corporates’ financial sustainability. Size, growth, and operational efficiency were significantly positive determinants of the sustainability of firms, but asset tangibility had a trivial effect on the entities’ sustainability. On the causal relations among the variables, there was a bilateral connection amidst current ratio and return on equity; between cash flow ratio and return on equity; between debt ratio and return on equity; between size and return on equity; between operational efficiency and return on equity. Additionally, a single-headed causality moving from growth to return on equity was uncovered. Finally, there was no causal liaison amidst tangibility and return on equity. Based on the findings, it was recommended, amongst other suggestions, that an optimal liquidity level that is capable of supplying the firms with sufficient liquid resources should be maintained. Furthermore, the firms should use more internal funds to back their activities because that choice is safer than the alternatives. The corporates should also prefer that option because it has no associated costs that could adversely impact their sustainability.

1. Introduction

1.1. Financial Sustainability

Financial sustainability is the capacity of a firm to create value for owners and maintain operations long-term by using the best possible mix of investments and funding sources [1]. At the corporate level, financial sustainability may also refer to security of business, stability, and viability. According to Myšková and Hájek [2], financial sustainability is the ability of entities to make profit, optimize their value of invested capital, and offset their long- and short-term obligations at the same time. Koleda and Oganisjana [3] also viewed financial sustainability as the distribution of financial resources that promotes the sustainable development of corporates in the long term. Since value and business continuity are linked by a number of financial factors, the scope of financial sustainability encompasses all those factors. Under certain business circumstances, the best mix of the factors guarantees an optimal level of financial sustainability. According to Samiloglu and Demirgunes [4], managers in their quest for continuity, frequently maximize solvency and liquidity, which can lower a firm’s profitability. In this setting, the idea of an entity’s financial sustainability is occasionally likened to the risk–return model that is derived from the theory of investment [5]. Hence, management at the corporate level must choose whether to minimize risk and retain solvency and liquidity, or optimize investment returns and enhance financial leverage [1]. However, the association between risk and return is complex and relies on a variety of exogenous and endogenous factors. For example, Amini and Bienstock [6] and Sardaro et al. [7] reported that the sector of a business, location, and the stage of a business cycle are non-financial factors that can influence the risk and return as well as the sustainability of firms’ finances. In the year 2017, for instance, manufacturing firms in Poland exhibited higher profitability and liquidity ratios as compared to firms that violated the principle of risk and return. In the same year, however, service entities in the country demonstrated lower profitability and higher liquidity as compared to entities that obeyed the risk and return principle [1]. This implies that financial performance is heterogeneous across firms and depends largely on the measurement methods adopted.

Moreover, some empirical evidence shows that the affiliation between entities’ financial variables do not obey the principle of risk and return. For example, Samiloglu and Demirgunes [4] and Muscettola and Naccarato [8] document that profitability ratio is often negatively related to debt ratio, and establishments with a higher liquidity and retention ratio demonstrate higher profitability in the long term. This assertion is in tandem with the profit recognition concept of accounting and supports the hypothesis of pecking order, which stipulates that managers, in choosing financing options for corporates, should first opt for internal sources such as retained earnings, followed by debt, and lastly equity [9]. Put differently, profits are often transferred to retained earnings to help boost the liquidity and solvency of establishments [1]. It is, therefore, possible that profitable firms will have higher levels of financial sustainability and solvency than non-profitable firms. Hence, management should establish a suitable financial strategy, taking into account the existing business environment to help boost the financial sustainability of body corporates. The link between finance and sustainability has been extensively explored in the last decade of the 20th century. According to Asonuma et al. [10] and Palmer [11], most of those prior investigations centered on designing financial measures and shaping financial policies that could support sustainable development.

The role those financial institutions played in sustainable development was also studied vigorously. For instance, Fila [12] reported that the level of financial sustainability of the poorest segments of the population increased when banking services were made more widely available and financial literacy was improved. The challenges of financial sustainability in homogeneous groups of corporates grouped based on varied socio-economic attributes was also investigated [13]. For example, in dairy cooperatives, Jansik and Irz [14] indicated that members’ dual roles, typically serving as both owners and raw material suppliers simultaneously, could lead to conflicts that could impair the institutions’ sustainability and financial plans. Various efforts to ascertain the measures of financial sustainability at the firm level have also been made [15,16,17]. For instance, Altman [18] and Li [19] measured financial sustainability as the risk of bankruptcy (the capacity to meet obligations and fund business undertakings). Henock [20] used the ratio of financial revenue to operating expenses to measure financial sustainability in cooperatives and affirmed its reliance on factors such as deposit mobilization, donation, debt–equity relation, operating efficiency, and return on assets (ROA). According to Schwab et al. [21], managers must take into account key performance indicators, such as customer accounts receivable flow time and credit limit permitted by financial partners, when setting up financial strategies because the risk of bankruptcy was the main challenge for the financial sustainability of growing SMEs in Switzerland. Zabolotnyy and Wasilewski [1] applied the fuzzy logic approach to measure the relative level of financial sustainability of 12 food entities in Northern Europe. Taking into consideration the issue of risk and return, the indicators used to measure financial sustainability in the corporates consisted of retained earnings, interest coverage, liquidity, debt, operating efficiency, productivity, market capitalization, and profitability. It was disclosed that only a handful of the establishments reached the optimal level of financial sustainability. This means they managed to raise their level of solvency and value. It was also uncovered that firms with minimal levels of sustainability substantially differed from their counterparts as they displayed low levels of operating efficiency, profitability, and solvency.

The literature of financial sustainability makes it clear that a variety of financial indicators can be used to explain financial sustainability. In this study, return on equity (ROE) was used to measure the corporates’ financial sustainability. This suggests that an increase in the firms’ ROE made them more financially sustainable and vice versa.

1.2. Background of the Study

Market competition is rising, and the rapid rate of change is putting unprecedented pressure on businesses to not only thrive, but also maintain their success going forward. Firms, investors, and consumers have all turned their attention to corporate sustainability in recent years as it has become increasingly important. Entities can, however, not be sustainable without strong liquidity and a capital structure base. According to Gryglewicz [22] and Diakoulaki et al. [23], financially sustainable firms demonstrate good liquidity and capital structure positions, as these two are highly related to the profitability and solvency of businesses. Ali and Bilal [24] viewed liquidity as the capacity of entities to meet their commitments timely, without delays. According to the authors, a liquid entity is the one that can draw the right balance between current resources and commitments and can also take advantage of lucrative investment opportunities. Swagatika and Ajaya [25] equally described liquidity as an entity having the wherewithal to fund increments in its resources and settle its debts timely. As indicated by Mohd and Asif [26], firms are financially stressed when their liquidity is very inadequate, thus, hindering their operations. As a result, good liquidity management is vital for improved financial performance of entities [24]. The overarching aim of a firm is to maximize profitability [27,28,29]; however, keeping the liquidity ratio high is also key [30]. Maximizing earnings at the expense of liquidity can result in financial stress; hence, one cannot be pursued without the other [27,28]. In the opinion of Omesa [30], the two should be pursued simultaneously since they are both key for the survival of firms. When entities do not consider their net earnings, they might face demise in the long run. Conversely, entities may become bankrupt when they do not consider their liquidity levels. In view of this, liquidity management should be critically adhered to in all entities [30].

Additionally, capital structure decisions are among the central decisions of firms if they are to optimize their earnings and be competitive [31]. According to Peavler [32], capital structure is a combination of equity and debt that entities use to finance their undertakings. Good capital structure decisions look at proposals that curtail capital costs and optimize earnings per share. Contrastingly, bad capital structure choices can surge the cost of capital, minimizing shareholders’ returns [33,34]. Managers should, therefore, select the best capital structure combination that could raise companies’ earnings and curtail their costs of commitments [35]. The relationship between liquidity and the financial sustainability of entities has been extensively studied. The results are, however, contrasting. For instance, Ali and Bilal, Swagatika and Ajaya, and Hamidah and Muhammad [24,25,36], among several others, found a positive association between liquidity and the financial sustainability of entities, whilst Majumder and Uddin, Cudiamat and Siy, and Matin [37,38,39] identified an adverse connection between liquidity and an entity’s financial sustainability. An increasing number of investigations have also analyzed the connection between capital structure and an establishment’s financial sustainability, churning out different results. For example, Kanwal et al. [40] and Ngoc et al. [41] revealed an adverse association between capital structure and a corporate’s financial sustainability, while Ahmad [42], and Ayad and Mustafa [43] concurred to a positive affiliation between capital structure and an entity’s financial sustainability. Despite the many studies regarding liquidity, capital structure, and firms’ financial sustainability, limited research has been carried out to examine how the two variables affect the financial sustainability of Ghana’s quoted non-financial firms. This study was, therefore, conducted to help fill that gap. According to Goodman [44], a greater percentage of businesses are established in Ghana every year. However, approximately 90% of these businesses phase out or become irrelevant within one to three years. A lot of business owners lose millions of cedis to business failure, while others are being chased by banks and other financial institutions to retrieve loans offered to them. The important question is: what really causes business failure in Ghana? Offering answers to this question, Goodman [44] indicated lack of commitment and sustainability, and lack of sustainable funds as some of the reasons why establishments in the country fail. However, liquidity and capital structure have been proven to be major determinants of corporates’ sustainability in many geographical locations. Therefore, undertaking research to examine the connection between liquidity, capital structure, and the financial sustainability of quoted non-financial establishments in Ghana to help raise policy options to improve the undertakings of the firms was deemed appropriate.

This study contributed to the extant literature in diverse ways. First, in most prior studies at the firm level, financial and non-financial firms were combined together and used for analysis. However, financial entities normally have minimal capital expenses as compared to non-financial firms. Combining these entities could, therefore, lead to misleading deductions. This investigation targeted only listed non-financial establishments because they have similar features with regards to their debt and liquidity structure, rendering the sample very appropriate for testing the formulated hypothesis. Additionally, most preceding studies conducted in Ghana, to the best of our knowledge, concentrated solely on the connection between liquidity and corporates’ financial sustainability, or the affiliation between capital structure and firms’ financial sustainability, without studying how the variables could influence the financial sustainability of corporates when combined together in a model. This study is different from those prior explorations because it combined both variables in a model to examine their effects on firms’ financial sustainability. Moreover, the study used more robust econometric methods than previous studies did. For example, the Pesaran [45] CD test, along with others, were employed. To date, these methodologies have been rarely applied on firm-level studies in Ghana. Different from prior investigations that focused on exploring only the elastic effects of regressors on the regressand, this study also explored the causal connections amidst the series of concern. This is an essential step that could help improve the liquidity, capital structure, and financial sustainability debate. Our research is significant because it acts as a blueprint that promotes learning. The study is also vital because it is a guide to the effective management of liquidity and capital structure in establishments. The other parts of the report are organized as follows. Part two explains the literature that guided the study’s conduct, while part three outlines the study’s methodology. In part four, the results and their discussions are outlined, while the final part is on the conclusions and policy recommendations.

2. Literature Review

2.1. Liquidity and Firms’ Financial Sustainability Nexus

Myriad of research on liquidity and corporates’ financial performance has been conducted with conflicting discoveries. In Mongolia, for example, Batchimeg [46] investigated 100 listed companies and established liquidity as a trivial predictor of the entities’ financial sustainability. This outcome might not be robust enough to be generalized for all corporations in the world because the study was limited to Mongolia. The interpretation of the result, therefore, demands some caution. The revelation further suggests that the debate on liquidity and corporates’ financial performance is not over yet and, therefore, warranted a study of this nature. Nyamibo et al. [47] reviewed some of Kenya’s selected listed firms and confirmed liquidity as a major determining factor of the businesses’ financial sustainability. This result cannot be generalized for all firms in the world because the factors that hinder companies’ liquidity vary in different jurisdictions. Navleen and Jasmindeep [48] investigated some corporates in India and found that liquidity predicted the firms’ financial sustainability. The question for this discovery is whether this is the same for other entities across the globe. Our exploration, therefore, adds more insight into the topic under discussion. Some 201 businesses in India were investigated by Saripalle [49]. The study’s revelations confirmed liquidity as a vital determinant of the firms’ financial sustainability. Though this investigation is essential, it only considered ROA as the financial sustainability indicator. This raises queries about the reliability of the study’s outcome. Our study was, therefore, viewed as relevant since it adds to the discoveries of the above exploration. Swagatika and Ajaya [25] investigated certain Indian manufacturing firms. The study’s findings confirmed liquidity as a favorable predictor of the ROA and net profit margin of the entities. Even though the above discovery is very pertinent, our exploration adds more insights to the topic under discussion since it was conducted in a different environment and employed ROE as a financial sustainability indicator.

Furthermore, 23 quoted industrial companies were studied in Jordan by Ali and Bilal [24]. It was revealed that liquidity had a substantially positive liaison with the corporates’ financial sustainability. Though this research is very insightful, its finding could be different from that of this study since it was confined to only industrial entities in Jordan. Additionally, 153 listed entities in Turkey were investigated by Isik [50]. The study’s verdict established liquidity as a vital determinant of the entities’ financial sustainability. The above analysis was confined to ROA as the financial sustainability indicator. This could raise doubts about the vigorousness of the results. Our research, on the other hand, adopted ROE as the indicator of financial sustainability, which could add more insights to the topic under discussion. Maja et al. [51] investigated 956 companies in Croatia. Per the discoveries, liquidity had a converse connection with the corporates’ financial sustainability. Although this investigation is very current, it was conducted in a geographical location different from that of this study. Results of the two explorations can, therefore, not be generalized for all entities around the globe. Matar et al. [52] conducted research in Jordan and found a favorable linkage amidst liquidity and financial sustainability. Although this study is interesting, the choice of Jordan might not yield results that are similar to this investigation because factors that affect entities’ liquidity and financial sustainability may be varied in the two geographical locations.

Raykov [53] carried out a study in Bulgaria and found that during a crisis, controllable liquidity had an inversely weak association with firms’ financial sustainability. In Kenya, Akenga [54] studied 30 listed firms. The results show that liquidity had a favorable affiliation with the firms’ financial sustainability. This outcome contrasts that of Matin [39], who uncovered an adverse association amid liquidity and entities’ financial sustainability. The conflicting results warrant the conduct of this research. Kimondo et al. [55] researched 39 businesses in Kenya. Per the outcome, liquidity had a favorable linkage with the financial sustainability of the firms. Though the above investigation is essential, it was limited to Kenya. Its findings can, therefore, not be generalized for all entities around the globe. Research on 21 companies in Malaysia was carried out by Hamidah and Muhammad [36]. Findings of the study established liquidity as a positive determinant of the entities’ financial sustainability. This means liquidity helped to advance financial sustainability of the entities. Nazish and Shehla [56] analyzed 50 listed companies in Pakistan and affirmed cash gap as a substantially adverse predictor of the firms’ financial sustainability, but current ratio was a materially positive determinant of the sustainability of the corporates. In Kenya, Kung’u [57] investigated some selected manufacturing firms. From the results, liquidity management activities promoted the financial sustainability of the firms. Although the above research is very essential, its limitation to Kenya makes the discovery very difficult to be generalized for all corporations in the world. Ashutosh and Gurpreet [58] researched some entities in Punjab. From the discoveries, liquidity had an insignificant influence on the entities’ financial sustainability. This revelation signposted that liquidity failed to contribute to the corporates’ sustainability advancements. An exploration in Kenya was undertaken by Mwashi and Miroga [59]. The outcome affirmed liquidity as a favorable predictor of firms’ financial sustainability. This revelation supports that of Musah and Yusheng [29], but contrasts that of Pratheepan [60].

On a sample of 3363 SMEs, Schulz [61] undertook research and confirmed liquidity as a negative predictor of the businesses’ financial sustainability. This disclosure is very material; however, the analysis was skewed to only SMEs and, therefore, makes the finding unsuited to generalization for establishments that are not in that sector. Onwumere and Mmesirionye [62] researched Nigeria’s agribusiness market. The study results showed that liquidity promoted the financial sustainability of the firms. Though this investigation is essential, it was confined to only some selected entities in the country. This makes the finding very difficult to be generalized for all businesses in the nation and other countries. An investigation on 10 entities was undertaken by Mehmet and Mehmet [63]. Revelations of the study affirmed liquidity as a noticeably favorable predictor of the financial sustainability of the businesses. This revelation suggests that the corporates had more liquid resources that they could use to back their undertakings to become viable. In Kenya, 5 firms were investigated by Mutwiri [64] (2015). The outcome established liquidity as a trivial predictor of the companies’ financial sustainability. Though this exploration is key, the use of 5 businesses as a sample implies the finding should be interpreted with caution. Mohd and Asif [26] analyzed some Indian corporates and found liquidity as a favorable determinant of the firms’ financial sustainability. On quoted agricultural entities in Kenya, Kanga and Achoki [65] undertook an exploration and affirmed a positive liaison amidst liquidity and the corporates’ return on equity and return on assets, but a trivial connection amidst liquidity and the earnings per share of the entities. EJike and Agha [66] investigated 5 establishments in Nigeria. From the estimates, operational liquidity had a noteworthy influence on the firms’ viability. Zuraida et al. [67] analyzed 150 entities in Indonesia and established liquidity as a vital determinant of the firms’ financial sustainability. Although this outcome is very useful, the study focused on Indonesia, whilst our analysis focused on some chosen companies in Ghana. Establishments in these two nations might have different factors that affect their liquidity positions. This, therefore, makes the generalization of results very cumbersome. In Kenya, Jepkemoi [68] studied 10 quoted firms and found a trivial connection amidst liquidity and the firms’ financial sustainability.

2.2. Capital Structure and Firms’ Financial Sustainability Nexus

The association between capital structure and the financial sustainability of entities has been expansively explored with contrasting findings. For instance, an exploration on 20 agro-based companies in Nigeria was undertaken by Bassey et al. [69]. From the discoveries, capital structure essentially explained the entities’ financial sustainability. This investigation is very relevant, but as it was limited to Nigeria, its finding cannot be generalized for all entities in the nation or the world at large. In Nigeria, 10 companies were also analyzed by Akeem et al. [70]. It was revealed that sustainability of the companies was adversely linked to their financial structure. The sample size of 10 implies the results should be interpreted with caution, because if a large sample was to be used, the outcome might be different. In addition, Jalloh [71] carried out an analytical study on 9 institutions in Nigeria. Revelations of the study confirmed a vital connection amid capital structure and financial sustainability. This outcome indicates that improvements in the capital structure of the companies helped to increase their financial sustainability. The revelation offers us a firm base to conclude that variations or shifts in capital structure affect the financial sustainability of businesses, hence, the need for more investigations. Wabwile et al. [72] analyzed Kenya’s Tier 1 listed businesses. Disclosures from the research confirmed a material link between capital structure and financial sustainability. This research is very essential; however, its results cannot be generalized for all entities in the world since the capital structure of companies varies from nation to nation. Research on 50 listed companies in Iran was undertaken by Abolfazl et al. [73]. It was disclosed that financial sustainability had an opposing correlation with the corporates’ capital structure. Although this study is noteworthy, it was limited to capital structure and its repercussions on corporate financial sustainability in Iran. Our study is distinct from that of the above in that it analyzes capital structure and its repercussions on corporate financial sustainability in Ghana.

Research was undertaken by Brien et al. [74] on Japanese businesses. The discoveries affirmed a clear correlation amidst capital structure and financial sustainability. This outcome supports Enekwe et al. [75], who affirmed the absence of association between capital structure and firms’ financial sustainability in Nigeria. The variations in findings indicate that the capital structure–financial sustainability argument is unceasing and calls for further investigations. In Pakistan, Rehman [76] investigated listed sugar firms and confirmed a positive association between capital structure and the firms’ financial sustainability. Although the scope of our investigation is consistent with the above, further insights on the liaison amid capital structure and financial sustainability are provided because it was performed in a different geographical environment. Khalaf (2013) analyzed 45 Jordanian companies and found a trivial affiliation amidst capital structure and the firms’ financial sustainability, conflicting that of Sivathaasan et al. [77] in Sri Lanka. The contradictory revelations imply more investigations on the connection between capital structure and firms’ financial sustainability are needed. In Nigeria, 101 companies were investigated by Olokoyo [78]. The revelations affirmed a negative association between leverage and the firms’ financial sustainability. Though their investigation is insightful on the funding trends of companies, it was limited to Nigeria alone. Our exploration on how capital structure induces the financial sustainability of certain entities in Ghana was, therefore, very fitting. Some 237 businesses were analyzed by Mumtaz et al. [79] in Malaysia. It was confirmed that capital structure reduced the financial sustainability of the corporates. This research is very relevant; however, its outcome cannot be generalized for all entities because different factors affect the capital structure of entities in different environments. An analysis of 7 companies was performed by Pachori and Totala [80]. It was revealed that capital structure had minimal impact on the firms’ financial sustainability. The sample size of 7 implies that the finding should be interpreted with caution.

Babalola [81] researched 31 companies in Nigeria and found a trade-off amidst the merits and costs of debts. This revelation suggests that there are other factors that might induce the capital structure and the financial sustainability of companies. This is an essential discovery because it helps to expand the argument on capital structure and firms’ financial sustainability. Hasan et al. [82] analyzed some Iranian industries and deduced that leverage did not impact the potential market valuation of the businesses. This conflicts with that of Njeri and Kagiri [83] for Kenya. In Botswana, Sathyamoorthi et al. [84] investigated some entities and confirmed that the debt to equity ratio minimized the financial sustainability of the businesses. This research is very relevant; however, it is not possible to generalize its disclosure across all organizations because capital structure varies from nation to nation. Some corporations in India were investigated by Chandra and Udhayakumar [85]. Revelations of the study established an immaterial relationship between capital structure and the firms’ financial sustainability. This conflicts with that of Akeem et al. [70], who affirmed an inverse association between capital structure and entities’ financial sustainability in Nigeria. These contradictory outcomes imply that the capital structure–financial sustainability debate is not over and calls for further investigations such as ours. In India, Chadha and Sharma [35] investigated 422 entities. From the disclosures, leverage mitigated the firms’ financial sustainability. Research on some chosen businesses in Indonesia was carried out by Saputra et al. [86]. It was revealed that capital structure reduced the entities’ financial sustainability, collaborating that of Rouf [87] in Bangladesh. The divergent disclosures imply more investigations on the link amidst capital structure and corporates’ financial sustainability are needed.

Saifadin [88] investigated some of Iraq’s listed entities and confirmed capital structure as a noteworthy determinant of firms’ financial sustainability. This research is very insightful; however, care should be taken in interpreting its discovery because it was limited to Iraq. The outcome might be different if other nations were included in the analysis. Nassar [89] researched some Istanbul companies and confirmed capital structure as a significantly inverse predictor of the entities’ financial sustainability, in agreement with that of Vuong et al. [41] for the UK and Le and Phan [90] for Vietnam. These contrasting revelations suggest that more explorations on the capital structure–financial sustainability connection is needed. Some listed companies in Malaysia were researched by Basit and Irwan (2017). Disclosures from the research confirmed a converse linkage amidst capital structure and the firms’ financial sustainability. Ahmed and Afza [91] conducted research on 396 corporations in Pakistan and verified capital structure as a determinant of the firms’ financial sustainability. Though the exploration is very beneficial, its verdict cannot be generalized for all nations because it was confined to Pakistan. The outcome could be different if other nations were included in the analysis. In Sub-Saharan Africa, Kareem [92] analyzed some selected listed manufacturing firms and deduced a significant association between capital structure and the firms’ financial sustainability, supporting that of Javed et al. [93] for Pakistan, Twairesh [94] for Saudi Arabia, and Ogenche et al. [95] for Kenya. These contradictory studies underscore the need for more research on the issue at hand. Research on some chosen companies in Germany was undertaken by Abdullah and Tursoy [96]. The outcome of the exploration confirmed capital structure as a positive predictor of the entities’ financial sustainability. Though this investigation is relevant, its outcome should be interpreted with caution because the factors that hinder capital structure vary among jurisdictions.

2.3. Literature Gap

In conclusion, investigations on liquidity, capital structure, and corporates’ financial sustainability have yielded varied and conflicting outcomes. Many explorations have identified a positive association between liquidity and firms’ financial sustainability, whilst others have affirmed an adverse connection between the two. Similarly, plentiful investigations have revealed positive affiliation between capital structure and corporates’ financial sustainability, whilst others have discovered an adverse linkage amidst the two. The conflicting outcomes might be due to differences in geographical locations, sample collection, time frame, variable selection, diverse hypothesis, and econometric methods among others. Despite the many studies regarding liquidity, capital structure, and firms’ financial sustainability, limited research has been carried out to examine how the two variables affect the financial sustainability of Ghana’s quoted non-financial firms. This study was, therefore, undertaken to help fill that void.

3. Materials and Methods

3.1. Data Source and Descriptive Statistics

An unbalanced panel data on 28 establishments for the period from 2008 to 2019 was engaged for the analysis. The time frame used for the study was purely dictated by data availability. All data used for the analysis were computed from the annual reports of the sampled entities. These included, the statement of comprehensive income, statement of financial position, statement of cash flows, statement of changes in equity, and the notes to the accounts. The annual reports were downloaded from the website of the stock regulator. This source was considered because it provides the most accurate and reliable information on Ghana’s quoted companies. Additionally, information sent by businesses to this platform are diligently inspected by seasoned accountants. Further details on the studied variables are exhibited

Table 1. Measurement of Study Variables.

Variable	Measurement	Proxy
Return on equity (ROE)	Net Income/Total Equity	Financial Sustainability
Current Ratio (CR)	Total Current Assets/Total Current Liabilities	Liquidity
Debt Ratio (DR)	Total Liabilities /Total Assets	Capital Structure
Firm Size (SIZE)	Log of Total Assets	Control Variable
Assets Growth (GRO)	(Sizet− Sizet−1)/Sizet-1	Control Variable
Operational Efficiency (EFF)	Gross Revenue/Total Assets	Control Variable
Assets Tangibility (TAN)	Tangible Assets/Total Assets	Control Variable

. All 29 listed non-financial companies in Ghana as of 31 December 2019 formed the study’s target population. This number could, however, not be utilized for the analysis because of data constraints. As such, the purposive sampling approach was engaged to select a sample for the study. In adopting this approach, firms that did not contribute at least five years’ data could not be considered for the analysis. After strictly applying this bench mark, 28 companies representing 96.55% of the population was chosen for the analysis, while 1 firm representing 3.45% was rejected. The analyzed firms operated in diverse sectors such as consumer goods, oil and gas, health care, basic materials, and technology, among others. The firms were heavily capitalized and had similar features with regards to their debt and liquidity structure. This made the sample appropriate for testing the formulated hypothesis.

3.2. Model Formulation

The goal of this exploration was to examine the effect of liquidity and capital structure on the financial sustainability of listed non-financial entities in Ghana. In achieving this aim, the Generalized Method of Moment (GMM) estimator of Arelano and Bond [97] was adopted. The dynamic panel model developed to examine the nexus amidst the series was specified:

$$RO{E}_{i,t}={\alpha }_i+{\lambda }_{i}RO{E}_{i,t-1}+{\beta }_{1}C{R}_{i,t}+{\beta }_{2}D{R}_{i,t}+{\beta }_3{(CR\times DR)}_{i,t}+{\beta }_{4}SIZ{E}_{i,t}+{\beta }_{5}GR{O}_{i,t}+{\beta }_{6}EF{F}_{i,t}+{\beta }_{7}TA{N}_{i,t}+{\mu }_{it}+{\epsilon }_{i,t}$$

(1)

where return on assets (ROE) is the response variable representing financial sustainability; current ratio (CR) is the proxy of liquidity; debt ratio (DR) is the surrogate of capital structure; firm size (SIZE), assets growth (GRO), operational efficiency (EFF) and assets tangibility (TAN) are control variables to help minimize model specification bias; $CR\times DR$ is the interactive term between liquidity and capital structure. Moreover, ${\alpha }_i$ is the constant term, while β₁,……β₇, and ${\lambda }_i$ are the parameters to be estimated. Further, i signifies the studied firms, while t represents the time frame. Finally, ${\mu }_{it}$ denotes the firm-specific effects, while ${\epsilon }_{i,t}$ is the random error term. Our exploration used return on equity (ROE) as a measure of financial sustainability because it is not asset-dependent. Due to that, it can be applied to any line of business or product. Flexibility of the return on equity (ROE) also allows firms with different asset structures to be compared with each other. Finally, the asset-independency of return on equity (ROE) allows firms to compare internal product line performance with each other. This would be difficult if a performance measure such as the return on assets (ROA) is considered. A positive sign was predicted for β₁ in that establishments with solid liquidity grounds are able to meet their operational needs. This helps them to make more returns and, therefore, become sustainable [98]. A positive sign was also predicted for β₂ because large entities gain taxable income benefits that help them to be financially sustainable [99,100]. The sign of β₃ was to be positive because the interaction between liquidity and capital structure could propel the financial viability of the corporates. Similarly, β₄ was to be positive because large organizations use new technologies and are more successful in controlling their expenditure to raise their sustainability [101]. Likewise, β₅ was to positively predict the firms’ financial sustainability because corporates that grow have the potential to gain economies of scale over their competitors. This helps to boost their level of sustainability [100]. Moreover, β₆ was to be positive because the efficient use of a firm’s resources helps to boost its sustainability via more returns [64]. A negative sign was finally predicted for β₇ because tangibles are normally employed as securities by firms to secure debt finance. However, debt has high associated costs that negatively induce the sustainability of corporates [102,103].

3.3. Analytical Procedure

The researchers began the analysis by conducting the Breusch–Pagan LM test, Pesaran scaled LM test, and the Pesaran [104] cross-sectional dependence (CD) test to examine dependencies or otherwise in the panel. The above techniques test the null hypothesis of no cross-sectional dependence in the residual terms of a model. Therefore, failure to validate the hypothesis implies that the residual terms are cross-sectionally dependent. Afterwards, the LLC, IPS, ADF, and PP unit root tests were performed to assess the variables’ features of integration. These tests assume non-stationarity in the studied series. The rejection of this conjuncture implies that the variables are stationary. At the third stage, the Kao and the Johansen Fisher panel cointegration tests were undertaken to assess the series cointegration attributes. The above methods test the null hypothesis of no cointegration amidst series. Failure to accept this hypothesis signposts that the variables under consideration are flanked by a long term cointegration association. Next, the GMM estimator was engaged to estimate the elasticities of the predictors. This estimator was used because it is robust to endogeneity and cross-sectional independence. According to Mensah et al. [105], endogeneity is detrimental because the actual impacts of explanatory variables in a model could be underestimated or overestimated. Additionally, decisions based on inferences from the model could be sub-optimal. Thus, in the presence of endogeneity, biased and inconsistent parameter estimates are produced, leading to misleading tests of hypotheses. The GMM estimator is very vigorous to endogeneity because its model incorporates the lagged response variable as an additional explanatory variable. Under this estimation technique, firm-specific unobserved variabilities are reduced through the first differencing transformation. It, therefore, eliminates impacts unique to establishments. At the fifth stage of the analysis, the Breusch–Pagan heteroscedasticity test and the Wooldridge serial correlation test were conducted to assess the validity of the established model. Lastly, the Engle and Granger [106] causality test was engaged to examine the causal connections between the variables. This test was engaged because it allows for cross-sectional independence in panel data analysis. The technique tests the null hypothesis of no causality amidst series. Therefore, failure to validate the above conjuncture signposts causation between the variables of concern.

4. Results and Discussions

4.1. Descriptive Analysis

The descriptive statistics of the series are portrayed in

Table 2. Descriptive Statistics on Study Variables.

Variable	Mean	Maximum	Minimum	Std. Dev.	Skewness	Kurtosis
ROE	0.002	0.095	−0.072	4.410	18.248	334.003
CR	3.490	7.610	0.036	4.7100	14.355	216.809
DR	22.921	42.00	2.805	327.085	17.239	306.683
CR*DR	2.542	16.411	1.767	8.042	7.113	14.448
SIZE	4.780	8.734	0.662	1.465	0.427	3.356
GRO	0.036	0.977	−0.671	0.132	2.012	20.441
EFF	1.234	7.924	0.034	1.157	2.289	8.597
TAN	0.770	0.915	0.009	0.360	4.721	64.446

. According to the table, debt ratio had the uppermost average value, whilst return on equity had the least mean value. In addition, the distributions of all the series were flattered positively to the right. Further, the distributions of the entire variables were leptokurtic in shape (kurtosis values more than the standard 3). With reference to the skewness and kurtosis outcomes, none of the variables were normally distributed. This is consistent with the disclosures of the Jarque–Bera test depicted in

Table 3. Multi-Collinearity and Normality Tests Results.

Variable	Multi-Collinearity Test		Normality Test
	VIF	Tolerance	Jarque–Bera	Prob.
ROE	-	-	1,552,530.0	0.000 ***
CR	1.09	0.917	651,536.9	0.000 ***
DR	1.01	0.990	1,307,766.0	0.000 ***
CR*DE	1.05	0.953	275,401.5	0.000 ***
SIZE	1.03	0.971	11.971	0.000 ***
GRO	1.02	0.981	4485.324	0.000 ***
EFF	1.08	0.926	731.8045	0.000 ***
TAN	1.07	0.935	54,107.49	0.000 ***

Note: *** denote significance at the 1% level.

. Finally, there was no collinearity among the predictors as per the variance inflation factor and tolerance tests exhibited in Table 3.

4.2. Cross-Sectional Dependence Analysis

Because of common factors that are not observed, the issue of dependencies among cross-sectional units persists. Strong linkages between firms, emanating from their daily dealings, might account for such correlations. As indicated by Mensah et al. [105], the ignorance of cross-sectional dependence in regression analysis may result in the choice of wrong methods of econometrics that might lead to inaccurate estimates. With this in mind, the three CD tests indicated in

Table 4. Residual Cross-Sectional Dependence Tests Results.

Test Type	Value	Prob.
Breusch–Pagan LM	386.514	0.127
Pesaran scaled LM	7.895	0.852
Pesaran CD	3.551	0.414

were performed. Revelations from the test confirmed the panel to be cross-sectionally uncorrelated, suggesting that there could be no spillover effects from one firm to the other. The independencies might be driven by differences in business operations, firm size, industry, and other microeconomic factors. This verdict conflicts those of Sun et al., Donkor et al., Chen et al., and Musah et al. [107,108,109,110], whose studies established dependencies in the panels under study. Based on this verdict, econometric methods that are robust to CD were engaged for the ensuing analysis.

4.3. Unit Root and Cointegration Analysis

Secondly, due to the presence of independencies in the studied panel, the adoption of conventional or first-generation econometric techniques in establishing the integration properties of the series was valid. This is because those techniques assume cross-sectional independence. Therefore, the four tests indicated in

Table 5. Unit Root Tests Results.

Variable	Levels				First Difference
	LLC	IPS	ADF	PP	LLC	IPS	ADF	PP
ROE	−1.5062	−2.8832	97.2932	185.855	−9.0665	−7.6778	173.3710	395.8220
	0.466	0.112	0.621	0.202	0.000 ***	0.000 ***	0.000 ***	0.000 ***
CR	1.600	0.9635	54.3471	80.4382	2.3000	−3.6829	108.602	254.807
	1.000	0.832	0.538	0.318	0.050 *	0.001 ***	0.021 **	0.000 ***
DR	2.1094	1.9962	45.5713	73.1354	−8.5945	−4.3858	132.625	251.924
	0.983	0.977	0.839	0.162	0.000 ***	0.000 ***	0.000 ***	0.000 ***
CR*DR	−4.676	−1.154	54.323	65.522	−8.195	−5.157	121.191	258.297
	0.410	0.529	0.511	0.218	0.000 ***	0.000 ***	0.000 ***	0.000 ***
SIZE	2.8079	2.6598	40.3645	82.6187	2.5198	0.5255	66.3852	266.498
	0.998	0.996	0.943	0.111	0.094 *	0.000 ***	0.061 *	0.000 ***
GRO	−0.4119	−3.1311	89.5319	198.388	−4.4781	−5.9411	140.601	421.361
	0.340	0.601	0.212	0.422	0.000 ***	0.000 ***	0.000 ***	0.000 ***
EFF	−1.7219	−1.4548	75.1238	77.2389	−6.9768	−4.6933	124.462	240.201
	0.143	0.733	0.245	0.352	0.000 ***	0.000 ***	0.000 ***	0.000 ***
TAN	−4.9424	−3.7346	99.9197	125.147	−6.9768	−4.6933	124.462	240.201
	0.222	0.431	0.441	0.914	0.000 ***	0.000 ***	0.000 ***	0.000 ***

Notes: The top values for the variables denote unit root statistics, whilst the down values represent the corresponding probabilities. ***, **, and * signify significance at the 1%, 5%, and 10% levels, respectively.

were engaged to assess the integration order of the variables. From the tests’ outcomes, the entire series were first-differenced stationary, aligning the works of Saleem et al., Samour and Pata, and Musah and Li et al. [108,111,112,113]. The variables’ integration order signposts that they could be relevantly affiliated in the long term. Therefore, the tests depicted in

Table 6. Johansen Fisher Panel Cointegration Test Results.

Hypothesized	Fisher Stat.	Prob.	Fisher Stat.	Prob.
No. of CE(s)	(From Trace Test)		(From Max-Eigen Test)
None	547.4	0.000 ***	165.7	0.000 ***
At most 1	304.5	0.000 ***	229.3	0.000 ***
At most 2	348.2	0.000 ***	176.6	0.000 ***
At most 3	222.5	0.000 ***	115.6	0.000 ***
At most 4	153.1	0.000 ***	93.73	0.000 ***
At most 5	112.2	0.000 ***	69.49	0.013 **
At most 6	78.29	0.000 ***	72.36	0.000 ***
At most 7	34.08	0.045 **	31.08	0.034 **

Note: *** and ** denote significance at the 1% and the 5% levels, respectively.

and

Table 7. Kao Residual Cointegration Test Results.

Test Type	t-Statistic	Prob.
ADF	−6.514	0.000 ***
Residual variance	0.0452
HAC variance	0.0448

Notes: *** denotes significance at the 1% level.

were conducted to examine the series cointegration attributes. From the discoveries, the variables were significantly cointegrated in the long term. This outcome supports the works of Ali et al., Musah et al., Phale et al., and Amin et al. [114,115,116,117,118]. Based on this finding, the researchers proceeded to estimate the elasticities of the predictors.

4.4. Results and Discussions

After confirming cointegration association amidst the series, the GMM estimator was engaged to estimate the elastic effects of the regressors on the regressand. From the estimates depicted in

Table 8. GMM Estimation Results with ROE as the Response Variable.

Variable	Coefficient	Z	Prob.
ROEt-1	−0.523	3.31	0.002 **
CR	0.937	4.12	0.000 ***
DR	0.841	3.55	0.004 ***
CR*DR	0.504	3.16	0.005 ***
SIZE	1.496	4.41	0.000 ***
GRO	0.647	2.14	0.024 **
EFF	0.894	3.85	0.001 ***
TAN	−0.047	−1.14	0.712
Sargan test		38.82(0.613)
AR [2] test		−0.43(0.422)

Note: *** and ** denote significance at the 1% and the 5% levels, respectively.

, the lagged response variable was negative and significant at the 5% level. Ceteris paribus, a percentage change in the previous year’s financial sustainability, reduced the current year’s financial sustainability by about 52.3%. This might be as a result of management’s inefficiency to utilize the resources of the firms to generate more revenues. It might also be due to the firms’ poor marketing strategies; low product or service quality; macroeconomic factors, such as inflation, GDP, exchange rate, and interest rate; global economic shocks, and more. In addition, liquidity represented by the current ratio had a significantly positive effect on the firms’ financial sustainability. Specifically, a 1% rise in the current ratio surged the firms’ sustainability by 0.937%. This indicates that liquidity improved the entities’ financial sustainability. The verdict also implies that efficient liquidity management strategies, such as speeding the collection of receipts from debtors, were implemented by the corporates to ensure quick access to adequate cash to help improve the operations of the companies and, ultimately, their financial sustainability. The disclosure also signposts that management were successful in the eradication of wasteful and unsustainable short-term financing to help improve the firms’ financial sustainability. This outcome collaborates that of Akenga and Kung’u [54,57], but conflicts with those of Jepkemoi and Batchimeg [46,68]. Moreover, the parameter estimates of debt ratio was substantially positive at the 5% level. Ceteris paribus, a 1% rise in debt ratio, improved the firms’ financial sustainability by 0.841%. This finding suggests that the capital structure decisions of the firms helped to improve their financial sustainability. A probable reason for the positive connection between debt ratio and return on equity (ROE) is, that as the entities went in for more debt facilities, they were able to go in for more machineries and equipment to expand their operations, thereby making them more profitable. The firms might also be having a good debt capacity. As such, they were able to service their debt payments and raise new debts to expand their operations. The entities with a strong debt capacity were capable of withstanding market downturns and took advantage of opportunities that came their way. This helped to improve their level of sustainability. The finding supports the trade-off theory that predicts a positive connection between capital structure and the financial sustainability of establishments. The finding is, however, contrasting to the pecking order theory’s proposition of an adverse connection between capital structure and entities’ viability.

Moreover, the interaction term between liquidity and capital structure positively explained the entities’ financial sustainability. All factors held constant and a percentage change in the interactive term increased the financial sustainability of the firms by 0.504%. This suggests that liquidity and capital structure jointly promoted the corporates’ financial sustainability. In other words, capital structure improved the favorable impact of liquidity on the firms’ financial sustainability. Additionally, the elastic effects of size on the firms’ financial sustainability was positive and statistically significant. Specifically, a percentage surge in size promoted the financial sustainability of the firms by 1.496%. This finding suggests that a rise in the firms’ scope resulted in a rise in their financial sustainability. The disclosure agrees with the work of Isik and Tasgin [119], but conflicts that of Trujillo-Ponce [120]. Additionally, growth positively predicted the corporates’ financial sustainability. All factors held constant and a 1% surge in growth increased the entities’ financial sustainability by 0.647%. The finding suggests that the businesses implemented methods that were sufficiently successful to accelerate their operations. This helped them to gain more revenue to boost their resource base, leading to their growth and sustainability. An investigation by Lazăr [121] collaborates this disclosure, but that of Bhutta and Hasan [82] contradicts the revelation of the study. Moreover, operational efficiency positively explained the firms’ financial sustainability. Ceteris paribus, a percentage rise in operational efficiency, improved the sustainability of the entities by 0.894%. This suggests that authorities efficiently utilized the firms’ resources to advance their financial sustainability. A study by Gichuhi [122] is consistent with this disclosure, but that of Alemu [123] conflicts the above revelation. Finally, asset tangibility negligibly adversely explained the firms’ financial sustainability. This suggests that the tangible assets of the businesses did not have any material influence on their financial sustainability. The finding supports that of Demis [124], but conflicts that of Rajan and Zingales [125].

Return on invested capital (ROIC) was employed as a proxy of the firms’ financial sustainability to help check robustness of the ROE outcomes. As displayed in

Table 9. GMM Estimation Results with ROIC as the Response Variable.

Variable	Coefficient	Z	Prob.
ROEt-1	−0.464	2.86	0.051 *
CR	0.822	3.82	0.003 ***
DR	0.748	3.14	0.008 ***
CR*DR	0.341	2.45	0.034 **
SIZE	1.828	4.55	0.000 ***
GRO	0.517	3.06	0.007 ***
EFF	0.453	2.81	0.035 **
TAN	−0.022	−1.02	0.757
Sargan test		34.17 (0.761)
AR [2] test		−0.29 (0.321)

Note: ***, **, and * denote significance at the 1%, 5%, and the 10% levels, respectively.

, the parameter estimates varied in terms of weight, but the elastic effects of the explanatory variables on the explained variable, in terms of sign under the return on invested capital (ROIC), were the same as those under the return on equity (ROE). This implies that the results were robust. On the causalities between the variables displayed in

Table 10. Pairwise Granger Causality Tests Results.

Null Hypothesis:	F-Statistic	Prob.
ROEt−1→ROE	−4.421	0.047 **
ROE→ROEt−1	0.568	0.832
CR→ROE	8.006	0.000 ***
ROE→CR	6.003	0.000 ***
DR→ROE	8.004	0.000 ***
ROE→DR	5.404	0.014 **
CR*DR→ROE	6.023	0.000 ***
ROE→CR*DR	0.011	0.527
SIZE→ROE	4.136	0.087 *
ROE→SIZE	0.988	0.246
GRO→ROE	6.059	0.000 ***
ROE→GRO	8.071	0.000 ***
EFF→ROE	6.796	0.000 ***
ROE→EFF	5.042	0.022 **
TAN→ROE	1.038	0.452
ROE→TAN	0.882	0.348

Note: ***, **, and * denote significance at the 1%, 5%, and the 10% levels, respectively.

, the previous year’s return on equity (ROE) negatively caused the current year’s return on equity (ROE). This implies that the result element did not change in the same direction as its cause element. The negative connection between ROE_t-1 and return on equity (ROE) reported under the GMM estimation is in tandem with this discovery. In addition, a bidirectional causality between return on equity and current ratio was disclosed. This implies that the current ratio caused the firms’ return on equity (ROE) to rise, validating the regression outcomes. The finding contradicts the works of Osadune and Ibenta [126] and Maina [127], but collaborates that of Jawed and Kotha [128]. Additionally, a two-way causality between cash flow ratio and the return on equity (ROE) of the corporates was unveiled. This suggests that the rise in cash flow ratio led to the rise in the firms’ return on equity (ROE). This discovery validates the positive association between cash flow ratio and return on equity (ROE) reported under the GMM estimation. An investigation by Anowar [129] confirmed this revelation, however, those of Olarewaju and Adeyemi [130] and Demirgunes [131]) contradict the above disclosure. Further, bidirectional causalities between debt ratio and return on equity (ROE), and between debt to equity ratio and return on equity (ROE), were discovered. This implies that an increase in debt ratio and debt to equity ratio led to an increase in the firms’ return on equity (ROE). The estimates reported under the GMM estimation are in tandem with this outcome. A study by Shehryar [101] supports this discovery. Additionally, a two-way causality between size and the corporates’ ROE was unfolded. This implies that a surge in the firms’ size led to a surge in their return on equity (ROE). The regression outcomes of the study are in agreement with this finding. An exploration by Agiomirgianakis et al. [132] confirmed this disclosure, however, that of Muthusi [133] contrasted the study’s discovery. Further, a unidirectional causality from growth to the corporates’ ROE was unfolded. This indicates that growth in the firms’ operations helped to improve their return on equity (ROE). The results reported under the GMM estimation are in alignment with this finding. The disclosure is consistent with Ajayi and Zahiruddin [134], but contradicts that of Bhutta and Hasan [82]. Moreover, a bidirectional causality between operational efficiency and the entities’ return on equity (ROE) was confirmed. This indicates that an increase in operational efficiency led to an increase in the entities’ return on equity (ROE). The study’s regression outcomes are consistent with this result. Cuong et al.’s [135] research supports this finding, but those of Gichuhi [122] and Mehmet and Nuri [136] contrast the discovery of the study. Finally, there was no causality between assets tangibility and the firms’ return on equity (ROE). This implies that asset tangibility and return on equity (ROE) did not cause each other. The insignificant affiliation between tangibility and return on equity (ROE) reported under the GMM estimation are in line with this finding. A study by Demis [124] aligns this revelation, but that of Birhan [137] conflicts the outcome of the study.

5. Conclusions and Policy Recommendations

This study examined the connection between liquidity, capital structure, and the financial sustainability of 28 quoted non-financial establishments in Ghana. Panel data for the period from 2008 to 2019 was used for the analysis. In order to obtain valid and reliable outcomes, more robust econometric methods were employed. From the results, the studied panel was cross-sectionally independent. Additionally, the series were first differenced stationary and cointegrated in the long run. The elasticities of the predictors were determined through the GMM estimator, and from the results, liquidity proxied by the current ratio (CR) improved the entities’ financial sustainability. In addition, capital structure proxied by the debt ratio (DR) promoted the financial sustainability of the establishments. Moreover, the interaction between capital structure and liquidity advanced the corporates’ financial sustainability. Finally, size (SIZE), assets growth (GRO), and operational efficiency (EFF) were significantly positive determinants of the sustainability of firms, but asset tangibility had a trivial effect on the entities’ sustainability. On the causal relations among the variables, there was a bilateral connection amidst the current ratio (CR) and return on equity (ROE); between debt ratio (DR) and return on equity (ROE); between size (SIZE) and return on equity (ROE); between operational efficiency (EFF) and return on equity (ROE). Additionally, a single-headed causality moving from growth (GRO) to return on equity (ROE) was uncovered. Finally, there was no causal liaison amidst tangibility (TAN) and return on equity (ROE).

It was deduced from the analysis that liquidity was a materially positive predictor of the firms’ financial sustainability. This implies that liquidity helped to improve the sustainability of the entities. Based on this disclosure, it is recommended that an optimal liquidity level that is capable of supplying the firms with sufficient liquid resources should be maintained. To help advance the inspirations of the firms. surplus liquidity (if any) should be directed towards viable investments. In addition, the businesses should increase their stake in short-term resources and also take advantage of the use of commercial credit. This approach will represent a liquidity maximization system that could assist in the effectual administration of cash resources and operational capital, thus, enhancing the viability of the establishments. As well as this, managers in charge of liquidity should minimize the establishments’ receivables and inventory turnover periods. This approach will ensure unceasing supply of cash to the body corporates. A shorter period will, thus, advance the viability of the corporates. Furthermore, growth strategies such as market segmentation and the diversification of products should be considered by the entities. This approach will help to expand the size of the firms and will also allow them to gain access to credits when they are in short supply of liquidity.

It was also inferred from the analysis that capital structure was a significantly positive determinant of the firms’ financial sustainability. This signposts that a percentage increase in any of the capital structure proxies leads to a rise in the firms’ financial sustainability. Based on this verdict it is suggested that the firms should use more internal funds to back their activities because that choice is safer than the alternatives. The corporates should also prefer that option because it has no associated costs that could adversely impact their sustainability. The stock market in Ghana is fit enough to assist the firms to obtain financing through equity. Additionally, the businesses are recommended to fix their debts to a point that will not harm their fortunes. This is because severe debts imply a high degree of risks. Firms under such circumstances may not be able to obtain funds under dignified conditions or may not be able to acquire additional funds at all. Lastly, monetary policies that would lessen the borrowing costs of businesses should be instituted by the government. This will allow the entities to borrow at lower costs to improve their operations and become profitable. The study was, however, subjected to some limitations. Firstly, the researcher intended to use all quoted non-financial establishments in Ghana for the analysis, however, due to data constraints, the study was confined to only 28 of them. Therefore, in the future, when such data become available, similar explorations could be conducted to authenticate the outcomes of this study. Furthermore, the exploration was confined to corporates in Ghana. Therefore, the findings cannot be generalized for all entities around the globe. Upon thorough investigations, the relationship between macroeconomic indicators and the financial sustainability of Ghana’s listed non-financial entities has not been expansively studied. The researchers, therefore, suggest that future studies should concentrate on the causalities between inflation, GDP, interest rate, exchange rate, and the ROE of the aforementioned corporates.