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Abstract

Growing literature on cash holding and managerial ability provides the idea of studying these two concepts in the context of the same model. The effect of cash holding on firm performance is established in this study, which also looked at the moderating effect of managerial ability on the direct relationship between cash holding and firm performance—analyzing 2,858 Chinese non-financial firms, we employ OLS, fixed effect, and robust standard error regression to test the formulated hypotheses. We employ several additional tests to confirm the robustness of our findings. This study offers compelling evidence that managerial ability significantly impacts the relationship between cash holding and firm performance. We show that cash holdings boost the operating performance of firms with exceptional managers. Therefore, managerial expertise is essential when considering the cash and performance relationship. Prior studies focus on the direct relationship between cash holdings and firm performance. However, managerial ability, which is a crucial factor and an effect that affects this relationship, is overlooked. This study shows that firms with highly able managers boost their performance by holding more cash.

Plain language summary

Impact of cash holdings on firm performance with the moderating role of managerial ability

In this study, we delve into the intertwined dynamics of cash reserves and managerial ability within firms. We explore how these factors jointly influence firm performance, using data from 2,858 Chinese non-financial firms. Employing various regression techniques and additional tests, we unveil a significant finding: managerial skill significantly moderates the impact of cash reserves on firm performance. Specifically, we find that firms with adept managers experience enhanced operating performance when holding greater cash reserves. This underscores the critical role of managerial expertise in optimizing the cash-performance relationship. Our study fills a gap in existing literature by highlighting the often overlooked influence of managerial ability in shaping firm outcomes. By shedding light on this relationship, we contribute valuable insights for firms seeking to leverage their cash holdings effectively to drive performance under capable leadership.

Keywords

cash holdings data envelopment analysis (DEA)operating performance managerial ability firm efficiency

Introduction

This study looks at how managerial skills help make relationships stronger. This study specifically looks into whether having better managerial skills influences how positively cash holdings affect firm performance. How well can the manager convey and put the company’s strategy into practice? Given that a company’s survival ability depends on how well it manages its cash, this study assume that cash is an essential internal resource that managers can use (Gan & Park, 2017). When their less capable rivals struggle to implement the proper cash policies, more capable CEOs are expected to monitor, measure, and respond to capital structure decisions more effectively.

According to (Jensen, 1986), the CEO’s unique skills and motivations impact the many variations in company cash flow. Jensen (1986) highlighted the agency dilemma, which underlines the possibility that managers may decide to prioritize their agendas over shareholders’ interests regarding the firm’s liquid assets. According to this theory, board members, investors, and stockholders must look at how efficiently CEOs use cash to optimize the company’s future returns. Intuitively, this research anticipate that outstanding managers will be capable of quickly spotting investment opportunities, implementing value-adding tactics, and optimizing the company’s financial procedures (Lee et al., 2018). However, it is still unclear how the traits of the CEO relate to various degrees of managerial discretion and financial holdings. This research contend that this phenomenon of different financing behavior of Chinese enterprises should be explained by the effect of administrative skills on the relationship between cash holdings and firm performance.

Research on cash holding has gained considerable importance in the last two decades, and high cash balance in the balance sheet is the main reason for this trend (Bigelli & Sánchez-Vidal, 2012; Guney et al., 2003; Harris & Raviv, 2017; Kalcheva & Lins, 2007; Opler et al., 1999; A.Ozkan & Ozkan, 2004). Existent literature reports that firms in countries all over the world hold substantial amounts (between 10% and 23%) of cash in their balance sheet (Bates et al., 2009; Drobetz et al., 2010; Ferreira & Vilela, 2004; Harris & Raviv, 2017; Kalcheva & Lins, 2007; Opler et al., 1999; A.Ozkan & Ozkan, 2004).

The trade-off theory states that firms bear two costs for holding excess cash: cash management and agency costs. Managers who want to increase the shareholders’ wealth hold more cash and accept the opportunity cost of investing that cash into profitable projects (Guizani, 2017). Conversely, managers who are not working to increase shareholder wealth will use the surplus cash to fulfill their personal goals, raising the agency cost (Saddour, 2006). Jensen (1986) argues that if firms hold more cash, they will avoid external financing, benefiting entrenched managers because they stay out of the market monitoring mechanism.

The transaction cost motive, precautionary motive, and speculative motive are the three reasons for retaining extra cash, according to the Keynes (1936) theory of liquidity preference. The high expenses of obtaining money or selling assets will be avoided if surplus cash is on hand, which claims the transaction cost incentive. However, in light of a precautionary motive, firms can use more liquid assets to fund their investment projects when no other funding sources are available. Based on speculative purposes, firms hold cash to benefit from future bargain purchases. For example, if firms expect material prices to decrease in the future, they will keep more money to purchase raw materials at a low price. Therefore, firms hold cash to yield the benefit through abnormal opportunities like low interest rates, a fall in raw material prices, or a promising change in government policy that can benefit the firm.

The precautionary motive of holding cash justifies the positive influence of cash holding on firm performance (Lei et al., 2022). For example, greater financial flexibility protects firms from macroeconomic shocks and saves time in liquidating fixed assets and future transaction costs. Better investment choices are made due to having more financial flexibility, which in turn improves the profitability and market value of the company. Additionally, the pecking order theory states that organizations prefer to hoard cash to internally finance their projects to lessen the information asymmetry resulting from the lack of external financing. Despite all these benefits, keeping more liquid assets, such as cash, is harmful to the firm because it may create agency problems, and entrenched manager uses liquid assets to fulfil their agenda (Brealey et al., 2003; Dittmar et al., 2003; Jensen, 1986; Kim et al., 1998; Opler et al., 1999). Despite the costs mentioned above and the benefits of holding cash, it is still unclear which one is predominant. The motive for holding cash may be two-fold: precautionary and entrenchment. The precautionary motive is positively associated with firm performance, while entrenchment harms firm performance and leads to low profitability and reduced firm value.

A cash holdings agency problem is referred to as an agency motivation. According to Jensen and Meckling (1976), managers frequently use corporate resources to further their interests by investing in low-NPV projects rather than maximizing owners’ wealth. According to Jensen (1986), companies with limited access to capital are valued higher than those with unlimited access to cash and are more likely to be involved in unsuccessful mergers and acquisitions. According to Harford et al. (2008), managers prefer to use corporate capital to expand their empires; hence, weaker corporate governance frameworks lead to lesser cash holdings (Jensen, 1986). On the other hand, the management of organizations with weak governance would prefer to have more cash on hand since it is more feasible for them and protects them from market scrutiny Easterbrook (1984). When corporations have poor corporate governance, Yun (2009) finds that they prefer unmonitored cash to bank credit. Furthermore, according to Seifert and Gonenc (2018), firm-level governance favorably correlates with cash value and inversely with cash holdings.

Managers control the firm’s assets, especially internal capital, including cash holding. It is totally under the manager’s authority and discretion how they spend cash Liu and Mauer (2011), whether they waste it through rent extracting or investing in profitable projects under the efficient contracting hypothesis. The neo-classical framework claims that competent managers continue investment in the profitable project until the equilibrium point of marginal cost and benefit (Habib & Hasan, 2017). This assertion is supported by the efficient market theory, which maintains that managers always have access to sufficient funding without incurring additional costs to invest in profitable projects and pay dividends on any remaining funds (Abel, 1983; Hayashi, 1982; Yoshikawa, 1980). Contrary to this argument, agency theory claimed that managerial self-interests urge managers to waste resources in negative NPV projects or through suboptimal investment decision.

this study investigate the phenomena of cash holding and operating performance for Chinese listed enterprises using a measure of managerial ability developed by Demerjian et al. (2012). Among all other growing Asian nations, China’s phenomenal economic growth is regarded as a miracle. The findings of this study are interesting. This research finds that a firm’s cash holding positively and significantly enhances the firm’s performance, as measured by the return on assets. Additionally, according to the results a positive relationship between cash holding and firm performance is more substantial in firms with highly exceptional managers while examining the moderating effect of managerial ability on the direct nexus between cash holding and firm performance.

In many aspects, this study adds to the body of literature. Primarily, by demonstrating the positive effect of cash holding on operating performance, this research enriches the current research on cash holding and a firm’s operating performance, especially in the Chinese context. Prior studies have only reported the value of a firm’s cash holding (Faulkender & Wang, 2006; Kalcheva & Lins, 2007; Opler et al., 1999; Pinkowitz et al., 2006; Pinkowitz & Williamson, 2007). Our best understanding indicates that no research has been done to test this phenomenon, particularly in the setting of China. Our focus in this study is on China’s fast-growing and emerging economy. The high ownership concentration, insufficient investor protection, and weak institutional structure still plague China’s economy, making it the perfect place to examine cash holding and firm performance and evaluate the moderating role of managerial ability. This study will add to the body of research on firm performance by examining the effect of cash-holding policies on firm performance. However, unlike other recent reviews on managerial ability and cash holding by Gan and Park (2017), this study have documented the moderating role in strengthening the cash performance relationship. While Gan and Park (2017) only describe the influence of managerial ability on a firm’s cash holding level.

Cash reserve management within corporate finance is a critical part of strategic decision-making, with significant effects on a company’s long-term viability, operational flexibility, and financial stability. Contemplating the “lifeblood” of a firm, cash reserves are a crucial fragment of its financial architecture, acting as a safeguard against unforeseen events, allowing for strategic expenditures and opening doors for expansion attempts (Cardella et al., 2021). The strategic potential of cash reserves to generate value and reduce risk, in addition to their critical role in preserving liquidity, makes them important. Firms with substantial cash reserves have a considerable advantage during market or economic declines because they can better weather financial storms, seize strategic opportunities, and come out stronger on the other side of hardship (Denis & Wang, 2024). Moreover, cash reserves provide stakeholders such as creditors, suppliers, and investors’ confidence by displaying the corporation’s strength and stability financially. Even though cash reserves are extremely important, the ideal degree of liquidity is still being discussed and examined in the financial community (Ezeani et al., 2023). For business executives, realizing the right equilibrium between liquidity and profitability is a persistent dilemma. They have to traverse a complicated environment of competing goals, such as commitments to shareholders, investment opportunities, and debt. Furthermore, outside variables like macroeconomic trends, legal requirements, and market conditions exacerbate the dynamics of cash management and call for flexible and well-informed decision-making (Houqe et al., 2023).

In light of this, understanding the effects of cash reserves has become an important area of study for academics and managers. Scholars have endeavored to elucidate the complexities involved in cash management choices by examining variables like firm size, industry traits, and budgetary limitations that impact cash holding strategies (Subramaniam et al., 2011). Furthermore, empirical research has attempted to determine the connection between cash reserves and firm performance, providing insight into the ways that liquidity affects shareholder value, investment behavior, and operational effectiveness (La Rocca & Cambrea, 2019).

In view of the aforementioned, this study aims to add to the growing body of research on cash reserves by examining the influence of cash reserves on business performance and the moderating function of management ability. This research aims to offer important insights into the strategic ramifications of liquidity management as well as its consequences for organizational resilience and value creation by exploring the dynamics of cash management within the framework of managerial decision-making. This study seeks to contribute to management practice and scholarly conversation by providing practical guidance for navigating the complexity of contemporary corporate finance through a thorough empirical examination.

Today’s competitive and dynamic business environment has made the strategic management of financial resources a crucial factor in determining a company’s success. Among these resources, cash holdings are crucial in determining a company’s operational effectiveness and financial health. The choice a company makes about the amount of cash reserves it keeps on hand can significantly impact its profitability, investment prospects, and liquidity management. Therefore, academics and finance and strategic management professionals must comprehend the elements that affect cash-holding practices and how they affect business outcomes. There are still several gaps in the body of knowledge regarding the causes and effects of cash hoarding, even after substantial research. Previous research has largely ignored the complex dynamics that underpin this relationship in favor of concentrating on the static trade-off between the advantages and disadvantages of keeping cash on hand.

Furthermore, little research has been done on the moderating effect of managerial competence, an essential but little-studied component, in the context of cash management choices. This paper attempts to bridge these gaps by examining the relationship between cash holdings and firm performance and the moderating effect of management skills. Our goal is to offer a thorough grasp of how managerial abilities and decision-making acumen influence the relationship between cash reserves and business performance by fusing ideas from organizational behavior and finance. Our research contributes to the body of knowledge by offering new insights into how managerial skill influences financial policies and fortifies firm performance resilience in economic uncertainty. Moreover, governments, investors, and business executives can practically benefit from our study. Our research can help organizations make more strategic decisions about how to allocate their resources, manage risk, and create value by clarifying the role that managerial talent plays in optimizing cash management techniques. Furthermore, our research emphasizes how crucial it is to develop and use managerial talent to improve organizational competitiveness and resilience in today’s fast-paced business environment.

Literature Review and Hypothesis Development

Managerial Ability

A sizable body of research has been done on how management aptitude, talent, and reputation have evolved and how that has affected organizational decision-making. Friend and Lang (1988) study was one of the first to assess how much leaders impact the financial practices of the firms. They found that the debt ratio tended to be higher when managers participated less in company decisions. Another study by Berger et al. (1997) confirms that the firm’s debt ratio decreases as manager oversight increases. On the other hand, a plethora of research shows that American businesses have sharply expanded their cash holdings over the past few decades (Harford et al., 2008; Pinkowitz et al., 2013). Although earlier research has extensively examined multiple firm-specific characteristics and institutional factors associated with cash holdings (Harford et al., 2008; Oler & Picconi, 2014; Opler et al., 1999; A.Ozkan & Ozkan, 2004; Pinkowitz et al., 2013), there has been little research to date on the relationship between managers’ human capital attributes and its impact on the cash holding and performance relation.

Extant literature in business management has discussed how different levels of managerial ability (MA afterward) significantly influence a firm’s decision-making quality, the ordinary course of action, and economic outcomes (Inam Bhutta et al., 2021). Prior literature has used different proxies of managerial ability according to research needs. Two of the proxies of managerial ability considered by the researcher in prior literature are the CEO’s compensation and firm performance (Brick et al., 2006; Core et al., 1999; N.Ozkan, 2011). As claimed by Harris and Holmstrom (1982) in their dynamic model of efficient wage contract, a manager’s productivity over time significantly reflects his/her ability, and many studies empirically supported this theoretical argument by testing and reporting a direct relationship between MA and firm performance (Baik et al., 2011; Habib & Hasan, 2017; Rajgopal et al., 2006). Chang et al. (2010) also reported that firm performance and CEO compensation are significantly and positively associated and lead to an improved labor market for the CEO.

Literature has also discussed a prominent proxy for managerial ability known as CEO reputation (Abdullah et al., 2016; Baik et al., 2011; Francis et al., 2008; Milbourn, 2003; Rajgopal et al., 2006) measured as CEO name citations in the public press articles. For instance, Milbourn (2003) developed and tested a model explaining the link between CEO reputation and stock-based pay sensitivities and reported a positive correlation. Francis et al. (2008) reported a positive link between CEO reputation and earnings quality. Moreover, Baik et al. (2011) provided evidence that the frequency of management earnings projections and the CEO’s abilities are positively correlated. The study further reported that earnings forecasts of high-ability CEOs followed by a positive market reaction compared to those issued by less able CEOs, indicating that high-ability CEOs convey more accurate and high-quality information than CEOs with lower abilities. Furthermore, Goodman et al. (2014) used another proxy of managerial ability measured through managers’ externally reported earnings forecasts and documented a positive association between MA and the quality of a firm’s investment decisions.

Although these proxies mentioned above of managerial ability have served their immediate purpose according to the research needs and objectives, there are some strong concerns and questions about the exhaustiveness of these measures and whether these managerial ability measures fully accounted for the manager-specific factors. Moreover, were related factors controlled while calculating those proxies? (Demerjian et al., 2012). To respond to these concerns and answer questions regarding the validity of prior measures, Demerjian et al. (2012) have developed an utterly exhaustive test of managerial ability. This new measure accounted for or captured actual managerial ability by dividing total efficiency into firm-specific and manager-specific efficiency. MA measure of Demerjian et al. (2012) measures the manager’s effectiveness in converting firms’ resources into sales compared to their industry peers. The author claimed that this measure of MA is less noisy and more valid than other standards as it only captures the manager’s specific factors of ability.

Extant literature has adopted MA measures developed by Demerjian. For instance, studies by Demerjian et al. (2013) used MA in earnings quality. They reported positive findings that MA positively impacts earnings quality, whereas Demerjian et al. (2012) and Baik et al. (2011) reported similar results across all managerial ability measures and measures of Demerjian. A recent study Cho et al. (2018) inspects the effect of MA on the cash holding speed of adjustment toward the optimum cash level. Results showed that MA is inversely connected to how quickly cash holdings fluctuate. This implies that firms with highly skilled management adjust slowly toward their cash-holding goals, particularly when they accumulate extra cash to the target level. A recent study on CEO managerial ability by Gan (2019) states that more capable CEOs make more effective investment choices because of their superior capacity to assess and foresee the dynamic changes in the business environment and identify growth prospects for their companies. More able CEOs efficiently handle capital expenditure, acquisition expenditure, and total investment, primarily when firms operate in under (over) investment situations. Mitra et al. (2019) investigated whether MA played a role in the relationship between managerial overconfidence and audit fees and revealed that managerial overconfidence increases audit fees. Lee et al. (2018) inspect the nexus between MA and investment opportunities. The study’s findings indicate a strong positive association between superior MA and investing opportunity, albeit this relationship varies depending on the economy.

All these studies have employed managerial ability measures developed by Demerjian simultaneously with other standards and reported better and consistent results.

Cash Holding and Operating Performance

After the inception of liquidity preference theory and its introduction to economic literature, academics got interested in cash hoarding. Keynes’ (1936) liquidity preference theory proposes three primary motives for keeping liquid assets: Firstly, future transaction costs and time will be reduced. Secondly, to grasp future growth opportunities while protecting the company from unforeseen shocks like the financial crisis. Finally, the speculative reason. On the other hand, many studies, such as Jensen (1986), argue that cash holding hurts firm performance. Since cash is a liquid asset, entrenched management can readily hoard it and utilize it to promote their goals (Dittmar & Mahrt-Smith, 2007).

According to Jensen (1986) theory of free cash flow, managers want to accumulate more funds, which they can use for their gain and give themselves a significant advantage in investment decisions. When businesses save considerable cash, their reliance on outside finance decreases, allowing managers to invest in less profitable activities that reduce owner wealth (Harford, 1999). Harford (1999) explains that businesses with much cash tend to participate in mergers and acquisitions that lower corporate value, believing that the company will have much cash on hand and possibilities for wise investments to address underinvestment. In contrast to other nations where investor protection is robust, Pinkowitz et al. (2006) showed that the association between business performance and cash holdings is substantially lower in countries where shareholder protection is low. Businesses typically maintain substantial cash holdings because they offer the benefits of financial flexibility and do not incur agency costs to avoid raising financing from outside sources (Myers & Majluf, 1984). Jensen (1986) counters that considerable cash reserves have agency costs and offer no financial flexibility; thus, businesses only keep small amounts of cash on hand. Based on the arguments in the empirical literature, one can claim that cash balances incur agency costs and give financial flexibility. Investors will pressure company management to keep cash holdings to a minimum to save agency costs, but they will also encourage managers to keep enough cash on hand in case unforeseen capital requirements arise. This is because maintaining large cash balances is not always advantageous. Fukuda (2011) shows that companies with large investment prospects regard their cash holdings highly, despite the fact that financial constraints like access to the capital markets and debt ratios have no bearing on a company’s success.

Given the above-mentioned competing viewpoints, determining the link between financial holding and the performance of firms, particularly in the context of China, is difficult. According to several studies, higher corporate performance results from enhanced liquidity and financial flexibility (Frésard & Salva, 2010; Kalcheva & Lins, 2007). Many authors have identified the drawbacks of holding liquid assets, including higher agency costs and inefficient resource management, ultimately resulting in subpar business performance (Huang et al., 2013; La Rocca & Cambrea, 2019). Although there is a wealth of literature on the connection between cash holdings and company performance, some studies indicate that this connection is not linear (Harford et al., 2008). Using the justifications presented above, this study suggests the following (Figure 1):

H1: Cash holding positively and significantly enhances operating performance.

Figure 1.

Conceptual framework.

Moderating Effect of Managerial Ability

Managers control the firm’s assets, especially internal capital, including cash holding. It is totally under the manager’s control and discretion on how they spend cash (Liu & Mauer, 2011). Since excess cash holding may be wasted through suboptimal investment decisions, which destroy firm performance, it is central to understand various firm-level and country-level control mechanisms for constraining these kinds of value-damaging activities. This study considers MA to be one of the most significant control mechanisms. Our current investigation into whether top managers impact critical business choices has piqued our curiosity in exploring the moderating role of MA on the direct relationship between cash holding and firm operating performance. Barney (1991) argued that the manager’s ability to recognize a firm’s environment and efficiently deploy the firm’s resources is considered a valuable resource that helps firms efficiently compete in the dynamic business environment. Managers play a significant role in business decision-making, whether with R&D expenditure or acquisition (Bertrand & Schoar, 2003).

Following Ensuing (Francis et al., 2008), this study will discuss the role of exceptional managers in deploying firms’ resources, especially internal capital. Two mutually exclusive hypotheses argue about how managers decide about the firm’s resource deployment. One is an efficient contracting hypothesis, and the second is the rent extraction hypothesis. The efficient contracting hypothesis justifies the positive effects of MA on the link between cash holding and firm performance. According to a previous study, managers with exceptional abilities are better at predicting the timings of returns and the risk associated with the investment (Demerjian et al., 2013). Managers with exceptional capabilities are better able to understand the market trend and also better able to obtain and interpret investment information. Therefore, they invest the firm’s resources in profitable projects (Chemmanur et al., 2009). Therefore, based on these arguments, this study proposed the following;

H2: The positive effect of Cash holding on a firm’s operating performance is more pronounced in firms with managers having exceptional abilities.

Data and Methodology

The China Stock Market and Accounting Research (CSMAR) database served as the source for the data used in this study. A and B shares are traded in China, with A shares being local currency-denominated and sold only to Chinese nationals. In contrast, B shares were launched in 1992 in foreign currency denomination and intended to be traded by foreigners. This study only used data related to A-shares (instead of B-shares) traded on the Shanghai and Shenzhen stock exchanges because B-shares are relatively small in numbers and trade have a low trading frequency as compared to A-shares (Li et al., 2013; Wang & Xu, 2004). Data for only non-financial firms from 2003 to 2018 has been extracted and used in this study. Financial firms have been excluded because of their mismatch in capital structure and leverage policies with that of non-financial firms.

Dependent Variables

Performance measurement is crucial to effectively and efficiently managing a firm’s resources (Al-Matari et al., 2014). Two primary measures are available to measure corporate performance: accounting-based and market-based. Return on Assets is an accounting-based metric used to assess how well a company’s operational and financial activities are performing (Love & Klapper, 2002) or The return on assets (ROA) informs shareholders how well an organization converts its assets into net capital (Arhinful & Radmehr, 2023). A high return on assets indicates that the firm effectively and efficiently uses its resources to achieve its goals and improve shareholders’ value (Arhinful & Radmehr, 2023; Ibrahim & Samad, 2011). The return on assets (ROA), calculated as operating profit divided by total assets, is the primary dependent variable to assess the firm performance. ROA is an accounting measure to test whether a firm uses its assets efficiently to earn profit and increase shareholder wealth. For the robustness check, an additional proxy of firm performance was also used. To verify the findings, this study employed another accounting-based metric called return on equity (ROE) (Arhinful & Radmehr, 2023). ROE is a profitability indicator used to calculate the return on shareholders’ investment in a company. It shows how well the money owned by shareholders has been invested. Net income is divided by total equity to get ROE. Because of the company’s low ROE, shareholder funds may be allocated more wisely. ROE is a crucial metric for assessing a business’s performance. A higher number means that the business successfully converts new investments into earnings. Investors compare the ROE of different companies in the market before making an investment (Arhinful & Radmehr, 2023).

Independent Variables

The primary independent variable in this study is regarded to be cash holding. Following prior literature, this study calculate cash holdings as the proportion of cash and cash equivalents to the total firm assets (Harford et al., 2008; A.Ozkan & Ozkan, 2004). Following Itzkowitz (2013) to use an alternative proxy of cash holding as our independent variable for the robustness check. Alternatively, cash holdings is measured as a natural logarithm of 1 + cash and cash equivalents scaled by total assets.

Moderating Variables

Measuring Firm Efficiency

This study uses Demerjian’s measure of Managerial Ability (MA) to inspect the moderating role of MA on cash and performance relationships. In the measurement procedure of MA, the first step is to calculate the firm’s efficiency using the data envelopment analysis (DEA) technique proposed by (Banker et al., 1984; Charnes et al., 1978). Data envelopment analysis is a nonparametric technique that calculates the relative efficiency of each decision-making unit (DMU) by benchmarking the efficient peers. In DEA, each DMU is considered as the processor of specific inputs (Net Property, Plant, and Equipment; Goodwill; R&D; Other Intangible Assets; Cost of goods sold; and Selling, General, and Administrative Expenses are the inputs in this case) and convert these inputs into outputs (i.e., sales revenue). The mathematical expression of this process is;

Max efficiency = \frac{\sum_{i = 1}^{s} u_{i} . y_{ik}}{\sum_{j = 1}^{m} v_{j} . x_{jk}}

(1)

where

k = 1, …., n

u_i, v_j ≥ 0

efficiency = 1

Where y denotes the output, x represents the input, and k means DMUs, which are firms used for analysis in this study. This study considered six inputs and one output; initially, there were seven inputs in Demerjian’s paper since the operating lease data is unavailable in China. Therefore, operating lease was dropped as input. The user inputs are directly affected by managers’ decisions, thus representing managers’ ability to deploy these inputs efficiently to convert them into maximum output. Equation (1), u, and v denote the non-negative weights assigned to outputs and inputs to calculate the relative efficiency score. After that, equation (1) optimized following Demerjian et al. (2012) find the efficiency scores of each DMU (firm); the efficiency score’s upper bond is 1, and the lower bond is 0. There are two significant benefits of using DEA in efficiency calculation. First, it calculates the ordinal ranking of relative efficiency scores. Second, compared to regression analysis, which computes the average based on data of all DMUs and indicates the average trend of aggregate data, DEA calculates the efficiency score of each DMU separately by benchmarking the best-performing peers.

Measuring the Managerial Ability

After calculating the efficiency scores for each firm, these scores can be used to measure managerial ability. Hence, these scores are attributed to firm-specific factors and managers’ specific factors; therefore, they are likely to overestimate managerial ability.

Therefore, measure the MA following Demerjian et al. (2012), to avoid contamination of firm-specific factors in MA, separated firm efficiency from managerial ability by controlling for the firm-specific factors contributing to firm efficiency through regression analysis. These firm-specific variables include firm size, market share, free cash flow, life cycle stage, diversification, and foreign operations.

Assuming the MA constant, Managers of more giant corporations with high market shares are expected to be more efficient and productive than others with small-size firms and low market share. Similarly, managers in firms with excessive cash flows are expected to pursue efficient investment policies. Furthermore, the firm life cycle stage might affect the firm’s efficiency by changing the investment opportunity set and the initial investment or start-up cost of projects. The life cycle has been calculated by subtracting the listing date from the current year, and the final variable is the number of years since the firm has been listed on the stock exchange (DeAngelo et al., 2010). Lastly, firm diversification has also been included in the model because firms operating in multiple industries make it challenging for managers to allocate resources efficiently to each business unit, therefore, require extensive knowledge and experience, also divide manager’s attention over multiple industries (Demerjian et al., 2012; Stein, 1997). A dummy variable to indicate the firm’s foreign operations was also used—finally, the final managerial ability variable will be calculated using the following equation. This equation uses clustered Tobit regression and cluster standard error by year and firm to control the cross-sectional and intertemporal correlation—the resulting residuals of this equation used as the final managerial ability variable.

\begin{matrix} Efficiency Score = α + β 1 FirmSiz e_{i} + β 2 FirmAg e_{i} + β 3 FC F_{i} \\ + β 3 MarketShar e_{i} + β 5 Diversificatio n_{i} \\ + β 6 ForeignOperati o_{i} \end{matrix}

(2)

Model

First, a static panel regression was employed to estimate the model. This methodology helps deal with individual heterogeneity and unobserved firm effects.

\begin{matrix} Performanc e_{it} = α + β_{1} Cas h_{it} + β_{2} TANG + β_{3} LE V_{it} \\ + β_{4} GRW T_{it} + β_{5} SIZ E_{it} + β_{5} Ag e_{it} + ε_{i} \end{matrix}

(3)

As previously said, the cash-performance link cannot be viewed as simple and direct as given in the equation (equation (3)) above. Further, this study will examine the moderating role of MA on the cash-holding firm performance relationship.

Consequently, the interaction term of managerial ability (MA) with cash holdings was included to estimate the following model.

\begin{matrix} FIRM_PERFORMANC E_{it} = α + β_{1} Cas h_{it} + β_{2} MA s_{it} \\ + β_{3} Cas h_{it} \times M A_{it} + Σ Contro l_{it} + ε_{i} \end{matrix}

(4)

Where $Cas h_{it}$ denotes cash holdings, $MA s_{it}$ represents managerial ability, $Σ Contro l_{it}$ represents a list of control variables, which includes leverage, size, tangibility, age, and growth, and $ε_{i}$ represents error term.

Results and Discussion

Summary Statistics

Summary statistics for the variables used in this study are shown in Table 2. The average return on assets in sample firms is 3.9%. Return on equity has a mean value of 6.6%. Cash holdings have a mean value of 0.174 which means approximately 17.4% of a firm’s total assets are held in the form of cash and cash equivalents. This value is as high as the literature on cash holdings shows (i.e., Lian et al., 2011). This high average cash holding value suggests that most Chinese companies maintain a sizable share of their assets as cash. The mean value of assets tangibility indicates that firms hold an average of 24.1% of total assets as tangible assets. Leverage indicates that the average value is 44.4%. Table 1 also shows that Chinese firms’ average sales growth rate is 22.2%. Finally, Table 2 shows that managerial ability has a mean score of 0.007.

Table 1.

Variable Description.

Variables	Definitions
CASH	Cash and cash equivalent divided by total assets
ALT.CASH	Ln (1 + cash and cash equivalent divided by total assets)
ROA	The ratio of EBITDA to total assets
ROE	Net profit divided by shareholder equity
LEVERAGE	Total debt divided by total assets
SIZE	Natural logarithm of total assets
GRWT	Percentage change in sales from year t to year t−1
ATGB	Tangible assets divided by total assets
MA	The managerial efficiency score created by Demerjian et al. (2012) for firm i in fiscal year t
ALT.MA	Five-year industry-adjusted return on assets (cumulative income before extraordinary items (IBC) scaled by average total assets (AT) from year t−5 to year t−1)

Table 2.

Descriptive Statistics.

Variable	Obs.	Mean	SD	Min	Max
ROA	25,461	0.039	0.06	−0.344	0.206
ROE	25,256	0.066	0.132	−1.033	0.360
Cash	25,409	0.174	0.140	0.005	0.682
Leverage	25,350	0.444	0.216	0.051	1.150
Size	25,350	3.130	0.056	2.472	3.385
Tangibility	25,461	0.241	0.175	0.002	0.744
Age	25,462	8.700	6.32	0.000	27.00
Growth	23,976	0.222	0.497	−0.591	3.335
MA	23,594	0.007	0.145	−0.611	0.932

Correlation Analysis

Table 3 provides VIF and correlations among variables included in this study. There is a positive association between cash holdings and firm performance, as depicted in Table 3. The table also shows that MA is negatively correlated with ROA and Cash. Most control variables, such as Age, Tangibility, and Leverage, show a negative association with ROA, while Growth and Size show a positive association with ROA. Overall, the values of VIF and correlation coefficient of independent and control variable are not very high. This suggest that multicollinearity is not an issue in this study.

Table 3.

Correlation Matrix.

Variables	VIF	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
(1) Cash	1.05	1.000
(2) ROA		0.081*	1.000
(3) ROE		0.042*	0.849*	1.000
(4) Leverage	1.20	−0.129*	−0.420*	−0.164*	1.000
(5) Size	1.18	−0.080*	0.055*	0.124*	0.360*	1.000
(6) Tangibility	1.03	−0.100*	−0.121*	−0.104*	0.107*	0.075*	1.000
(7) Age	1.12	−0.084*	−0.160*	−0.064*	0.347*	0.322*	0.037*	1.000
(8) Growth	1.11	−0.002	0.188*	0.190*	0.043*	0.058*	−0.079*	−0.029*	1.000
(9) MA	1.11	0.040*	0.338*	0.320*	0.018*	0.002	−0.141*	0.020*	0.190*	1.000

p < .05.

Cash Holding and Operating Performance

Results of the baseline model are provided in Table 4. We estimate the baseline model through ordinary least squares (OLS) without including the moderating variable (MA) in the model. Since the OLS model does not control for firm-specific effects and individual heterogeneity, we also employ the fixed-effect model to overcome this problem and for robustness check.

Table 4.

Baseline Regression.

Variables	(1) ROA OLS	(2) ROA FE	(3) ROA RSE
Cash	0.003***	0.001**	0.001**
Cash	(0.001)	(0.001)	(0.001)
Leverage	−0.133***	−0.160***	−0.163***
Leverage	(0.002)	(0.003)	(0.006)
Size	0.261***	0.167***	0.192***
Size	(0.007)	(0.014)	(0.032)
Tangibility	−0.023***	−0.048***	−0.051***
Tangibility	(0.002)	(0.004)	(0.006)
Age	0. 454***	0.084***	0. 010
Age	(0. 059)	(0. 011)	(0. 030)
Growth	0.023***	0.023***	0.023***
Growth	(0.001)	(0.001)	(0.001)
Constant	−0.716***	−0.424***	−0.483***
Constant	(0.020)	(0.045)	(0.098)
Observations	23,822	23,822	23,822
R ²	.261	.246	.235
Industry dummy	No	Yes	Yes
Year dummy	No	Yes	Yes
JB χ²	1,313
p-Value	.000
ADF	7,389.745
p-Value	.000

Note. Robust standard errors are in parentheses.

p < .05. ***p < .01.

Columns (1) to (3) in Table 4 show the results of OLS, fixed-effect (FE), and FE with robust standard error models, respectively. All three models consistently demonstrate a favorable association between cash holding and ROA. There is no significant change in the direction or significance level. Having sufficient cash reserves gives businesses the financial adaptability they need to take advantage of investment opportunities, weather economic downturns, and pay unforeseen expenditures. Because of this flexibility, businesses are able to invest in successful projects or acquisitions on time, increasing their capacity to generate income and raising ROA. Having cash on hand can protect you from financial hardship and reduce your risk of running out of liquidity, especially in times of market or economic instability. Businesses that have enough cash on hand are better able to weather negative shocks, keep things running smoothly, and take advantage of possibilities with distressed assets, all of which enhance ROA. Cash-rich companies might benefit from lower agency costs brought on by management opportunism and information asymmetry. Control variables show consistent results with previous studies and according to our projections (La Rocca & Cambrea, 2019; La Rocca et al., 2019). Because debt financing is an inappropriate option for external funding, leverage harms a company’s performance. This is because, unlike developed countries such as the USA and the UK, the bond market in China is underdeveloped. Compared to non-state firms, state-owned enterprises (SOEs) have easy access to debt financing in China. This is because the primary source of external funding is banks, which SOEs can easily access.

Furthermore, results show that Growth is positively related to financial performance, while asset tangibility shows a negative relationship. Based on the above-mentioned factors about debt financing in China, firms try to accumulate more cash to reduce the opportunity cost of debt financing. Finally, Table 4 shows that firm size positively impacts ROA.

Moderating Effect of Managerial Ability

Although our primary analysis shows a positive relationship between cash holdings and firm performance, numerous important variables can affect this relationship. One of these is managerial ability. We provide the results of the moderating variable in Table 5. As mentioned earlier, managerial ability is the moderating variable in this study.

Table 5.

Moderating Effect of Managerial Ability.

Variables	(1) ROA OLS	(2) ROA FE	(3) ROA RSE
Cash	0.008***	0.006***	0.006**
Cash	(0.002)	(0.002)	(0.003)
MA	0.139***	0.200***	0.200***
MA	(0.003)	(0.004)	(0.008)
Cash × MA	0.045***	0.036***	0.036*
Cash × MA	(0.011)	(0.010)	(0.019)
Leverage	−0.134***	−0.135***	−0.135***
Leverage	(0.002)	(0.002)	(0.006)
Size	0.273***	0.304***	0.304***
Size	(0.006)	(0.013)	(0.031)
Tangibility	−0.008***	−0.007**	−0.007
Tangibility	(0.002)	(0.003)	(0.006)
Age	0.000***	0.001***	0.001***
Age	(0.000)	(0.000)	(0.000)
Growth	0.016***	0.013***	0.013***
Growth	(0.001)	(0.001)	(0.001)
ROA_t−1
Constant	−0.757***	−0.869***	−0.869***
Constant	(0.019)	(0.041)	(0.095)
Observations	23,428	23,428	23,428
R ²	.356	.356	.356
Industry dummy	No	Yes	Yes
Year dummy	No	Yes	Yes

Note. Robust standard errors are in parentheses.

p < .1. **p < .05. ***p < .01.

Column 1 in Table 5 illustrates the results of simple OLS regression; coefficients for cash holding and firm performance are positive and significant, as depicted by the p values. The moderating effect of MA (Cash × MA) is positive and significant. High ability managers have excellent operational knowledge, strategic vision, and decision-making abilities. These managers are better suited to allocate resources wisely, spot lucrative investment possibilities, and spend cash reserves sensibly in the context of cash management. As a result, the association between cash holdings and company performance is positively moderated by managerial skill, indicating that companies with competent managers are better equipped to use their liquidity buffers to increase returns on assets. The distribution of financial resources, particularly cash reserves, throughout businesses is influenced by managerial aptitude. Strong managers are skilled in determining the firm’s investment prospects, weighing trade-offs between risk and return, and coordinating cash allocation choices with strategic goals. Because of this, the positive moderating effect of management competence suggests that companies with competent managers are better able to deploy their financial reserves, putting them toward initiatives that add value and boost overall company performance. High ability managers respond to shifting market conditions and competitive demands with more resilience and adaptability. These managers are better positioned to handle obstacles, take advantage of new possibilities, and maximize cash management methods to boost company performance during times of economic instability or industry disruption. The notion that managerial competence has a positive moderating effect implies that companies with competent managers are more adept at using their cash reserves to boost profitability.

All the control variables have the expected results, as reported in Table 3. Column 2 of Table 5 reports the results of the fixed-effect model, where the cash and performance relationship is insignificant with a positive sign, and the moderating effect of MA is also positive. The last column reports the results with robust standard errors; all the results are significant, and the signs are according to our hypothesis. The moderating effect of MA is positive, indicating that the positive impact of cash holding on firm performance is more pronounced in firms with high-ability managers. Hence, H2 is accepted robustly on the empirical grounds.

Robustness Test: Alternate Proxy of Cash Holding

We utilize an alternate measure of cash holding to assess the reliability of our findings. We calculate cash holdings as the natural logarithm of 1 plus cash and cash equivalents to verify the results. Table 6 presents the robustness test results using an alternative proxy for cash holdings. The coefficient sign and significance validate the primary findings. These results imply that our findings are robust and insensitive to different proxies.

Table 6.

Alternative Proxy of Cash Holding.

Variables	(1) ROA OLS	(2) ROA FE	(3) ROA RSE
Cash	0.015***	0.008***	0.008***
Cash	(0.001)	(0.001)	(0.002)
Leverage	−0.128***	−0.163***	−0.163***
Leverage	(0.002)	(0.003)	(0.006)
Size	0.271***	0.220***	0.220***
Size	(0.007)	(0.014)	(0.031)
Tangibility	−0.016***	−0.045***	−0.045***
Tangibility	(0.002)	(0.004)	(0.006)
Age	0.000***	0.000	0.000
Age	(0.000)	(0.000)	(0.000)
Growth	0.023***	0.023***	0.023***
Growth	(0.001)	(0.001)	(0.001)
ROA_t−1
Constant	−0.755***	−0.575***	−0.575***
Constant	(0.02)	(0.044)	(0.096)
Observations	23,868	23,868	23,868
R ²	.269	.240	.240
Industry dummy	No	Yes	Yes
Year dummy	No	Yes	Yes

Note. Robust standard errors are in parentheses.

***

p < .01.

Robustness Test: Alternate Proxy of Managerial Ability

We use more robustness tests to support our findings. This study uses an alternative measure of managerial ability. Results of the model having an alternative proxy of managerial ability are presented in Table 7. The results indicate that the coefficients are still significant when we change the proxy of MA, hence validating our findings.

Table 7.

Alternative Proxy of Managerial Ability.

Variables	(1) ROA OLS	(2) ROA FE	(3) ROA RSE
Cash	0.000***	0.000***	0.000***
Cash	(0.000)	(0.000)	(0.000)
AMA	−0.001***	−0.001***	0.000**
AMA	(0.000)	(0.000)	(0.000)
Cash × AMA	0.002***	0.001*	0.001**
Cash × AMA	(0.000)	(0.000)	(0.000)
Leverage	−0.134***	−0.161***	−0.163***
Leverage	(0.002)	(0.003)	(0.006)
Size	0.268***	0.188***	0.213***
Size	(0.007)	(0.014)	(0.033)
Tangibility	−0.024***	−0.059***	−0.051***
Tangibility	(0.002)	(0.004)	(0.006)
Age	0.000***	−0.001***	−0.001**
Age	(0.000)	(0.000)	(0.000)
Growth	0.023***	0.023***	0.022***
Growth	(0.001)	(0.001)	(0.001)
ROA_t−1
Constant	−0.736***	−0.459***	−0.547***
Constant	(0.020)	(0.044)	(0.100)
Observations	23,242	23,242	23,242
R ²	.264	.221	.240
Industry dummy	No	Yes	Yes
Year dummy	No	Yes	Yes

Note. Robust standard errors are in parentheses.

p < .1. **p < .05. ***p < .01.

Robustness Test: Alternate Proxy of Firm Performance and GMM

To further check the robustness of our findings, we use ROE as an alternative proxy for firm performance. Results in Table 8 show that the direction and significance level of the coefficients did not change when we changed the proxy. This confirms the robustness of the results.

Table 8.

Alternative Proxy of Firm Performance.

Variables	(1) ROE OLS	(2) ROE FE	(3) ROE RSE
Cash	0.000***	0.000***	0.000***
Cash	(0.000)	(0.000)	(0.000)
MA	0.289***	0.458***	0.458***
MA	(0.006)	(0.009)	(0.018)
Cash × MA	0.048***	0.043***	0.043***
Cash × MA	(0.017)	(0.006)	(0.006)
Leverage	−0.182***	−0.236***	−0.236***
Leverage	(0.004)	(0.007)	(0.016)
Size	0.660***	0.923***	0.923***
Size	(0.017)	(0.040)	(0.079)
Tangibility	−0.033***	−0.026***	−0.026***
Tangibility	(0.005)	(0.005)	(0.005)
Age	−0.001***	0.002**	0.002**
Age	(0.000)	(0.001)	(0.001)
Growth	0.037***	0.030***	0.030***
Growth	(0.002)	(0.002)	(0.002)
Constant	−1.916***	−2.746***	−2.746***
Constant	(0.051)	(0.122)	(0.242)
ROE_t−1
Observations	23,232	23,232	23,232
R ²	.211	.239	.239
Industry dummy	No	Yes	Yes
Year dummy	No	Yes	Yes

Note. Robust standard errors are in parentheses.

p < .05. ***p < .01.

Moreover, to deal with potential endogeneity we employ system GMM. Table 9 provides the results of system GMM. Column (1) of the table shows the baseline regression results without including the moderator. These results are consistent with our previous findings. The second column of the table provides the results of system GMM having a moderating variable (MA) in the model. These results are also in line with our main findings. In summary, we employ several robustness tests, address the potential endogeneity issue, and observe that our results are robust.

Table 9.

GMM.

Variables	(1) ROA GMM	(2) ROA GMM
Cash	0.038***	0.002
Cash	(0.011)	(0.007)
Leverage	−0.109***	−0.109***
Leverage	(0.003)	(0.002)
Size	0.209***	0.007
Size	(0.008)	(0.087)
Tangibility	−0.017***	−0.020***
Tangibility	(0.004)	(0.003)
Age	0.000	0.000**
Age	(0.000)	(0.000)
Growth	0.020***	0.021***
Growth	(0.001)	(0.001)
MA		0.115**
MA		(0.053)
Cash × MA		0.013**
Cash × MA		(0.005)
ROA_t−1	0.252***	0.299***
ROA_t−1	(0.012)	(.009)
Constant	−0.609***	−0.052
Constant	(0.025)	(0.239)
AR(2)	1.430	0.980
p-Value	.153	.328
Sargan test	31.87	47.97
p-Value	.374	.555
Observations	21,494	21,493
Industry dummy	Yes	Yes
Year dummy	Yes	Yes

Note. Standard errors are in parentheses.

p < .05. ***p < .01.

Reverse Causality Concerns

Results show a positive relationship between cash holdings and firm performance. However, there is a concern that high-performing firms may hoard more cash, resulting in reverse causality. We follow Ali et al. (2022) methodology to address this concern. We replaced the explanatory variables with 1-year lagged values and re-estimated our models. Regression with lagged independent variables controls the endogeneity effects and reverse causality (Ali et al., 2022). Table 10 provides the results of the regression analysis with lagged independent variables. These results are in line with our main findings. Hence, reverse causality and endogeneity issues are addressed.

Table 10.

Lagged Variables.

Variables	(1) ROA_t	(2) ROA_t
Cash_t−1	0.002***	0.004**
Cash_t−1	(0.001)	(0.002)
Leverage_t−1	−0.095***	−0.087***
Leverage_t−1	(0.002)	(0.002)
Size_t−1	0.175***	0.195***
Size_t−1	(0.009)	(0.009)
Tangibility_t−1	−0.015***	0.006**
Tangibility_t−1	(0.003)	(0.003)
Age_t−1	0.000***	0.000***
Age_t−1	(0.000)	(0.000)
Growth_t−1	0.014***	0.009***
Growth_t−1	(0.001)	(0.001)
MA_t ₋₁		0.117***
MA_t ₋₁		(0.004)
Cash × MA_t₋₁		0.016***
Cash × MA_t₋₁		(0.005)
Constant	−0.497***	−0.542***
Constant	(0.027)	(0.027)
Observations	20,149	19,821
R ²	.179	.234
Industry dummy	Yes	Yes
Year dummy	Yes	Yes

Note: Standard errors are in parentheses.

p < .05. ***p < .01.

Discussion

By presenting empirical evidence on the moderating effect of management competence, our study adds to the body of knowledge already available on cash holding and company success. Analyzing our results against previous research provides important context for understanding the subtleties of cash management choices and how they affect organizational results. The static trade-off theory, which contends that businesses keep cash reserves to weigh the advantages of flexibility and investment opportunities against the costs of financial turmoil, has dominated prior studies. Our findings support this notion by showing a positive correlation between cash reserves and business performance, suggesting that increased liquidity levels are typically associated with increased operational effectiveness and financial stability. These results are in line with important studies by Yun et al. (2021) and La Rocca and Cambrea (2019), which have emphasized the significance of cash reserves as a strategic asset for businesses functioning in unpredictable situations. But by looking at the moderating impact of managerial competence on the cash-performance link, this study goes beyond the conventional static trade-off approach. According to our research, the influence of cash reserves on a company’s success depends on the caliber of managerial decision-making; companies run by managers with higher levels of competence gain more from cash holdings in terms of performance. This sophisticated view of managerial aptitude as a moderator deepens our study and emphasizes the role that human capital plays in determining organizational results.

A number of important conclusions are drawn from comparing our findings with earlier research. First off, our results support the expanding corpus of research indicating that management ability is a key factor in determining business performance outcomes. Research by Inam Bhutta et al. (2021) and Fernando et al. (2020) has emphasized the significance of managerial skill in guiding strategic choices and resource distribution in businesses. Through the application of this line of investigation to the field of cash management, our study demonstrates the importance of managerial competence as a critical factor in determining company performance.

Second, findings of this research add to the growing body of knowledge regarding the contingent nature of cash management choices. The effectiveness of cash holding policies can be better understood by considering the human aspect, as our research shows. Previous studies have mostly concentrated on firm-level features like size, leverage, and development prospects (Denis & Wang, 2024; Houqe et al., 2023). The intricate relationship between financial resources, management abilities, and business performance is clarified by this study by acknowledging the moderating effect of managerial competence.

Managerial Implications

Optimal cash management policies: The significance of implementing ideal cash management strategies that weigh the advantages and disadvantages of maintaining cash reserves is highlighted by our findings. The advantages of having cash on hand for liquidity should be carefully weighed against the opportunity costs of missing out on potential investments by managers. Businesses can reduce the risk of financial difficulty while still having enough flexibility to take advantage of investment opportunities and strategic initiatives by keeping a suitable level of cash reserves.

Strategic investment decisions: Managers ought to think about how cash reserves affect their choices for investments and capital allocation plans. Having too much cash on hand can indicate inefficiency or underuse of resources, even though it can also act as a safety net during uncertain economic times. To maximize firm value, companies should keep a close eye on their cash situation and allocate any extra liquidity to shareholder payouts or value-enhancing initiatives. This will optimize the use of financial resources.

Managerial talent development: Our research emphasizes how crucial managerial skill is in determining cash management choices and how those choices affect business performance. Managers must to put money into gaining the knowledge and abilities required to evaluate risk-reward trade-offs, make wise financial decisions, and maneuver through challenging financial situations. Establishing a culture that values strategic thinking and financial literacy can help businesses improve managerial performance and create long-term value.

Theoretical Implications

Refinement of Static Trade-Off Theory: Through an analysis of the moderating effect of managerial competence on the cash-performance relationship, our research advances the continuous improvement of the static trade-off theory. Our findings imply that management considerations are crucial in influencing cash holding decisions, even though the static trade-off paradigm has historically concentrated on the financial determinants of these decisions. The need for a more sophisticated comprehension of the behavioral aspects of cash management is shown by this expansion of the static trade-off model.

Integration of Behavioral Perspectives: Our study incorporates behavioral perspectives into the static trade-off paradigm by using management skill as a moderating component. Conventional models, which presume managers’ rationality and information symmetry, frequently ignore the behavioral components of decision-making. Our research, however, emphasizes the diversity in managerial abilities and decision-making approaches, underscoring the necessity of taking behavioral aspects into consideration when simulating cash management choices and the effects they have on business success.

Implications for Agency Theory: In particular, our results have implications for agency theory about the alignment of managerial interests with the maximizing of shareholder value. The efficacy of cash management systems appears to depend on managerial competence, despite agency theory’s prediction that managers may hoard surplus wealth to further their own goals or construct empires. Capable managers enable a company to allocate cash reserves more wisely, increase firm value, reduce agency costs, and match management incentives with shareholder interests.

Conclusion

Although the manager’s contribution to corporate performance, investment efficiency, and quality of financial reporting is essential, there remain differences of opinion on various organizational outcomes concerning manager-specific effects. Extant literature on managers’ effect on organizational outcomes attributed from a performance perspective only researched the firm and industry-specific effects rather than analyzing managers-specific effects. This research contributes to managerial ability, cash holding, and performance literature by investigating the moderating role of administrative ability on the direct relationship between cash holdings and firm performance.

This study employed the managerial ability measure developed by Demerjian et al. (2012), calculated based on firm-level financial statement information. Using two proxies of cash holding, two proxies of firm performance, and two proxies of managerial ability, we have documented a positive effect of cash holding on firm performance. Further, our findings report a decisive moderating role of managerial ability on the direct relationship between cash holding and firm performance—this decisive moderating role of managerial ability is attributed to the efficient contracting hypothesis. The neo-classical framework claims that efficient managers continue investment in the profitable project until the equilibrium point of marginal cost and benefit (Habib & Hasan, 2017). This claim is valid under an efficient market hypothesis, which claims that managers have enough funds available anytime without extra cost to invest in profitable projects and return excess cash to shareholders in the form of dividends (Abel, 1983; Hayashi, 1982; Yoshikawa, 1980).

This study investigated the moderating role of managerial ability on the relationship between cash holding and firm performance in the Chinese context. Future studies should also consider external institutional quality as moderating variables and incorporate performance indicators based on the market, such as share price growth. This study only used data from 2,858 Chinese companies, limiting the study’s generalization. We advise investigating the same phenomenon globally with more observations to improve its generalizability. We only used managerial skills; future research might look at the moderating impact of variables beyond the firm’s control and found in the external environment, such as macroeconomic indicators.

Footnotes

Appendix

Appendix A.

Cash Holdings Across Industries

Industry	N	Mean	SD	Min	Max
Agriculture	156	0.196	0.150	0.014	0.682
Air transportation	135	0.107	0.088	0.008	0.406
Ancillary activities for mining	88	0.169	0.143	0.026	0.682
Automobile manufacturing	807	0.155	0.110	0.005	0.682
Telecommunications, broadcast, television, and satellite transmission services	151	0.242	0.190	0.005	0.682
Building construction	7	0.237	0.118	0.112	0.418
Business service	321	0.171	0.138	0.005	0.682
Catering industry	24	0.237	0.123	0.076	0.496
Chemical fiber manufacturing	212	0.102	0.074	0.005	0.515
Civil engineering	526	0.169	0.116	0.005	0.682
Coal mining and processing	292	0.149	0.115	0.005	0.682
Comprehensive utilization industry of waste resources	27	0.100	0.088	0.005	0.327
Computer, communication and other electronical device manufacturing	2,139	0.208	0.153	0.005	0.682
Conglomerates	237	0.156	0.102	0.005	0.674
Construction and installation	2	0.355	0.203	0.211	0.498
Construction decoration and other construction	135	0.164	0.123	0.009	0.682
Culture and arts	38	0.178	0.149	0.005	0.682
Culture and education, arts and crafts, sports and entertainment products manufacturing	54	0.250	0.163	0.031	0.648
Ecological preservation and environmental treatment industry	142	0.171	0.152	0.008	0.682
Education	23	0.159	0.080	0.013	0.295
Electric machines and apparatuses manufacturing	1,497	0.189	0.140	0.005	0.682
Farm products processing	305	0.155	0.115	0.005	0.642
Farming, forestry, animal husbandry, and fishery	12	0.143	0.076	0.050	0.316
Ferrous metal mining	42	0.176	0.163	0.005	0.531
Fishery	75	0.135	0.091	0.022	0.476
Food manufacturing	284	0.186	0.146	0.005	0.682
Forestry	18	0.145	0.135	0.006	0.446
Furniture manufacturing	69	0.205	0.156	0.025	0.682
General equipment manufacturing	835	0.187	0.145	0.005	0.682
Graziery	92	0.160	0.126	0.016	0.617
Highway transport	384	0.117	0.094	0.005	0.682
Hotels	85	0.122	0.088	0.005	0.423
Instrument and meter manufacturing	184	0.282	0.181	0.034	0.682
Internet and related services	370	0.243	0.199	0.005	0.682
Leasing industry	31	0.163	0.101	0.035	0.375
Leather, fur, feathers, and related products and shoe-making	51	0.204	0.122	0.059	0.584
Loading, unloading and transportation agency	30	0.255	0.167	0.026	0.564
Metal products	351	0.156	0.124	0.005	0.682
Mining and dressing of nonferrous metals	225	0.134	0.128	0.005	0.665
News and publishing industry	170	0.261	0.160	0.011	0.682
Non-metallic mineral products	670	0.130	0.112	0.005	0.653
Other manufacturing	102	0.125	0.116	0.005	0.682
Papermaking and paper products	258	0.110	0.101	0.007	0.682
Petroleum processing, coking and nuclear fuel processing	157	0.123	0.121	0.005	0.556
Petroleum and gas extraction	78	0.078	0.084	0.005	0.566
Pharmaceutical manufacturing	1,654	0.200	0.151	0.005	0.682
Postal industry	36	0.186	0.102	0.030	0.485
Printing and reproduction of recorded media	76	0.179	0.117	0.017	0.682
Production and supply of gas	174	0.127	0.093	0.005	0.682
Production and supply of electric power and thermal power	155	0.113	0.064	0.005	0.380
Production and supply of water	769	0.091	0.092	0.005	0.682
Professional technological service	154	0.256	0.179	0.011	0.682
Public facilities management	157	0.159	0.125	0.005	0.634
Railroad transportation	44	0.103	0.073	0.006	0.318
Railway, shipbuilding, aerospace and other transportation equipment manufacturing	392	0.193	0.127	0.013	0.682
Raw chemical materials and chemical products	1,563	0.155	0.123	0.005	0.682
Real estate	1,496	0.134	0.099	0.005	0.682
Research and experimental development	16	0.265	0.203	0.079	0.682
Retail trade	871	0.194	0.121	0.005	0.669
Rubber and plastic product industry	397	0.155	0.113	0.010	0.682
Sanitation	74	0.247	0.157	0.005	0.682
Smelting and pressing of ferrous metals	410	0.089	0.069	0.005	0.502
Smelting and pressing of nonferrous metals	600	0.129	0.106	0.005	0.682
Software and IT services	1,042	0.308	0.180	0.005	0.682
Special equipment manufacturing	1,178	0.194	0.151	0.005	0.682
Telecommunications, broadcast, television, and satellite transmission services	124	0.216	0.157	0.019	0.682
Textile	303	0.141	0.114	0.011	0.682
Textiles, garments and apparel industry	229	0.223	0.155	0.018	0.682
Timber processing, timber, bamboo, cane, palm fiber and straw products	65	0.146	0.129	0.014	0.679
Warehousing	49	0.213	0.126	0.027	0.666
Water transportation	291	0.130	0.110	0.014	0.682
Wholesale	775	0.162	0.120	0.005	0.682
Wine, drinks and refined tea manufacturing	424	0.201	0.148	0.005	0.682
Total	25,409	0.175	0.141	0.005	0.682

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU242315].

ORCID iDs

Farman Ali

Hassan Ahmad

Imran Ali

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Unlocking the Power of Cash Reserves: How Managerial Ability Shapes Firm Performance

Abstract

Plain language summary

Keywords

Introduction

Literature Review and Hypothesis Development

Managerial Ability

Cash Holding and Operating Performance

Moderating Effect of Managerial Ability

Data and Methodology

Dependent Variables

Independent Variables

Moderating Variables

Measuring Firm Efficiency

Measuring the Managerial Ability

Model

Results and Discussion

Summary Statistics

Correlation Analysis

Cash Holding and Operating Performance

Moderating Effect of Managerial Ability

Robustness Test: Alternate Proxy of Cash Holding

Robustness Test: Alternate Proxy of Managerial Ability

Robustness Test: Alternate Proxy of Firm Performance and GMM

Reverse Causality Concerns

Discussion

Managerial Implications

Theoretical Implications

Conclusion

Footnotes

Appendix

Declaration of Conflicting Interests

Funding

ORCID iDs

Data Availability Statement

References