Determinants of Firms’ Propensity to Use Intercorporate Loans: Empirical Evidence from India

Abstract

Several studies have investigated the determinants of firms’ capital structure choices. Though an intercorporate loan is an essential source of corporate debt, there are no studies that examine the determinants of firms’ preference to use the intercorporate loan as a source of debt. This study examines the relevance of the conventional capital structure determinants in explaining firms’ tendency to use intercorporate loans. The study is based on a dataset of 53,112 firm-year observations comprising 3739 non-financial listed Indian firms for 21 years from 2002 to 2022. The random effect logistic regression model is used to investigate the objectives. The conventional capital structure determinants are relevant in explaining firms’ decisions to use intercorporate loans. Firm size, asset tangibility, and earnings volatility favorably influence the tendency to use intercorporate loans, whereas profitability, growth, uniqueness, dividend payment, ownership concentration, and foreign promoter holdings adversely affect the same. The results reveal that the influence of firm size, uniqueness, earnings volatility, and ownership concentration are not unidirectional for group-affiliated and standalone firms. The findings are mostly consistent with the arguments of conventional capital structure theories. The results of this study will be pragmatic for financial managers in their capital structure decisions.

1. Introduction

Capital structure has been a central topic of academic inquiry for over seven decades, particularly following the groundbreaking work of Modigliani and Miller (Modigliani and Miller 1958). The decision to use debt as a source of finance is one of the most crucial financial decisions a firm can make, given the associated costs and benefits (Graham 2000). An optimal capital structure strikes a balance between these costs and benefits, ensuring that marginal units of debt are effectively utilized. Corporations have various sources of debt, including bonds, debentures, and loans from banks and financial institutions. However, an often overlooked but significant source of corporate debt is intercorporate loans (ICLs). These loans, which are extended by one company to another, are a vital yet underexplored element of corporate financing. ICLs are typically used by firms with surplus funds, seeking to reinvest in related or affiliated companies, often to revitalize struggling entities or capitalize on lucrative investment opportunities within the corporate group.

The phenomenon of ICLs is more prevalent in emerging economies than in industrialized nations (Naskar and Vaidya 2019). In countries like India and China, the incidence of ICLs has been steadily rising, contrasting with a relatively static or declining trend in developed economies (Naskar and Vaidya 2019). ICLs offer several advantages over traditional external borrowing. For one, they minimize the risk of information leakage, which is a significant concern with external debt (Sharpe 1990). This is particularly relevant given that the disclosure of sensitive financial information can adversely affect a firm’s valuation. Additionally, ICLs provide a buffer against unforeseen risks such as insolvency or financial distress (Gopalan et al. 2007). They also allow firms to access funds quickly and with minimal compliance costs, provided surplus funds are available (Lensink et al. 2003). However, the use of ICLs is not without its drawbacks. A primary concern is the type II agency problem, where controlling shareholders may expropriate resources from minority shareholders through mechanisms like tunneling, a risk that can undermine the long-term sustainability of ICLs (Anderson et al. 2019).

Traditional finance theories assume that firms make capital structure decisions based on rational trade-offs between debt and equity. However, behavioral finance challenges this rational perspective, recognizing that psychological biases and cognitive limitations influence financial decision-making (Shefrin 2001). Overconfidence bias can lead managers to take on excessive debt, underestimating financial risks (Malmendier and Tate 2005), while loss aversion may cause firms to avoid necessary leverage out of fear of financial distress (Kahneman and Tversky 1979). Additionally, herd mentality can drive firms to mimic industry trends, leading to group-affiliated firms favoring ICLs as an internal financing mechanism rather than seeking external funding (Shiller 2000). Cultural factors and risk perception further shape financing choices (Chui et al. 2002), particularly in emerging economies where firms may prefer ICLs due to greater control and reduced regulatory scrutiny. These behavioral biases add complexity to corporate financing strategies, reinforcing the need to examine ICL usage through both traditional and behavioral lenses.

Existing literature on capital structure has extensively explored the determinants influencing firms’ capital structure choices. Several factors, including firm size, profitability, and asset tangibility, have been identified as key determinants of financial leverage. Larger firms are typically able to access financial markets more readily and thus tend to use higher leverage (Fama and French 2002; Rajan and Zingales 1995). Conversely, highly profitable firms tend to rely more on internal funds to meet their financial needs, aligning with the pecking order theory which suggests that firms prefer internal financing to avoid the costs associated with external financing (Rajan and Zingales 1995). Similarly, the non-debt tax shields (NDTS) negatively correlate with financial leverage, as higher NDTS reduce the benefits of debt financing (Fama and French 2002). Firms with higher levels of tangible assets are also more likely to use debt, as these assets can serve as collateral (Frank and Goyal 2003).

Variables namely firms’ growth opportunities, earnings volatility, dividend payout, affiliation to business groups, etc., have been widely considered in the extant literature. The relationship between growth opportunities and financial leverage is relatively more complex. Firms with high growth potential may avoid debt to maintain financial flexibility and avoid potential underinvestment in the future (Rajan and Zingales 1995). Whereas, growing firms may use debt to capitalize on expansion opportunities, as higher growth prospects can increase the firm value (Banerjee et al. 2000; Titman and Wessels 1988). Furthermore, firms that operate in industries with high earnings volatility may shy away from debt to mitigate the risk of financial distress (Banerjee et al. 2000; Titman and Wessels 1988). Dividend payments also impact capital structure decisions. Firms paying dividends may utilize it as a mechanism to reduce agency costs associated with free cash flow, which could otherwise be used to increase debt (Frank and Goyal 2003). Finally, being part of a business group tends to have a positive effect on financial leverage as group affiliation can reduce agency problems, mitigate information asymmetry, and provide access to both internal and external capital markets (Gopalan et al. 2007).

Despite the substantial body of work on capital structure determinants, studies have predominantly focused on external sources of debt, particularly financial leverage, which measures the proportion of debt relative to total capital or assets. However, ICLs remain an underexplored area of study, especially in emerging economies like India, where business groups play a dominant role in corporate financing. The use of ICLs is often influenced by agency costs, information asymmetry, and transaction costs, making them a distinct alternative to traditional financing avenues like bank loans or bonds. From an agency theory perspective, controlling shareholders may use ICLs as a tool to either mitigate or exacerbate agency conflicts. While ICLs can serve as an internal capital market, efficiently reallocating resources within business groups, they can also be misused for tunneling, where dominant shareholders transfer resources at the expense of minority investors (Malmendier and Tate 2005). Additionally, information asymmetry plays a crucial role in firms’ financing decisions, as firms with higher asymmetry may find it costly to raise funds from external capital markets due to increased risk perceptions by lenders (Dyck and Zingales 2004). Consequently, these firms may prefer ICLs, as they allow financing within a trusted network, reducing disclosure requirements and regulatory scrutiny. Moreover, transaction costs associated with securing external debt, such as underwriting fees, legal expenses, and compliance costs, make ICLs an attractive alternative, particularly for firms with established intra-group relationships. Given their significance, this study seeks to fill this gap in the literature by examining the determinants that drive firms’ propensity to use ICLs as a source of corporate debt. The primary objective of this study is to assess whether conventional capital structure determinants, such as firm size, profitability, growth prospects, and business group affiliation, influence a firm’s likelihood of utilizing ICLs. The secondary objective of the study is to determine whether the relationship between these determinants and a firm’s use of ICLs differs between standalone firms and those affiliated with business groups.

The novelty of this research lies in its exclusive focus on identifying the determinants of firms’ reliance on ICLs within the context of a major emerging economy, India. As the first study of its kind, the study will contribute to the existing literature by providing a comprehensive analysis of ICLs in the Indian corporate sector, focusing on their usage patterns and determinants. Firstly, it will reveal the overall trend in ICL usage and separately analyze the trends for group-affiliated and standalone firms, offering insights into how these firms differ in their reliance on internal financing. Secondly, the study will identify the key factors that influence firms’ propensity to use ICLs in the Indian context, filling a crucial gap in the literature on alternative financing mechanisms in emerging economies. Thirdly, it will investigate whether the determinants of ICL usage vary between group-affiliated and standalone firms, shedding light on how ownership structures and financial strategies impact corporate borrowing behavior. The findings will be valuable for policymakers, regulators, and financial managers in understanding corporate financing patterns and in formulating strategies to ensure transparency and efficiency in financial transactions.

The remainder of the paper is structured as follows: Section 2 presents the hypotheses development, Section 3 outlines the empirical framework, Section 4 discusses the empirical findings, and Section 5 concludes the study.

2. Hypotheses Development

2.1. Firm Size

Larger firms typically benefit from greater operational diversification, which reduces their exposure to bankruptcy risks (Ang et al. 1982). Additionally, smaller firms face disproportionately higher costs in issuing debt and securities compared to their larger counterparts, making access to external financing more challenging (Titman and Wessels 1988). Empirical studies consistently support a positive relationship between firm size and financial leverage, as larger firms generally have more stable cash flows and lower default risks, allowing them to secure debt at favorable terms (Frank and Goyal 2003; Rajan and Zingales 1995). Given their superior market access and lower risk profiles, larger firms are also more likely to utilize innovative financing mechanisms, such as ICL. This expectation stems from the trade-off theory, which posits that firms weigh the benefits of debt financing (such as tax shields) against the risks of financial distress. Since larger firms experience lower bankruptcy costs and have stronger reputational standing, they are more inclined to adopt financing structures that optimize their capital mix. Thus, the hypothesis that larger firms exhibit a greater propensity to use ICL is grounded in both theoretical and empirical literature. Hence, the following hypothesis is proposed:

H1. 

Firm size positively influences firms’ propensity to use ICL.

2.2. Firm Profitability

The pecking order theory posits a negative relationship between firm profitability and financial leverage. This theory suggests that profitable firms prefer internal funding over external debt, as internally generated funds are not subject to information asymmetry costs, leading to a reduction in financial leverage (Myers and Majluf 1984). Empirical evidence strongly supports this perspective, demonstrating a consistent inverse relationship between profitability and leverage across various market contexts (Fama and French 2002; Frank and Goyal 2003; Rajan and Zingales 1995). Conversely, the trade-off theory presents a competing view, arguing that profitability enhances a firm’s capacity to service debt while reducing financial distress and bankruptcy risks. According to this perspective, highly profitable firms should exhibit a higher preference for debt financing, as they can better leverage tax advantages associated with interest payments and maintain lower default probabilities (Rajan and Zingales 1995). Despite these contrasting theoretical arguments, prior empirical findings predominantly align with the pecking order theory, reinforcing the expectation that firms with greater profitability are less reliant on ICL. Besides, as firms achieve greater profitability, they may choose to avoid ICLs to minimize external influence from other corporate entities. Based on this, the following hypothesis is proposed:

H2. 

Profitability negatively influences firms’ propensity to use ICL.

2.3. NDTS

Beyond debt financing, firms can also benefit from tax advantages through mechanisms such as depreciation expenses, depletion allowances, and investment tax credits, collectively termed NDTS. According to the trade-off theory, NDTS reduces a firm’s reliance on debt for tax benefits, as these deductions lower taxable income without incurring the costs associated with borrowing (Rajan and Zingales 1995; Myers and Majluf 1984). This suggests a negative relationship between NDTS and financial leverage, as firms with significant non-debt tax shields have less incentive to accumulate debt purely for tax advantages. Empirical studies have largely supported this argument, demonstrating that firms with higher NDTS tend to maintain lower levels of debt due to the availability of alternative tax-saving options (Shiller 2000; Fama and French 2002; Frank and Goyal 2003; Rajan and Zingales 1995; Ghose et al. 2022). Given this well-established theoretical and empirical foundation, it is expected that firms with higher NDTS will exhibit lower dependence on ICL as a financing mechanism. Based on the argument, the following hypothesis is developed:

H3. 

NDTS negatively affects firms’ propensity to use ICL.

2.4. Tangibility

Asset tangibility is a crucial determinant of a firm’s capital structure, influencing its ability to secure external financing. The trade-off theory suggests that firms strategically balance the benefits of tax shields from debt financing against the costs of financial distress. Tangible assets serve as collateral, reducing the risk for lenders and enabling firms to secure debt at more favorable terms. Consequently, firms with higher asset tangibility tend to rely more on debt financing, as creditors perceive them as less risky borrowers (Kahneman and Tversky 1979; Chui et al. 2002; Banerjee et al. 2000; Titman and Wessels 1988). Empirical evidence supports this argument, highlighting that firms with substantial fixed assets have higher leverage ratios due to their ability to pledge collateral. This collateralization effect lowers borrowing costs, mitigates agency conflicts between creditors and shareholders, and enhances firms’ access to credit. Furthermore, firms with greater tangibility experience lower information asymmetry, reducing adverse selection problems that may otherwise deter lenders from extending credit (Chui et al. 2002; Banerjee et al. 2000; Titman and Wessels 1988). In this context, firms with a higher proportion of tangible assets are expected to face fewer financial constraints, allowing them to access ICL more easily. As secured lending becomes more viable, firms can leverage their tangible asset base to negotiate better credit terms. This expectation aligns with prior empirical findings that asset tangibility plays a vital role in capital structure decisions by facilitating external debt financing. Based on the arguments of trade-off theory, it is expected that firms with greater tangibility of assets have easier access to ICL. Accordingly, the hypothesis is formulated as below:

H4. 

Tangibility positively influences firms’ propensity to use ICL.

2.5. Growth

The relationship between growth opportunities and leverage has been a topic of significant debate in capital structure research. The trade-off theory posits a negative relationship, suggesting that firms with greater growth prospects avoid excessive debt to minimize the risk of underinvestment problems. This occurs because higher leverage can limit a firm’s ability to pursue future profitable projects due to restrictive debt covenants and increased agency costs (Rajan and Zingales 1995). Conversely, some studies argue for a positive relationship, reasoning that growth opportunities enhance a firm’s valuation, thereby improving market perceptions. This positive perception can facilitate debt financing as creditors view firms with robust growth prospects as less risky (Banerjee et al. 2000; Titman and Wessels 1988). Grounded in the trade-off theory, this study anticipates that firms with significant growth opportunities will limit their reliance on ICL to preserve financial flexibility and mitigate associated agency costs. Thus, the hypothesis is formulated as follows:

H5. 

Growth negatively influences firms’ propensity to use ICL.

2.6. Uniqueness

Firms classified by unique operations, specialized labor, and industry-specific assets face distinct challenges, especially in financial distress and bankruptcy scenarios. Unlike firms with standardized assets that can be easily resold in secondary markets, unique firms often struggle to find a ready market for their specialized equipment and infrastructure. As a result, their assets yield lower resale value, thereby reducing their effectiveness as collateral for securing debt financing (Titman and Wessels 1988). Additionally, the requirement of specialized labor may create significant employment constraints in the event of liquidation. Unlike general-skilled workers who can transition smoothly to other firms or industries, employees in unique firms may find limited job opportunities outside their niche sector (Williamson 1988). This heightens the cost of financial distress, making creditors more cautious about extending debt to such firms. To mitigate the risks of liquidation, these firms typically maintain lower leverage, avoiding excessive debt exposure (Harris and Raviv 1991). Given these inherent structural limitations, unique firms are expected to have restricted access to ICL as well. Since ICLs rely heavily on creditworthiness and collateralization, firms with lower tangible asset value and higher liquidation costs may struggle to attract such funding (Rajan and Zingales 1995). Based on these arguments it can be deduced that unique firms have less access to ICL due to their underlying limitations and consequently, the hypothesis is developed as below:

H6. 

Uniqueness negatively influences firms’ propensity to use ICL.

2.7. Earnings Volatility

Earnings volatility plays a crucial role in shaping a firm’s capital structure, as high volatility introduces uncertainty, increasing perceived risk for both investors and lenders. Firms with unstable earnings are often viewed as less creditworthy, leading to higher borrowing costs and restricted access to debt financing (Antoniou et al. 2008b). The rationale behind this is that fluctuating earnings increase the probability of financial distress, thereby amplifying the likelihood of loan defaults and making creditors hesitant to extend funding (Banerjee et al. 2000; Titman and Wessels 1988). From a capital structure perspective, the trade-off theory suggests that firms balance the tax advantages of debt against the risks of financial distress. However, for firms with high earnings volatility, the risk of bankruptcy outweighs potential tax benefits, prompting them to maintain a lower proportion of debt in their capital structure (Myers 1984). Similarly, the pecking order theory posits that firms with uncertain earnings prefer internal financing over debt, given the increased information asymmetry and reluctance of external financiers to provide credit at favorable terms (Banerjee et al. 2000). This negative relationship between earnings volatility and debt financing extends to ICL as well. Given that ICLs function as a substitute for formal credit markets, firms that face higher financial distress risks due to volatile earnings are less likely to obtain such financing. Lenders within corporate networks prefer extending credit to firms with stable cash flows to ensure predictable repayment structures. Consequently, it is anticipated that firms exhibiting greater earnings volatility will have limited access to ICL, reinforcing the argument that financial stability plays a key role in inter-corporate lending decisions. Based on the above-mentioned arguments, it is expected that firms with greater earnings volatility will have limited access to ICL. The formulated hypothesis is:

H7. 

Earnings volatility negatively influences firms’ propensity to use ICL.

2.8. Dividend Payout

Dividend policy plays a crucial role in shaping a firm’s capital structure and financial decisions, with agency and signaling theories offering divergent perspectives on its impact. According to agency theory, dividend payments are a substitute for debt in mitigating agency costs associated with free cash flow, thereby reducing firms’ reliance on debt (Fama and French 2002). On the other hand, signaling theory posits that higher dividend payments convey positive signals about a firm’s future earnings potential, which can lower the cost of equity capital and incentivize firms to favor equity over debt (Antoniou et al. 2008b, 2008a). These perspectives collectively suggest a negative relationship between dividend payouts and debt usage. However, contrasting evidence suggests that dividend payments may enhance a firm’s credibility in the financial market. Firms with higher dividend payouts are perceived as financially robust, with strong debt-servicing capabilities, which can improve their access to external debt, including ICL. This perspective underscores the favorable impact of dividends on debt-raising capacity (Frank and Goyal 2003; Ghose and Kabra 2016). Given these opposing theoretical arguments, this study hypothesizes that dividend policy influences firms’ reliance on ICL, a subset of corporate debt. To account for the theoretical ambiguity, a sign-neutral hypothesis is proposed:

H8. 

Dividend-payment status affects firms’ propensity to use ICL.

2.9. Ownership Concentration

Private information is argued to be higher in firms with a concentrated ownership structure (Dyck and Zingales 2004). Due to the greater information gap, firms with concentrated ownership are more likely to incur higher costs of external financing in comparison to firms with dispersed ownership (Dyck and Zingales 2004). Further, since equity financing suffers the worst from information asymmetry (Myers and Majluf 1984), a greater information gap induces firms to preserve their debt-raising capacity to avoid issuing equity in the future (Kasbi 2009). Besides, it is argued that concentrated ownership reduces type I agency conflict either through active monitoring of managerial actions by controlling shareholders or because of the alignment of interest of management and shareholders (Ghose et al. 2022) which can minimize the need for debt. However, in firms with concentrated ownership, controlling shareholders either actively monitor management or directly influence decision-making, reducing the need for external discipline mechanisms like debt (Anderson and Reeb 2003). This mitigation of agency conflicts further lowers the firm’s reliance on external borrowing, including ICLs. On the contrary, ownership concentration enhances firms’ access to financing by reducing agency costs, improving financial discipline, and increasing investor confidence (Shleifer and Vishny 1997). Large shareholders, especially institutional investors, provide stability, making firms more attractive to lenders (La Porta et al. 1999). In emerging markets, it facilitates relationship-based lending, as lenders perceive such firms as lower-risk borrowers (Khanna and Palepu 2000). Additionally, concentrated ownership signals long-term commitment, fostering better-borrowing terms (Anderson and Reeb 2003). Therefore, a positive association between ownership concentration and ICL can also be expected based on these arguments. Given the conflicting theoretical arguments, the following sign-neutral hypothesis is developed:

H9. 

Ownership concentration affects firms’ propensity to use ICL.

2.10. Business Group Affiliation

Group-affiliated firms have been found to derive greater benefits from internal corporate loans (ICL) compared to standalone firms (Manos et al. 2012). Through their affiliation, these firms gain access to an internal capital market, which serves as an alternative to traditional external financing sources. This internal market enables group-affiliated firms to secure debt under more favorable terms (Chang and Choi 1988), often acting as a financial safety net for weaker firms within the group Manos et al. 2012). Additionally, group affiliation provides firms with intragroup guarantees and co-insurance mechanisms, further enhancing their borrowing capacity (Gopalan et al. 2007). These firms also experience reduced information asymmetry compared to standalone firms, as their close-knit relationships with investors foster greater trust and transparency (Dewenter and Warther 1998). Based on these arguments, it is posited that group-affiliated firms enjoy greater access to ICL than their standalone counterparts. Thus, the following hypothesis is proposed:

H10. 

Business Group Affiliation positively affects firms’ propensity to use ICL.

2.11. Foreign Promoters Holdings

The presence of foreign promoters in a firm’s ownership structure is widely recognized as a factor that enhances governance mechanisms (Agarwal and Chaudhry 2022). In alignment with agency theory (Jensen and Meckling 1976), foreign shareholding is argued to provide enhanced monitoring and protection for investors, thereby reducing the necessity of debt as a tool to discipline managerial actions (Short et al. 2002). A study on strategic ownership and minority shareholder protection (Anderson et al. 2019) highlights the tunneling practices by controlling shareholders, often involving the use of ICL to expropriate resources from minority shareholders, and are curtailed in the presence of foreign strategic investors. This oversight ensures that resources are allocated efficiently and ethically, thereby reducing the reliance on ICL as a financing tool. Based on these arguments, foreign promoter holdings are expected to negatively influence firms’ propensity to use ICL. Consequently, the following hypothesis is proposed:

H11. 

Foreign promoter holdings negatively influence firms’ propensity to use ICL.

3. Empirical Framework

3.1. Sample Firms

ICLs have become an integral part of corporate financing in emerging economies like India, where business groups play a dominant role in shaping financial strategies. Unlike developed markets, where firms primarily rely on external financing options such as bank loans and bonds, Indian corporations frequently use ICLs as an alternative funding source. This practice is particularly prevalent among firms affiliated with large business groups, which utilize internal capital markets to optimize resource allocation, mitigate financial distress, and exploit investment opportunities. However, despite the increasing reliance on ICLs, there is a significant gap in empirical research examining the determinants influencing firms’ propensity to use them as a financing tool. Most existing studies on capital structure focus on conventional sources of debt, such as bank loans and bonds, without adequately addressing the role of ICLs. Given the unique corporate landscape of India—characterized by concentrated ownership, family-run businesses, and regulatory complexities—it is essential to explore how firm-specific factors, such as size, profitability, asset tangibility, and ownership concentration, impact the decision to utilize ICLs. Moreover, concerns regarding corporate governance, transparency, and the potential misuse of ICLs for tunneling and expropriation of minority shareholders further emphasize the need for a detailed investigation into this financing mechanism.

The initial sample consists of all listed Indian firms available in the ‘Prowess’ database for 2002–2022. Following prior studies, the financial and utility firms are excluded from the study because of the influence of regulatory norms in their financing decisions (Rajan and Zingales 1995). Firms with non-positive total assets are also excluded from consideration as they are used as the denominator in the computation of certain variables (Ghose and Kabra 2016). Finally, the study considers only those firms for which required data are available for at least three consecutive financial years.1 The final dataset contains data for 3739 firms totaling 53,112 firm-year observations with a minimum of three years and a maximum of 21 years of observations for each firm.

3.2. Measurement of Variables

The dependent variable of the study is a dummy variable (ICL) representing firms’ use of intercorporate loans as a source of finance. ICL takes the value ‘1’ if the firm has taken an intercorporate loan in a particular year and ‘0’ otherwise. The study considered 11 firm characteristics as determinants of firms’ propensity to use intercorporate loans as a source of finance. The variables considered for the study are firm size (SZ), tangibility of assets (TAN), profitability (PROF), non-debt tax shield (NDTS), growth (GRW), uniqueness (UNQ), earning volatility (EVL), dividend payers (PAYERS), ownership concentration (OC), foreign promoter holdings (FPH) and business group affiliation (BGF). The study uses standard definitions of variables based on the existing literature and is provided in

Table 1. Definition of independent variables.

Variable	Abbreviation	Definitions of Variable
Firm size	SZ	Natural logarithm of Total Assets (Flannery and Rangan 2006; Ghose et al. 2025; Roy et al. 2025)
Tangibility of Assets	TAN	PPE divided by Total Assets (Chang et al. 2014)
Profitability	PRF	EBIT divided by Total Assets (Chang et al. 2014)
Non-debt tax shield	NDTS	Depreciation divided by Total Assets (Flannery and Rangan 2006)
Growth	GRW	Market value of assets divided by the book value of assets (Frank and Goyal 2003; Flannery and Rangan 2006)
Uniqueness	UNQ	Selling expenses divided by Total Assets (Ghose et al. 2024)
Earnings Volatility	EVL	Moving standard deviation of past 3 years’ profitability (EBIT to total assets) (Dang 2013)
Dividend Payers	PAYERS	Dummy variable—‘1’, if the firm pays dividend in a particular year and ‘0’ otherwise (Ghose et al. 2024)
Ownership Concentration	OC	Dummy variable—‘1’, if the promoters’ holdings are 50% or more in a particular year and ‘0’ otherwise (Ghose et al. 2022)
Foreign Promoter Holdings	FPH	Dummy variable—‘1’, if the firm has foreign promoters’ holdings in a particular year and ‘0’ otherwise
Business Group Affiliation	BGA	Dummy variable—‘1’, if the firm is affiliated with any business group and ‘0’ otherwise (Naskar and Vaidya 2019; Ghose and Kabra 2016)

Source: authors’ own compilation.

.

3.3. Empirical Model

The study uses several statistical tests to investigate the hypotheses of the study. The study makes use of the ‘t-test’ and ‘rank-sum test’ to test the differences in mean and median values of different firm characteristics between firms using and not using ICL. The study further used the ‘chi-square test’ to examine the association between firms’ usage status of ICL and firm characteristics which are categorical in nature, namely PAYERS, OC, FPH, and BGF. Finally, the multivariate analysis is conducted with the help of logistic regression to examine the impact of different firm characteristics on firms’ propensity to use ICL. The equation of the logistic regression takes the following form:

$$\mathrm{P}\mathrm{r}(\mathrm{I}\mathrm{C}\mathrm{L}=1|\mathrm{X})={\displaystyle \frac{1}{1+e^{-(\mathsf{\alpha }+\mathrm{X}\mathsf{\beta })}}}$$

where, ICL is the binary dependent variable as defined in Table 1. X is the vector representing the explanatory variables considered in the study, β is the vector of coefficients of explanatory variables and α is the constant of the model. The unobserved time-specific effects are controlled by including time dummies in the model. Both pooled and random effect (RE) estimation techniques are used to estimate the coefficients and the choice between the two estimates is made based on the results of the likelihood ratio test (Ghose et al. 2022).

3.4. Descriptive Statistics

Table 2. Descriptive statistics.

Variables	Mean	Median	Standard Deviation	Minimum	Maximum
SZ	6.70	6.62	2.30	0.92	12.37
TAN	0.27	0.24	0.22	0.00	0.88
PRF	0.06	0.06	0.13	−0.57	0.47
NDTS	0.03	0.02	0.03	0.00	0.13
GRW	1.57	1.05	1.69	0.24	12.19
UNQ	0.02	0.01	0.04	0.00	0.22
EVL	0.04	0.02	0.06	0.00	0.29

Source: authors’ own compilation.

presents the descriptive statistics for the continuous explanatory variables, while

Table 3. Correlation matrix.

Variables	SZ	TAN	PRF	NDTS	GRW	UNQ	EVL
SZ	1
TAN	0.12 *	1
PRF	0.26 *	−0.01	1
NDTS	0.04 *	0.57 *	−0.05 *	1
GRW	−0.07 *	−0.08 *	0.02 *	−0.001	1
UNQ	0.11 *	0.01 **	0.13 *	0.08 *	0.16 *	1
EVL	−0.27 *	0.02 *	−0.17 *	0.12 *	0.23 *	−0.02 *	1

Source: authors’ own compilation. Note: * and **, respectively, denote test statistics are statistically significant at 1% and 5% level of significance.

reports the correlation matrix for these variables. To mitigate the influence of outliers, all non-dummy variables were winsorized at the 1st and 99th percentiles, following the approach of Flannery and Rangan (Flannery and Rangan 2006). The descriptive statistics in Table 2 indicate that the mean and median values of all variables are closely aligned, suggesting a symmetric distribution. Additionally, the standard deviation (SD), minimum, and maximum values demonstrate adequate variation across the explanatory variables, supporting the feasibility of meaningful statistical analysis. The correlation matrix in Table 3 shows expected levels of correlation among the explanatory variables, which is typical for financial data. Notably, the highest correlation is observed between TAN and NDTS, with a coefficient of 0.57. This strong positive relationship can be attributed to the fact that firms with a higher proportion of tangible assets tend to report higher depreciation, contributing to their non-debt tax shields.

The study further reports on the year-wise distribution of sample firms based on their status of the ICL in

Table 4. Proportion of firms using ICL.

Year	All Firms			Standalone Firms			Business Group Firms
	Total (Nos.)	Used ICL (Nos.)	Used ICL (%)	Total (Nos.)	Used ICL (Nos.)	Used ICL (%)	Total (Nos.)	Used ICL (Nos.)	Used ICL (%)
2002	1644	461	28.04	1031	271	26.29	613	190	31.00
2003	1748	495	28.32	1106	293	26.49	642	201	31.31
2004	1850	542	29.30	1170	337	28.80	680	206	30.29
2005	1939	637	32.85	1227	402	32.76	712	235	33.01
2006	2049	657	32.06	1305	417	31.95	744	240	32.26
2007	2142	714	33.33	1375	467	33.96	767	246	32.07
2008	2210	742	33.57	1415	476	33.64	795	265	33.33
2009	2289	762	33.29	1473	492	33.40	816	269	32.97
2010	2380	768	32.27	1543	491	31.82	837	276	32.97
2011	2497	926	37.08	1638	609	37.18	859	316	36.79
2012	2555	980	38.36	1693	662	39.10	862	317	36.77
2013	2667	1028	38.55	1796	694	38.64	871	333	38.23
2014	2834	1093	38.57	1952	765	39.19	882	328	37.19
2015	2991	1056	35.31	2083	727	34.90	908	330	36.34
2016	3104	1044	33.63	2172	724	33.33	932	320	34.33
2017	3162	1034	32.70	2201	715	32.49	961	320	33.30
2018	3143	998	31.75	2194	693	31.59	949	305	32.14
2019	3080	947	30.75	2151	661	30.73	929	286	30.79
2020	2901	880	30.33	2017	595	29.50	884	284	32.13
2021	2951	922	31.24	2066	616	29.82	885	291	32.88
2022	2976	935	31.42	2083	627	30.10	893	298	33.37
Total	53112	17621	33.18	35691	11734	32.88	17421	5856	33.61

Source: authors’ own compilation. Notes: “Nos.” stands for the number of observations.

. The distribution is provided for the overall sample, separately for standalone and group-affiliated firms as well. It is evident from Table 4 that 33.38% of the firm-year observations have used ICL as a source of finance during the study period. There is not much difference in firms’ reliance on ICL between the standalone and group-affiliated firms as the percentage value stands at 33.23% and 33.63%, respectively, for the two groups of firms. This is unanticipated as the proportion is expected to be higher for the latter (Figure 1). However, this finding is in line with the findings of (Naskar and Vaidya 2019) who observed no difference in reliance on ICL for group and standalone firms.

4. Results

Prior to conducting multivariate logistic regression, the study employed mean difference tests (t-test) and median difference tests (rank-sum test) to examine the preliminary determinants of firms’ tendency to use ICL. Additionally, the chi-square test of independence was further used to explore associations between categorical variables and the use of ICL. However, the inferences regarding the hypotheses are drawn primarily from the results of the logistic regression analysis, as it provides a clearer understanding of the impact of each explanatory variable on the dependent variable while holding other factors constant.

The results of the t-test and rank-sum test are presented in

Table 5. Mean and median difference of firm characteristics.

Variables	ICL = 1		ICL = 0		Mean Difference (1–0)	Median Difference (1–0)
	Mean	Median	Mean	Median	t-Test	Rank-Sum Test
SZ	6.737	6.706	6.676	6.567	0.061	0.139
					(2.90) *	(4.50) *
TAN	0.302	0.278	0.259	0.225	0.043	0.053
					(21.02) *	(20.39) *
PRF	0.044	0.057	0.067	0.067	−0.023	−0.009
					(−19.68) *	(−18.67) *
NDTS	0.028	0.023	0.027	0.022	0.001	0.001
					(5.28) *	(6.10) *
GRW	1.435	1.027	1.636	1.072	−0.202	−0.044
					(−11.11) *	(5.94) *
UNQ	0.015	0.004	0.020	0.005	−0.005	−0.001
					(−14.08) *	(−9.05) *
EVL	0.044	0.021	0.040	0.021	0.004	0.001
					(6.89) *	(4.06) *

Source: authors’ own compilation. Note: (1) Figures under parentheses are t-statistics for the t-test and z-statistics for the rank-sum test. (2) * denotes test statistics are statistically significant at 1% level of significance.

, while the chi-square test results are shown in

Table 6. Independence of ICL usage and firm characteristics (categorical variables).

Variables	Categories	ICL		Chi-Square Test
		ICL = 1	ICL = 0
PAYERS	PAYERS = 0	37.20%	62.80%	(599.11) *
	PAYERS = 1	26.84%	73.16%
OC	OC = 0	32.88%	67.12%	(5.65) **
	OC = 1	33.95%	66.05%
FPH	FPH = 0	34.82%	65.18%	(197.53) *
	FPH = 1	26.18%	73.82%
BGF	BGF = 0	33.23%	66.77%	(0.91)
	BGF = 1	33.64%	66.36%

Source: authors’ own compilation. Note: (1) Figures under parentheses are chi-square statistics. (2) * and **, respectively, denotes test statistics are statistically significant at 1% and 5% level of significance.

. The results reveal that firms using ICL tend to be larger in size and have more tangible assets, higher NDTS, and greater earnings volatility compared to firms that do not use ICL. Conversely, firms not using ICL are more profitable, exhibit higher growth rates, and possess greater uniqueness. These findings are largely in line with the trade-off theory and pecking order theory of capital structure. The trade-off theory suggests that firms with higher profitability and growth prospects may avoid external financing (such as ICL) to mitigate the risks of financial distress, while the pecking order theory implies that firms with more profitable operations are more likely to rely on internal funds.

The chi-square test indicates that firms’ tendency to use ICL is significantly associated with their dividend payment policies, ownership concentration, and foreign promoter holdings. These factors suggest that firms with concentrated ownership or foreign promoters may rely less on ICL due to better internal governance and monitoring mechanisms. However, the test finds no significant association between business group affiliation and ICL usage, suggesting that group-affiliated firms do not significantly differ from standalone firms in their reliance on ICL.

The multivariate logistic regression results are presented in

Table 7. Logistic Regression (overall sample).

Variables	Pooled Logit			RE Logit
	Coef.	Z-Stats.	Prob.	Coef.	Z-Stats.	Prob.
Constant	−1.10	−13.25	0.00	−1.93	−11.38	0.00
SZ	0.07	9.40	0.00	0.06	2.61	0.01
TAN	1.03	15.34	0.00	1.34	9.06	0.00
PRF	−1.61	−14.22	0.00	−1.38	−8.11	0.00
NDTS	−4.11	−6.65	0.00	0.63	0.56	0.58
GRW	−0.05	−6.47	0.00	−0.08	−5.58	0.00
UNQ	−3.95	−10.12	0.00	−1.67	−2.05	0.04
EVL	0.60	2.41	0.02	0.99	2.60	0.01
PAYERS	−0.60	−20.99	0.00	−0.66	−12.96	0.00
OC	0.14	5.69	0.00	−0.11	−2.07	0.04
FPH	−0.37	−11.02	0.00	−0.43	−5.40	0.00
BGA	0.04	1.33	0.18	0.12	1.08	0.28
Time Effect	Yes			Yes
Wald Test (prob.)	0.00			0.00
Pseudo R2	0.05			-
Rho	-			0.66
Likelihood Ratio (LR) test (prob.)	-			0.00

Source: authors’ own compilation.

, which includes both the pooled logit model and the random effect (RE) logit model. The decision to use the RE logit model over the pooled logit model is based on the results of the likelihood ratio (LR) test. Since the LR test result is statistically significant at the 1% level (indicated by the probability value), the RE logit model is preferred for further discussion and inference regarding the hypotheses. Additionally, Table 7 reports the probability value of the Wald test under the null hypothesis of zero joint significance of the explanatory variables included in the model. The Wald test result is statistically significant at the 1% level, confirming that the explanatory variables in the model are jointly significant in explaining the firm’s propensity to use ICL. These results provide strong evidence that the independent variables significantly influence the likelihood of a firm using ICL as a source of finance. The subsequent discussion will focus on the interpretation of individual coefficients, including the direction and magnitude of the effects of each explanatory variable, based on the RE logit model.

The results of the logistic regression largely align with the findings from the t-test, rank-sum test, and chi-square test. Several variables show significant impacts on firms’ tendency to use ICL, consistent with the theoretical frameworks and hypotheses formulated in the study. The logistic regression results indicate that SZ and TAN both have a positive impact on firms’ likelihood of using ICL. Larger firms and those with greater tangible assets are more likely to use ICL, suggesting that they have better access to intercorporate loans due to factors such as collateral, reputation, and easier access to financing (Frank and Goyal 2003; Rajan and Zingales 1995). This finding supports Hypotheses 1 and 2 of the study.

In line with the pecking order theory, PRF has a negative effect on firms’ reliance on ICL. Firms that are more profitable tend to rely on retained earnings rather than external debt, including intercorporate loans (Frank and Goyal 2003). This result confirms Hypothesis 3. Contrary to expectations, NDTS does not significantly influence the use of ICL. This result suggests that the theoretical expectation of tax shields driving firms to reduce debt is not applicable in the context of ICL. Further, the lack of a relationship between NDTS and the usage of ICL is consistent with the prior empirical studies that established that NDTS does not influence the capital structure choices of Indian firms (Ghose et al. 2024). Both GRW and UNQ show significant negative impacts on ICL usage, supporting Hypotheses 4 and 5. The negative relationship with growth aligns with the trade-off theory, as firms with higher growth opportunities tend to avoid debt to prevent the risk of debt overhang and underinvestment (Rajan and Zingales 1995). Similarly, the negative relationship with uniqueness indicates that firms with unique products may avoid debt to mitigate future liquidation costs (Titman and Wessels 1988).

EVL unexpectedly has a positive effect on firms’ propensity to use ICL, contrary to the predictions of the trade-off theory, which suggests that volatility should discourage debt due to bankruptcy risks (Banerjee et al. 2000; Titman and Wessels 1988). This result is consistent with a previous study(Antoniou et al. 2008a), which argued that in bank-based economies, concerns about earnings volatility are less pronounced. A plausible explanation for this finding is that firms facing earnings volatility may prefer ICL due to lower information asymmetry and easier restructuring, as compared to traditional external debt. PAYERS exhibit a significant negative relationship with ICL usage, confirming Hypothesis 7. Firms that pay dividends are less likely to use intercorporate loans, which align with the pecking order and free cash flow agency theories. Dividend-paying firms tend to have higher levels of internally generated funds and lower agency costs, thus minimizing the need for external financing (Antoniou et al. 2008a, 2008b).

OC is found to have a significant negative impact on ICL usage, supporting the primary arguments of hypothesis 8. Firms with concentrated ownership are less likely to use intercorporate loans, because of higher information costs and a preference to preserve their debt capacity for future financing (Dyck and Zingales 2004). These firms may face higher costs in accessing external markets, particularly the equity market (Myers and Majluf 1984), prompting them to rely on internal sources of financing. Contrary to the expectation of a positive relationship, BGA does not significantly affect a firm’s reliance on ICL, suggesting that affiliation with a business group does not influence the likelihood of using intercorporate loans. This finding aligns with the descriptive analysis in Table 4 and is consistent with the results of (Naskar and Vaidya 2019). One possible explanation for this result could be that all group-affiliated firms may not require ICL and the usage of ICL is more prevalent in smaller and weaker firms in the group rather than larger and stronger firms (Naskar and Vaidya 2019). Therefore, further segregation of group firms based on their size and financial position in future studies is expected to shed more light on this important aspect. FPH exhibits a significant negative relationship with ICL usage. This finding suggests that firms with foreign promoters are less likely to use intercorporate loans. The presence of foreign promoters often enhances governance through active monitoring, which reduces the need for debt to discipline managers (Short et al. 2002) and mitigates the use of ICL for tunneling practices by controlling shareholders (Anderson et al. 2019).

4.1. Business Group Affiliated Versus Standalone Firms

The existing literature highlights that group firms often have access to internal capital markets, which provide an alternative to traditional external capital markets for raising funds (Chang and Choi 1988). It is well-documented that group firms tend to support financially weaker companies within their conglomerate. This support is not only aimed at improving the financial performance of the group but also serves to signal positive market information that enhances the group’s valuation and market capitalization (Khanna and Palepu 2000). However, recent studies have indicated an increasing trend of standalone firms raising intercorporate loans (Naskar and Vaidya 2019). Given the fundamentally different ownership structures of group and standalone firms, the present study posits that the impact of various firm characteristics on their propensity to use intercorporate loans may differ between these two types of firms. For instance, variables such as firm size and earnings stability may play a significant role in a standalone firm’s access to intercorporate loans. In contrast, these factors may be less relevant for group-affiliated firms, as they benefit from intragroup guarantees and coinsurance provided by other group members (Gopalan et al. 2007). To explore these differences, the study further investigates the determinants of ICL by categorizing the sample firms into group-affiliated and standalone firms. The results of the multivariate logistic regression are presented in

Table 8. Logistic regression (standalone vs. business group firms).

Variables	Standalone Firms			Business Group Firms
	Coef.	Z-Stats.	Prob.	Coef.	Z-Stats.	Prob.
Constant	−2.44	−11.48	0.00	−0.50	−1.52	0.13
SZ	0.14	5.11	0.00	−0.09	−2.46	0.01
TAN	1.37	7.32	0.00	1.26	5.23	0.00
PRF	−1.10	−5.36	0.00	−1.97	−6.39	0.00
NDTS	0.82	0.94	0.35	−0.67	−0.77	0.38
GRW	−0.06	−3.53	0.00	−0.13	−4.23	0.00
UNQ	−0.70	−0.72	0.47	−3.54	−2.40	0.02
EVL	1.60	3.48	0.00	−0.25	−0.36	0.72
PAYERS	−0.69	−10.60	0.00	−0.62	−7.57	0.00
OC	−0.19	−2.84	0.00	−0.02	−0.18	0.86
FPH	−0.56	−4.81	0.00	−0.31	−2.77	0.01
Time Effect	Yes			Yes
Wald Test (prob.)	0.00			0.00
Rho	0.66			0.64
Likelihood Ratio (LR) test (prob.)	0.00			0.00

Source: authors’ own compilation.

, with findings from the RE logit model reported for brevity.

The findings presented in Table 8 reveal that the impact of TAN, PRF, NDTS, GRW, PAYERS, and FPH on firms’ propensity to use ICL is consistent across both group-affiliated and standalone firms, concerning both the direction of the impact and statistical significance. Specifically, in both groups, firms with higher levels of tangible assets and lower levels of profitability and growth opportunities are more likely to use ICL. Additionally, dividend-paying firms and those with foreign promoter holdings exhibit a lower tendency to use intercorporate loans in both categories. The impact of NDTS remains insignificant for both groups, aligning with the findings for the overall sample.

However, the effects of SZ, UNQ, EVL, and OC differ across group-affiliated and standalone firms. SZ has a positive impact on the propensity of standalone firms to use ICL, indicating that as standalone firms grow larger, they gain better access to intercorporate loans. In contrast, for group-affiliated firms, SZ has a negative impact, suggesting that as group firms grow in size, their reliance on ICL decreases as they shift toward external capital markets, having access to an internal capital market. The negative impact of UNQ on the propensity to use ICL is statistically significant only for group-affiliated firms. This suggests that the trade-off theory holds true in the case of group firms, where firms dealing in unique products are more cautious about taking on debt to avoid future liquidation costs. On the contrary, UNQ fails to influence the usage of ICL for stand-alone firms possibly due to their limited access to external financing. On the other hand, EVL has a positive effect on ICL only for standalone firms, suggesting that standalone firms may be more likely to rely on ICL as their earnings increase volatility. These results indicate stand-alone firms’ preference for funds from closely connected sources increases with the increase in earnings volatility whereas, EVL fails to influence ICL usage for group firms having better financial flexibility compared to standalone firms. Finally, OC negatively affects ICL use only for standalone firms. This implies that concentration of ownership plays a crucial role in standalone firms’ decisions to use ICL. However, for group-affiliated firms, ownership concentration does not appear to significantly influence their reliance on ICL, possibly due to the already established, closely-knit ownership structure within the group, which minimizes the need for external financing.

4.2. Robustness Check (Balanced Panel)

This section is incorporated to test the robustness of the results reported in the previous sections. For robustness check, the study considers a balanced panel dataset for analysis which includes only those firms for which data are available for the entire study period i.e., from 2002 to 2022. The results obtained from multivariate logistic analysis are reported in

Table 9. Logistic Regression (balanced panel).

Variables	All Firms			Standalone Firms			Business Group Firms
	Coef.	Z-Stats.	Prob.	Coef.	Z-Stats.	Prob.	Coef.	Z-Stats.	Prob.
Constant	−1.30	−5.34	0.00	−2.20	−6.92	0.00	0.20	0.46	0.65
SZ	−0.03	−0.82	0.42	0.11	2.61	0.01	−0.19	−3.91	0.00
TAN	1.10	5.21	0.00	1.50	5.23	0.00	0.57	1.84	0.07
PRF	−1.25	−4.94	0.00	−0.59	−1.87	0.06	−2.56	−5.77	0.00
NDTS	0.57	0.35	0.72	0.92	0.45	0.66	−0.27	−0.10	0.92
GRW	−0.10	−4.15	0.00	−0.09	−2.81	0.01	−0.09	−2.07	0.04
UNQ	−0.88	−0.81	0.42	0.57	0.42	0.67	−3.02	−1.65	0.09
EVL	1.44	2.42	0.02	2.13	2.85	0.00	0.32	0.31	0.75
PAYERS	−0.61	−8.94	0.00	−0.72	−8.03	0.00	−0.47	−4.44	0.00
OC	−0.14	−1.86	0.06	−0.21	−2.13	0.03	−0.08	−0.72	0.47
FPH	−0.62	−5.84	0.00	−0.98	−5.98	0.00	−0.37	−2.61	0.01
BGA	0.06	0.34	0.73	-	-	-	-	-	-
Time Effect	Yes			Yes			Yes
Wald Test (prob.)	0.00			0.00			0.00
Rho	0.62			0.61			0.62
Likelihood Ratio (LR) test (prob.)	0.00			0.00			0.00

Source: authors’ own compilation.

. The likelihood ratio tests suggest that the RE logit model is more appropriate than the pooled logit model and hence, only RE logit model results are reported in the table. The results are portrayed separately for the overall sample, standalone firms, and business group firms in Table 9. Comparison of Table 9 with Table 7 and Table 8 reveals that the results obtained from the multivariate analysis on the balanced panel dataset are mostly consistent with the primary results of the study except for a couple of deviations in the case of the overall sample i.e., SZ and UNQ. These are found to be statistically insignificant in the case of balanced panel analysis. Overall, the consistency in the findings indicates that the results are robust irrespective of the type of dataset considered for the study.

5. Conclusions

Capital structure has been a key area of research in corporate finance for over seven decades. Numerous studies have examined the determinants of firms’ capital structure choices, with intercorporate loans emerging as a significant source of corporate debt and an integral component of firms’ overall capital structure decisions. In emerging economies like India, where firms are often affiliated with business groups, the use of intercorporate loans is particularly prevalent. Despite its importance, empirical studies focusing on the determinants of firms’ tendency to use intercorporate loans as a funding source remain scarce, particularly in the Indian context. This study fills this gap in the existing literature by investigating the relevance of conventional capital structure determinants in explaining firms’ tendency to use intercorporate loans.

The study utilizes an unbalanced panel dataset consisting of 53,112 firm-year observations over a 21-year period i.e., from 2002 to 2022. In addition to conducting preliminary analyses using t-tests, rank-sum tests, and chi-square tests, the study employs multivariate random effects logit regression analysis to achieve its objectives. The study examines 11 firm characteristics as determinants of firms’ intercorporate loan usage: firm size, tangibility, profitability, NDTS, growth, uniqueness, earnings volatility, dividend payment status, ownership concentration, foreign promoter holdings, and business group affiliation. The findings reveal that firm size, tangibility, and earnings volatility positively influence firms’ tendency to use intercorporate loans. In contrast, profitability, growth, uniqueness, dividend payment, ownership concentration, and foreign promoter holdings negatively impact this tendency. However, the effects of firm size, uniqueness, earnings volatility, and ownership concentration vary between standalone and group-affiliated firms. Despite these differences, the findings are robust across alternative sampling units and are largely consistent with the predictions of conventional capital structure theories.

The study has significant managerial implications. Firstly, it provides insights into the trend of firms’ reliance on intercorporate loans, highlighting their importance as a source of debt in the Indian context. Secondly, the study identifies key factors influencing firms’ tendency to use intercorporate loans, offering financial managers a valuable framework for making decisions about intercorporate loans based on these characteristics. Moreover, the theoretical arguments presented in the study will help financial managers in extending surplus funds as intercorporate loans. Despite these practical contributions, the study has certain limitations that open avenues for future research. First, the study focuses solely on whether firms use intercorporate loans without considering the actual value of such loans. Investigating the nature and determinants of the level of intercorporate loans could provide additional insights. Second, the study does not incorporate specific corporate governance aspects such as board characteristics like board size, board independence, board gender diversity CEO duality, etc., and macroeconomic variables like financial crisis, COVID-19 pandemic, etc., as determinants, which could be explored in future research. Finally, conducting a cross-country study, particularly involving both emerging and developed economies, would help generalize the determinants of intercorporate loans and further enrich the understanding of this important funding source.