Does promoters' share-pledging deteriorate the quality of reported earnings? Evidence from the Indian market

Share-pledging (SP) is a bilateral contract between promoters and lenders, wherein the shares serve as collateral for acquiring personal debt with minimal due diligence. Even though SP is a strategic decision by promoters to raise funds without disposing of their voting rights for the pledged shares, it exposes them to an increasing risk of maintaining the margin levels (Kalia, 2024; Chan et al., 2018). However, when the promoter fails to adhere to the margin call, the lenders are entitled to liquidate the pledged shares in the open market to recover the default amount. The involuntary liquidation triggers the “torpedo effect” (Asija et al., 2014), wherein the stock prices drop further. Thus, the promoters surrender both shares and their private benefits of control.

Although SP maintains the firm's capital structure, mitigating personal liquidity restrictions (Chang et al., 2022), it carries significant adverse consequences when SP activity is more frequent or of considerable proportions. Thus, it intensifies the probability of involuntary liquidation, which can exacerbate stock volatility or, in the worst case, loss of ownership and control over the firm (Chauhan et al., 2020). The inherent risks associated with SP increased the demands of creditors and investors, leading to higher costs of both debt and equity capital (Liu and Tian, 2021; Anderson and Puleo, 2020). Such adverse consequences of SP motivate promoters to engage in risk-reducing behaviour and ownership-control discrepancy at the corporate level, such as deleveraging, forgoing risky positive NPV projects, and earnings management (EM henceforth) to sustain the stock price and alleviate the possibility of losing management control (Chauhan et al., 2020; Puleo et al., 2020; DeJong et al., 2020). Consequently, this results in wealth expropriation and probable conflicts of interest among minority shareholders and promoters (Dou et al., 2019). However, research investigating SP's influence on important earnings quality properties and the tension surrounding overall financial reporting quality in emerging countries remains an empirical question.

We undertake this study with three interconnected motivations that aim to address this question. First, the footprint of SP activity is gaining momentum in developing markets, such as China, India, and Taiwan; its prevalence is far less common in developed markets, notably the United States, due to its strict anti-pledging policies. For instance, according to a 2014 proxy disclosure survey, 68% of surveyed US companies had strict anti-pledging policies, with an additional 20% requiring advance approval for SP ^[1]. Conversely, SP statistics from emerging markets highlight the prevalence of these practices. As of 2017, SP among Chinese listed firms' promoters had risen to 45% of which 21% had a pledging ratio of more than 60% (Hu et al., 2021). Similarly, in Taiwan, 30% of promoters pledge their shares due to the convenience and flexibility of raising funds through this method compared to mortgages (Chan et al., 2018). The Financial Stability Report, issued by the Reserve Bank of India (RBI) in June 2019, also addressed concerns about the high magnitude of SP by promoters in India ^[2], indicating poor firm health and an inability to access other external finance (RBI, 2019, p. 47). According to Prime Database Group, the value of SP by promoters in the NSE-listed companies surged 56% to Rs 2.77 lakh crore as of August 2020, marking a three-year high. This highlights a significant concern for global market participants and regulators, underscoring the need for a focused study on an emerging market, such as India, which is not only relevant but also necessary. This concern is further justified by the fact that several high-profile Indian firms have experienced stock crashes following a failure to meet margin calls on high promoter SP. The cases of Satyam Computer Services, Reliance ADA Group, Café Coffee Day, GMR Infrastructure, and Zee Entertainment serve as a clear testament to this risk ^[3]. Thus, India presents an attractive setting due to its concentrated ownership, documented history of financial misconduct associated with SP, and a substantial increase in promoters' SP over the decade.

Second, while the literature has extensively documented a significant association between SP and EM, its specific impact on earning quality remains an open question. Previous studies (e.g. Asija et al., 2014; Bhatia et al., 2019; DeJong et al., 2020) show that promoters often manipulate earnings through real-EM (REM) over accrual-based EM (AEM) to alleviate margin call pressure, while separate stream of research examines the implications of SP on firm's accounting conservatism (Xu, 2019; Avabruth et al., 2024). More recently, You et al. (2023) and Shi et al. (2023) posit SP renders earnings less informative in the Chinese market. The present study extends this research to the Indian market with two key methodological advancements. We employ distinct models for both earnings persistence (EP) and earnings informativeness (EI), following the methodologies of prominent scholars such as Dechow and Dichev (2002), Atwood et al. (2010), and Li (2019). Furthermore, we argue that in emerging markets, financial reporting is often driven by promoters' incentives rather than just managers' choices (Fan and Wong, 2002). To capture these incentives, our study employs a granular approach that measures the magnitude of pledged shares at both the firm and promoter levels using a continuous variable, thereby moving beyond the use of simple dummy variables. Therefore, extending on the foundation of prior research on EP ^[4], we offer a fresh set of empirical findings that deepens our understanding of how promoter SP affects the two important properties of earnings quality (Dechow et al., 2010; Li, 2019), namely, EP and EI.

Lastly, our study is motivated by the opportunity to examine a significant exogenous event in the Indian market, a strategy that follows the precedent set by research on the Sarbanes-Oxley Act (SOX) (e.g. Cohen et al., 2007). In June 2019, the Securities and Exchange Board of India (SEBI) ^[5] tightened the operational framework in response to a series of financial misconduct and the significant rise of SP, culminating in Regulation 31(1), which mandated additional detailed SP disclosures from the promoters. Specifically, the rule required greater transparency regarding the reasons for encumbrance and the final use of the borrowed funds, aiming to better inform the market of the associated financial risk.

This approach contrasts sharply with the substantive 2018 Chinese regulation, which mandates a maximum pledging ratio not exceeding 50% of a promoter's ownership. As Shi et al. (2023) documented, this stricter rule successfully alleviated negative effects on EI among SP firms. Consequently, given that the Indian regulation is a disclosure-based mandate rather than a strict cap, we postulate that its effects will differ from the positive outcomes observed in China. As the effectiveness of such disclosure-based mandates as a countermeasure has not yet been thoroughly investigated, our study represents a pioneering attempt to exploit this specific regulatory change. We provide empirical evidence on whether stricter disclosure requirements led to a substitution from AEM to REM, and how this impacts overall earnings quality among SP firms ^[6].

Using a sample of 16,572 firm-year observations from 2015 to 2022, we examine the influence of promoters' SP on the EP and its EI. A panel data regression model (fixed effects) has been used to examine our research questions. To address potential endogeneity concerns and strengthen our baseline results, we utilize the 2019 regulatory change as a quasi-natural experiment. Additionally, robustness tests were incorporated to strengthen the study findings. The outcome of this study is of great significance to regulators, policymakers, investors, and lenders since we demonstrate the differential financial reporting strategies of SP firms and their subsequent impact on the earnings quality.

We make three significant contributions to the contemporary literature landscape. First, the study enhances the understanding of the burgeoning literature on earnings quality and SP. This paper attempts to elucidate how promoters' SP could influence the EP and informativeness of firms' reported earnings. Unlike prior studies that used specific proxies, such as core return on assets or the earnings response coefficient (e.g. You et al., 2023; Shi et al., 2023), we employ a more rigorous and comprehensive approach. By following the methodologies of prominent scholars such as Dechow and Dichev (2002), Atwood et al. (2010), and Li (2019), our study provides a fresh perspective on EP and EI. Our granular approach and a distinct earnings quality model uncover supplementary evidence that reinforces how transaction management's phantom affects the earnings quality among the pledged firms. Second, this study contributes to the canon of classical EM literature, positing that the choice between AEM and REM among SP promoters is complementary rather than preferential. Therefore, researchers investigating earning quality research must consider a more holistic approach toward AEM and REM for more definitive findings. Lastly, we provide evidence on the influence of promoters' pledging on the firm's financial reporting quality within India, serving as a unique setting to measure the pledging aftermath. By exploiting the SEBI Regulation 31(1) of 2019, our findings provide a basis for urging regulators and policymakers to strengthen SP regulations and heighten attention toward promoter pledges, offering valuable insights for regulators, investors, and minority shareholders.

The remainder of the paper is structured as follows: We begin with the theoretical framework and development of the hypothesis in Section 2. The methodology for this study is outlined in Section 3, and then moves on to Section 4, which describes the sample and descriptive statistics. Section 5 discusses the findings of the study. Section 6 concludes the study.

Share-backed loans have become one of the preferred sources of finance for promoters in emerging markets, where promoters are sensitive towards control and ownership, allowing them to pledge their shares as collateral for borrowings without relinquishing their voting rights and dividend receipts (Wang and Cao, 2022). This is contrary to developed markets like the US, which have strict promoter trading policies that limit SP practices (Larcker and Tayan, 2010; McWalter and Ritchken, 2022). However, this reliance on SP exposes promoters to significant risks, particularly the need to maintain margin levels to avoid involuntary liquidation. To mitigate this risk, promoters are incentivized to engage in EM to sustain stock prices and avert margin calls. Kicking off the trajectory of SP from the Indian market, Asija et al. (2014) demonstrated that firms increase their use of REM in subsequent years following their pledge. Subsequently, Bhatia et al. (2019) observed that manipulations of financial reports occur before pledging shares to enjoy maximum benefit from share collateral. Similarly, using the Chinese data, DeJong et al. (2020) identified that during the SP period, the promoters prefer REM to attain certain earnings thresholds, discouraging AEM practices due to their reversal nature and the rise in lenders' monitoring. These practices result in financial misreporting and compromise the quality of financial disclosure.

Building on this foundational literature, we develop our theoretical framework based on the signalling theory and bad news hoarding theory. Through the lens of the signalling theory, managers manipulate earnings to convey favourable information about their forthcoming investment decisions and profitability to stakeholders (Subramanyam, 1996). Such reported earnings fail to persist into the future (Atwood et al., 2010; Li, 2019; Ajid et al., 2024), thereby reducing the overall persistence of earnings and their predictive value for future cash flows. Interestingly, some studies reveal that firms engaging in REM are likely to experience less persistent earnings and lower future stock returns and performance (Cheng et al., 2016; Li, 2019). Correspondingly, the bad news hoarding theory offers a valuable supplement to this signalling perspective. Since promoters among SP firms prefer REM to strategically avoid sending negative signals to the market and prevent stock price crashes, which is particularly relevant for firms with high SP (Zhou et al., 2021). Consistent with this, recent scholarly work has found a negative association between SP and EP, especially when SP is a strong indicator of weak firm performance (Shi et al., 2023).

At the conceptual level, while signalling theory elucidates the motivation to convey positive information, the bad news hoarding theory explains the promoter's drive to suppress negative information, particularly where SP instigates promoters to present encouraging financial reports through EM to maintain the margin call level. Although theoretically, REM is the preferred strategy over AEM among SP firms, which adversely affects the firms' real operational expenditures and future performance (Chang et al., 2022; Chauhan et al., 2020; Hu et al., 2021). Thus, we conceptualize that higher promoters' engagement in EM strategies weakens the firms' EP, potentially hindering future performance and heightened agency conflicts. Building on the arguments presented, we posit the following hypothesis:

According to Schipper and Vincent (2003), EP determines the fraction of present earnings that is sustained to forecasted earnings and is associated with the usefulness of earnings. It plays a significant role in equity valuation and financial statement analysis, which drives stock prices and investment decisions. However, EP does not necessarily equate to the ability to predict future cash flows. Thus, there is a need to investigate whether the abnormal reduction in real operational activities influences the relationship between the current reported earnings and future cash flow (i.e. EI). Because increased EP could exhibit a weaker relationship with future cash flows if the present reported earnings lack information content ^[7]. In addition, Deren and Ke (2018) observed that SP promoters are prompt to exploit the reported earnings to sustain the share price and avoid losing control over the firm; such practices could lead to poor EI. Therefore, it becomes crucial to investigate whether the managing component of earnings impacts the relationship between the present earnings and future cash flows among the SP firms.

India is one of the few countries that officially mandates frequent disclosure requirements, including information on the funds' end-use details obtained through SP at the promoter level. The Securities Exchange Board of India (SEBI) issued a regulation in January 2009 (Regulation 8A: Disclosure of Pledged Shares) for firms to mandatorily disclose promoters' pledged shares within seven days. Under this regulation, the information on pledged shares is accessible to the public for Indian firms and other stakeholders; however, Raju and Sapra (2010) identified key information limitations. In response to an alarming rise in share-backed loans (as of April 26, 2019, 2,932 companies had pledged shares out of 5,000+ BSE-listed firms), these limitations were addressed under Regulation 31(1).

On June 27, 2019, SEBI authorized disclosure under this regulation of the reason for encumbrance by promoters if the total pledge is equal to or greater than 20% of the total share capital or 50% of the promoter's holdings, and to disclose the details of the end use of the funds from the encumbrance. This disclosure-based regulatory change provides a valuable setting for investigating the SP behaviour of promoters and its impact on earnings quality. While Shi et al. (2023) have shown that a restrictive regulation in the Chinese setting can alleviate the negative impact of SP on EP and EI, the effect of a disclosure-based change like India's remains an open empirical question. This leads to our central inquiry: how the 2019 regulatory change moderates the overall earnings quality of SP firms. Furthermore, consistent with the logic of Cohen et al. (2007), we hypothesize that the 2019 regulatory change had unintended consequences, leading to a substitution from AEM to REM. Therefore, we formulate a non-directional hypothesis to guide this investigation:

Prior research has predominantly measured SP as a dummy/binary variable to capture the presence or absence of promoters' SP. This study exploits the detailed disclosure requirements in the Indian capital markets to construct a continuous measure of SP at both firm and promoter levels. In this study, we measure SP on promoter-level pledging (PL_pledge) and firm-level pledging (FL_pledge) to capture the intensity of promoters' pledging ratio variation. PL_pledge is measured as the percentage of promoters' SP divided by the total shares held by the promoters, and FL_pledge is equal to the percentage of promoters' SP divided by the total shares outstanding within a firm. This granulated approach allows for a nuanced investigation of the relationship between promoters' SP and their financial reporting quality.

Prior studies suggest that high EP are more informative about the firm's future cash flows and enable analysts to make sound forecasts for future cash flows, thus facilitating the investors to make sound investment decisions (Collins and Kothari, 1989; Wang, 2019). We follow Call et al. (2015) and Li (2019), measuring EP as the slope coefficient derived from regression analysis of future earnings with current earnings. In equation (1), $Earnit$ is earnings before any extraordinary items for the year.

Consistent with Li (2019) and Atwood et al. (2010), we measure EI by examining how sound present earnings predict future cash flows. This approach is critical because while EP is positively associated with future cash flows, this relationship becomes significantly weaker when the persistence is achieved through earnings smoothing or management. Thus, earnings quality is diminished when persistent earnings do not accurately reflect a firm's ability to generate future cash flows. Following this perspective, we measure EI as the slope coefficient derived from a regression of future cash flows on present earnings. This model captures the extent to which reported earnings inform investors about the firm's future operational cash-generating ability. In this Equation (2), $Future_CashFlowi,t+1$ represents the future cash flow from operations, scaled by average total assets.

It is beneficial for investors and other stakeholders to identify whether top-level management and managers manipulate earnings. Thus, several studies focusing on detecting EM have directed us towards pivotal heuristics to identify corporate EM.

The study follows the Modified Jones model, Dechow et al. (1995) proposed to identify discretionary accruals as a proxy for AEM. The proposed model adjusts the variation in revenue and receivables to capture managerial discretion processed over the revenues, henceforth overcoming the limitation of the classic Jones model 1991.

In equation (3), total accruals $TACCi,t$ is determined by taking the change between the earnings before extraordinary items and cash flows from operations during the year t. The $TotalAssetst−1$ illustrates the total value of assets held by the firm in year t−1. $ΔRevi,t$ denotes the change in an entity's revenue between the year t and the year t−1. $ΔReci,t$ is the change between the net receivables in year t and year t−1, followed by the gross value of the property, plant, and equipment (⁠$PPEi,t$⁠) held by the entity (1) during the year-end t. The signed discretionary accruals are the difference between total accrualsand non-discretionary accruals.

Roychowdhury (2006) argues that managerial intervention goes beyond accounting estimates and methods and includes managing real operational activities to meet certain earnings thresholds. We follow the modified Roychowdhury (2006) model, proposed by Srivastava (2019), to estimate operational activities based on manipulations using abnormal production levels, discretionary expenses, and cash flow from operations. The author argues that all abnormal real activities cannot account for manipulations; the firm's life cycle stages or competitive strategies could lead to abnormalities. Therefore, researchers must consider cross-sectional variation in firms' competitive strategies before interpreting spurious (fake) results. To overcome the measurement error, Srivastava (2019) enhances the current model with additional control variables like market size, market-to-book ratio, return on assets, future sales, and elapsed expenditures.

1. Modified model interpreting abnormal levels of discretionary expenditures.

1. Modified model interpreting abnormal levels of production.

1. Modified model interpreting abnormal levels of cash flow from operations.

In Equation (4), $Disexpi,t$ is the sum of the average level of research and development expenditures (R&D), advertisements (ADV), and selling, general and administrative expenses (SG&A). In Equation (5), $Prodt$ is the total cost of goods sold in year t and the change in the inventory scaled by the lagged total assets. The $Cashflowi,t$ represented in Equation (6), which measures the cash flow from operations extracted from the cash flow statement for year t. $TotalAssetsi,t−1$ is the total assets in year t−1. $REVi,t$ is the total revenue for the year t and $ΔRevi,t−1$ represents the lagged value of the change in an entity's revenue over the year t over a year interval (t−1).

The additions incorporated in the modified Roychowdhury model proposed are $log⁡_Sizei,t$⁠. $Mtbi,t$, $ΔRevi,t+1$⁠. and elapsed $Disexpi,t−1$⁠, $Prodi,t−1$ and $Cashflowi,t−1$ scaled by lagged total assets $(TotalAssetsi,t−1)$⁠.

We source the Indian firm-level and promoters' share-pledging (SP) data for 2015 to 2022 from the Prowess database maintained by the Centre for Monitoring Indian Economy (CMIE). Since financial sector firms adhere to distinct regulatory norms, we restrict our study to non-financial firms, excluding the financial firms (n = 908) and data points with missing values for the computation of EM and firm-specific control variables from the sample. Thus, our final unbalanced panel data sample comprises approximately 2,119 firms, with a maximum of 16,672 firm-year observations, although the number of observations varies depending on the type of test undertaken.

Table 1 reports the descriptive statistics of the dependent and independent variables among the pledging firms. We report that the average value for all EM proxies is close to zero because they are estimated residuals of the respective models: AEM (−0.003) and REM (0.001). This indicates that our sample is representative of the population of SP firms. Among the sample firms, the frequency of share pledging is approximately 38%, and most of these firms exhibit a greater involvement in accruals than in cash. Moreover, the median promoter shareholding is 54%, which is overwhelming evidence that our sample is already drawn from a population characterized by high ownership concentration. Lastly, except for the dummy variables, all key variables are scaled by lagged total assets and winsorized at the 1st and 99th percentiles to minimize the influence of outliers in the study.

Table 2 reports the estimated correlations between the variables. The correlations between the SP and proxies of EM are positive (except AEM) and statistically significant at 1%; moreover, it is observed that the correlation coefficient between the proxies of REM and AEM is negative (−0.59), suggesting that SP firms prefer to be involved in real activity-based manipulations over managing accounting methods and estimates. The coefficient of correlation for $Earni,t$ and $Cashflowi,t$ suggests that the current earnings positively reflect the operation's cash flow from operations. Similarly, the correlation between AEM and REM_Cashflow is negative (−0.07), indicating that higher accruals reduce cash availability from operations. This could be the result of earnings smoothing through accruals; these results are consistent with those of Roychowdhury (2006). Also, promoter holding (Prom_holdn) is positively correlated with proxies of EM, suggesting higher ownership involvement and concentration incentivized to earnings manipulations (Asija et al., 2014). Lastly, the correlation coefficients between the independent variables are below 0.5, exhibiting a low risk of multicollinearity. The panel unit root tests confirmed the stationarity of all variables included in the analysis.

To test H1, we investigate the impact of promoters' SP on EP and EI. The analysis hinges on the conceptual assumption that promoters engaging in REM reduce EP and lower the informativeness of future cash flows among SP firms. Therefore, we first measure the impact of SP and both AEM and REM among SP firms in section 5.1. Subsequently, in section 5.2, we examine the effect of SP on EP and its informativeness about future cash flows. Finally, Section 5.3 investigates whether the recent regulatory change influences the relationship between SP and earnings quality.

We use two distinct panel data (fixed effects) regression models for our independent variables, PL_pledge and FL_pledge, to measure SP. We also control for firm-specific characteristics and performance measures. A detailed description of the control variables is provided in Table 3: Variable Definitions.

First, we measure the explicit impact of a unit change in SP (i.e. PL_pledge and FL_pledge) on earnings management (EM), holding other firm-specific variables constant in the regression model (7):

We measure EM by considering firms' two distinct financial reporting strategies to manipulate reported earnings: accrual-based EM (AEM) and real EM (REM), thereby uncovering the preferred method of EM among SP firms.

In models (1) and (2) of Table 4, the empirical results are consistent with antecedent literature (Asija et al., 2014; DeJong et al., 2020); the coefficient on SP; PL_pledge (−0.232, t = −5.90) and FL_pledge (−0.362, t = −5.02) is significantly negative at a 1% level, stating that the incentive to manipulate earnings through AEM is the least favoured method of EM because of the elevated level of monitoring by lenders (financial institutions) over the promoters' collateralized securities.^0482001

In Table 4, the models (3) and (4) report the following results. Consistent with the literature, a significant positive relationship between PL_pledge (1.176, t = 5.88), FL_Pledge (2.051, t = 5.59), and REM, suggesting that the willingness to manipulate earnings through altering the real operational activities is preferred over AEM since it attracts less auditors' scrutiny and is challenging to detect (Bhatia et al., 2019). It emphasized that managerial intervention extends beyond accounting estimates and methods, encompassing the management of real operational activities when firms undergo financial turmoil and alleviating margin call pressure.

The empirical results in Table 5 provide a detailed explanation of the abnormal levels of operational activities under REM. A significant negative relationship exists between REM_Cashflow and PL_pledge (−1.125, t = −7.18) and FL_pledge (−1.888, t = −6.56), suggesting that firms involved in SP have lenient credit terms with their suppliers or engage in aggressive sales price promotions and discounts, leading to peculiarly short cash flow from operations. Moreover, models (7) and (8) in Table 5 highlight a positive relationship at the 1% significance level between SP and REM_Prod, indicating that high production costs are attained through abnormal surges in production. It states that firms involved in SP attempt to lower the cost of sales through abnormally increasing production. REM_Disexp underlines a significant negative with SP in Table 5 of models (9) and (10), resulting in abnormally low discretionary expenditures to inflate current reported earnings and to signal favourable future profitability; however, the motivation to manipulate earnings through REM_Cashflow and REM_Disexp is conspicuous from the sample firms compared to reducing the abnormal level in REM_Prod.

To recapitulate the findings, our results in Table 4 reveal a positive relationship between REM and SP. This supports the underlying theory, which suggests that promoters among SP firms engage in REM over AEM to increase current reported earnings and maintain margin call levels with financial institutions. These results indicate a zero-sum game wherein upward REM partly offsets the downward AEM (via negative discretionary accruals). This inclination stems from the heightened scrutiny of lenders, high-quality auditors, the accounting freedom of firms, and the inherent reversibility associated with AEM. Therefore, SP firms engage more in REM to meet earnings targets, which involve aggressive, tangible actions to meet short-term financial targets and typical incentives for misreporting in debt covenants (Dyreng et al., 2020).

The H1a conjectures that SP by promoters decreases EP when firms manipulate earnings using REM. We test the hypothesis by incorporating an independent variable $SPi,t$ and position an interaction variable $SPi,t*Earni,t$ followed by the $Controlsi,t.$ ^[8] We run this equation using pooled regression for each measure of SP (PL_pledge and FL_pledge) separately.

Table 6 (Panel A) outlines the results supporting our conjecture on H1b. Examining the interaction terms from model (1) to model (3), we find the coefficients on these interaction variables to be negative at 1% significance, $PL_pledgei,t*Earni,t$ (−0.126, t = −3.79) and $FL_pledgei,t*Earni,t$ (−0.209, t = −3.70). The results demonstrate that promoters' SP decreases the persistence of reported earnings significantly. The negative effect of SP on EP is due to REM, which artificially inflates the reported earnings; such earnings fail to persist into the future. $Earni,t$ is positively significant, indicating that present earnings are informative of future earnings, primarily consistent with prior literature.

The H1b predicts that promoters' pledging of shares attenuates the relationship between the current earnings and future cash flows. To test this hypothesis, we estimate Equation (9).

where $CFOi,t+1$ is the future cash flow from operations scaled by lagged total assets in the year. Other variables are defined in detail in the previous model.

Table 6 (Panel B) reports the results. In all the models, $Earni,t$ is significantly positive, indicating that the present earnings are indicative of future earnings, which primarily corroborates with previous literature works (Atwood et al., 2010; Li, 2019). Examining the interaction terms, we find the coefficients on these interaction variables (⁠$∝3$⁠) to be negatively associated, $PL_pledgei,t*Earni,t$ (−0.017, t = −2.20) and $FL_pledgeit*Earnit$ (−0.026, t = −2.05). Demonstrating that the predictive power of current earnings for future cash flows diminishes when firms engage in SP. Since the earnings reported through REM negatively influence the current EP and its informativeness about subsequent cash flows. Overall, the findings contribute to the existing literature that promoters' SP attenuates the EP, reducing its informativeness or predictive power of the current earnings associated with future cash flow generation. The overall empirical analysis reveals that SP significantly reduces EP and cash flow informativeness, thereby signalling EM practices and financial instability in SP firms, which aligns with the signalling theory proposed in this study. Furthermore, the decreased EI reflects the withholding of unfavourable information, strengthening the validity of the bad news hoarding theory.

To recapitulate, the study's findings suggest that SP negatively affects the firms' financial reporting quality, serving as a negative signal and facilitating information hoarding. Consequently, this exacerbates agency conflict between promoters and minority shareholders.

In June 2019, SEBI authorized disclosure-based regulation under Regulation 31(1). This approach contrasts sharply with the more restrictive 2018 Chinese regulation on SP, which mandated a maximum pledging ratio not exceeding 50% of a promoter's ownership. According to Shi et al. (2023), this stricter regulation successfully alleviated the negative association between SP and EP, leading us to postulate that the effects of the Indian regulation will differ. To test this hypothesis, we employ the Difference-in-Differences (DiD) regression model to examine the exogenous effect of the regulatory change on earnings quality between SP firms (the treatment group) and non-SP firms (the control group). Our research design is similar to the methodologies employed by Shi et al. (2023) and You et al. (2023).

To test the H2, we estimate Equation (10a) and (10b)

To test the H3, we estimate Equation (11a) and (11b)

In equations (10) [equation 11], we classify a set of $Treat_firmsi,t$ as entities whose promoters engage in SP during the sample period, as 1 and 0 otherwise. We use$Post_Regi,t$ as our time dummy variable, which captures the year before and after the regulatory change; $Post_Regi,t$ takes the value 1 for the years after 2018 and 0 otherwise. The variable of interest is the three-way [two-way] interaction variable (⁠$∝6$⁠) [$∝3]$ which captures the changes in EP and EI [AEM and REM] before and after the 2019 regulatory change among the SP firms (treatment group) and non-SP firms (control group).

The results from DiD analysis confirm our baseline findings and provide evidence of the regulation's impact. As reported in Table 7, Panel A, the three-way interaction variable (⁠$Earni,t*Treat_firmsi,t*Post_Regi,t$⁠) in Model (1) shows a significant negative association between SP and EP at 1% level (−0.128, t = −5.11). This suggests that following the 2019 regulation, SP firms experienced a significant deterioration in EP.