Regulatory actions against corporate irregularities in India: analyzing the stock market impact

Abstract

In this article, I use a unique dataset consisting of listed Indian firms that have been indicted for economic malpractice/default or have been non-compliant with laws/ regulations/ guidelines to estimate the stock price impact of regulatory actions against corporate irregularities. The sample consists of regulatory charges imposed by two major Indian regulators, (i) the Ministry of Corporate Affairs (MCA) and (ii) the Securities and Exchange Board of India (SEBI). I find that regulatory actions are an effective deterrence against corporate misconduct and have a significantly negative impact on a firm’s stock price. The level of negative effect on the stock price of a firm is directly related to the severity of regulatory charges against it, i.e., cases of fraud or cheating, or payment default attract a much more negative reaction as compared to cases such as failure to disclose information, other non-compliance, etc. Finally, the results indicate that younger and less profitable firms have a higher (more negative) stock price reaction to regulatory action announcements.

Keywords:

• Corporate governance
• misconduct
• fraud
• penalty
• event study

JEL Codes:

• G2
• G3
• K2
• K4

1. Introduction

As of March 2022, India’s equity market is among the world’s top five in terms of market capitalization. The country’s total market cap stands at $3.21 trillion, which is higher than that of the U.K. ($3.19 trillion), Saudi Arabia ($3.18 trillion), and Canada ($3.18 trillion).¹ After China, India is the largest emerging economy in terms of stock market capitalization. However, despite the ever-growing size of the Indian equity market, corporate governance remains a significant issue. The corporate sector of India has seen numerous irregularities, including large financial scams, and shareholder disputes over the years, most of which saw lapses in governance. In such cases, the regulators initiate action against the promoters, directors, and even auditors of the firm and amend and introduce new legislations.²

In this paper, I analyze the stock price impact due to the announcement of regulatory charges against various irregularities by the listed firms in India. I examine the role of two major corporate regulators in India in this context: (i) the Ministry of Corporate Affairs (MCA) and (ii) the Securities and Exchange Board of India (SEBI). I use the event study approach for our analysis. The nature of irregularities may be financial or non-financial. Some non-financial irregularities include failure to file financial statements, failure to disclose information such as the shareholding pattern and insider trades, failure to appoint a compliance officer, etc. Corporate frauds can have a detrimental effect on a firm’s market value (Rad et al., 2021). While financial misconducts are certainly more disastrous for the value of a firm, other operational misconducts and irregularities are critical too and indicate operational indiscipline of the firm. Non-financial misconducts gain less traction and have not received due attention in the literature. I compare the impact of such non-financial irregularities to financial irregularities by classifying the regulatory charges against firms into various categories such as disclosure, payment default, non-compliance, fraud or cheating, and others.

The results suggest that regulatory actions are an effective deterrence against corporate misconduct and have a significantly negative impact on the stock price of a firm. The regulatory actions by SEBI have a more negative reaction by stock market participants, as compared to actions by the MCA. This is because SEBI deals with issues directly related to investor protection, such as fraud, cheating, default in payment by firms, etc., which are relatively more critical than the issues such as a delay in filing reports, which the MCA monitors. The level of negative impact on the stock price of a firm is directly related to the severity of regulatory charges against it. A multivariate regression analysis suggests that younger and less profitable firms have a higher (more negative) stock price reaction to regulatory action announcements.

India provides an interesting setting to study the issue of corporate irregularities due to multiple reasons. First, since the judicial regime is weaker in India compared to developed economies, it is crucial to identify the cases of corporate misgovernance before they become too big. India has ranked 79 out of 139 countries and jurisdictions in the World Justice Project’s (WJP) Rule of Law Index 2021.³ Second, India has a high proportion of retail investor participation in traditional asset classes such as bank fixed deposits, gold, etc., and a low fraction in stock markets. India’s GDP to market ratio is rising, standing at 122% as of 1 September 2021, although it is still a fair distance behind the developed economies. For comparison, in 2020, India had a market-cap to GDP ratio of 97.6%, and for the U.K., Japan, and the U.S., the figure was 115.7%, 132.8%, and 194.9%, respectively.⁴ Further, India has a lower average population age and, thus, has a higher proportion of young investors with a higher risk appetite than countries with higher average population age.⁵ The value destruction because of governance failures and the consequent erosion of investor trust or confidence means that only a handful of Indian companies attract a governance premium in a universe of well over 5,000 stocks.⁶ Hence, it is imperative to identify and address governance issues in listed firms to ensure higher investor protection and further encourage greater participation of investors in equity markets. Finally, the growth of developing countries such as India is highly dependent on foreign capital inflows. The foreign investors are particularly wary of cases of corporate misconduct, as filing litigation in a foreign country with a weak judicial system is cumbersome and costly, with little chance of any resolution.

Past studies, especially those in accounting research, generally employ indirect proxies of managerial discretion to see its impact on firm performance. Such proxies include earnings management, managerial compensation and perks, etc. In such cases, promoters and managers often play within the rules of the law to maximize their own welfare at the expense of minority public shareholders and other stakeholders. Such managerial indiscretions may not necessarily attract regulatory actions. In this study, I shift the focus from these proxies to more direct evidence of corporate misconduct and financial irregularities. Unlike past studies, our sample helps us identify the nature of irregularities by the firms and the details of the actions taken against them by the regulator.

1.1. The regulatory environment in India

Two major regulators of the corporate sector in India are the Union Ministry of Corporate Affairs (MCA) and the Securities and Exchange Board of India (SEBI).⁷ MCA is primarily concerned with the “administration of the Companies Act 2013, the Companies Act 1956, the Limited Liability Partnership Act, 2008 & other allied Acts and rules & regulations framed there-under mainly for regulating the functioning of the corporate sector in accordance with law”. It is also responsible for “administering the Competition Act, 2002 to prevent practices having adverse effect on competition, to promote and sustain competition in markets, to protect the interests of consumers through the commission set up under the Act”.⁸ On the other hand, SEBI was initially constituted as a non-statutory body in 1988 through a resolution of the Government of India and was later established in 1992 as a statutory body. The basic functions of SEBI are “ … to protect the interests of investors in securities and to promote the development of, and to regulate the securities market and for matters connected therewith or incidental thereto”.⁹ SEBI monitors and regulates the corporate governance of listed companies in India through Clause 49. This clause is incorporated in the listing agreement of stock exchanges with companies, and listed companies must comply with its provisions.

Corporate irregularities not only diminish shareholder value, but also impact the economy at large. Financial frauds mostly come at the expense of the firm’s shareholders and lenders (i.e., banks, and ultimately the retail depositors of the bank). Financial frauds of large magnitude may lead to bank runs (e.g., PMC bank fraud case, see, Gupta (2021)), resulting in loss of trust of the general public in formal channels of investment. Frauds have major implications for not just the shareholders of the firm, but for other stakeholders too, such as employees (losing a job), bankers (bad debts), suppliers (loss of business and trade credit), etc. Corporate misconducts also reduce foreign inflows in the economy due to resulting lack of trust in the governance and regulatory oversight. Prolonged judicial proceedings in cases of corporate misconduct also increase mistrust in the judicial system and the country’s government and may increase political instability in the long term.

During the recent decade and a half (2005–21), India has seen many corporate frauds that have rocked its economy, including the infamous accounting scandal of Satyam, also known as India’s Enron (2009, see, Bhasin (2013)), the willful default of Vijay Mallya (see, Giriprakash (2014)), PNB—Nirav Modi scam (see, Pande and Prakash (2019)), Yes Bank—DHFL scam (see, Deb (2021)), etc. While the cases of corporate misconduct and financial frauds are not new and have been occurring for centuries, with the rise of digital and social media, a higher number of cases of outright fraud are coming into the light, and more quickly, and attract an immediate and harsher action from both, regulators, and stock market participants. Some of the global cases of corporate financial frauds include accounting scandals such as Enron (Oct 2001, see, Y. Li (2010)), Bernard Madoff Ponzi Scheme (late 2008, see, Smith (2010)), etc.

Finally, with the advent of the internet and resultant digitization, various stakeholders can file complaints against a firm online for any grievance they have. As most of the grievance redressal systems move online, the job of a regulator becomes slightly easier since they can track the entire life cycle of a complaint, financial or otherwise, as well as any corrective measures taken by the firm. Regulators also make public any actions that they take against the wrongdoings of a firm through their website. This keeps the market updated about the firm’s compliance with various rules and regulations and facilitating greater transparency with respect to the actions of the firm and the regulator.¹⁰

1.2. Theory

A perennial issue in corporate governance literature is how to minimize principal-agent problems arising from conflict of interest. Numerous researchers have studied corporate misconduct and how managers use their discretion for personal benefits (e.g., Baker & Griffith, 2011; Liu, 2016; Punch, 1996). Some ways of dealing with the principal-agent problem include the appointment of the board of directors, institutional investors, the possibility of hostile takeovers, etc. Researchers have extensively investigated the effectiveness of these traditional ways of dealing with agency problems and have found mixed evidence.

1.3. Literature

Despite its importance, the literature on corporate misconducts and frauds is relatively nascent worldwide. One major reason for this is the lack of reliable data on corporate irregularities. There have been a few studies in the Chinese context (see, Aggarwal et al., 2015; Gong et al., 2021). Aggarwal et al. (2015) study corporate frauds in Chinese firms between 2001 and 2011 and find wide occurrences of fraud and a strong negative market reaction on the announcement date. Gong et al. (2021) that punishment announcements by regulatory authorities in China increase the cost of debt for firms facing punishment. This lack of focus on corporate misconduct motivates us to dig deeper into the issue. Apart from China, to the best of my knowledge, the research of corporate frauds and other irregularities in emerging countries is practically non-existent.

Entrusting the implementation and enforcement of laws to regulatory agencies is one of the fundamental mechanisms to minimize corporate irregularities. Researchers have widely studied the role of regulatory agencies in the stock market (see, (B. Li & Liu, 2017)). Regulatory agencies act as disciplinary agents in the market with an objective to protect the interests of various stakeholders. The firms that undergo regulatory scrutiny may face not only legal consequences, but also reputational. B. Li and Liu (2017) investigate how regulatory oversight of the U.S. Securities and Exchange Commission (SEC) affects the price formation of initial public offerings (IPOs). They examine the effects of comment letters issued by the SEC in the IPO process and find that the comments letters by the SEC result in a reduction of offer price by the IPO issuers, and the price reduction is directly proportional to the amount of correspondence with the SEC.

There are various factors which contribute to the practice of corporate misconduct, including the culture of the firm and the background of the senior leadership. Chowdhury and Doukas (2022) examine the role of CEOs in corporate failures and find that CEO inefficiency is more likely to be linked with corporate failures. They further establish that high-ability (low-ability) CEOs are less (more) likely to be associated with bankruptcy. Liu (2016) uses a large sample of listed U.S. firms and examines the effect of corporate culture on corporate misconduct. The study uses the cultural background information on key company insiders and find that corporate corruption culture has a significant positive effect on corporate misconduct such as earnings management, accounting fraud, option backdating, and opportunistic insider trading. They also document that senior leadership with questionable ethical values may spoil the culture of the entire firm and destroy firm value. While I do not explore the role of these factors in determining corporate irregularities in the study due to unavailability of culture and CEO data for the firms in our sample, it is certainly a critical issue which can be addressed going forward, especially in an emerging economy such as India.

There is a direct relation between corporate governance, risk mitigation, and regulatory compliance. If firms are run based on sound principles, they will naturally work efficiently and comply with statutory laws and guidelines.¹¹ Consequently, this efficiency will result in the firm performing better and its stock price rising. Frooman (1997) meta-analyzes 27 event studies that have measured the stock market’s reaction to firms’ socially irresponsible and illicit behavior. They find that acting in a socially responsible and lawful manner is a necessary but not sufficient condition for increasing shareholder wealth. They establish that socially irresponsible and illicit behavior negatively impacts shareholder wealth, and the effect is statistically and economically significant. Gunthorpe (1997) examines whether the financial markets penalize public corporations for unethical business practices. Using the event study methodology, they find that the announcement of investigation against a firm due to some unethical behavior leads to a statistically significant negative abnormal (excess) return. Bouzzine and Lueg (2020) examine how environmental violations affect the stock returns of the violating firm and how these financial implications then spread to industry peers. They examine Volkswagen’s diesel emissions scandal (Dieselgate) and the German automotive industry. They identify 10 Dieselgate events and employ event study methodology to detect abnormal stock reactions. Based on agency and signaling theory, their results indicate that Dieselgate has substantially harmed Volkswagen’s stock returns and those of its industry peers.

The rest of the paper is structured as follows. Section 2 gives the details of our dataset. Section 3 outlines the methodology. Section 4 presents the results, and section 5 concludes.

2. Data

The data of regulatory actions on firms is obtained from the Watchout Investor database. The database lists economic offenders and aims at alerting and protecting the investors. It is the world’s only national web-based registry of information on entities and persons who have been indicted for economic malpractice/default and/or have been non-compliant with laws/regulations/guidelines.¹² The sample consists of 449 regulatory actions. 395 observations correspond to regulatory actions by SEBI, and 54 observations are due to actions by the MCA. Our sample ranges from 2004 to 2018. Table 1 reports the year-wise number of observations in our sample. I use the CMIE Prowess database to obtain the stock price of firms. I obtain market returns from the factor returns dataset available on the IIMA library (Agarwalla et al., 2014).

Table 1. This table reports the number of irregularities by year for the period 2004–2018. There are a total of 449 firm-date-regulator observations in the final sample. The source of our data is the Watchout Investor database

Year	Number of Observations
2004	25
2005	15
2006	20
2007	10
2008	20
2009	42
2010	44
2011	64
2012	11
2013	52
2014	32
2015	24
2016	11
2017	35
2018	44
Total	449

The firm names in the Watchout Investor database don’t match exactly with the Prowess firm names. I create a matching methodology to merge the data from the Watchout Investor database with the corresponding firms in the CMIE Prowess database. First, I use a common identifier, corporate identification number (CIN), between the two databases to get firm characteristics and stock price data.¹³ I further use a string-matching approach to match the firm names from the two databases. I remove spaces, special characters, and strings such as LTD., PVT., IND., CO., merged, amalgamated, and CORP, Co, LTD, etc., from the firm names of both databases. Finally, I join the two datasets using the cleaned firm names.

I also classify the regulatory charges against firms into various categories related to disclosure, payment default, non-compliance, fraud or cheating, and others. Table 2 reports the keywords used in classifying charges against the firm. One case may be classified into multiple categories, depending on the text it contains.

Table 2. This table reports the keywords used in classifying charges against the firm into various categories. One case may be classified into multiple categories, depending on the text it contains. The text matching is case-insensitive. “|” signifies logical OR

Charges	Keywords
Disclosure related	disclos | did not submit | did not file | did not make public announcement | did not inform
Default of dues or payment	default | did not pay | non payment
Non-compliance related	did not comply | did not adhere
Fraud or Cheating	fraud |cheat | manipulation
Others	Remaining observations

Since our objective is to analyze the stock price impact of the regulatory actions, I keep only listed firms in the sample. If the stock price data is not available on the reported date of regulatory action (either due to no trading, or weekend or holiday), I define event day (day 0) as the next trading day on which stock price data of the firm is available.¹⁴ I consider only liquid firms in our sample. I require that each firm has at least 200 trading days in the period [−250, −6] trading days around the action date (Day 0). Also, all firms must trade on all 16 trading days in the [−5, +10] days trading window, around the event day. Finally, there are observations in our data set where the regulator(s) has imposed multiple actions/penalties on a firm on a single date. Thus, I aggregate the data on a firm-action date level. I further define daily returns, profitability, and leverage as:

$\mathrm{D}\mathrm{a}\mathrm{i}\mathrm{l}\mathrm{y}\mathrm{R}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}:R_t=\frac{P_t}{P_{t-1}}-1$

$\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{f}\mathrm{i}\mathrm{t}\mathrm{a}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}{\mathrm{y}}_{\mathrm{t}}=\frac{PBIDT{A}_{t-1}}{SALE{S}_{t-1}}$

$\mathrm{L}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}{\mathrm{e}}_{\mathrm{t}}=\frac{BORROWING{S}_{t-1}}{TOTALASSET{S}_{t-1}}$

3. Methodology

I use the event-study approach to analyze the stock price impact of regulatory action announcements. Using a pre-event estimation window of [−250, −6] days, I run the market model regression to calculate the beta of a firm.

$R_{it}=\hspace{0.17em}{\alpha }_i+{\beta }_i\times R_{mt}+{\in }_{it}$

where R_it denotes the daily stock return of stock i on day t and R_mt denotes the market return on day t. I use the intercept ($\alpha$) and the coefficient ($\beta$) of this estimation window regression to compute the daily abnormal returns in the post-event window. Abnormal return of stock i on day t is given by:

$A{R}_{it}=(R_{it}-E\left[R_{it}\right])$

$A{R}_{it}=(R_{it}-{\alpha }_i-{\beta }_i\times R_{mt})$

$CA{R}_{i,t_1,t_2}=\sum _{t=t_1}^{t_2}A{R}_{it}$

For each event, let $CA{R}_{i,t_1,t_2}$ denote the cumulative abnormal returns of stock i from the day $t_1$ to day $t_2$ around the event day. In this paper, I calculate the CAR for the [0, 1] trading day window around the event. Let $CAA{R}_{i,t_1,t_2}$ be the cumulative average abnormal returns (averaged across all events) from the day $t_1$ to day $t_2$, and N denotes the sample size (i.e., the number of observations). The t-statistic for testing $H_0:E\left[CAAR\right]=0$ is given by¹⁵

$tsta{t}_{CAAR}=\sqrt{N}\times \frac{CAA{R}_t}{S_{CAA{R}_t}}$

where $S_{CAA{R}_t}$ denotes the standard deviation across events at period t based on:

$S_{CAA{R}_t}^2=\frac{1}{N-1}\sum _{i=1}^N{\left(CA{R}_{it}-CAA{R}_t\right)}^2$

4. Results

Table 3 reports the cumulative average abnormal returns (CAAR [0, 1]) across the events, grouped by the two regulators. As we can see, firms, on average, experience −2.16% (t-stat = −5.20) cumulative abnormal returns relative to the market in the [0, 1] trading day window around the announcement of the regulatory charges by SEBI. Similarly, when MCA announces regulatory charges against firms, there is an average of −1.71% (t-stat = −2.29) cumulative abnormal returns. This shows that regulatory actions have a significantly negative impact on the stock price of a firm. Clearly, the regulatory actions by SEBI have a higher negative reaction by stock market participants, as compared to actions by the MCA. The statistical significance is also higher.

Table 3. This table reports the cumulative average abnormal returns (CAAR [0, 1]) across the events, grouped by the each of the regulators

Regulatory/Authority	Abbreviation	Number of occurrences	CAAR [0, 1] (%)	t-stat
Securities and Exchange Board of India	SEBI	395	−2.16	−5.20
Ministry of Corporate Affairs	MCA	54	−1.71	−2.29
Total		449

Table 4 reports the number of cases that fell under each type of charge against firms, along with the cumulative average abnormal returns (CAAR [0, 1]) across the events, grouped by the type of the regulatory charge. The observations in the table are ordered by most negative CAR at the top of the least negative at the bottom. The regulatory charges related to fraud, cheating or manipulation attract the most severe CAAR of −3.68% (t-stat = −3.02). This is followed by the charges of default of payment or dues, due to which firms experience a CAAR of −3.16% (t-stat = −2.54). This is followed by others (CAAR = −2.49%, t-stat = −3.09), disclosure related (CAAR = −1.82%, t-stat = −4.19) and non-compliance related charges (CAAR = −0.88%, t-stat = −0.77).

Table 4. This table reports the number of cases that fell under each type of charge against firms. One case may be classified into multiple categories, depending on the text it contains

Charges	Number of occurrences	CAAR [0, 1] (%)	t-stat
Fraud or Cheating	30	−3.68	−3.02
Default of dues or payment	16	−3.16	−2.54
Others	158	−2.49	−3.09
Disclosure related	211	−1.82	−4.19
Non-compliance related	44	−0.88	−0.77

The majority of the 49 regulatory actions by MCA in our sample are related to delays in filing reports (mostly financial reports). Since we are dealing with only listed firms in our study, most corporate governance-related issues fall under the jurisdiction of SEBI, which deals with issues that are directly related to investor protection, such as cases of fraud, cheating, default in payment by firms, etc. These issues are relatively more critical than a delay in filing reports, which the MCA monitors. Thus, the level of negative impact on the stock price of a firm is directly related to the severity of regulatory charges against it.

Table 5 reports the results of the regression analysis. The dependent variable is the cumulative abnormal returns ((−1)*CAR [0,1]). The negative CAR has been taken for simpler interpretation of the coefficients, i.e., a positive coefficient will indicate a higher and more negative stock price reaction. The results suggest that the stock price impact of a regulatory action announcement is larger and more negative for younger firms. The effect is significant at 5% level of significance across all the four regression models. Further, I find that more profitable firms have lesser stock price impact due to regulatory action announcements. The effect is highly significant in all the models and p-value < 0.01 in the most comprehensive model (model 4). This indicates that investors react less when more profitable firms undergo regulatory scrutiny, as compared to the less profitable firms. Further, larger firms (with more assets) have a higher stock price impact, although the effect is insignificant. More leveraged firms have a lower stock price reaction, which is counter-intuitive, although the effect is not statistically significant.

Table 5. This table reports the regression analysis. The dependent variable is the cumulative abnormal returns ((−1)*CAR [0,1]). The negative CAR has been taken for simpler interpretation of the coefficients, i.e., a positive coefficient will indicate a higher and more negative stock price reaction. The coefficients are heteroskedasticity robust

	(1)	(2)	(3)	(4)
	(−1)*CAR [0,1]	(−1)*CAR [0,1]	(−1)*CAR [0,1]	(−1)*CAR [0,1]
Age	−0.000553**	−0.000554**	−0.000522**	−0.000529**
ln assets	0.00358	0.00361	0.00411*	0.00618
leverage	−0.00873	−0.00871	−0.0126	−0.00982
profitability	−0.000192**	−0.000192**	−0.000211***	−0.000196***
Constant	0.0104	0.0108	0.0129	−0.0177
Regulator FE	No	Yes	Yes	Yes
Irregularity Type FE	No	No	Yes	Yes
Industry FE	No	No	No	Yes
Observations	449	449	449	449
Adjusted R^2	0.014	0.012	0.011	−0.018

* p < 0.10, ** p < 0.05, *** p < 0.01

5. Conclusion

In this article, I use a unique dataset consisting of listed Indian firms that have been indicted for various financial and non-financial irregularities. I use a sample of regulatory charges imposed by two major Indian regulators, (i) the Ministry of Corporate Affairs (MCA) and (ii) the Securities and Exchange Board of India (SEBI). I also classify the regulatory charges against firms into various categories related to disclosure, payment default, non-compliance, fraud or cheating, and others. The results suggest that regulatory actions are an effective deterrence against corporate misconduct.

I show that regulatory actions have a significantly negative impact on the stock price of a firm. The regulatory actions by SEBI have a higher negative reaction (as well as a greater statistical significance) by stock market participants, as compared to actions by the MCA. Since we are dealing with only listed firms in our study, most corporate governance-related issues fall under the jurisdiction of SEBI, which deals with issues that are directly related to investor protection, such as cases of fraud, cheating, default in payment by firms, etc. These issues are relatively more critical than a delay in filing reports, which the MCA monitors.

I further find that the abnormal returns are more negative for charges of fraud or cheating, default of payment or dues, compared to charges of failure to disclose information and other non-compliance-related irregularities. Thus, the level of negative impact on the stock price of a firm is directly related to the severity of regulatory charges against it. A multivariate regression analysis suggests that younger and less profitable firms have a higher (more negative) stock price reaction to regulatory action announcements.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author received no direct funding for this research.

Notes

1. https://www.business-standard.com/article/markets/india-breaks-into-world-s-top-five-club-in-terms-of-market-capitalisation-122031200004_1.html.

2. https://timesofindia.indiatimes.com/business/India-business/irregularities-found-in-cos-under-ibc/articleshow/68,983,427.cms.

3. Source: https://currentaffairs.adda247.com/india-ranks-79th-in-world-justice-projects-rule-of-law-index-2021.

4. Source: https://www.business-standard.com/article/companies/india-s-market-capitalisation-to-gdp-ratio-hits-13-year-high-of-122-121090100076_1.html.

5. The median population age in India is 28 years, as compared to 38 years in China and the US, 40 years in UK, 41 years in Canada, and 48 years in Japan and Germany. Source: https://statisticstimes.com/demographics/countries-by-median-age.php.

6. https://www.livemint.com/opinion/online-views/corporate-scandals-resurfacing-shows-governance-standards-remain-weak-11645005602985.html.

7. https://www.business-standard.com/article/markets/how-mca-and-sebi-are-cleaning-the-corporate-universe-117071000688_1.html.

8. https://www.mca.gov.in/content/mca/global/en/about-us/aboutmca/roles-responsibilities.html.

9. https://www.sebi.gov.in/about-sebi.html.

10. For instance, SEBI often takes regulatory action against companies (corporate entities) and/or their directors (individuals) for non‐redressal of investor grievances. Directions under section 11B/11 (4) (b) of SEBI Act debars companies and its directors from accessing the securities market and from buying, selling, or dealing in securities directly or indirectly, in whatsoever manner, till all the investor’s grievances against the company are resolved by them. Source: https://www.sebi.gov.in/sebi_data/attachdocs/1370334798726.pdf.

11. https://www.proschoolonline.com/blog/corporate-governance-india.

12. https://www.watchoutinvestors.com/default2a.asp.

13. WI database also has permanent account number (PAN) and director identification number (DIN). However, I could not find PAN number in CMIE Prowess database.

14. I discard an observation if the stock price data is neither available on the reported action date, nor in the next 2 calendar days.

15. https://www.eventstudytools.com/significance-tests.