Editorial Board

A Refereed Monthly International Journal of Management

Promoter Ownership and Firm Performance: Evidences from BSE Listed Companies

 

Shilpa Lodha

Assistant Professor

Department of Accountancy and Business Statistics

Mohanlal Sukhadia University, Udiapur

 

Udai Lal Paliwal

Professor

Institute of Commerce,

Nirma University, Ahmedabad

Abstract

Shareholding pattern or ownership structure is perceived to play an important role in corporate governance, thus an enabler of improved financial performance. The purpose of the present paper is to investigate whether the shareholding pattern especially promoter holding influences financial performance of Indian corporate sector. The paper is based on 870 firm year observations of the companies listed on BSE 200 index. Panel regression shows that the financial performance of Indian corporates is most influenced by leverage and size. None of the ownership variables is found to be a cause of superior financial performance of Indian Corporates, when firm performance was measured through ROA, ROCE and Tobin’s Q. But firm performance measured through RONW or ROE led to better explanation of firm performance through ownership variables. Indian promoter and foreign promoter ownership negatively impact firm performance whereas Indian corporate promoter and government promoter ownership positively impact firm performance. Institutional promoter ownership does not have significant impact on firm performance. The paper is limited in scope as we did limit our sample to non-financial companies for a pre Covid period of five years, i.e.; 2015-16 to 2019-20 only.  As per our information the study is unique as it analyses the impact of promoter holdings on financial performance of Indian corporates as most of previous studies in Indian context studied effect of ownership concentration on firm performance. The findings may be useful for improving firm value by having appropriate ownership structures.

Keywords: Shareholding pattern, promoter ownership structure, ownership structure, financial performance, RONW, ROA

Introduction

Financial performance of an entity is influenced by both internal (e.g.; economies of scale, access to key resources or competitive advantage) and external (e.g.; competition, regulation, stability of operating environment) variables. However, their impact varies across the firms, which may be attributed to the managerial decision making and impact of ownership structure on corporate governance including managerial decisions (Desoky, Mousa, Yassin & Raya, 2020). Hence, the suitability of managerial decisions(as influenced by ownership structure) for the benefit of the corporation vis-a-vis the influencing shareholder groups remains a topic of debate.

Shareholding pattern or ownership structure plays an important role in governance as well as performance of the corporate entities. Corporate India is known for its distinct ownership structure, which consists of about 50% shareholding by promoter groups (OECD, 2020).  Interestingly, this ownership concentration has been unchanged for past two decades while the Indian economy underwent structural changes and most rapid growth recording an average GDP growth of above 7%.

The gradual empowerment of SEBI (Securities and Exchange Board of India) and the measures put in place by the regulator (SEBI) for improved governance including disclosure requirements have helped protect the rights of minority shareholders in an environment, which is dominated by the promoters in Indian context. Though the promoter shareholding remains a majority chunk of corporate ownership, the overall ownership structure of ‘promoter managed’ Indian corporates has witnessed greater transformation during past few years. Institutional ownership has nearly doubled between 2001 and 2018, of the top 500 listed companies. Within this, the share of foreign institutional investors has seen a higher growth during the same period from a meager 11% in 2001 to 46% in 2014of the total institutional investment (OECD, 2020). Although Companies Act 2013 does not mention any specific restriction on promoters in terms of their capital contribution, SEBI has imposed several quantitative requirements for capital contribution by promoters in case of public issues by listed and unlisted companies, offer for sale, composite issues etc. SEBI has also prescribes the calculation procedure for promoters’ contribution; lock-in requirements etc. All these requirements have put forth the responsibility of investors’ protection on the shoulders of promoters to some extent. Definitely, these provisions may affect the firm performance, hence, the study proposes to undertake finding out the impact of promoter ownership on form performance.

Literature Review

Ownership structure and its effects on firm performance are considered as one of the significant fundamental issues in corporate governance (Shah & Paliwal, 2022; Katragadda and Sreeram, 2018).The academic literature has divergent views about such concentration or lack of it and its impact on firm performance (Ashrafi, 2019). On the one hand the higher shareholding by a particular group, generally promoters, is viewed as a detriment to the wellbeing of other shareholders (Demsetz and Lehn, 1985;Moolah, Farooque& Karim, 2012).  While the other (Xiang and Zuhui, 1999; Jensen &Meckling, 1976; Lehmann and Weiggand, 2000; Javed& Iqbal, 2008), Zhang & Kyaw, 2017; Yang and Ren (2017)) viewpoint concludes that the higher concentration of ownership such as that by promoters or institutional investors is beneficial and removes agency problem. The third view as supported by researchers such as Kamaruzaman, Ali, Ghani and Gunardi (2019), Feng, Bing, and Bing (2002), Demsetz andVillalonga (2001) argues that structure of ownership has no systematic effect on corporate performance. It is dispersed ownership that improves firm’s financial performance and mitigates agency conflicts (Moolah, Farooque& Karim, 2012). Leech and Leahy (1991) found that greater dispersion of ownership implies a higher valuation ratio, profit margin and growth rate of net assets.

The findings support the general hypothesis that the firm value is a function of the structure of ownership, though the effect has been found to be divergent by various researchers. Ongore (2011) found that firm performance is negatively related with ownership concentration and government ownership; at the same time, study found positive correlation between firm performance and foreign ownership, corporation ownership, manager ownership and diffuse ownership. On the contrary, Chen (2001) found strong relation between corporate performance and ownership concentration. Additionally, a favourable correlation between ownership concentration and firm value was discovered by Alimehmeti and Paletta (2012). Haija and Alrabba (2017) found that firm performance is positively correlated with managerial, institutional and family ownership but they do not have a significant impact on firm performance. Similarly, Griffith (1999) found that the CEO ownership does have a dominating effect on firm value; however, the effect varies as the ownership level varies.

Because they have the resources and know-how to effectively oversee management's decisions and improve the company's performance, institutional investors are considered to be good owners  (Fazlzadeh & Hendi, 2011).Roufand Hossain (2018) as well as Pant and Pattanayak (2007) found a significant positive impact of the foreign promoter/ collaborator shareholding on firm value. Similar to Griffith (1999), they also found an oscillating relationship between insider shareholding and firm value. Zhang, Gao, Seiler and Jiawei (2016) found positive correlation between ownership concentration and corporate performance. They also concluded that the degree of diversification and corporate performance are negatively related and corporations decrease diversification to maintain corporate value.Using panel regressions with fixed effects, the effect of ownership concentration on the connection between corporate governance and firm performance was examined by Vu and Pratoomsuwan (2019). They also came to the conclusion that state ownership affects how well corporate governance works for a company's performance. One corporate governance structure that works well in other developed markets might not work well in emerging countries, hence there is no one size fits all solution.

Javedand Iqbal (2008) underlined that expropriation by the controlling shareholder at the expense of minority shareholders as well as control obtained through complex pyramid structures may be disadvantageous to the other stakeholders. Corporate assets may be utilised to enrich managers rather than increasing firm value when shareholders are too dispersed to keep an eye on them.Yang and Ren (2017) found that foreign institutional investment and return on equity and total assets turnover exhibited significant positive correlation between. In this light, the research question raised by this paper is whether ownership structure affects firm performance in Indian context? Further, if yes, what form of ownership affects the firm performance? As was discussed in review of prior literature that several ownership variables like ownership concentration, CEO ownership, management ownership, state or government ownership, family ownership, institutional ownership etc. have been used in extant but research on promoter ownership has been very scarce. Thus this study aims to fulfill this research gap as the main focus of the study is on promoter ownership.

Conceptual Framework

In the field of corporate governance, relationship between ownership structure and financial performance of a firm has been a central area of attraction for researchers. In India, ownership structure is generally classified into promoter holdings, government holdings, institutional holdings, foreign holdings and other retail holdings.

Company format itself involves separation of ownership and control due to large number of shareholders who cannot supervise the work of board of directors (Vandiar & Paliwal, 2018). The seminal work of Berle and Means (1932) first pointed towards this separation of ownership and control. If a company has dispersed shareholders and does not have ownership concentration, then it tends to under-perform. Agency theory highlights the possible conflict that may arise when dispersed ownership fails to monitor and influence managers to work in the most beneficial way for the owners (Jensen & Meckling, 1976). The "separation of ownership and control" of the firm causes managers to put in insufficient effort to meet their own preferences, which leads to principal-agent conflicts  (Berger & di Patti, 2006). Ideally, the agent is required to expand shareholders’ wealth, however, Proffitt (2000) argues that chain of command (ownership structures) may affect agency costs and thereby influence firm performance. Some authors claim that large outside owners may have a role to play as managers' monitors and may therefore improve performance, in contrast to agency theory, which contends that higher levels of managerial ownership structure improves business performance. According to a different perspective that goes against agency theory, a high degree of ownership concentration could result in the dominant owners taking advantage of the company's resources at the detriment of other shareholders (Laiho, 2011). This paper is an attempt to understand how the ownership structure of BSE listed firms affected their performance. To study how the ownership structure especially the promoter ownership can impact firm performance, the paper uses the following conceptual relationship (Figure1). 

Figure 1: Conceptual Framework

Hypotheses of the Study

As the study proposes to explore relationship between promoter-ownership and firm performance, formulated hypotheses are as follows:

H₀₁: There is no significant impact of Indian promoter-ownership on firm performance.

H₀₂: There is no significant impact of Indian corporate promoter-ownership on firm performance.

H₀₃: There is no significant impact of foreign promoter-ownership on firm performance.

H₀₄: There is no significant impact of government promoter-ownership on firm performance.

H₀₅: There is no significant impact of institutional promoter-ownership on firm performance.

Research Methodology

Data Collection

We consider companies listed on BSE stock exchange and included in BSE200 index. The period of data collection was pre-Covid five years i.e.; from 2015-16 to 2019-20. We collected data on variables broadly in three categories: ownership structure variables, firm performance variables and control variables. We used CMIE PROWESS database for data collection, some of the data were hand collected from the annual reports of the sample companies. In spite of all efforts, some data of 26 companies could not be obtained. Hence final sample reduced to 174 companies and 870 firm year observations.

Ownership Structure Variables

The study uses ownership structure variables broadly confined to promoter ownership, that too is further divided into Indian and foreign ownerships. We consider Indian Promoter-Ownership, Indian Corporate Promoter-Ownership, Foreign Promoter-Ownership, Government Promoter-Ownership and Institutional Promoter-Ownership.

Firm Performance Variables

We have taken four measures of firm performance – ROA, ROCE, RONW and Tobin’s Q. While ROA is calculated as EBIT divided by total assets (Nashier and Gupta, 2020; Mollah, Farooque & Karim, 2012; Haldar and Rao, 2011), ROCE is calculated as Net Profit divided by Capital Employed (Rashid, 2016; Bazhair & Alshareef, 2022). RONW also known as return on equity represents the amount of profits available for equity shareholders. It is calculated as net income divided by equity shareholders’ fund (Mollah, Farooque &Karim (2012; Ongore, 2011).

Tobin’s Q has been used to capture market-based firm performance (Ongore, 2011; Adamu & Haruna, 2020; Elvin & Hamid, 2016; Jwailes, Sulong and Ahmad, 2020). Tobin’s Q has been used as the market-based performance measure while the other three measures are accounting-based measures.

Control Variables

Following control variables have been taken in this research:

Age

Age of a firm is represented by difference between current year and year of incorporation. The firm age indicates how long the company has been in business (Phung & Mishra, 2015). Long-running businesses gain experience, which may aid in improving performance. Because family management has a tendency to become entrenched in the firms, Andres (2008) looked into the relationship between family ownership and firm performance and found that firm age can be detrimental in these cases. The age of the company is ascertained in this study by counting the years from its incorporation.

Leverage

Leverage is represented by debt-equity ratio. Leverage provides a tax shield benefit and positively impacts firm performance (Miller & Modigliani, 1963). Introduction of debt in the capital structure mitigates the agency problem and help boost firm performance (Jenson, 1986). Hence leverage has been taken as another control variable, presuming positive impact on firm performance.

Size

Size is represented by natural log of total assets and often included to capture economies or diseconomies of scale (Mnasri, 2015). While Downs (1967) argued that bigger size leads to coordination and bureaucratization problems, Sidhu & Bhatia (1993) and Montgomery (1979) demonstrated that big firms have economies of scale. We therefore, hypothesize that size has a positive impact on firm performance.

Table 1 shows the definition of variables along with their sources.

Table 1: Variable Definition

Variable	Definition	Source
IndProm	Indian Promoter Ownership	Pant and Pattanayak (2007)
IndCorpProm	Indian Corporate Promoter Ownership	Pant and Pattanayak (2007)
ForProm	Foreign Promoter Ownership	Ongore (2011);
InstProm	Institutional Promoter Ownership	Ongore (2011);
GovProm	Government Promoter Ownership	Ongore (2011)
Size	Ln(Total Assets) i.e.; natural log of total assets	Nashier and Gupta (2020); Javed and Iqbal (2008)
Lev	Leverage measured by Debt-Equity Ratio	Javed and Iqbal (2008)
Age	Current Year-Year of Incorporation	Leech and Leahy (1991)
ROA	Return on Total Assets	Nasheir and Gupta (2020); Mollah, Farooque and Karim (2012)
ROCE	Return on Capital Employed	Rashid (2016); Bazhair & Alshareef (2022)
RONW	Return on Net Worth	Arora and Sharma (2016); Arora and Sharma (2018)
Tobin’s q	Market Value of Equity and Debt / Book Value of Equity and Debt	Mollah, Farooque and Karim (2012); Pant and Pattnayak (2007)

Source: Various studies as cited above

Using the variable as explained above, the following regression model was used to test the study hypothesis:

Accordingly, following four equations were tested using Panel Data Regression:

Equation 1

Equation 2

Equation 3

Equation 4

Table 2: Descriptive Statistics

	Mean	Median	Maximum	Minimum	Std. Dev.	C. V.
RONW	16.065	15.060	140.720	-66.730	18.191	113.23%
ROA	9.173	7.430	73.790	-8.870	8.952	97.59%
TOBIN_S_Q	177.558	40.050	2860.825	0.000	335.164	188.76%
ROCE	13.415	10.650	110.000	-45.320	14.878	110.91%
IPROM	42.980	50.000	98.110	0.000	26.076	60.67%
ICPROM	22.075	9.050	100.000	0.000	25.040	113.43%
INSTPROM	0.491	0.000	51.000	0.000	4.336	884.00%
FPROM	11.619	0.000	75.000	0.000	22.850	196.66%
GOVPROM	9.324	0.000	95.840	0.000	23.047	247.18%
SIZE	9.820	9.504	15.190	6.389	1.705	17.36%
AGE	46.684	39.000	125.000	1.000	27.191	58.25%
LEVERAGE	0.780	0.200	12.550	0.000	1.511	193.89%

Source: Authors’ calculation based on CMIE Prowess Data

Table 2 presents the descriptive statistics of the variables. It is found that RONW is having mean value of 16.06, with maximum value of 140.7 and minimum value of -66.7. ROA has mean value of 9.18 and that for ROCEis 13.42. These are accounting-based measures whereas Tobin’s Q is a market based measure and it is having mean value of 177.56 with maximum value of 2860.825 and minimum value of 0. It is having highest value of standard deviation and Coefficient of Variation among all firm performance variables, indicating its different nature. All the ownership variables have lowest value of 0, indicating that some companies are having 0% of the ownership holdings from respective promoter groups. Maximum value of Indian promoter ownership is 98%, while for Indian corporate promoter ownership is 100%, for institutional promoter ownership is 51%, foreign promoter ownership is 75% and government promoter ownership is 95%.

For control variable, age, highest value is 125 and lowest is 1 (the company formed in 2014 - 15). Thus, there is high variation in the age of companies. The mean age is 46.7 years. Leverage has minimum value of 0.00 (debt-free company) and maximum value is 12.550. This high value of leverage shows high level of debt as compared to equity. However, mean leverage is 0.78 which is quite low.

Table 3 presents the correlation matrix among variables. It is found that there is high degree positive correlation among RONW, ROA and ROCE, indicating their similar nature. On the other hand, Tobin’s Q has low degree positive correlation with these firm performance variables. IPROM, GOVPROM and INSTPROM have negative correlation with all firm performance variables. ICPROM also has negative correlation with all firm performance variables but RONW. FPROM has positive correlation with all firm performance variables. Leverage also has negative correlation with all firm performance variables.

Estimated results for pooled model have been presented in Table 4. For all the estimated four models, F value was found to be significant at 5% level of significance, highest for ROA and lowest for Tobin’s Q. The highest F value was for ROA and the lowest was for Tobin’s Q. Adjusted R-square was highest for ROCE followed by for ROA. The lowest value for adjusted R-square was for Tobin’s Q. in all, the explanatory power ranged for pooled models between 17% and 29%. Thus, all the four models appear to be pretty good in terms of explanatory power.

It is further found that for ROA pooled model, none of the ownership variable was found to be significant. However, IPROM, ICPROM and FCPROM were found to have negative coefficients whereas GOVPROM and INSTPROM showed positive coefficients. Only leverage and age were found to have significant yet negative impact on firm performance. For ROCE pooled model, IPROM, leverage and age were found to have significant negative impact on firm performance.

For RONW pooled model, IPROM, FCPROM, age and size showed significant negative impact on firm performance. For Tobin’s Q model, FCPROM (positive), GOVPROM (negative) and leverage (negative) had impacted firm performance significantly. Thus there is no uniformity in significant variables in all the four models. Then, Breusch-Pagan test was applied to find the existence of random effects.

 

Table 3: Correlation Matrix

Variables	RONW	ROA	Tobin’s Q	ROCE	IPROM	ICPROM	INSTPROM	FPROM	GOVPROM	Size	Age	Leverage
RONW	1.000
ROA	0.798	1.000
Tobin’s Q	0.286	0.332	1.000
ROCE	0.891	0.925	0.389	1.000
IPROM	-0.249	-0.101	-0.286	-0.243	1.000
ICPROM	0.012	-0.021	-0.070	-0.052	0.392	1.000
INSTPROM	-0.128	-0.121	-0.014	-0.130	0.030	-0.100	1.000
FPROM	0.257	0.217	0.393	0.341	-0.695	-0.345	-0.058	1.000
GOVPROM	-0.290	-0.184	-0.177	-0.238	0.389	-0.338	0.009	-0.206	1.000
Size	-0.421	-0.483	-0.141	-0.472	0.110	-0.154	0.184	-0.312	0.512	1.000
Age	-0.141	-0.101	0.035	-0.054	-0.218	-0.232	-0.054	0.130	0.229	0.220	1.000
Leverage	-0.167	-0.375	-0.139	-0.353	0.094	-0.009	0.411	-0.211	0.121	0.435	-0.106	1.000

 

Table 4: Results of Pooled Model

Parameters	Dependent Variable
	ROA		ROCE		RONW		Tobin’s Q
	Coefficient	t-statistic	Coefficient	t-statistic	Coefficient	t-statistic	Coefficient	t-statistic
C	33.51068	14.47314*	51.64745	13.56381*	70.68118	14.07877*	-36.96547	-0.379529
IPROM	-0.017570	-1.025716	-0.087309	-3.099307*	-0.206974	-5.572494*	0.352292	0.485728
ICPROM	-0.021605	-1.584456	-0.011735	-0.523303	0.014552	0.492163	0.405819	0.719194
FCPROM	-0.002667	-0.163942	0.042795	1.599431	-0.078909	-2.236826*	6.158880	8.974834*
GOVPROM	0.027368	1.550767	0.037271	1.284196	0.042303	1.105520	-1.835342	-2.478791*
INSTPROM	0.083532	1.283239	0.070253	0.656253	-0.120711	-0.855228	2.568836	0.962879
LEVERAGE	-1.347656	-6.997125*	-1.828573	-5.773064*	-0.721305	-1.727192	-19.99767	-2.372398*
AGE	-0.021816	-2.099211	-0.023067	-1.349656	-0.071356	-3.166520*	-0.134086	-0.314928
SIZE	-2.174622	-10.48182*	-3.327419	-9.752450*	-4.259147	-9.467968*	16.42032	1.883800
F	44.9279*		47.2336*		33.0943*		23.5250*
Adj R2	0.2799		0.2903		0.2212		0.1718

*represents significant at 5% level of significance.

Source: Authors’ calculation based on CMIE Prowess Data

 

Table 5: Breusch-Pagan Test Results

Models	Statistic	P Value
ROA	1258.010*	0.00
ROCE	1247.453*	0.00
RONW	804.1220*	0.00
Tobin’s Q	637.2137*	0.00

Source: Authors’ calculation based on CMIE Prowess Data

 

Table 5 shows the results of Breusch-Pagan Test. The test indicates whether random effect model is better than pooled model. The results show that for dependent variables ROA, ROCE, RONW and Tobin’s Q, B-P test statistic for cross section was found to be significant. The p values for all models were lower than 0.05 when tested for cross-sections. Hence for these variables, random effect model (for cross section) was proved to be better than pooled model. Table 6 presents results of random effect model estimated for the four equations.

 

Table 6 presents the results of random effect model estimated for all four variables. It is found that F statistic is significant for all four models at 5% level of significance, highest for RONW and lowest for Tobin’s Q. Adjusted R Square was 11.66%, 12.74%, 15.09% and 6.49% respectively.

For ROA model, no change was observed from pooled model, as none of the ownership variable has significant coefficient and only Leverage and Age are having negative coefficients that have p values less than 0.05. Exactly similar results were obtained for ROCE model. Only Age and Leverage are significant coefficients and having negative impact on firm performance. For RONW model, surprisingly, all variable except INSTPROM were significant. IPROM, FCPROM, Leverage, Age and Size are having negative coefficients whereas ICPROM is having positive coefficient. Amongst these, Size and Leverage are having highest negative impact. Thus, RONW model has shown significant changes in results after introducing random effects in the model.

 

Table 6: Results of Random Effect Model

Variables	Dependent Variable
	ROA		ROCE		RONW		Tobin’s Q
	Coefficient	t-statistic	Coefficient	t-statistic	Coefficient	t-statistic	Coefficient	t-statistic
C	34.38070	10.56118*	54.23942	10.07165*	91.92272	11.93035*	-95.93477	-0.626211
IPROM	-0.005895	-0.262028	-0.047475	-1.273696	-0.396474	-7.198959*	0.584006	0.525772
ICPROM	-0.033308	-1.595836	-0.022033	-0.638184	0.143295	2.943558*	-0.146938	-0.156608
FCPROM	-0.017853	-0.737870	0.053407	1.335811	-0.220489	-3.953166*	5.988917	5.225861*
GOVPROM	0.008548	0.328549	0.014756	0.342853	0.233541	3.822491*	-2.039218	-1.713411
INSTPROM	-0.068567	-1.284864	-0.201607	-2.273162	-0.028206	-0.195854	-0.410176	-0.139915
LEVERAGE	-0.855362	-4.980333*	-1.351273	-4.734935*	-2.352163	-5.118668*	-35.43938	-2.964642*
AGE	-0.007469	-0.358404	-0.015410	-0.449811	-0.111006	-2.614168*	-0.469111	-0.597129
SIZE	-2.353540	-7.486715*	-3.794511	-7.306354*	-5.582046	-7.752080*	26.00285	1.827507
F	15.920*		17.506*		21.0834*		7.4689
Adj R2	0.1166		0.1274		0.1509		0.0649

            *represents significant at 5% level of significance.

Source: Authors’ calculation based on CMIE Prowess Data

 

For Tobin’s Q model, FCPROM, GOVPROM and Leverage were variables with significant coefficients. FCPROM is positive whereas other two are negative coefficients. Leverage is having the highest negative coefficient value and FCPROM has highest positive coefficient value.

Results were again tested for fixed effects using Hausman Test, shown in Table 7.

 

Table 7: Results of Hausman Test

Models	Chi-square Statistic	P Value
ROA	9.514	0.3008
ROCE	8.552	0.3814
RONW	53.683	0.0000*
Tobin’s Q	13.292	0.1022

Source: Authors’ calculation based on CMIE Prowess Data

 

It is found from the results all the four models, except RONW model, were having Chi-square statistic for Hausman Test not significant at 5% level of significance. Thus, it shows that random effect model is better for three models than fixed effect model. On the other hand, for RONW model, the Chi-square statistic was 53.683 with a p value of 0.00. Therefore for the RONW model, the fixed effect model performs better than the random effect model. For RONW as the dependent variable, a fixed effect model was therefore estimated and results are presented in Table 8.

 

Table 8: Results of Fixed Effect Model (RONW)

Variable	Coefficient		t-Statistic
C	142.7534		9.357138*
IPROM	-0.626531		-7.037568*
ICPROM	0.446759		5.073478*
FCPROM	-0.402589		-3.022779*
GOVPROM	0.503503		4.370338*
INSTPROM	0.054978		0.300923
LEVERAGE	-3.203989		-5.328309*
AGE	-0.163913		-0.501219
SIZE	-10.15413		-4.368245*
Adj R2		0.768140
F-statistic		16.93037*

Source: Authors’ calculation based on CMIE Prowess Data

Table 8 reveals that there is a drastic change after estimating model with fixed effects. Adjusted r-square value rises to 76.81% and F value is also significant. As far as variable coefficients are concerned, all variable except INSTPROM and Age are significant. IPROM, FCPROM, Leverage and Size are having negative coefficients whereas ICPROM and GOVPROM are having positive coefficients. Thus, it can be concluded that government promoter ownership has positive impact on firm performance, indicating trust of general public that funds are efficiently utilized in maximizing shareholders wealth. Indian promoter ownership is showing negative impact on firm performance whereas Indian Corporate promoter ownership is showing positive impact on firm performance. This shows efficiency of corporate promoters in managing funds and affairs of company. Foreign Corporate Ownership is showing negative impact on firm performance and institutional promoter ownership is not impacting firm performance. A summary of hypotheses testing may be presented as follows:

S. N.	Hypothesis*	Impact	Decision
1	There is no significant impact of Indian promoter ownership on firm performance.	Negative	Rejected
2	There is no significant impact of Indian corporate promoter ownership on firm performance.	Positive	Rejected
3	There is no significant impact of foreign promoter ownership on firm performance.	Negative	Rejected
4	There is no significant impact of government promoter ownership on firm performance.	Positive	Rejected
5	There is no significant impact of institutional promoter ownership on firm performance.	Positive	Accepted

*Firm performance has been measured through RONW or ROE

 

Conclusions and Policy Implications

Present paper explored relationship between promoter ownership and firm performance. Researchers collected data for BSE-200 companies for five years from 2015-16 to 2019-20. Researchers focused on promoter ownership under various categories i.e.; Indian, Indian corporate, foreign corporate, government and institutional. Researchersalso considered control variables like size, age and leverage of the firm. Firm performance was proxied by ROA, ROCE, RONW and Tobin’s Q. These variables were regressed on ownership structure variables and control variables using panel data regression. It was found that for models where ROA, ROCE and Tobin’s Q were dependent variables, random effect model was better than pooled model as well as fixed effect model. But for the model where RONW was dependent variable, fixed effect model was better than random model and pooled model.

 For RONW model, all ownership variables except INSTPROM were found to have significant impact on firm performance. While for other models none of the ownership variable was found to have significant impact on firm performance (except for FCPROM for Tobin’s Q model). RONW model reveals that performance of the company is positively impacted by Indian corporate promoter and government promoter ownership, but negatively impacted by Indian promoter and foreign promoter ownership. Institutional promoter ownership has no discernible effect on the success of the firm. Positive impact of government ownership on firm performance is not supported by prior studies such as Alawi (2019, 1087) and Al-Malkawi and Pillai (2018, 16). At the same time these results are contrary to Zeitun (2014, 75). Leverage is having negative impact on firm performance. These results are consistent with Nashier and Gupta (2020, 14) and Rajan and Zingales (1995, 1457) who also found negative relationship between leverage and profitability though Javed and Iqbal (2006, 957) and Baum, Schafer and Talavera (2007, 14) documented positive association between these two.

A variety of limitations must be taken into consideration while interpreting the study's findings. First, only five years (pre-Covid) data is included in the evaluation of the proposed relationships in the current study. To produce more reliable results, future studies may incorporate data spanning longer periods say 10 years. Second, the sample consisted all 200 companies listed on the BSE 200 index were taken into consideration. Future research may concentrate on a specific industry to study the industry specific outcomes, if any. Third, only promoter ownership has been taken into consideration. Non-promoter ownerships might also be investigated in future to better understand the hypothesized relationship.

In spite of all these limitations, findings of the study bear important implications for investors, policy-makers and regulators. By examining certain effective corporate ownership structures that have a significant impact on firm performance, the study's findings partially validate the theoretical framework for corporate governance. Additionally, it shows how various ownership structures affect the way a company performs. High degree of promoter ownership may have resulted in increased investor confidence, better alignment with shareholder interests and swiftness of decision making. On the one hand the corporate reputation so gained might also have resulted in lower cost of capital while on the other hand adaptability, stability and continuity of management is believed to have resulted into better corporate performance. To improve company performance and save agency costs, business owners can use increased corporate promoter ownership and government promoter ownership.Based on the ownership structure of a company, investors can make wise and thoughtful investment decisions. They can invest in businesses with significant government and corporate promoter ownership to benefit from high market performance resulting from superior performance of such companies due to the factors cited above and reduced agency costs.

 

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