Exploring New Aspects of Corporate Dividend Policy: Case of an Emerging Nation

Abstract

The present study focuses on how various firm characteristics influence their dividend payout policies. The study finds empirical evidence with regard to primarily two aspects of corporate dividend decisions—dividend increase and decrease, whose exploration is inadequate in the past literature. The random effect logistic regression has been considered in order to analyze the panel dataset from 2001–2002 to 2021–2022 including 3739 listed Indian firms. The empirical models are formatted based on the relevant dividend-related theories in the Indian context such as the residual theory, transaction cost theory, signalling theory, etc. Further, additional tests are conducted regarding the robustness of the reported results. The empirical results document that firm size, profitability, promoter holdings, cash holdings, and life cycle have a favourable influence on the propensity of both increasing and decreasing dividend payouts. In contrast, earnings volatility, leverage, and free cash flow reduce firms’ tendency to increase and decrease dividend payments. These results indicate that higher liquidity and ownership concentration provide firms with greater financial flexibility to adjust their dividend policies as per their prevailing opportunities. The findings of the study offer insightful information about how to arrange dividend policies with firm-specific traits which will be helpful for managers and investors to make better decisions.

1. Introduction

A firm’s dividend policy is inclusive of multi-dimensional factors, involving major corporate financial decisions as it influences the firm’s market value, stakeholders’ profile, tax composition, capital structure, etc. (Almeida et al., 2015; Chang & Rhee, 1990; Renneboog & Trojanowski, 2007). Such prominence makes dividend-related decisions a sensitive and complex matter for all firms. Offering dividends is crucial to fulfilling the stakeholders’ expectations as they play a huge role in the firms’ long-term survival in the market (Farinha, 2003). Even the stakeholders’ demands regarding dividend rewards often vary. While some long for long-term growth, others may prefer short-term benefits. At the same time, the distribution of the entire surplus as dividends can also be hurtful to firms’ future endeavours or financial distressful situations. Therefore, firms have to be very careful when selecting their dividend policies and have to consider an inclusive approach.

The above statements make it quite clear that a firm’s dividend policy is equally vital for both firm managers and stakeholders (M. Baker & Wurgler, 2004; Barros et al., 2020). Firm managers should have knowledge of the various firm characteristics or governance traits that can impact their dividend policies. Such knowledge is critical for them to determine and achieve effective dividend policies which can maximize the shareholders’ wealth (Budagaga, 2020). Similarly, interested stakeholders or investors also need to understand how the various firm characteristics can affect their dividend returns and choose a firm where they can fulfil their investment goals. Studies focusing on such dimensions can help investors make more informed and precise investment decisions (Duong et al., 2021; Yousaf et al., 2019). However, the number of studies on similar lines is inadequate in the existing literature, which calls for more research work to fill the prevailing research gaps. In this context, it is important to highlight some key limitations in the existing literature that warrant further investigation. Firstly, most studies in the past literature have focused on investigating the factors of dividend payouts or propensity to pay dividend payouts, while ignoring other crucial aspects of dividend payments such as dividend increase, decrease, etc. Secondly, the number of studies that have focused on developing or emerging nations is minimal, while most studies have focused on developed economies. Additionally, India is currently one of the fastest-growing emerging nations, and the market has been growing rapidly in recent years. Thus, exploring such dimensions of the dividend policy in Indian firms is crucial for their investors and firm managers to find out if the results differ from other countries’ contexts. Thirdly, the existing literature has shown mixed results considering the impact of several firm characteristics on dividend payouts. Such various conclusions indicate the need for more empirical studies in order to arrive at more concrete outcomes.

Considering the existing gaps, this study investigates the impact of various traits of Indian listed firms on two crucial dividend aspects—increase and decrease. The empirical outcomes are believed to contribute extensively to the existing literature. Firstly, as per the conducted review process, the present study is a novel attempt to explore the influences of the firm-level factors on the dividend payout policy in the Indian context. The corporate sector in India has seen remarkable growth in recent years as one of the major emerging economies. Therefore, exploring the arguments of dividend decisions in the Indian context is imperative from the perspective of international market conditions as well. Secondly, although previous studies exist on similar lines (Adhikari & Agrawal, 2018; AlGhazali & Yilmaz, 2023; Cave & Lancheros, 2024; De Souza Junior et al., 2024; Dsouza et al., 2025; Grennan, 2019), their focus and extent of investigation differ from the scope of the current study. For instance, Adhikari and Agrawal (2018) and Cave and Lancheros (2024) did not primarily identify firm characteristics that may impact dividend decisions, AlGhazali and Yilmaz (2023) highlighted the role of profitability but failed to highlight other firm characteristics, De Souza Junior et al. (2024) and Dsouza et al. (2025) do not consider the increasing or decreasing factors of dividend payouts in particular, etc. Thus, studies that solely explored identifying firm characteristics that impact the increase and decrease features of dividend policies are not adequate in the existing literature despite their significance for investors’ decision-making process. Thirdly, the practical applicability of popular dividend theories such as residual theory, agency theory, signalling theory, etc. is also discussed in the present study.

The present study is ordered in separate sections. Section 2 is prepared in order to provide a detailed knowledge of the existing literature. The empirical methodology is summarized in Section 3, while its results are discussed in Section 4. The robustness test results are reported in Section 5. Lastly, the study is concluded in Section 6.

2. Review of the Literature

In the existing literature, several studies have been conducted with regard to firms’ dividend policies. These studies have investigated different aspects of dividend policies. While most studies have explored the levels of dividend payouts (Belda-Ruiz et al., 2022; Cheng et al., 2021; Duong et al., 2021), a few others have also emphasized the propensity to pay dividends (Budagaga, 2020; Easterwood et al., 2021; Kowerski & Kazmierska-Jozwiak, 2022). Studies have been using different indicators to evaluate the diverse aspects of dividend policies in firms. Some of them are as follows: the ratio of dividend to earnings before extraordinary items (Agarwal & Chakraverty, 2023; Do, 2021), dividend to sales (Ankudinov & Lebedev, 2016; Jabbouri, 2016), dividend per share to earnings per share (Bahreini & Adaoglu, 2018; Budagaga, 2020; Denis & Osobov, 2008), dividends to net profit (Akhtar, 2018; Cheng et al., 2021), dividend to total assets (Oh & Park, 2021; Xu et al., 2021; Yousaf et al., 2019), dividends to cash profit (Sharma, 2021), etc.

Empirical studies in developed countries have been ample in the prevailing literature. Perretti et al. (2013) documented that size, capital mix, and growth opportunities positively affect the propensity to pay dividends in the U.S. Almeida et al. (2015) found in the context of Portugal that market value, net profit per share, profitability, size, and financial autonomy positively influence the ratio of dividend payouts in firms. On the other hand, the previous year’s dividends, operating income, and business dimension show an unfavourable impact on the same. Adhikari and Agrawal (2018) documented the significant impact of peer influence on U.S. firms’ dividend payouts. Such an effect is reported to be stronger for firms with greater product market competition. Similarly, another study, Grennan (2019), reported that peer effects lead to an increase in dividend payouts but fail to significantly influence repurchases. In the case of European firms, Barros et al. (2020) inferred that taxes, profitability, size, and the presence of shares outstanding in free float increases the volume of dividend payouts, whereas analysts’ coverage prevents a higher dividend payout. Krieger et al. (2021) documented that net income and debt volume are two significant determinants of dividend lowering in the U.S. The relationship between them was found to be more significant during the COVID-19 pandemic. On the other hand, an inverted U-shaped curve relationship was demonstrated between working capital and paying dividends by Xu et al. (2021). The study was carried out on firms from the London Stock Exchange. Oh and Park (2021) asserted a positive association between corporate sustainable management and the dividend payout ratio in Korea. Duong et al. (2021) established that in the presence of conservative managers, U.S. firms tend to retain profits over distributing them as dividends among the shareholders. Kowerski and Kazmierska-Jozwiak (2022) confirmed an inverted U-shaped curve between the tendency to pay dividends and the propensity to make share repurchases in Poland. With respect to U.S. firms, Cave and Lancheros (2024) evidenced that dividend decisions are impacted by local peers. Such influence is greater in the presence of a retail investor clientele, institutional clientele, and agency-cost clientele.

Similar studies have been found in the context of developing economies also. H. K. Baker and Kapoor (2015) stated that the stability of earnings, pattern of past dividends, level of current earnings, and level of future expected earnings lead to higher dividend offerings in India. Ankudinov and Lebedev (2016) showed that profitability and the firm size help offer better dividend rewards, whereas growth opportunities and leverage have the opposite impact in terms of Russian companies. As per the findings reported by Elyasiani et al. (2019), a higher profitability, business risk, effective tax rate, and lower leverage result in a higher tendency to pay dividends in Iran. In India, liquidity, leverage, firm size, and growth are documented as a hindrance to higher dividends as per the empirical findings by Sharma (2021). In contrast, firm risk and lagged dividends posited an improved dividend output. Cheng et al. (2021) reported that firms with higher leverage reduce firms’ commitment towards paying higher dividends in China. Ghose et al. (2022) provided empirical evidence from India for an increase in the propensity to pay dividends according to firm size, profitability, market-to-book ratio, capital expenditure, cash holding, ownership concentration, and group affiliation. In contrast, free cash flow, earnings volatility, leverage, and illiquidity have negative impacts.

Along similar lines, studies in the context of multiple countries are also found in the prevailing literature. Denis and Osobov (2008) reported the probability of paying dividends to be favourably impacted by the profitability, size, and capital mix. Chay and Suh (2009) presented that firms in initial growth stages with higher cashflow fluctuations choose lesser dividend payouts. Bahreini and Adaoglu (2018) explored the impacts of various firm, sector, and country-specific factors on dividend policies. Among the firm-specific determinants, the profitability, size, and growth opportunities have favourable outcomes. In the case of sector-specific determinants, the capital intensity and leverage are found to adversely affect the dividend payout volume. Lastly, country-specific variables like effective dividend tax (EDT) inversely influences the dividend payouts in specific sub-sectors. Barros et al. (2020) evidenced that larger firms lead to greater chances of paying higher dividends to their shareholders. Budagaga (2020) carried out an empirical study considering MENA countries and reported that the size, profitability, level of capital adequacy, and age positively influence the decisions on dividend payments. However, credit risk works adversely in this context. It was found by De Souza Junior et al. (2024) that taxes, size, and leverage positively affect, whereas free cash flow and earnings negatively impact, dividend payouts. The study considered 11 emerging countries from the G20 economic union. Agarwal and Chakraverty (2023) documented that more growth opportunities reduce the propensity of firms to pay healthy dividend payments. If the firms have to mandatorily adopt the International Financial Reporting Standards (IFRS), this adverse relationship becomes more prominent. AlGhazali and Yilmaz (2023) considered a sample of 29 emerging nations and found that profitability is the most prominent influencer in firms’ dividend decisions. During the COVID-19 pandemic, most firms showed either an increase or decrease in their dividend amounts. Dsouza et al. (2025) reported that the firm size, profitability, and dividend per share of the preceding year favourably impact the current year’s dividend per share with respect to the S&P 500 listed firms.

The above discussion hints at the mixed findings obtained from different studies based on different locations. Most studies have limited their empirical investigation to dividend payouts and the propensity to pay dividends. Other dividend aspects such as dividend increase and decrease are not adequately explored. Also, these studies fail to provide a uniform indication of how various firm characteristics influence the decisions related to dividend policies. Therefore, it is vital to conduct similar empirical studies in the Indian context to understand the dynamics between new aspects of dividend policy and firm characteristics. Moreover, as the above literature has indicated, most studies are carried on in terms of developed countries. As India is considered one of the fastest-growing developing nations, the present study will provide more relevance to developing countries’ dividend-related decisions.

3. Theoretical Arguments and Study Hypotheses

In the existing literature related to dividend policy, researchers have referred to various theoretical arguments.

Table 1. Related theories of dividend policy.

Theory Name	Theoretical Argument	References
Dividend irrelevance proposition	A firm’s dividend policy fails to influence its market value, assuming that there exists perfect competition, and no corporate tax is present. This theory is based on impractical assumptions of the actual market conditions.	(Miller & Modigliani, 1961)
Life cycle theory	In the initial growth stages, firms offer lower dividend payouts due to a lack of capital market access, abundant resources, and strong market presence. However, towards its maturity, firms overcome such issues and reward good returns to the shareholders.	(DeAngelo et al., 2006; Fama & French, 2001; Mueller, 1972)
Agency theory	The dividend is considered an effective tool for reducing Type I agency issues (between the principal and its agent) and Type II agency problems (between the minority and majority shareholders). Therefore, firms facing agency issues are expected to pay higher dividends.	(Ding et al., 2021; Jensen, 1986; Jensen & Meckling, 1976; Rozeff, 1982)
Signalling theory	When a firm offers healthy returns to shareholders, it helps disseminate positive market signals to the shareholders. On the other hand, if the firm fails to maintain regular dividends or reduces the dividend amounts, it sends a negative signal about the firm’s financial state.	(Bhattacharya, 1979, 1980; John & Williams, 1985; Miller & Rock, 1985)
Transaction cost theory	Firms have to incur some additional costs while raising funds, especially from external sources. Therefore, firms may reduce their dividend payouts if they have limited access to the capital market and transaction costs become difficult to bear without doing so.	(Al-Najjar & Hussainey, 2009; Budagaga, 2020; Holder et al., 1998)
Residual theory	Generally, the firms prioritize meeting their short and long-term investments and liabilities when funds are generated in the business. Only after fulfilling these needs, are the residual amounts distributed as dividends among the shareholders. Based on this, it is expected that firms which generate greater revenues and have greater residual finances can afford to provide higher dividend amounts.	(Almeida et al., 2015; Budagaga, 2020)

(Authors’ compilation).

provides an overview of such theories in empirical studies.

The present study provides empirical evidence for two dividend aspects: dividend increase (Div_Inc) and decrease (Div_Dec). As explanatory variables, nine firm characteristics are considered: firm size (FSIZE), profitability (PROF), earnings volatility (EVOL), growth opportunities (GROW), leverage (LEV), free cash flow (FCF), cash holdings (CSH), promoters’ holdings (PMH), and firm life cycle (LFC).

3.1. FSIZE

The larger firms are usually mature and have larger cash holdings and fewer growth opportunities. Further, they have better accessibility in the external capital market and lesser transaction costs. Accordingly, the arguments of the life cycle theory and transaction costs theory suggest that larger firms have more flexibility to make changes in their dividend payout to suit their financing needs. These arguments suggest the following hypotheses:

H1a: 

Size positively affects firms’ propensity to increase their dividend payout (Div_Inc).

H1b: 

Size positively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.2. PROF

An increase in profitability improves firms’ liquidity position to support their dividend payout. Moreover, in line with the arguments of the signalling theory, profitable firms have fewer incentives to provide a positive signal to stakeholders by reducing the increases or decreases in dividend payments. Like size, profitability also increases firms’ capital market accessibility and reduces their cost of transactions, ultimately boosting their financial flexibility. All these arguments suggest the following hypotheses:

H2a: 

Profitability positively affects firms’ propensity to increase their dividend payout (Div_Inc).

H2b: 

Profitability positively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.3. EVOL

A volatility in earnings adversely affects firms’ dividend payout (Ghose et al., 2022). A firm usually chooses to refrain from frequent increases or decreases in dividend payments as it creates chances of disseminating adverse signals to outsiders. Firms with great earnings volatility are usually young, smaller in size, and in the early stages of their growth. Therefore, based on the arguments of signalling theory, life cycle theory, and transaction cost theory, the following hypotheses are framed:

H3a: 

Earnings volatility negatively affects firms’ propensity to increase their dividend payout (Div_Inc).

H3b: 

Earnings volatility negatively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.4. GROW

Growth opportunities adversely affect firms’ dividend payout as they need funds to meet their financing requirements. The adverse impact on the dividend payout is also consistent with the propositions of the residual theory of dividend policy. However, the propositions of signalling theory suggest the opposite viewpoint that higher dividends are attached to higher growth opportunities as firms intend to signal their future growth prospects and maintain favourable terms with the investors. Nevertheless, previous studies have mostly documented a negative association between growth and dividend payout (Benavides et al., 2016; Duygun et al., 2018; Jabbouri, 2016; Nyere & Wesson, 2019). Therefore, the following hypotheses are formulated:

H4a: 

Growth negatively affects firms’ propensity to increase their dividend payout (Div_Inc).

H4b: 

Growth positively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.5. LEV

The proponents of agency theory opine that financial leverage is an effective tool to contain agency problems (Jensen, 1986; Jensen & Meckling, 1976). The compulsory interest payment on debt minimizes the free cash flow available to managers (Ankudinov & Lebedev, 2016). Hence leverage can substitute dividends as a tool for mitigating free cash flow agency conflict (Ghose et al., 2022). Further, protective debt covenants can also restrict firms’ flexibility concerning their dividend payouts (Renneboog & Trojanowski, 2007). Moreover, the arguments of the signalling theory imply that increasing leverage should discourage firms from increasing or decreasing their dividend payouts as frequent changes will convey adverse signals to the lenders. Based on these points, hypotheses are formulated as below:

H5a: 

Leverage negatively affects firms’ propensity to increase their dividend payout (Div_Inc).

H5b: 

Leverage negatively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.6. FCF

The variable free cash flow is positively linked to firms’ liquidity position. Firms with a greater free cash flow are better equipped to distribute dividends. The arguments of agency theory also suggest that firms with a higher free cash flow should distribute more dividends to minimize the agency costs associated with a free cash flow (Jensen, 1986). Additionally, the propositions of signalling theory also indicate a similar impact on the dividend payout. Based on these, the following hypotheses are framed:

H6a: 

Free cash flow positively affects firms’ propensity to increase their dividend payout (Div_Inc).

H6b: 

Free cash flow negatively affects firms’ propensity to decrease their dividend payout (Div_Dec).

3.7. CSH

Greater cash holdings mean greater liquidity which suggests a favourable impact on firms’ dividend payout. The arguments of agency theory and the signalling theory also suggest the same. Additionally, firms with significant cash holdings are usually larger in size and attain the maturity stage. Hence, the arguments of life cycle theory and transaction cost theory also indicate a favourable relationship between cash holdings and firms’ dividend payments. Finally, an increase in cash holdings also offers financial flexibility to make changes in their dividend payout based on the requirements. Accordingly, the following hypotheses are developed:

H7a: 

Cash holdings positively affect firms’ propensity to increase their dividend payout (Div_Inc).

H7b: 

Cash holdings positively affect firms’ propensity to decrease their dividend payout (Div_Dec).

3.8. PMH

Promoter holdings have serious implications for agency conflicts as an increase in promoter holdings leads to the absorption of the controlling power in the hands of a few, thus creating an environment for the expropriation of minority shareholders through the tunnelling of resources. Dividend payment has the potential to minimize not only the owner–manager agency conflict but also the agency conflict between majority and minority shareholders. However, the concentration of ownership offers greater controlling power to promoters allowing flexibility in their dividend decisions, that is to alter (increase or decrease) the dividend payout at ease to suit the requirements of the firm. These theoretical arguments suggest the following hypotheses:

H8a: 

Promoter holdings positively affect firms’ propensity to increase their dividend payout (Div_Inc).

H8b: 

Promoter holdings positively affect firms’ propensity to decrease their dividend payout (Div_Dec).

3.9. LFC

The life cycle theory states that in the initial stage of their life cycle, firms pay lower dividends as they need more funds for growth opportunities. In contrast, firms in the later stages of their life cycle, characterized by fewer growth opportunities and stronger cash flows, tend to distribute higher dividends. Additionally, mature firms are usually large in size which offers them better accessibility to the external capital market. Thus, with better accessibility and available cash balances, such firms enjoy considerable flexibility over their dividend payout decisions. Denis and Osobov (2008) stated that firms’ ratio of retained earnings to common equity increases as they progress in their life cycle. The present study uses the same measure for the life cycle where higher values indicate greater maturity. Based on the theoretical arguments, the following hypotheses are framed:

H9a: 

Life cycle positively affects firms’ propensity to increase their dividend payout (Div_Inc).

H9b: 

Life cycle positively affects firms’ propensity to decrease their dividend payout (Div_Dec).

4. Methodological Framework

4.1. Sample and Study Period

The present empirical study considers a sample of 3739 listed firms from F.Y. 2001–2002 to F.Y. 2021–2022. Overall, unbalanced panel data of 53,112 firm-year observations were considered with at least three consecutive years of data. Moreover, in the final sample, financial and utility firms were excluded due to their fundamental differences and regulatory distinction from their counterparts (Miah et al., 2021). Further, firms holding non-positive values for total assets were also removed as the same were used as denominators to normalize a few datapoints. The required data were obtained from the CMIE Prowess database.

4.2. Empirical Model and Measurements of Variables

In this study, logistic regression analysis is utilized to examine the impact of various firm characteristics on dividend increases and decreases based on Model (1). In the model, DV is the dependent variable, α is the constant term, β is the coefficient of the explanatory variable, and X is the vector of firm characteristics, presenting the generic form of logistic regression. For controlling time-specific impacts, time dummies are also considered in the empirical model (Budagaga, 2020).

$$\mathrm{Pr}\left(DV=1|X\right)={\displaystyle \frac{1}{1+e^{-(\alpha +X\beta )}}}$$

(1)

Table 2. Variables’ description.

Variables	Abbreviations	Measurement of Dummy Variables
Dependent variables:
Increase in Dividend Payout	Div_Inc	Dummy variable equals 1 if the current year’s payout ratio is more than last year’s payout ratio, and 0 otherwise
Decrease in Dividend Payout	Div_Dec	Dummy variable equals 1 if the current year’s payout ratio is less than last year’s payout ratio, and 0 otherwise
Independent variables:
Size	FSIZE	Natural logarithm of total assets
Profitability	PROF	EBIT/total assets
Earnings Volatility	EVOL	Moving standard deviation of past 3 years’ profitability ratio
Growth	GROW	Market value of assets/book value of assets
Leverage	LEV	Total debt/total assets
Free Cash Flow	FCF	Free cash flow/total assets
Cash Holdings	CSH	Cash and cash equivalents/total assets
Promoter Holding	PMH	Proportion of equity held by promoters
Life Cycle	LFC	Retained earnings/common equity

(Authors’ compilation).

provides the details of all the considered variables. The dependent variables (Div_Inc and Div_Dec) are dummy variables taking the values of 0 and 1. On the other hand, nine crucial firm characteristics are considered to be explanatory variables in the study (Chakkravarthy et al., 2023; DeAngelo et al., 2006; Jensen, 1986; Nyere & Wesson, 2019). After including the dependent and explanatory variables, the regression models formulated are as follows:

$$\begin{gathered} \mathrm{l}\mathrm{n}\left({\displaystyle \frac{Div\_Inc}{1-Div\_Inc}}\right)={\beta }_0+{\beta }_{1}FSIZE+{\beta }_{2}PROF+{\beta }_{3}EVOL+{\beta }_{4}GROW+{\beta }_{5}LEV+{\beta }_{6}FCF+{\beta }_{7}CSH+{\beta }_{8}PMH \\ +{\beta }_{9}LFC+\epsilon \end{gathered}$$

(2)

$$\begin{gathered} \mathrm{l}\mathrm{n}\left({\displaystyle \frac{Div\_Dec}{1-Div\_Dec}}\right)={\beta }_0+{\beta }_{1}FSIZE+{\beta }_{2}PROF+{\beta }_{3}EVOL+{\beta }_{4}GROW+{\beta }_{5}LEV+{\beta }_{6}FCF+{\beta }_{7}CSH+{\beta }_{8}PMH \\ +{\beta }_{9}LFC+\epsilon \end{gathered}$$

(3)

5. Empirical Results

Table 3. Descriptive statistics.

Variables	Mean	Median	SD	Min	Max
FSIZE	6.697	6.621	2.296	0.916	12.369
PROF	0.059	0.063	0.126	−0.573	0.471
EVOL	0.041	0.021	0.057	0.001	0.288
GROW	1.569	1.053	1.686	0.237	12.190
LEV	0.352	0.247	0.535	0.000	3.982
FCF	0.036	0.034	0.177	−0.667	0.773
CSH	0.045	0.016	0.081	−0.006	0.500
PMH	0.515	0.535	0.192	0.009	0.899
LFC	8.724	2.174	18.604	−13.122	114.458

(Authors’ calculations).

reports the summary statistics of the variables. Among the table’s noteworthy findings are the following: During the research period, Indian enterprises’ average profitability was 5.90%; their market value was 1.569 times their book value, indicating an adequate growth rate; and 35.20% of their assets were made up of corporate debt, indicating a moderate degree of leverage. Indian companies have modest levels of free cash flow and cash holdings, accounting for 3.60% and 4.50% of total assets, respectively. In conclusion, the promoters own an average of 51.50% of the stock, demonstrating how common a concentrated ownership structure is in Indian businesses. There is enough variance in the dataset for additional analysis, as shown by the SD, min, and max values for each variable. Since the strongest correlation coefficient between company size and life cycle is 0.489, much below the threshold value of 0.80, the correlation matrix presented in

Table 4. Correlation matrix.

Variables	FSIZE	PROF	EVOL	GROW	LEV	FCF	CSH	PMH	LFSC
FSIZE	1
PROF	0.261 *	1
EVOL	−0.267 *	−0.171 *	1
GROW	−0.072 *	0.018 *	0.225 *	1
LEV	−0.135 *	−0.251 *	0.264 *	0.259 *	1
FCF	0.072 *	0.326 *	0.040 *	0.006	−0.009 **	1
CSH	−0.106 *	0.067 *	0.100 *	0.139 *	−0.034 *	−0.051 *	1
PMH	0.222 *	0.153 *	−0.078 *	0.011 **	−0.042 *	0.040 *	0.023 *	1
LFC	0.489 *	0.226 *	−0.143 *	0.070 *	−0.185 *	0.054 *	0.012 *	0.125 *	1

• (Authors’ calculations).
  Note: * = significant at 1% level, ** = significant at 5% level.

also shows the lack of multicollinearity (Gujarati & Porter, 2004).

To investigate the variations in firm characteristics according to various aspects of the firm’s dividend policy, the study then conducted univariate analysis (t-test).

Table 5. Univariate analysis (t-test).

Dividend Dimensions	Groups	FSIZE	PROF	EVOL	GROW	LEV	FCF	CSH	PMH	LFC
Dividend Increase	NO	6.413	0.047	0.044	1.572	0.378	0.034	0.043	0.502	6.417
	YES	8.233	0.116	0.029	1.632	0.231	0.050	0.052	0.568	19.658
	Mean Diff.	−1.820	−0.070	0.016	−0.060	0.147	−0.016	−0.008	−0.065	−13.241
	t-test	(−73.37) *	(−49.96) *	(23.66) *	(−2.89) *	(24.23) *	(−8.20) *	(−8.87) *	(−29.01) *	(−64.59) *
Dividend Decrease	NO	6.450	0.047	0.044	1.577	0.370	0.033	0.044	0.506	6.885
	YES	7.867	0.108	0.031	1.613	0.279	0.050	0.049	0.551	16.305
	Mean Diff.	−1.417	−0.061	0.014	−0.037	0.091	−0.016	−0.005	−0.045	−9.420
	t-test	(−59.13) *	(−46.27) *	(22.05) *	(−1.83) ***	(15.72) *	(−8.61) *	(−5.86) *	(−20.83) *	(−47.51) *

• (Authors’ calculations).
  Note: * = significant at 1% level, *** = significant at 10% level.

shows that the t-test’s test statistics remain statistically significant. For Div_Inc and Div_Dec, the findings are found to be similar. In comparison to their opposite counterparts, companies that increase or decrease their dividend payments (relative to the prior year) are found to be larger, more profitable, and mature in character. They also have more chances for growth, free cash flow, cash holdings, and promoter holdings. These findings largely support the predictions that were developed, and they show that companies with varying dividend policies have distinct underlying features. Since univariate analysis is merely indicative and a comprehensive interpretation cannot be derived, conclusions will be derived from the findings of multivariate analysis.

The results of the multivariate regression analysis are reported in

Table 6. Regression results.

Variables	Div_Inc	Div_Dec
Constant	−4.77 (−33.64) *	−4.75 (−36.64) *
FSIZE	0.34 (23.31) *	0.27 (21.37) *
PROF	4.69 (19.89) *	4.70 (21.94) *
EVOL	−3.98 (−8.03) *	−4.07 (−9.00) *
GROW	−0.04 (−3.06) *	−0.01 (−0.48)
LEV	−1.43 (−13.71) *	−0.25 (−3.43) *
FCF	−0.71 (−5.87) *	−0.28 (−2.57) **
CSH	0.23 (0.94)	0.07 (0.31)
PMH	1.52 (12.16) *	0.73 (6.42) *
LFC	0.01 (11.72) *	0.01 (6.35) *
Wald Chi2 (1)	2457.41 *	2160.88 *
Wald Chi2 (2)	462.08 *	575.36 *
LR Chi2	874.69 *	946.83 *
Rho	0.19	0.17

• (Authors’ calculations).
  Note: * = significant at 1% level, ** = significant at 5% level.

. To perform the post-estimation diagnostics, this study employed the Wald test (1) and Wald test (2) to assess the overall significance of the regression models and the joint significance of the time dummies, testing the null hypothesis of zero significance. The empirical results of the Wald test (1) and Wald test (2) in Table 6 validate the overall significance of the formulated models, respectively. Furthermore, the significant test statistics of the LR chi-squared test confirms the suitability of the random effects logistic regression over the pooled logistic regression. The random effects logistic regression accounts for unobserved heterogeneity across entities and accommodates the panel structure of the data—conditions under which the pooled model’s assumption of independence across observations would be violated.

Table 6 establishes that FSIZE has a significant positive impact on Div_Inc and Div-Dec. As per the arguments of the life cycle theory, larger firms usually stand at the maturity stage of the business life cycle, implying that significant amounts of cash holdings are available to them (DeAngelo et al., 2006). The transaction cost theory of dividends also supports that larger firms possess better access to external and internal funds due to their established market stand and reputation (Chang & Rhee, 1990). The positive impact on Div_Inc and Div_Dec indicates that their secured financial ability allows them to be more flexible with dividend decisions, i.e., to increase or decrease dividends as per their needs and requirements. The results support the formulated hypotheses $H_{1a}$ and $H_{1b}$.

Similarly, PROF also demonstrated a significant positive impact on Div_Inc and Div_Dec. These results confirm the arguments of the signalling theory and transaction cost theory. Profitable firms have an incentive to signal their healthy financial position to the stakeholders by paying persistent and large dividends. Secondly, firms with higher profitability are expected to generate greater cash flows, thus increasing their liquidity position to support dividend payments (Bahreini & Adaoglu, 2018; Jensen, 1986). Additionally, their profitable position helps them to avail better accessibility in the capital market, ultimately reducing their transaction costs. All these benefits ultimately offer greater flexibility to profitable firms in their dividend policy, allowing them to increase or decrease their dividend payments at will. Overall, the results confirm the study’s hypotheses $H_{2a}$ and $H_{2b}$.

EVOL adversely affects firms’ propensity to allow for increases and decreases in dividend payments. Usually, small firms are the ones that face the issues of volatile earnings capacity. They are mostly perceived as early-stage firms from the business perspective of the life cycle theory and therefore, their transaction costs are expected to be higher. As a result, firms with a high earning volatility attempt to avoid increasing or decreasing their dividends, expecting that it will send positive signals among the investors and build a good market reputation (DeAngelo et al., 2006; Michaely & Moin, 2022). Thus, the empirical results confirm hypotheses $H_{3a}$ and $H_{3b}$.

As per the results, GROW demonstrated a significantly negative impact on the propensity for Div_Inc, while it showed a non-significant impact on Div_Dec. This negative influence can be elucidated with reference to the residual theory and life cycle theory. Firms in their early growth stages demand massive financial resources to accomplish further growth and market expansion (Agarwal & Chakraverty, 2023). A growing firm must invest a big chunk of its revenues in new growth investments which lowers the level of residual income. Over time, when their focus increases on growth projects, more emphasis is given to retaining the profits with the firm and sharing less with the shareholders to make the necessary funds available (Al-Kayed, 2017; Sharma, 2021). Due to such events, growing firms oppose Div_Inc. Here, the empirical outcomes support only $H_{4a}$ but reject $H_{4b}$.

A significantly negative impact on Div_Inc and Div_Dec is observed from LEV. The signalling theory argues that if firms choose to offer frequently fluctuating dividend payments to the existing shareholders, it discharges poor signals regarding the firm’s financial position. In that case, creditors may not be willing to offer additional funds to the firms due to the perceived high risks attached (Ghose et al., 2022). Therefore, firm managers are reluctant to decrease or increase their dividend payouts due to the possible negative signals. Thus, higher LEV discourages Div_Inc and Div_Dec for firms, confirming hypotheses $H_{5a}{\mathrm{a}\mathrm{n}\mathrm{d}H}_{5b}$.

Next, FCF exerts a significantly adverse influence on Div_Inc and Div_Dec. These results of FCF oppose the agency theory arguments (Jensen, 1986) and negate the usual expectation of greater dividend distribution with increased FCF. However, the negative impact of FCF on Div_Dec partially supports the argument that greater liquidity reduces firms’ propensity to decrease their dividends. Nevertheless, more research along similar lines is required to provide a concrete conclusion regarding the effects of FCF on these aspects of dividend policy. Overall, the results related to FCF confirm only hypothesis $H_{6b}$, whereas $H_{6a}$ is rejected.

In the case of CSH, a non-significant impact on Div_Inc and Div_Dec is reported by the empirical outcomes. Firms with higher cash holdings are usually categorized as larger and more mature firms. Based on the arguments of the life cycle theory and transaction cost theory, such firms are expected to enjoy better capital market accessibility which ultimately allows them to exploit considerable flexibility in their dividend policy. However, the rejection of $H_{7a}$ and $H_{7b}$ hints at the need for more similar studies in the Indian context.

PMH documented a favourable influence on firms’ decisions regarding Div_Inc and Div_Dec. An increase in the concentration of ownership through higher promoters’ holdings provides more control and power to the controlling shareholders to make decisions related to dividend payouts. Such flexibility in decision making allows firms with greater promoter holdings to increase or decrease their dividend payout as per their requirements. Based on these arguments, the positive coefficients of PMH in the case of Div_Inc and Div_Dec are justified. Therefore, $H_{8a}\mathrm{a}\mathrm{n}\mathrm{d}{H}_{8b}$ are confirmed.

Lastly, LCF showed a significantly positive effect on Div_Inc and Div_Dec. The results can be explained by reference to the arguments of the life cycle theory. When firms grow and enter the maturity stage of the business life cycle, they are expected to become financially protected and settled, lowering their degree of reliance on the shareholders’ funds. With their established reputation in the market, they already have the privilege of accessibility to internal and external funds at lower costs. Therefore, such firms become less concerned about disseminating positive market signals (Budiarso, 2018; DeAngelo et al., 2006). Hence, firms in the later stage of their life cycle exhibit an increased propensity to increase or decrease their dividend payments as per the demands of their opportunities. Overall, the results support hypotheses $H_{9a}\mathrm{a}\mathrm{n}\mathrm{d}{H}_{9b}$.

6. Robustness Check

To verify the reliability of the presented empirical findings in Table 6, the study performed an additional logistic regression analysis. For each of the two dividend dimensions examined in the study, different indicators were used as shown in

Table 7. Description of variables for robustness check.

Variables	Measurement of Dependent Variables
Dividend Increase	Dummy variable equals 1 if the current year’s payout ratio is increased by at least 2% from last year’s payout ratio, and 0 otherwise
Dividend Decrease	Dummy variable equals 1 if the current year’s payout ratio is decreased at least by 2% from last year’s payout ratio, and 0 otherwise

(Authors’ compilation).

. The empirical results are presented in

Table 8. Regression results for additional analysis.

Variables	Div_Inc	Div_Dec
Constant	−4.37 (−31.66) *	−4.20 (−33.86) *
FSIZE	0.29 (20.78) *	0.21 (17.74) *
PROF	3.22 (14.08) *	3.09 (15.24) *
EVOL	−1.85 (−3.91) *	−1.71 (−4.06) *
GROW	−0.04 (−2.57) *	−0.01 (−0.63)
LEV	−1.38 (−13.24) *	−0.25 (−3.58) *
FCF	−0.53 (−4.26) *	−0.12 (−1.04)
CSH	−0.20 (−0.80)	−0.28 (−1.19)
PMH	1.39 (11.20) *	0.60 (5.46) *
LFC	0.01 (8.76) *	0.01 (4.20) *
Wald Chi2 (1)	1785.54 *	1378.52 *
Wald Chi2 (2)	371.26 *	416.14 *
LR Chi2	684.83 *	574.34 *
Rho	0.17	0.13

• (Authors’ calculations).
  Note: * = significant at 1% level.

. The additional results support the earlier findings, with only one exception. In Table 8, the significant impact of FCF on Div_Dec becomes non-significant. This is contrary to the previously reported negatively significant effect.

Next, an additional analysis was conducted with a distinction made between business group affiliated firms (BGFs) and standalone firms (SAFs), with the original variable indicators in Table 2. The results of the logistic regression are reported in

Table 9. Regression results for additional analysis (BGFs vs. SAFs).

Variables	Div_Inc		Div_Dec
	BGFs	SAFs	BGFs	SAFs
Constant	−2.97 (−13.44) *	−6.12 (−29.32) *	−3.36 (−15.70) *	−5.73 (−31.25) *
FSIZE	0.22 (11.08) *	0.47 (19.70) *	0.16 (8.94) *	0.39 (18.91) *
PROF	3.61 (10.27) *	5.46 (17.14) *	5.40 (15.65) *	4.13 (15.21) *
EVOL	−5.22 (−6.94) *	−3.24 (−4.89) *	−7.65 (−9.96) *	−1.90 (−3.41) *
GROW	−0.08 (−3.71) *	−0.01 (−0.5)	−0.05 (−2.67) *	0.03 (1.67) ***
LEV	−1.43 (−9.69) *	−1.64 (−10.99) *	−0.50 (−4.10) *	−0.16 (−1.81) ***
FCF	−0.73 (−3.99) *	−0.65 (−4.04) *	−0.34 (−1.92) **	−0.25 (−1.76) ***
CSH	−0.10 (−0.26)	0.55 (1.64)	−0.14 (−0.39)	0.26 (0.82)
PMH	0.69 (3.80) *	1.96 (11.38) *	0.20 (1.18)	0.94 (6.21) *
LFC	0.01 (10.22) *	0.01 (5.70) *	0.01 (6.21) *	0.001 (2.65) **
Wald Chi2 (1)	858.92 *	1528.56 *	833.36 *	1253.83 *
Wald Chi2 (2)	181.77 *	321.22 *	234.78 *	360.05 *
LR Chi2	239.12 *	568.67 *	238.61 *	668.30 *
Rho	0.13	0.22	0.12	0.2

• (Authors’ calculations).
  Note: * = significant at 1% level, ** = significant at 5% level, *** = significant at 10% level.

. Again, most of the results are found to be robust and similar when compared to Table 6, with few exceptions. Firstly, the effect of GROW on Div_Inc becomes non-significant in the case of SAF. Secondly, the impact of GROW on Div_Dec is found to be negatively and positively significant for BGFs and SAFs contrary to the previous results. Thirdly, PMH showed a non-significant influence on Div_Dec with regard to BGFs.

Apart from the above-highlighted cases, all the results are reported to be robust and reliable across the separate empirical investigations. More studies along similar lines will provide a clearer decision on the results which have not conformed to the original results in Table 6.

Further, an additional regression analysis was conducted considering industry-fixed effects dummies in order to control the effects of different industries and verify if the results still remain robust. The empirical results in

Table 10. Regression results with industry-fixed effects dummies.

Variables	Div_Inc	Div_Dec	Div_Inc		Div_Dec
			BGF	SAF	BGF	SAF
Constant	−4.25 (−17.27) *	−4.61 (−19.93) *	−2.23 (−5.83) *	−5.79 (−17.37) *	−3.32 (−8.65) *	−5.70 (−18.72) *
FSIZE	0.34 (22.42) *	0.28 (21.18) *	0.22 (10.98) *	0.47 (19.06) *	0.18 (9.71) *	0.40 (18.64) *
PROF	4.40 (18.65) *	4.55 (21.13) *	3.33 (9.45) *	5.15 (16.19) *	5.26 (15.11) *	4.00 (14.68) *
EVOL	−3.86 (−7.78) *	−3.83 (−8.47) *	−5.31 (−7.01) *	−3.07 (−4.63) *	−7.42 (−9.62) *	−1.70 (−3.06) *
GROW	−0.04 (−2.60) *	0.00 (−0.24)	−0.07 (−3.27) *	0.00 (−0.21)	−0.06 (−2.78) *	0.03 (1.86) ***
LEV	−1.59 (−14.62) *	−0.29 (−3.88) *	−1.57 (−10.38) *	−1.79 (−11.53) *	−0.62 (−4.83) *	−0.17 (−1.87) ***
FCF	−0.70 (−5.82) *	−0.29 (−2.64) *	−0.73 (−4.00) *	−0.64 (−3.97) *	−0.35 (−2.02) **	−0.26 (−1.81) ***
CSH	0.34 (1.37)	0.17 (0.73)	0.06 (0.16)	0.61 (1.82) ***	0.07 (0.20)	0.29 (0.92)
PMH	1.39 (11.09) *	0.68 (5.91) *	0.61 (3.46) *	1.83 (10.49) *	0.23 (1.31)	0.89 (5.80) *
LFC	0.01 (10.64) *	0.01 (5.25) *	0.01 (9.84) *	0.01 (5.13) *	0.0068 (5.57) *	0.00 (1.97) **
Wald Chi2 (1)	2599.74 *	2306.57 *	997.48 *	1609.08 *	955.43 *	1339.43 *
Wald Chi2 (2)	451.20 *	567.08 *	183.42 *	314.45 *	239.90 *	355.07 *
LR Chi2	721.20 *	810.84 *	140.68 *	463.71 *	153.13 *	589.37 *
Rho	0.17	0.16	0.09	0.19	0.09	0.19

• (Authors’ calculations).
  Note: * = significant at 1% level, ** = significant at 5% level, *** = significant at 10% level.

confirm that the results are in line with the original empirical outcomes reported in the preceding sections. Similar analyses are reported in Table 10 with respect to the BGF and SAF categorization of the firms, and the results are confirmed to be consistent herewith.

Lastly, there is a possibility for simultaneity bias or endogeneity existing between the dependent and explanatory variables in the formulated regression models that are conducted in the present study. To overcome such issues, another regression analysis was conducted with industry-fixed effects dummies and lag values of the explanatory variables. The results are reported in

Table 11. Regression results with industry-fixed effects dummies and lag value of explanatory variables.

Variables	Div_Inc	Div_Dec	Div_Inc (BGF)	Div_Inc (SAF)	Div_Dec (BGF)	Div_Dec (SAF)
Constant	−4.19 (−16.59) *	−5.28 (−19.71) *	−2.09 (−5.31) *	−5.70 (−16.44) *	−3.56 (−8.47) *	−6.79 (−18.54) *
L.FSIZE	0.29 (18.69) *	0.34 (21.03) *	0.20 (9.38) *	0.39 (15.35) *	0.22 (10.34) *	0.48 (17.90) *
L.PROF	8.94 (32.87) *	4.48 (17.12) *	8.92 (21.51) *	8.77 (24.31) *	2.96 (7.61) *	5.48 (15.44) *
L.EVOL	−5.23 (−9.29) *	−9.31 (−15.47) *	−6.82 (−7.88) *	−4.20 (−5.65) *	−10.30 (−11.31) *	−8.88 (−10.91) *
L.GROW	−0.08 (−4.92) *	−0.03 (−1.66) ***	−0.16 (−6.70) *	−0.01 (−0.51)	−0.03 (−1.38)	−0.01 (−0.37)
L.LEV	−1.36 (−11.93) *	−1.05 (−9.57) *	−1.47 (−9.14) *	−1.36 (−8.61) *	−1.31 (−8.41) *	−1.02 (−6.62) *
L.FCF	−0.76 (−5.97) *	−0.63 (−4.97) *	−0.79 (−4.05) *	−0.71 (−4.19) *	−0.68 (−3.55) *	−0.55 (−3.28) *
L.CSH	0.25 (0.97)	0.19 (0.72)	0.11 (0.29)	0.44 (1.25)	−0.51 (−1.33)	0.82 (2.34) **
L.PMH	1.21 (9.13) *	1.32 (9.87) *	0.46 (2.47) **	1.64 (8.93) *	0.47 (2.46) **	1.77 (9.59) *
L.LFC	0.01 (11.65) *	0.00 (1.84) ***	0.01 (9.83) *	0.01 (6.36) *	0.01 (3.83) *	0.00 (−1.22)
Wald Chi2 (1)	2847.71 *	2201.59 *	1177.20 *	1666.84 *	837.46 *	1379.27 *
Wald Chi2 (2)	321.01 *	718.19 *	122.61 *	236.75 *	333.84 *	430.05 *
LR Chi2	603.60 *	841.39 *	111.39 *	395.99 *	174.35 *	584.78 *
Rho	0.16	0.19	0.09	0.19	0.11	0.22

• (Authors’ calculations).
  Note: * = significant at 1% level, ** = significant at 5% level, *** = significant at 10% level.

. The results validate and conform to the original results, confirming that the endogeneity bias does not persist in the existing models. Similar robustness is documented with respect to the results for the BGFs and SAFs.

7. Conclusions

The present empirical study investigates the impact of several firm characteristics on corporate dividend decisions in the Indian setting. Previous research on the factors influencing the dividend policy mostly focused on the level of dividend payout and the propensity of businesses to pay dividends, ignoring the other elements. The current study took into account two important aspects of dividend policies, i.e., firms’ propensity to increase and decrease their dividend payouts. Given the diversity of shareholder expectations, a firm’s management must pay close attention to all of these dividend payout-related factors. The study consisted of a dataset of 3739 listed Indian companies from 2001–2002 to 2019–2022 and used random effect logistic regression for the empirical analysis. The empirical results reveal that firms’ size, profitability, promoter holdings, cash holdings, and life cycle favourably affect firms’ propensity to both increase and decrease their dividend payouts. On the contrary, the results are exactly the opposite in the case of earnings volatility, leverage, and free cash flow, i.e., these characteristics adversely impact firms’ likelihood to both increase and decrease their dividend payouts. The observed results affirm that large and mature firms and firms with more liquidity and ownership concentration have substantial financial flexibility to increase and decrease their annual dividend payouts. Additionally, an increase in earnings volatility and leverage possibly curtails firms’ financial flexibility in frequently changing the dividend amounts. Lastly, the relevance of various dividend theories is also discussed in the Indian context.

This study offers valuable insights for managers, investors, and policymakers involved in dividend-related decision making. First, the findings suggest that managers should carefully consider the firm-specific characteristics—such as profitability, leverage, and ownership structure—when formulating dividend policies. Being mindful of the traits that are associated with dividend increases or decreases can help avoid unnecessary volatility in payouts, which may otherwise harm the firm’s market reputation. Second, the study’s results hold significant implications for investors, especially institutional investors whose expectations and investment mandates may differ based on their type (e.g., mutual funds, pension funds, foreign institutions). By understanding the underlying drivers of dividend changes, investors can better interpret payout decisions as signals of a firm’s quality or risk. For example, the life cycle theory and transaction cost theory suggest that large, mature, and profitable firms are more likely to enjoy financial flexibility to make changes in their dividend payouts, while the agency theory implies that dividend payouts may serve as a mechanism to mitigate the agency conflicts in firms with concentrated ownership or weaker governance. Recognizing these patterns allows investors to align their portfolio strategies with their risk tolerance and investment goals, particularly in the face of the regulatory and economic volatility common in emerging markets.

Third, from a policy and regulatory perspective, particularly in the Indian context, the study highlights the need for stronger transparency and disclosure norms around dividend decisions. Given that the dividend behavior can convey information about firms’ prospects and governance quality (as posited by signalling theory), enhancing the reporting standards may strengthen investor protection and market efficiency. Policymakers should also consider how institutional frameworks—such as taxation policies, minority shareholder rights, and corporate governance codes—shape the dividend practices and influence the capital allocation across firms. Finally, by distinctly analyzing the determinants of both dividend increases and decreases in the Indian context, this study contributes novel evidence to the dividend literature in emerging markets. The unique institutional features of India—such as evolving corporate governance norms, increasing financial market integration, and diverse ownership structures—create a rich environment to examine how traditional dividend theories play out. This contextual grounding not only enhances the relevance of the findings but also supports broader efforts toward developing a more robust, transparent, and investor-friendly capital market in India, ultimately aiding the country’s economic development.

The present study inherits certain limitations which future studies can overcome. Firstly, the impact of the firm characteristics may show different results when compared to other developing nations. As the empirical evidence in this study is only in the Indian context, the results should not be generalized across all countries. Secondly, the present study only attempts to identify the firm characteristics that may affect the decisions either to increase or decrease dividend payouts. However, the magnitude of change is not addressed. Future studies can be conducted to investigate this novel dimension of firms’ dividend policy decisions. Thirdly, the study only focuses on dividend decisions related to the increase and decrease in payouts, whereas other aspects such as dividend stability, persistence, omissions, etc. are not included in the empirical investigations. Focusing on these aspects through future exploration can potentially add further significance to the existing literature. Fourthly, there are many other relevant firm characteristics such as CEO duality, board diversity, board impendence, etc., whose possible influence on the dividend policy is not explored in the current study. Their exploration will add equal significance in making dividend- and investment-related decisions for the stakeholders. Fifthly, the present study does not consider the specific industry and macroeconomic variables in the empirical model to investigate their effect on firms’ dividend offerings. Their inclusion will undoubtedly provide more insights into the prevailing literature.