The aim of this paper is to document the effect of advertising expenditures on the dividend policies adopted by non-financial firms from India firms during the period between 2000 and 2019. Our results show that advertising expenditures have a significantly positive impact on dividend payout ratios. Our results are robust across various proxies of advertising expenditures and dividend policies. These results are consistent with the argument that advertising expenditures improve the information environment of firms by increasing their visibility among stock market participants. Superior information environment makes expropriation technology expensive and leads to greater sharing of corporate profits. Furthermore, our findings also show that dividend payouts are more valuable for firms that incur low advertising expenditures. It indicates that dividend payouts improve firm value more when information environment is opaque.
Research Article
Advertising expenditures and dividend policy: Evidence from an emerging market
https://doi.org/10.21203/rs.3.rs-2248179/v1
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Marketing
Dividend Policy
Value
Agency Problems
Emerging Markets
The determinants of corporate dividend policies have attracted significant interest in prior literature (Miller and Rock, 1985; John and Williams, 1985; La Porta et al., 2000; Chen et al., 2017; Farooq and Ahmed, 2019; Ye et al., 2019; Farooq and Aktaruzzaman, 2020). Most of this literature focuses on understanding the impact of firm-specific characteristics and country-specific characteristics on the dividend policies adopted by firms. Farooq and Ahmed (2019), for instance, highlight the effect of country-specific characteristics by documenting that political uncertainty is a significant determinant of corporate dividend policies. They report significantly higher dividend payout ratios during the years characterized by high political uncertainty. In contrast, Ye et al. (2019) document the importance of firm-specific characteristics by reporting significantly higher dividend payout ratios for firms with greater gender diversity in their boards. This strand of literature argues that firm-specific characteristics and country-specific characteristics determine the information asymmetries embedded in the working of firms and firms set their dividend policies in response to these information asymmetries. La Port et al. (2000) hypothesize two competing explanations for why firms set their dividend policies in response to information asymmetries. On one extreme are the arguments in which they consider dividends as an instrument that can be used by shareholders to monitor managers. They argue that firms operating in an environment with high information asymmetries make high dividend payments to ensure that minority shareholders are treated fairly. These firms build their reputation by paying high dividends. By distributing high amount of cash as dividends, firms ensure that managers do not have enough cash to expropriate (Sawicki, 2009; Mitton, 2004). On the other extreme are the arguments in which La Port et al. (2000) maintain that firms operating in an environment with low information asymmetries make high dividend payments because better information environment curtails the ability of managers to expropriate corporate resources. In other words, when information asymmetries are low, it is easier to spot unscrupulous behavior of managers. The managers fear getting exposed and refrain from expropriating corporate resources. Prior literature, such as Li and Zhao (2008) and Lin et al. (2017), argue that when corporate insiders cannot expropriate, they tend to distribute high proportion of earnings as dividends.
Both of the hypotheses floated by La Port et al. (2000) highlight significant role of information asymmetries in determining the dividend policies adopted by firms. However, which hypothesis will hold in any given situation is an empirical question. In this paper, we focus on another factor – advertising – that can significantly affect the dividend policies adopted by firms. We hypothesize that adverting exerts its impact on dividend policies by improving the information environment of a firm. The impact of advertising on the information environment is well established. Joshi and Hanssens (2009) consider advertising to be an important channel via which information about the products and services offered by the firm is communicated to individuals. Chauvin and Hirschey (1993) highlight the importance of information obtained through advertising by documenting that investors use this information to form expectations about the size and the variability of future cash flows. Prior literature notes that the information conveyed via advertising can reduce information asymmetries between insiders and outsiders. Grullon et al. (2004), for example, document that stocks of firms that advertise more have higher liquidity (as is shown by smaller bid-ask spreads) than stocks of other firms.[1] In this paper, we argue that superior information environment associated with firms that advertise heavily should affect their dividend policies. Our arguments take their motivation from prior literature that documents significant relationship between information environment of a firm and its dividend policy. Li and Zhao (2008), for example, document high dividend payments for firms that have more transparent information environment. Farooq and Aktaruzzaman (2020) also report similar findings by documenting high dividend payments for firms that operate in more transparent information environment. The argument underlying these findings is that improvement in information environment reduces the ability of managers to expropriate corporate resources. When managers cannot expropriate, they are more likely to distribute profits to shareholders.
Another reason that may be cited for the positive impact of adverting activity on the dividend payouts is based on the assumption that adverting leads to better performance of firms (Rahman et al., 2020; Farooq and Pashayev, 2020). We argue that advertising activities increase the awareness of consumers regarding the products and services offered by the firm. Equipped with more awareness, the consumers are more likely to purchase the goods and services of a firm, thereby leading to a positive impact on the performance of firms (Mizik and Jacobson, 2003; Pauwels et al., 2004; Joshi and Hanssens, 2009; Luo and de Jong, 2012; Farooq and Pashayev, 2020). Another reason underlying the positive impact of advertising on firm performance is the creation of brand image and customer equity. Prior literature associates both of these factors with superior performance of firms (Johansson et al., 2012; Vomberg et al., 2015; Wang et al., 2015). An obvious outcome of better performance is the high dividend payments. The impact of performance/profitability on dividend payments is understandable in a way that dividends are fundamentally determined by earnings. Higher earnings, usually, lead to higher dividends (Skinner, 2008; Healy and Palepu, 1988). Damodaran (2014) also notes that dividends tend to increase when a fundamental long-term increase in earnings takes place.
Consistent with above arguments, this paper documents significantly positive impact of advertising expenditures on dividend payout ratios in India during the period between 2000 and 2019.[2] Our findings also hold in various sub-samples and when we use alternate proxies of dividend policy and adverting expenditures. Interestingly, this paper also shows that the value of dividend policy (as indicated by the impact of dividend policy on firm performance) is higher for firms that spend less on advertising activities. This result is consistent with prior literature that argues that dividend policy is more important for firms that have poor information environment (La Port et al., 2000). Given that firms with relatively low advertising expenditures are more likely to have poor information environment, the dividend policy becomes an important mechanism via which to resolve information asymmetries between insiders and outsiders.
This paper contributes to prior literature in a number of ways. First, it extends the literature on marketing and advertising by bringing in the shareholder/investor focus. The paper uses an indicator from the marketing domain and shows how significant it is for stock market investors in an emerging market. It is in contrast to the traditional literature on marketing and advertising that has been primarily driven by the perspectives of customers and concentrated on the marketing-sales relationship. Therefore, this paper extends the literature that intersects the domains of marketing and finance (Joshi and Hanssens, 2009; Joshi and Hanssens, 2010; Luo and de Jong, 2012; Farooq and Pashayev, 2020). We would also like to stress that, contrary to the usual literature that intersects marketing and finance, we are not primarily concerned with the impact of advertising on firm value. We are more concerned about its impact on dividend policy – an important corporate finance decision. Second, we highlight the role of advertising activities on the information environment of a firm in an emerging market setting. Given that information environment is a major concern for investors in emerging markets, our findings provide an indication of the role played by advertising in resolving some of the concerns regarding information environment. We believe that to the best of our knowledge, this paper is an initial attempt to document the relationship between advertising and dividend policy.
The remainder of paper is structured as follows: Section 2 builds the hypothesis. Section 3 presents the methodology and summarizes the data. Section 4 documents the main results. Section 5 and Section 6 presents sensitivity tests and additional tests, respectively. The paper ends with Section 7 where we present our conclusions.
[1] Smaller bid-ask spreads and higher liquidity are characteristics of lower information asymmetries between insiders and outsiders.
[2] We focus on India because it is one of the fastest growing emerging markets. With a constantly rising economic growth rate, the country has attracted significant interest from international investors in the recent years (Garg and Dua, 2014). However, it still suffers from weaknesses in the governance environment. According to the World Economic Forum, the ranking of India on the efficacy of corporate boards decreased to 97 in 2017 from 35 in 2007. Similarly, the ranking of India on the protection of minority shareholders decreased to 42 in 2017 from 19 in 2007. Weak governance environment can diminish the quality of information disclosure and increase the information asymmetries and agency problems (Saha and Kabra, 2020). Under such ambiguous environment, it becomes worthwhile to explore the factors that can predict important corporate indicators, such as the dividend policy.
This paper hypothesizes that advertising intensity is a significant determinant of dividend policies adopted by firms in emerging markets. Our arguments are based on the assumption that advertising intensity affects dividend policy by improving not only the performance/profitability of firms, but also their information environment. Both of these factors are supposed to positively affect the dividend policies adopted by firms (La Port et al., 2000; Li and Zhao, 2008; Skinner, 2008; Farooq and Aktaruzzaman, 2020).
2.1 Adverting and its effect on firm’s performance
This paper argues that one of the major aims of undertaking the advertising activity is the improvement of firm’s performance (Farooq and Pashayev, 2020; Luo and de Jong, 2012; Joshi and Hanssens, 2009; Pauwels et al., 2004; Mizik and Jacobson, 2003; Kotabe et al., 2002). A firm that spends more resources on advertising can increase its sales by encouraging the existing customers to buy more of its products and by inducing the customers of competing firms to switch to its products. These firms can also create the competitive advantage vis-à-vis other firms by influencing the choices of customers, employees, and investors (Bick, 2009). In the process of increasing sales, a firm can also build its brand (Aaker, 1996). Wang and Sengupta (2016) argue that brand building is based on the premise that strong brands generate long-term competitive advantages for firms. Because of the strong brands, it is possible for firms to charge premium prices. It, therefore, increases and maintains the profitability of firms. Steenkamp (2014) argues that the products associated with stronger brands are more likely to sustain a price premium as compared to the products associated with weaker brands. It is for this reason that the strength of a brand is viewed as one of the most significant strategic assets (Vomberg et al., 2015).[3] Prior literature notes that brand creates competitive advantages for a firm in a number of ways (Johansson et al., 2012; Vomberg et al., 2015; Wang et al., 2015). For instance, brands may encourage customers’ repeat purchase by reducing their search cost. It may also reduce their inclination for comparison shopping. Moreover, brands may reduce the competitive pressure by making customers less susceptible to competitors’ marketing activities. Furthermore, strong brands can create long-term sustainable advantage for firms by cultivating the customer equity (Rust et al., 2005). The greater is the customer equity, the higher is the subjective assessment of the brand by customers. Johansson et al. (2012) note that customer equity positively affects customer’s satisfaction.
An obvious outcome of the above arguments is the high correlation between advertising and firm value (Yeung and Ramasamy, 2008; Kirk et al., 2013; Wang et al., 2015). Hirschey (1985), for example, reports a significantly positive relationship between the market value of a firm and its advertising expenditures. Helsen et al. (1993) also document greater likelihood of success for firms that firms undertake higher advertising activities. In another related study, Graham and Frankenberge (2000) show that changes in advertising expenditures are positively associated with changes in market values. Singh et al. (2005) confirm the above findings by reporting that firms with higher advertising expenditures experience better performance. The essence of above studies is that firms with higher advertising activities generate more profits than firms with a lower advertising activities. Kotabe et al. (2002) note that firms with extensive advertising activities can enhance their performance by targeting the customer needs and by having better bargaining power with both distributors and consumers.
Another argument that can be cited for the positive impact of adverting of firm performance is based on the assumption that advertising activities create intangible market-based assets (Srivastava et al., 1998). The intangible market-based assets consist of (among other things) brand, customer relationships, channel relationships, and partner relationships. These assets are valuable and can improve the performance/value of the firm. Sougiannis (1994) argues that investors put heavy emphasis on the valuation of intangible assets, including advertising expenditures. Kim (2008) shows that such intangible assets increase the performance of firms. Furthermore, the intangible market-based assets can improve the performance of the firms by insulating them from stock market volatility (McAlister et al., 2007). Srivastava et al. (1998) document that intangible assets, such as those created due to advertising, improve firm performance by “accelerating and enhancing cash flows, and lowering the volatility and vulnerability”.
2.2 Adverting and its effect on firm’s information environment
The real markets are characterized by imperfect information. The availability of less than perfect information leads to the deterioration of informational efficiency of these markets. Provision of information is, therefore, a very valuable and desirable trait in these markets. One of the mechanisms that can assist firms in disclosing and disseminating their information is advertising. Joshi and Hanssens (2009) maintain that advertising is important because it creates the demand not only for the products and services offered by the firms, but also for the information about these products and services. We argue that, by providing information via advertising, firms can generate interest among individuals, thereby increasing the demand for additional information about the firm.[4] Chauvin and Hirschey (1993) document that investors can use the information on advertising activities to form expectations about future cash flows. Our arguments are also supported by the actual events, such as discontinuation of information on advertising expenses by the Apple Inc. in 2016. Financial analysts and investors raised complaints about this action because they considered the information contained in the advertising expenses to be a useful. The informational value of advertising can also be judged from the stock market liquidity generated by firms that advertise heavily. Grullon et al. (2004) document that the stocks of firms that advertise are more liquid and have smaller bid-ask spreads than the stocks of other firms that do not advertise much. The argument underlying the informational role of advertising is based on the assumption that it can be used as a signaling mechanism to reduce the information gap between two entities. More specifically, firms can use advertising activities to send signals to potential investors about its growth and value. Advertising may also indicate that the firm is less risky. Allen and Faulhaber (1989) argue that firms can use mechanisms, such as advertising activities, to signal that their firm is better than other firms.[5]
2.3 Advertising and its possible impact on dividend policy
Our arguments suggest that adverting activity not only affects the performance of firms, but also affects their information environment. Plentiful of prior literature relates both of these factors with higher dividend payments (Skinner, 2008; Farooq and Aktaruzzaman, 2020). The impact of performance/profitability on dividend payments is obvious. The firms with high profitability have higher capacity to pay dividends. In fact, dividends are fundamentally determined by earnings (Skinner, 2008). The firms that generate higher earnings on a per share basis are more likely to pay higher dividends. Lee and Ryan (2002) show that current earnings are significant determinant of dividends. Furthermore, while highlighting the relationship between earnings and dividends, Damodaran (2014) notes that dividends follow earnings. He argues that managers will increase dividends only if they are sure that a permanent shift in earnings has occurred. In other words, changes in dividends depend on the level of earnings generated by firms. In another related study, Healy and Palepu (1988) show that firms initiating dividends also have positive earnings. They also show that dividend omission is preceded by two years of earnings declines that continue during the year of the omission. Lipson et al. (1998) also report similar findings by showing that firms that initiate dividends have greater earnings increases than those firms that do not initiate dividends.
The relationship between information environment of a firm and dividend policy has also generated considerable interest. Prior literature argues that better information environment curtails the ability of managers to expropriate corporate resources (La Port et al., 2000; Li and Zhao, 2008; Lin et al., 2017; Apergis and Eleftheriou, 2017). The underlying argument in this strand of literature is that better information environment makes it difficult for managers to expropriate corporate resources. In the presence of more transparent information environment, it is easier for shareholders to notice the deceitful behavior of managers. Consequently, managers are reluctant to misuse corporate resources. An outcome of this disciplining role of information environment is that managers are more likely to share higher proportion of earnings with shareholders. These arguments are supported by significant number of prior empirical studies that document low dividend payments for firms with high information asymmetries. Li and Zhao (2008), for example, find that the extent of information asymmetries – analyst earnings forecast errors and the dispersion in their forecasts – negatively affect dividend payouts. They document that firms with higher information asymmetries are less likely to pay, initiate, or increase dividends. They also show that such firms pay small dividends whenever they have to pay relative to firms with lower agency problems. Leary and Michaely (2011) also come to the same conclusion by showing that firms with higher levels of asymmetric information distribute lower dividends. Brockman and Unlu (2011) use the international sample and show that firms from countries where disclosure environments are not transparent (higher information asymmetries) pay lower dividends. More recently, Farooq and Aktaruzzaman (2020) show that firms with higher information asymmetries pay lower dividends. Above arguments lead us to hypothesize the following.[6]
|
Hypothesis 1: |
There is a positive relationship between advertising expenditures and dividend payments. |
[3] Once the brand is established, it becomes relatively inimitable and non-substitutable. This characteristic makes it very desirable for the firms to have a strong brand (Barney et al., 2001).
[4] It is possible that, due to search costs, it may be hard for some of the market participants to track the activities of firms. For such market participants, advertising can be helpful because it may disclose and disseminate some of the valuable information.
[5] The ability of advertising to create intangible market-based assets may also increase the demand for information, thereby reducing the information asymmetries. Given that valuation of intangible assets require more effort and resources, it is possible that investors and analysts increase their search for information about firms that have higher advertising activities.
[6] In contrast to the arguments presented above, there is a competing strand of literature that suggests the opposite. This strand of literature considers dividend policy as a mechanism via which firms can reduce information asymmetries. Grossman and Hart (1980), Jensen (1986), and La Porta et al. (2000) serve as good references on these arguments.
3.1 Sample
The sample used in this paper comprises of non-financial firms from India.[7] Our baseline analysis is based on the data of all firms for which we can obtain information on advertising expenditures and dividend policy. The time period of this study covers the period between 2000 and 2019. The data used in this paper is obtained from the Worldscope and Thomson Reuters Eikon database.
3.2 Methodology and the definition of variables
In order to test the validity of our arguments, we estimate various versions of the following pooled OLS regression equation.[8]
The dependent variable (DIVIDEND) used in the above equation measures the dividend policy adopted by the firm. For the purpose of this paper, we use the percentage of earnings that are paid out as cash dividends as a proxy for the dividend policy (Farooq and Ahmed, 2018). The main independent variable of interest measures the advertising activity (ADVERT). For the purpose of this paper, this variable is defined as the ratio of total advertising expenditures and total assets (Farooq and Pashayev, 2020).
In addition to ADVERT, we also control for the following variables in the above regression equation.
- SIZE: It is defined as log of firm’s total assets. We argue that large firms are mature and have relatively fewer growth opportunities. Therefore, they are more likely to pay high dividends (Al-Malkawi, 2007; Ali et al., 2017; Eriotis, 2005).
- LEVERAGE: It is defined as total debt to total asset ratio. We argue that high debt reduces the capacity of firms to have residual income to warrant dividend payments, thereby resulting in a negative impact on dividend payments (Gugler and Yurtoglu, 2003).
- EPS: It is defined as earnings per share. We argue that profitable firms are more likely to pay high dividends than other firms (Eriotis and Vasiliou, 2003; Kumar and Sujit, 2018).
- GROWTH: It is defined as the growth in sales over the last one year. We argue that firms with more growth have higher appetite to retain earnings for expected investment projects, thereby reducing the dividend payments.
- ANALYST: It is defined as the total number of analysts issuing earnings forecast for a firm in a given year. The analysts are tasked with gathering and disseminating relevant information about firms. Therefore, it is expected that higher analyst coverage should lead to the gathering and dissemination of more information, thereby resulting in lower agency problems (Farooq and Satt, 2014). We expect lower agency problems to have a significant effect on dividend policies adopted by firms.
- ER: This variable measures the excessive spending of firms on managerial perks. It is computed by dividing operating expenses with total annual sales. Ang et al. (2000) and Farooq and Pashayev (2000) consider this variable as a proxy for agency problems. They associate higher value of this variable with higher agency costs. Higher agency costs should have significant effect on dividend policies adopted by firms.
- AUR: This variable indicates the loss in revenues that can be attributed to inefficient utilization of assets. It is equal to total annual sales divided by total assets. Ang et al. (2000) and Farooq and Pashayev (2000) associate lower values of this variable with higher agency problems. Given its correlation with agency problems, we expect this variable to have a significant effect on dividend policies.
- CASH: It is the ratio of cash and equivalents to total assets. Labhane and Mahakud (2016) argue that the dividend decisions of the firm are affected by the level of its cash holdings.
- GROUP: This variable is used to distinguish between firms that are affiliated with business groups and those that are stand-alone firms. The definition of this variable is based on the one used by the Center for Monitoring Indian Economy (Khanna and Rivikin, 2001; Chittoor et al., 2014). Labhane (2019) shows significant impact of a membership in the business group on dividend policies.
- RESEARCH: This variable is defined as research expenses to sales ratio. Lee and Lee (2019) report negative impact of research intensity on dividend payments.
- AGE: It is the total number of years since the firm got incorporated. According to the “Maturity Hypothesis”, older companies are more likely to pay dividends because they generate high free cash flows (Al-Malkawi, 2007; Grullon et. al., 2002).
- YDUM: It includes the set of year dummies to control for year-specific effects on dividend policy.
- PDUM: It includes the set of province dummies to control for province-specific effects on dividend policy. It is possible that firms headquartered in some provinces pay higher dividends than the others.
- IDUM: It includes the set of industry dummies to control for industry-specific effects on dividend policy.
3.3 Summary statistics
Table 1 documents the descriptive statistics of variables used in this analysis. The table shows that the average dividend payout ratio of the firms used in this analysis is relatively low – a little more than 14 percent. Lower dividend payout ratios may be due to high growth experienced by the Indian firms. The average growth rate of revenues is 17.30 percent during our sample period. Furthermore, the average earnings per share of the Indian firms are found to be Rs. 9.21. All of these values are consistent with the high growth of entire Indian economy. The table also shows that the average advertising expenditures are 1.49 percent of total assets for an average Indian firm. The table shows that, on average, more than a quarter of assets (27.52 percent) of Indian firms are financed by debt. Table 1 also shows that median analyst coverage is zero. It indicates relative infancy of analyst industry in India.
[Insert Table 1 here]
Table 2 shows that the average values of the control variables for firms below the 25th percentile of advertising expenditures and firms above the 75th percentile of advertising expenditures are statistically different from each other. It justifies the use of control variables by showing that characteristics of firms that incus and high and low levels of advertising expenditures are significantly different from each other.
[Insert Table 2 here]
We report the correlation between variables in Table 3. As is evident from relatively low levels of correlations, multicollinearity does not appear to be a problem in our analysis.[9]
[Insert Table 3 here]
[7] We exclude the financial firms from analysis because the control variable, such as leverage that is normal for these firms does not have the same meaning for non-financial firms. In non-financial firms, high leverage may signal the likelihood of financial distress. This is also a common practice in research. As an example, see the data section of Fama and French (1992).
[8] We have highly unbalanced panel. In such cases, pooled OLS is preferred choice of estimations. Our argument is based on Wooldridge (2010), who mention that pooled OLS is employed when we select a different sample for each period of the panel data. Fixed effects or random effects are employed when we are going to observe the same sample for each period.
[9] We also compute the Variance Inflation Factor (VIF) after estimation of every regression. The VIF values come out to be significantly less than 10. It also indicates that multicollinearity is not an issue in our analysis.
4.1 Adverting expenditures and dividend policy: Graphical analysis
Figure 1 shows the graphical relationship between the yearly averages of adverting expenditures and the yearly averages of dividend policies. The figure shows the fitted values (regression line) for the effect of adverting expenditures (ADVERT) on dividend policies (DIVIDEND). The figure indicates that adverting expenditures has a positive impact on dividend policies. The slope of the regression line is 5.97 and is significant. It indicates that one-unit increase in the adverting expenditures result in more than six-unit increase in dividend payments. Furthermore, the R-Square is 0.3286. It indicates that almost one third of the variation in dividend policies can be explained by the adverting expenditures. The figure highlights the significant effect of advertising expenditures on dividend polices.
[Insert Figure 1 here]
4.2 Adverting expenditures and dividend policy: Multivariate analysis
The results obtained after estimating Equation (1) are reported in Table 4.[10] Our findings suggest a significantly positive impact of advertising expenditures on dividend polices of firms. The Model (1) through Model (5) show significantly positive coefficient of ADVERT. One explanation of these findings is based on the assumption that advertising expenditures leads to better information environment (Joshi and Hanssens, 2009; Gow et al., 2017). By providing information, firms that advertise heavily generate interest among individuals, thereby increasing the demand for additional information about the firm (Chauvin and Hirschey, 1993). Furthermore, advertising expenditures can also help in improving the performance of firms (Luo and de Jong, 2012; Joshi and Hanssens, 2009). By expending more resources on advertising, firms can improve their performance by encouraging the repeat purchases by customers (Vomberg et al., 2015; Wang et al., 2015). Both of these factors should lead to higher dividend payments. Our arguments are consistent with prior literature that associates higher profitability and better information environment with higher dividend payments (Farooq and Aktaruzzaman, 2020; Healy and Palepu, 1988). La Port et al. (2000) argue that better information environment curtails the ability of managers to expropriate corporate resources by making the expropriation technology expensive. Farooq and Aktaruzzaman (2020) note that when managers cannot expropriate, they tend to share higher proportion of corporate profit with shareholders.
[Insert Table 4 here]
[10] We also compute the standard errors by clustering the observations within each firm. This estimation can account for serial correlation and heteroskedasticity (Peterson, 2009). Our unreported results show that significance of variables remains qualitatively the same.
5.1 Adverting expenditures and dividend policy: Alternate measures
In order to further highlight our results, we re-estimate Equation (1) by using the alternate proxies of dividend policy as a dependent variable. For the purpose of this paper, we identify two alternate measures of dividend policy. The first alternate measure is a dummy variable that takes the value of 1, if the firm pays dividend and 0 otherwise.[11] The other alternate measures of dividend policy is the dividend yield. The choice of alternate measures is based on prior literature, such as Farooq and Ahmed (2018), who also use these variables as alternate measures of dividend policy. Our results are reported in Table 5. As is evident from the coefficient of ADVERT, the findings of this table support our hypothesis by showing significantly positive impact of advertising expenditures on the dividend polices of firms. Furthermore, we redo the analysis by replacing advertising expenditures with its two alternate proxies. The first alternate measure of advertising expenditures is the ratio of total advertising expenditures to total sales, and the second alternate measure is the ratio of total advertising expenditures to total operating expenses (Farooq and Pashayev, 2020).[12] As was the case before, the results show significantly positive impact of advertising expenditures on the dividend polices of firms. We report significantly positive coefficient of ADVERT for all models.
[Insert Table 5 here]
5.2 Adverting expenditures and dividend policy: Concerns regarding estimation procedures
In this sub-section, we redo the analysis by using three alternate estimation procedures. First, we estimate Equation (1) with Tobit regression. The choice of Tobit regression is based on the fact that the dependent variable is censored on the left and on the right side. The dividend payout ratio is always between 0 percent and 100 percent. Second, we take care of reverse causality problem by using one period ahead dividend payout ratio as a dependent variable. Third, we use the instrumental variable regression to address the concerns about the endogeneity of advertising expenditures.[13] The unreported analysis shows that the instrument is valid (uncorrelated with the error term) and relevant (have high correlation with the endogenous variable).[14] The results of our analysis are reported in Table 6. As expected, we report significantly positive coefficient of ADVERT for all estimations.
[Insert Table 6 here]
[11] Due to categorical nature of first alternate measure of dividend policy, we use pooled logistic regression to estimate Equation (1).
[12] The correlation between first alternate measure and the original measure of advertising expenditures is 0.79 and the correlation between first alternate measure and the original measure of advertising expenditures is 0.66. Therefore, it seems that each alternate measure captures additional information about advertising.
[13] For the purpose of this paper, we use the average advertising expenditure of the industry as an instrument. The industry classification was based on two-digit SIC code.
[14] The first stage of instrumental variable regression estimation confirms that our instrument is indeed appropriate.
Section 2 highlights the importance of advertising in improving the information environment of a firm (Chauvin and Hirschey, 1993; Grullon et al., 2004). A corollary of those arguments is that firms with low advertising expenditures (firms with relatively poor information environment) may find it worthwhile to use dividends to improve their information environment. In other words, dividends may be used by these firms to substitute for the role played by advertising in improving the information environment. This assertion is based on La Port et al. (2000) who consider dividend policy as an important mechanism via which firms can reduce information asymmetries between insiders and outsiders. By paying dividends, firms convey an important signal to investors – that is, managers in these firms cannot expropriate corporate resources by spending them on unprofitable projects (Grossman and Hart, 1980; Jensen, 1986). Therefore, stock market participants consider dividend policies of these firms more valuable than dividend policies of firms that advertise heavily. In order to test this conjecture, we estimate various versions of the following pooled OLS regression. In the following regression, RET is the yearly stock return for the firm. All other variables are as defined above.
Table 7 documents the results of our analysis. The main variable of interest in this table is ADVERT*DIVIDEND. Our analysis shows that the impact of dividend policy on stock prices is less pronounced for firms that advertise heavily. Table 7 reports significantly negative coefficient of ADVERT*DIVIDEND in all models. One possible explanation of this finding is that the firms with low advertising expenditures may suffer from relatively poor information environment. As a result, the dividend policy becomes more important mechanism via which to resolve information asymmetries between insiders and outsiders.
[Insert Table 7 here]
This paper documents the relationship between advertising expenditures and dividend policies of Indian firms during the period between 2000 and 2019. The results suggest that there exists a significantly positive relationship between the two. The findings of this paper are also robust across various proxies of advertising expenditures and dividend policies. The paper argues that firms with higher advertising expenditures have better information environment due to higher visibility among stock market participants. Superior information environment makes expropriation expensive by exposing unscrupulous managers. Lower expropriation, eventually, leads to greater sharing of corporate profits. This paper also shows that the impact of dividend policy on stock prices is more pronounced for firms that have lower advertising expenditures. This result is consistent with prior literature that argues that dividend policy is more important for firms that have poor information environment (La Port et al., 2000).
Funding: The authors received no funding for this paper.
Conflicts of interests: There is no conflict of interest.
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Table 6 is not available with this version
Table 1: Descriptive statistics
|
Variables |
25th Percentile |
Mean |
Median |
75th Percentile |
Standard Deviation |
Observations |
|
DIVIDEND |
0 |
14.3212 |
7.3600 |
22.6300 |
18.7518 |
11363 |
|
ADVERT |
0.0475 |
1.4937 |
0.2206 |
1.1194 |
3.5885 |
11363 |
|
SIZE |
14.0536 |
15.3308 |
15.2971 |
16.5636 |
1.9428 |
11356 |
|
LEVERAGE |
7.4500 |
27.5231 |
26.2550 |
42.5700 |
21.6596 |
11126 |
|
EPS |
0.6500 |
9.2138 |
4.6555 |
13.6995 |
18.4436 |
11092 |
|
SGROWTH |
0.9200 |
17.3078 |
12.9600 |
27.5200 |
42.9734 |
10777 |
|
ANALYST |
0 |
2.5786 |
0 |
1 |
6.7078 |
11363 |
|
ER |
85.7644 |
92.6571 |
91.5592 |
96.7381 |
18.5900 |
10864 |
|
AUR |
53.8093 |
94.8853 |
86.6601 |
125.7637 |
58.5183 |
11131 |
|
CASH |
1.4548 |
8.2396 |
3.7613 |
10.1493 |
10.8239 |
11200 |
|
GROUP |
0 |
0.4536 |
0 |
1 |
0.4978 |
11182 |
|
RESEARCH |
0 |
0.2294 |
0 |
0.0300 |
0.89907 |
11363 |
|
AGE |
19 |
32.6874 |
27 |
40 |
20.1234 |
9835 |
NOTE: All variables are as defined in Section 3.
Table 2: Difference between the average values of control variables at the 25th and the 75th percentile of advertising expenditures
|
Variables |
ADVERT < 25th Percentile |
ADVERT > 75th Percentile |
Difference |
|
SIZE |
15.1483 |
15.7690 |
-0.6207*** (-12.03) |
|
LEVERAGE |
33.4689 |
20.3422 |
13.1267*** (22.92) |
|
EPS |
4.7796 |
13.6147 |
-8.8350*** (-17.52) |
|
SGROWTH |
13.5452 |
18.0673 |
-4.5221*** (-3.78) |
|
ANALYST |
1.2734 |
5.0151 |
-3.7416*** (-19.81) |
|
ER |
95.1294 |
90.7951 |
4.3342*** (8.22) |
|
AUR |
77.5935 |
114.8301 |
-37.2366*** (-23.34) |
|
CASH |
6.0023 |
10.6553 |
-4.6530*** (-16.07) |
|
GROUP |
0.4450 |
0.5294 |
-0.0843*** (-6.31) |
|
RESEARCH |
0.0824 |
0.3570 |
-27.4568*** (-12.09) |
|
AGE |
28.1469 |
38.7018 |
-10.5549*** (-17.76) |
NOTE: All variables are as defined in Section 3.
Table 3: Correlation matrix
|
No. |
Variables |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
|
1 |
DIVIDEND |
1.00 |
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
ADVERT |
0.22 |
1.00 |
|
|
|
|
|
|
|
|
|
|
|
|
3 |
SIZE |
0.15 |
0.06 |
1.00 |
|
|
|
|
|
|
|
|
|
|
|
4 |
LEVERAGE |
-0.26 |
-0.20 |
0.13 |
1.00 |
|
|
|
|
|
|
|
|
|
|
5 |
EPS |
0.19 |
0.08 |
0.22 |
-0.30 |
1.00 |
|
|
|
|
|
|
|
|
|
6 |
SGROWTH |
-0.06 |
-0.01 |
-0.02 |
0.02 |
0.04 |
1.00 |
|
|
|
|
|
|
|
|
7 |
ANALYST |
0.19 |
0.19 |
0.56 |
-0.12 |
0.22 |
-0.01 |
1.00 |
|
|
|
|
|
|
|
8 |
ER |
-0.19 |
-0.05 |
-0.20 |
0.13 |
-0.30 |
-0.14 |
-0.18 |
1.00 |
|
|
|
|
|
|
9 |
AUR |
0.16 |
0.24 |
-0.11 |
-0.14 |
0.16 |
0.06 |
-0.01 |
0.01 |
1.00 |
|
|
|
|
|
10 |
CASH |
0.19 |
0.17 |
0.11 |
-0.41 |
0.26 |
0.01 |
0.19 |
-0.14 |
0.03 |
1.00 |
|
|
|
|
11 |
GROUP |
0.12 |
0.07 |
0.42 |
0.05 |
0.07 |
-0.04 |
0.24 |
-0.03 |
-0.03 |
0.01 |
1.00 |
|
|
|
12 |
RESEARCH |
0.05 |
0.01 |
0.10 |
-0.07 |
0.08 |
-0.01 |
0.16 |
-0.06 |
-0.03 |
0.06 |
0.05 |
1.00 |
|
|
13 |
AGE |
0.21 |
0.12 |
0.25 |
-0.10 |
0.19 |
-0.10 |
0.13 |
0.01 |
0.08 |
0.07 |
0.26 |
0.06 |
1.00 |
NOTE: All variables are as defined in Section 3.
Table 4: Effect of advertising expenditures on dividend policy
|
|
All Firms |
Small Firms |
Large Firms |
||
|
Variables |
Model (1) |
Model (2) |
Model (3) |
Model (4) |
Model (5) |
|
ADVERT |
1.0920*** (16.79) |
1.0516*** (16.98) |
0.4886*** (7.50) |
0.2239** (2.22) |
0.6008*** (7.41) |
|
|
|
|
|
|
|
|
SIZE |
|
1.4591*** (15.46) |
0.8591*** (5.40) |
1.9407*** (6.09) |
0.9480*** (3.00) |
|
LEVERAGE |
|
|
-0.1697*** (-15.93) |
-0.1307*** (-8.79) |
-0.2057*** (-13.06) |
|
EPS |
|
|
0.0010 (0.09) |
0.1100*** (3.97) |
-0.0305** (-2.30) |
|
SGROWTH |
|
|
-0.0341*** (-8.09) |
-0.0313*** (-6.98) |
-0.0394*** (-4.46) |
|
ANALYST |
|
|
0.1555*** (4.40) |
0.9245** (2.11) |
0.1619*** (3.93) |
|
ER |
|
|
-0.1453*** (-12.72) |
-0.1134*** (-8.86) |
-0.1513*** (-6.96) |
|
AUR |
|
|
0.0382*** (9.71) |
0.0308*** (6.15) |
0.0429*** (6.38) |
|
CASH |
|
|
0.1125*** (5.02) |
0.0719** (2.30) |
0.1282*** (4.30) |
|
GROUP |
|
|
1.4807*** (3.17) |
1.5582** (2.09) |
1.4995*** (2.56) |
|
RESEARCH |
|
|
0.0721 (0.33) |
1.4805*** (3.65) |
-0.1619 (-0.71) |
|
AGE |
|
|
0.1099*** (9.20) |
0.0895*** (4.03) |
0.1116*** (7.82) |
|
|
|
|
|
|
|
|
Year Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
Industry Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
Province Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
|
|
|
|
|
|
|
Observations |
11362 |
11356 |
8405 |
3989 |
4416 |
|
F-Value |
21.74 |
29.00 |
42.81 |
238.15 |
68.37 |
|
R-Square |
0.0948 |
0.1119 |
0.2128 |
0.1713 |
0.2726 |
NOTE: All variables are as defined in Section 3. The t-values are in parenthesis. The variables that are significant at 1% are followed by ***, at 5% are followed by **, and at 10% are followed by *.
Table 5: Effect of advertising expenditures on dividend policy: Alternate measures
|
|
Alternate Measures of Dividend Policy |
Alternate Measures of Advertising Expenditures |
||
|
Variables |
Decision to Pay Dividends |
Dividend Yield |
Advertising Expenditures to Total Operating Expenses Ratio |
Advertising Expenditures to Total Sales Ratio |
|
ADVERT |
0.0376*** (3.33) |
0.0498*** (6.34) |
0.2932*** (4.89) |
0.2819*** (4.10) |
|
|
|
|
|
|
|
SIZE |
0.4286*** (16.19) |
0.0142 (1.15) |
0.8705*** (5.44) |
0.8681*** (5.44) |
|
LEVERAGE |
-0.0185*** (-10.61) |
-0.0196*** (-22.81) |
-0.1750*** (-16.37) |
-0.1763*** (-16.49) |
|
EPS |
0.0710*** (10.72) |
0.0054*** (4.12) |
-0.0026 (-0.22) |
-0.0031 (-0.27) |
|
SGROWTH |
-0.0027*** (-3.84) |
-0.0026*** (-8.52) |
-0.0346*** (-8.21) |
-0.0345*** (-8.17) |
|
ANALYST |
0.0218** (2.33) |
0.0393*** (9.38) |
0.1725*** (4.85) |
0.1801*** (5.07) |
|
ER |
-0.0444*** (-10.87) |
-0.0172*** (-14.56) |
-0.1433*** (-12.47) |
-0.1480*** (-12.86) |
|
AUR |
0.0071*** (11.56) |
0.0028*** (9.23) |
0.0452*** (11.44) |
0.0454*** (11.48) |
|
CASH |
0.0056 (1.44) |
0.0214*** (9..61) |
0.1210*** (5.38) |
0.1223*** (5.44) |
|
GROUP |
-0.1716*** (-2.51) |
0.0083 (0.21) |
1.4974*** (3.19) |
1.4709*** (3.13) |
|
RESEARCH |
0.1558*** (3.94) |
0.0183 (0.85) |
0.0412 (0.19) |
0.0353 (0.16) |
|
AGE |
0.0139*** (7.50) |
0.0072*** (6.50) |
0.1129*** (9.49) |
0.1138*** (9.56) |
|
|
|
|
|
|
|
Year Dummies |
Yes |
Yes |
Yes |
Yes |
|
Industry Dummies |
Yes |
Yes |
Yes |
Yes |
|
Province Dummies |
Yes |
Yes |
Yes |
Yes |
|
|
|
|
|
|
|
Observations |
8405 |
8193 |
8393 |
8405 |
|
F-Value / Wald Chi-Square |
1373.23 |
41.69 |
41.48 |
41.26 |
|
R-Square / Pseudo R-Square |
0.3484 |
0.3176 |
0.2075 |
0.2078 |
NOTE: All variables are as defined in Section 3. The t-values and z-values are in parenthesis. The variables that are significant at 1% are followed by ***, at 5% are followed by **, and at 10% are followed by *.
Table 7: Effect of advertising expenditures on dividend policy: Alternate estimation procedures
|
Variables |
Instrument Variable Regression |
Dependent Variable = DIVIDENDt+1 |
Tobit Regression |
|
ADVERT |
0.6788*** (2.70) |
0.4750*** (7.33) |
0.4803*** (6.34) |
|
|
|
|
|
|
SIZE |
0.8181*** (4.99) |
0.6398*** (3.86) |
2.8623*** (11.02) |
|
LEVERAGE |
-0.1685*** (-13.03) |
-0.1830*** (-17.15) |
-0.2881*** (-15.93) |
|
EPS |
0.0014 (0.12) |
0.0351*** (2.81) |
0.0876*** (5.31) |
|
SGROWTH |
-0.0345*** (-7.82) |
-0.0259*** (-6.24) |
-0.0563*** (-6.15) |
|
ANALYST |
0.1459*** (3.62) |
0.1770*** (4.71) |
0.0247 (0.56) |
|
ER |
-0.1496*** (-12.09) |
-0.1544*** (-12.21) |
-0.4665*** (-13.72) |
|
AUR |
0.0375*** (6.89) |
0.0345*** (8.84) |
0.0869*** (14.04) |
|
CASH |
0.1013*** (4.25) |
0.1216*** (5.13) |
0.0863*** (2.79) |
|
GROUP |
1.0831** (2.28) |
1.3171*** (2.76) |
1.7241*** (2.58) |
|
RESEARCH |
0.0969 (0.43) |
0.0539 (0.24) |
0.4186 (1.39) |
|
AGE |
0.1105*** (8.92) |
0.1081*** (8.71) |
0.1374*** (8.80) |
|
|
|
|
|
|
Year Dummies |
Yes |
Yes |
Yes |
|
Industry Dummies |
Yes |
Yes |
Yes |
|
Province Dummies |
Yes |
Yes |
Yes |
|
|
|
|
|
|
Observations |
7993 |
7534 |
8405 |
|
F-Value / Wald Chi-Square |
2451.10 |
45.71 |
48.16 |
|
R-Square / Pseudo R-Square |
0.2202 |
0.2389 |
0.0501 |
NOTE: All variables are as defined in Section 3. The t-values and z-values are in parenthesis. The variables that are significant at 1% are followed by ***, at 5% are followed by **, and at 10% are followed by *.
Table 8: Advertising expenditures and the value of dividend policy
|
|
All Firms |
Small Firms |
Large Firms |
||
|
Variables |
Model (1) |
Model (2) |
Model (3) |
Model (4) |
Model (5) |
|
ADVERT |
0.0172*** (5.38) |
0.0173*** (5.48) |
0.0098*** (3.38) |
0.0097** (2.17) |
0.0082** (2.27) |
|
DIVIDEND |
0.0020*** (6.29) |
0.0021*** (6.39) |
0.0005 (1.39) |
0.0001 (0.05) |
0.0011** (2.10) |
|
ADVERT*DIVIDEND |
-0.0003*** (-5.11) |
-0.0003*** (-5.22) |
-0.0002*** (-4.43) |
-0.0001 (-1.32) |
-0.0002*** (-4.28) |
|
|
|
|
|
|
|
|
SIZE |
|
-0.0011 (-0.32) |
0.0017 (0.29) |
-0.0072 (-0.56) |
-0.0151 (-1.57) |
|
LEVERAGE |
|
|
-0.0006 (-1.48) |
-0.0003 (-0.50) |
-0.0005 (-0.94) |
|
EPS |
|
|
0.0011*** (3.05) |
0.0019** (2.18) |
0.0010*** (2.56) |
|
SGROWTH |
|
|
0.0008*** (3.97) |
0.0009*** (3.37) |
0.0004* (1.66) |
|
ANALYST |
|
|
-0.0033*** (-3.36) |
-0.0099 (-1.00) |
-0.0024** (-2.18) |
|
ER |
|
|
-0.0019*** (-3.80) |
-0.0026*** (-3.39) |
-0.0009 (-1.47) |
|
AUR |
|
|
0.0011*** (7.46) |
0.0007*** (3.46) |
0.0014*** (6.45) |
|
CASH |
|
|
0.0005 (0.73) |
0.0010 (0.90) |
0.0001 (0.23) |
|
GROUP |
|
|
0.0230 (1.54) |
-0.0187 (-0.80) |
0.0595*** (3.00) |
|
RESEARCH |
|
|
0.0043 (0.65) |
0.0108 (0.85) |
0.0006 (0.08) |
|
AGE |
|
|
0.0010*** (2.73) |
0.0009 (1.20) |
0.0010** (2.26) |
|
|
|
|
|
|
|
|
Year Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
Industry Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
Province Dummies |
Yes |
Yes |
Yes |
Yes |
Yes |
|
|
|
|
|
|
|
|
Observations |
10801 |
10795 |
8147 |
3790 |
4357 |
|
F-Value |
157.77 |
240.67 |
123.19 |
141.73 |
123.85 |
|
R-Square |
0.3864 |
0.3849 |
0.4305 |
0.4237 |
0.4552 |
NOTE: All variables are as defined in Section 3. The t-values are in parenthesis. The variables that are significant at 1% are followed by ***, at 5% are followed by **, and at 10% are followed by *.