Public companies have several options when it comes to earning profits. Depending on their corporate goals and financial situation, they may choose to reinvest the funds to help grow the business, buy back some of their shares on the stock market, or distribute earnings to shareholders as dividends.
Dividend policy refers to the more principled approach adopted by a company’s general meeting of shareholders or board of directors to all aspects of dividends (Chen, 2020). It is the firm’s policy and strategy for deciding if, how much, and when to pay dividends, and it primarily concerns the strategic question of whether the corporation should share its earnings or keep them for reinvestment. Dividend policy refers to a fair distribution of after-tax revenue by publicly traded firms, which has an impact on the capital market’s stability and the company’s future growth.
An organization’s dividend distribution policy can affect its social image and investor interest not only in the short term but also in the long term. As a result, the dividend policy is linked to the protection of shareholders’ rights and interests, which has an impact on the company’s long-term health. Paying a dividend allows a company to share its profits with shareholders, which helps to thank them for their continued support through higher returns and motivates them to continue to hold the stock.
A stable dividend is often seen by investors as a sign of a company’s strength and an indication that the company’s management has positive expectations for future earnings growth. This makes the company more attractive to investors, which helps drive the stock price higher. As a result, the change in dividend policy has a significant impact on the company’s success. Dividends are an important part of the “total return” of a stock investment. Using this dividend income to purchase more shares also further builds the value of an investor’s holdings by harnessing the power of compound interest over time.
At first glance, the technology industry is booming. The top five U.S. tech companies, Alphabet, Amazon, Apple, Facebook and Microsoft, all boast impressive revenues, profits and stock market valuations. Chinese competitors across the pond, particularly Alibaba, Huawei and Tencent, are doing the same, leveraging their leadership position in the Chinese market to aggressively develop international market share. Technology development has been one of the main drivers of economic integration in the world. It can be said that technological development and economic globalization are going hand in hand, and that technological progress is bringing humanity into a more integrated economic era.
When investing in stocks, investors also include the technology sector in their investment plans, including ourselves, who also bought shares of Apple, and through experience, technology stocks will indeed bring high returns to investors in the future. Therefore, we wanted to look at the internal factors that drive dividends for technology companies and what factors make the companies we choose to have unimpressive dividend returns.
Our goal is to investigate the factors that influence dividend policy and provide useful conclusions for the company’s shareholders and investors, so that the company’s shareholders may use our findings to alter their business plan and investors can benefit from our findings. The findings of our research can be used by shareholders of the company to adjust their business plans and by investors to choose investment firms or consider their investment strategy.
The organization of this study begins with a literature review. A review of theoretical and empirical literature will be presented, in which we read 25 articles that examine the factors of dividend policy and how dividend policy affects firm performance. The development of research hypotheses, model description, and defining samples will make the content next. We hypothesise that financial determinant factors have a statistically significant influence on the dividend payout ratio of Canadian corporations from 2010 to 2019. In selecting the data, we used a total of 30 US and Canadian companies for the analysis, and we used regression analysis, where the dividend payout ratio is the independent variable, and the firm’s ROA, ROE, size of the firm, FCF, and leverage ratio is a dependent variable. The research methodology will be presented in the last section.
The topic of dividend policies and relevant theories has been researched and published in literature dating back to the 1950s. Among the research completed, one of the most well known and impactful studies was completed by experts, Miller and Modigliani, who developed their infamous thesis on dividend Policy, growth and the valuation of shares in 1961. This publication induced a comprehensive discussion about the research on dividend policy and as such, has led to many other studies providing various findings within various types of markets throughout the world. The purpose of this literature review is to gain insights into what has already been concluded concerning the drivers of dividend policy so we can compare those previous findings with our research to see if the results are transferable in the Canadian Technology sector.
Sector and Industry Research
Of interest to our research question, Denis, D. J., and Osobov, I. (2008) provided relevant evidence of dividend policy on an international level over the period of 1989 to 2002, with their sample including Canada. By examining cross-sectional and time-series data on the tendency to pay dividends, Denis, D. J., and Osobov analyzed whether the characteristics of dividend payers and non-payers were similar across countries. Their investigation found that the determinants influencing a firm’s decision to pay dividends appear to be remarkably similar across countries, with dividends being affected by firm size, profitability, and growth opportunities, and earned equity mix. More precisely, they found that larger, more profitable firms and those with a greater proportion of earned equity are more likely to pay dividends, while the effect of growth opportunities on the likelihood of dividend payments is mixed. Additional research pertinent to this paper is the work of Pinto and Rastogi (2019), on the sectoral implications of dividend policy. Despite their analysis of multiple sectors, their evidence specific to the technology sector supports that firms with a larger size, higher interest coverage ratio and profitability, and low business risk and debt are likely to distribute higher dividends. Similarly, Mahdzan, Zainudin, and Shahri (2016), completed an interindustry analysis of dividend policy in emerging markets, which although differs from Canada, their results provide an interesting perspective. Their study found that firm size, leverage position, and profitability were significant determinants of dividend policy, with size and leverage playing the most significant role in the technology sector. Their results within an emerging market appear to be on par with those of a developed market emphasizing the universality of dividend policy drivers. Moving away from the technology sector, as determining the common factors across various sectors can help identify the most impactful and significant determinants of dividend policy, Jovkovic, Vasic and Bogicevic (2021) examined the factors that determine the dividend policy of the Serbian banking sector. Contrary to previous works, the empirical evidence of their research showed that last year’s dividend posed a positive impact on the dividend policy. Their results support the development of dividend policies based on the previous year’s characteristics, emphasizing the importance of conducting our research over a ten year timeline to obtain an understanding and perspective of the firm throughout the years Neves, Cunha & Vilas, (2020) also contributed to dividend policy research but in the telecommunications sector, a sector less susceptible to volatility in the global financial markets and usually pay higher dividends than in other industries. They found that specific factors such as investment in fixed capital, indebtedness, price to book value ratio, free cash flow (FCF), liquidity, and dividends paid in the previous year are decisive in explaining the dividends distributed in the entire period. It appears, through an analysis of literature, that the most impactful drivers across various sectors and industries are size, liquidity, cash flows, and leverage. This will provide a base and starting point for our research within the Canadian market.
Single Variable Analysis
Building on the more broad scope across various sectors, different research has been conducted to specifically analyze the impact of individual variables. Lee and Lee (2019) provided evidence concerning the impact of R&D on dividend policy on Bio-Tech firms in South Korea, a variable not typically considered, yet applicable to our research on technology companies who generally spend larger amounts on research and development (Molla, 2017). Their evidence indicated a negative correlation between R&D intensity and dividend payout while the correlation between cash dividend payout ratio and R&D intensity of firms with high levels of cash is significantly positive. As such, our research intends to focus more on cash flows as an important independent variable of dividend policy as opposed to R&D given that it appears to be a more significant determinant. An additional factor that was tested by Harun, Kamil, and Elias (2018) was intellectual capital in Malaysian firms, as it is a factor not typically considered when analyzing dividend policy, and the researchers study its impact particularly on technology firms. Their results found no significant relationship between intellectual capital and dividend policy with employed efficiencies being the only intellectual capital variable showing a significant positive relationship. Barclay, Smith, and Watts, (1995) also discussed dividend policy in their publication “The determinants of corporate leverage and dividend policies”. They concluded that the company’s investment prospects appeared to be the most important systematic indicator of its leverage ratio and dividend yield, with high proportions of intangible growth options resulting in much lower leverage ratios and dividend yields. Another relevant study completed was that of Al-Najjar and Kilincarslan (2016) who explain how ownership structure has an impact on the dividend policy of the firm. The empirical results showed that foreign and state ownership are associated with a less likelihood of paying dividends, while family involvement, domestic financial institutions and minority shareholders are insignificant in affecting the probability of paying dividends. Another study conducted by Barros, Verga Matos, and Miranda Sarmento (2020) focused heavily on the impact of size, as it is a well known variable in determining dividend policy. They showed that dividends are consistent and regularly paid in large established firms, emphasizing the importance of size in driving dividend policy, and additionally concluded that efficient dividend policies can improve a company’s financial position and an investor’s impression of the firm. As well, Bae, El Ghoul, Guedhami, and Zheng (2020) used board reforms as a variable in dividend policies in 40 countries worldwide. After implementing board reform, the study found that firms pay higher dividends and the increase in dividend payouts is more pronounced for firms with weak board governance in the pre-reform period and in countries with strong external governance mechanisms. Ultimately, board reforms empower outside shareholders to force management to pay higher dividends. Overall, there appears to be some importance of the variables discussed above, but not in all, as should be considered when structuring a firm’s dividend policy.
Share Price Volatility
With numerous variables considered, other researchers studied how dividend policies and share price are related. Hooi, Albaity, and Ibrahimy (2015) contributed to the study of dividend policies by examining the relationship between share price volatility and dividend policies. Their testing found a statistically negative relationship between dividend policies and share price volatility, meaning a more stable stock pays more dividends. As well, the researchers noted that the size of the firm and share price are also negatively related, which makes sense given that the larger the firm, the more stable they typically are. Similarly, Hussainey, Mgbame, and Chijoke‐Mgbame (2011) examined the impact of dividend policies on share price changes in the UK. They identified a positive relationship between dividend yield and stock price changes and a negative relationship between dividend payout ratio and stock price changes. In addition, the results show that a firm’s growth rate, debt level, size and earnings also explain stock price changes, which inherently also affect the dividend payout ratio as well. In conjunction with share prices, Driver, Grosman and Scaramozzino, (2020) examined the impact of investor pressure via the threat of takeovers, shareholder value oriented corporate governance, and trading and institutional ownership patterns and how it impacts managers’ decision toward dividend policy. The testing found that firms adopt a higher dividend payout to discourage takeover bids and that firms who are most focused on shareholder value governance in the form of equity-based compensation and a higher share of independent directors, display a higher dividend payout.
Ultimately, investigating the drivers of dividend policy is majorly important as a firm’s dividend policy has a significant impact on their capital structure and financial performance. The importance of dividend policy is particularly demonstrated by Wang (2010), Mercer (2019), and Shude, Han, and Yan (2019). Wang (2010) investigated the causal relationships between investment, financing, dividend policies, and corporate performance of high-tech companies and found that dividend policy, along with the other variables, has a positive influence on the firm’s financial results. Mercer (2019) introduced the concept of dividends and dividend policies in private firms to see the importance of dividends on the business’s investment returns. The study concluded that dividends are essential for the organization as it is a source of diversification for a private company and allows the firm to focus on financial performance. Next, Shude, Han, and Yan (2019) concluded in their research on perfecting the equity and dividend incentive policies that dividend incentive policies are of great significance for investors’ decisions concerning their investment in public entities and the issuance of dividends sends positive signals to those considering an investment in a firm. Therefore, a firm issuing dividends is more likely to attract more shareholders and investors. Additionally, Kanakriyah (2020) looked more directly at industrial and service sector companies to determine the relation between the corporate’s financial performance and the dividend policy in emerging nations. The study’s conclusion is that dividend policy explains a lot of a company’s financial performance, meaning policy has a statistically significant impact on company financial performance. Raed (2020) also provided empirical findings to the study of dividend policy with its effects on financial performance as well as the primary factors that influence financial performance. Raed (2020) showed that firm size had the most substantial impact on the dividend payout ratio as well as dividend yield and ultimately concluded that dividend policy has a statistically significant impact on a company’s financial performance.
Despite the extensive amounts of research conducted and empirical evidence about dividend policy, each study is accompanied by its own limitations and there appears to be a lack of research concerning Canadian companies. Nonetheless, there seems to be a dominance amongst the evidence provided about the importance of size, profitability, leverage, cash flow, and liquidity. Although there were many individual variables that were proven to be related to dividend policy as well, their impact, such as board reform and ownership structure, may appear within the leverage, liquidity, and size of the firm.
Research Questions and Hypotheses Development
Based upon the research from the papers summarized in the literature review segment above, there are various factors which contribute to the development of companies’ dividend policies. However, in the case of Canadian firms, there are relatively limited explorations as to whether these factors would continue to persist in affecting the Canadian firms’ dividend policies. It was for this reason that we intend to examine whether the factors previously identified in research could continue to persist in the case of Canadian firms. This is also based on our recognition of La Porta et al. (2000)’s arguments that the local business environment might shape firms’ business policies – including their dividend policies. In addition, we would also like to examine whether there are changes in dividend policies amongst Canadian firms, as measured based on the development of their respective dividend payout ratio, to understand the characteristics of Canadian firms’ dividend policies.
Therefore, there are two primary research questions which shall be investigated by this study in the case of Canada. First: “What are the pattern of Canadian firms’ dividend distributions?” was posed to examine the characteristics of dividend distributions in Canada, as indicated by the sample firms’ dividend payout ratio. Second: “What are the factors that drive dividend distribution policy?” intends to examine the prevalence of factors that are discussed in the literature reviews in Canada, while also intends to examine the possible reasons for each factors’ significance or of insignificance in affecting Canadian firms’ dividend distribution policy.
From the literature compilation, we derived five factors which could be regarded as the generic factors affecting firms’ dividend distributions. These factors consist of Return on Assets (ROA), Return on Equity (ROE), firm size, Free Cash Flow, as well as the firm’s leverage ratio. At the same time, it is also important to recognise that although these factors had been heavily featured in the models that are discussed in the literature, it is also not uncommon to see that some of these factors are often lacking universality to explain firms’ dividend policies. It was particularly for this reason that authors such as Shao et al. (2010) emphasize the need for specific examinations of a particular business segment, and recognising the influence of different business environments towards the development of firms’ dividend policies. Therefore, the following hypotheses would be focused to specifically examine the case of US and Canadian firms’ dividend distribution.
H0: “Financial Determinant factors had no statistically significant influence on Canadian firms’ dividend payout ratio from 2010 to 2019”
H1: “Financial Determinant factors have statistically significant influence on Canadian firms’ dividend payout ratio from 2010 to 2019”
Related to our second research question, the second hypothesis of this study specifically examines the influence of various financial determinant factors towards the dividend policies of the Canadian firms (as measured based on their dividend payout ratio). This is also to identify factors in the literature that might not be able to explain the Canadian firms’ dividend policies, and discuss possible reasons for such inability.
This study shall utilize secondary data as the main source of information. Secondary data was preferred due to its practicalities and its readiness to be immediately inputted into the data analysis process. The nature of the secondary data in this study is quantitative: consisting of numerical information about the financial performance of the sample Canadian firms.
In terms of sampling, we first define our population as Canadian firms which have been in operation between 2010 and today, and have also disclosed their annual financial statements regularly throughout this time period. Accordingly, a random sampling approach would be adopted, aiming to select 30 companies from the sample pool. Random sampling was preferred for this study, because it is consistent with this study’s focus to examine the situation in entire Canada, rather than being constrained to a particular industrial segment. This is related to the capabilities of the random sampling approach in allocating a similar degree of probabilities for all firms in the population to be chosen as sample. According to Goertzen (2017), this allows that data to possess a higher degree of representativeness to the population.
After establishing a sample pool consisting of 30 Canadian firms, this study would obtain corresponding annual financial information based on the sample firms’ disclosed financial figures. In particular, this study will obtain the financial ratios and market capitalisation data through COMPUSTAT. For cross-checking purposes, this study would also obtain financial figures based on the sample firms’ historical financial statement records in Morningstar (https://www.morningstar.com/). Morningstar’s financial statement figures would also be employed to manually calculate any financial ratios which might not be available in COMPUSTAT. The focus of the data collection shall be centred on financial information that are disclosed throughout 2010 to 2019. Year 2019 serves as a cut-off point in this study, to account for the biases which might be introduced by extraordinary events – particularly the impact of COVID-19 pandemic towards financial performance.
This study would adopt a quantitative approach to analyze the data, focusing on the proponents of Multiple Regression Analyses. According to Petchko (2018), MRA is a statistical procedure that aims to examine the relationship between one dependent variable and two or more predictors (independent variables). MRA calculates the degree of dependent variable’s variance that could be explained in each of the independent variables. In other words, this calculation examines the relative importance of each independent variable towards the relationship with the dependent variable.
In this study, the dependent variable is the dividend policy of sample firms – as represented by the sample firms’ dividend payout ratio. On the other hand, the predictor variables consist of the four general factors of Return on Equity (ROE), firm size, Free Cash Flow, as well as the firm’s leverage ratio. This is represented by the following regression equation:
DPR = α + β1 ROA + β2 SIZE + β3 FCF + β4 LEVR + e, where:
- DPR = Sample firms’ dividend policy, as represented by sample firms’ annual Dividend Payout Ratio
- ROA = Annual Return on Assets Ratio
- SIZE = Corporate Size
- FCF = Firms’ Free Cash Flow Ratio
- LEVR = Firms’ Leverage Ratio
The impact of each of the predictor variables can be examined based on the regression coefficients, which represent the degree to which a predictor variable contributes itself towards the dependent variable’s variances, after the impact of other predictor variables is statistically removed. The regression coefficient in this study also measures the importance of each predictor variable in the regression equation.
In addition, to examine the changes of Canadian firms’ dividend payout ratio from 2010 to 2019, this study adopts the proponents of t-test analysis, focusing on examining whether there are statistically significant differences in the dividend payout ratio patterns disclosed by the Canadian firms.
This study investigates the role of firm-specific characteristics in determining the dividend decisions of Canadian technology firms using estimates from a regression model. Table 1 presents a summary of the full model that estimates the relationship between dividend payout ratio, DPR, and the four independent variables; ROA, SIZE, FCF, and LEVR. The complete model output is displayed in Appendix A. The variables FCF and SIZE were standardized by dividing the free cash flows by the firm’s total assets and taking the natural log of the firm’s market capitalization.
Table 1 suggests that none of the model variables are strong determinants of the dividend policies of technology firms in Canada. At the 5% significance level, ROA, SIZE, FCF, and LEVR, display p-values larger than 0.05. As a result, we fail to reject the null hypotheses. By doing so, we conclude that the financial determinant factors expressed in our model have no statistically significant influence on Canadian technology firms’ dividend payout ratio from 2010 and 2019. There is no empirical evidence to suggest that the independent variables correlate significantly with a firm’s dividend payout ratio, and we would therefore ignore coefficient outputs as well.
The regression also returned an R squared value of 18.44% (Appendix A). This value is a second indication, in addition to the p-values, that the financial determinants analyzed are not explaining much in the variation of the dividend payout ratio. As such more variables must be considered to fill the gap within the variance.
These results contradict the conclusion of previous research conducted by Pinto and Rastogi (2019) and Mahdzan, Zainudin, and Shahri (2016), who both concluded in their individual studies that a technology firm’s dividend policy is impacted by their size, profitability, and leverage positions. Further investigation should be conducted on the sample firms of our study to determine the most significant factors affecting their dividend policy. The time period under analysis were years of significant growth for most technology firms, and as such, their growth rate may have been a stronger contributor to their dividend payout ratio. Other potential factors of interest for future interest could include investor pressure, corporate governance, or regulation.
Individual Variable Analysis
Given the results of the multivariate regression, an additional simpler linear regression was conducted to test the correlation between dividend payout ratio and each independently. The correlations and p-values for each variable is summarized in Table 2.
Table 2 shows that when the variables are run individually against the dividend payout ratio, ROA is the only variable with a p-value < 0.05. This would imply that a firm’s return on assets is significantly related to their DPR. Additionally, ROA exhibits a negative coefficient, meaning that it moves inversely with a firm’s dividend payout ratio. As the company’s return on assets increases, the firm distributes less dividends. This is surprising given that a rising ROA would indicate better financial health as a company is increasing its profits with each investment dollar it spends, and would therefore have more to payout as dividends. This analysis, however, is once again limited by a R square of 13.89% (Appendix B). Inherently, with a single variable regression the R square will be lower as ROA cannot solely determine a firm’s dividend policy. As such, as previously discussed, more variables should be examined to determine the real factors affecting a technology firm’s dividend policy.
Appendix A – Multivariate Regression Output
Appendix B – ROA Regression Output
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Academic Integrity Form
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|I/we declare that the work submitted in the attached research proposal/report is my/our work. |
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|Student Name Chenxi Zhu |
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|Due Date Nov 22 2021|