Abstract
In this document, unique data was utilized to determine the correlation between financial reporting quality and the dividend policy of a firm. Financial reports pertain to any and all disclosures made by firms to report current performance and direction. The quality of financial reports is critical because it drives capital market decision makers significantly. To test this hypothesis, data from fourteen Kuwaiti real-estate corporations were collected and analyzed. The dividends dispensed by these companies were analyzed against their reported Net Income, Total Revenue, Total Assets, Total Liabilities and free Cash. Regression analysis was conducted and the results were analyzed.
The regression analysis results indicated that the key financial indicators are relatively good predictors of the availability of future dividends. The conclusion that was gleaned from the study indicates that if the quality of the financial reports provided, as shown in the data that were utilized for the analysis is high, then capital markets will have a reasonably intelligent and reliable indicator of company performance. Companies that perform highly and submit relatively high quality financial reports would be attractive to investors and other potential business partners.
Introduction
A business must collate and review information about how much money it is spending and how much money it is earning. The use of financial reports delivers this type of information to shareholders and other business stakeholders (such as lenders or creditors and government institutions). Financial reports are useful for making economic decisions about a company; therefore its importance to business stakeholders is such that it influences how economic markets react to a firm, an industry or even to a country’s economy.
For financial reports to be relevant and useful, it must be reported at the very highest quality possible. Qualities of financial reports however, have been a subject of debate for financial manager due to the difficulty in measuring it. In addition, these reports are examined contextually, meaning the users of the information seek certain information from the reported numbers. According to van Beest, Braam, Boelens (2009), the context-specificity of financial reports inevitably includes the preferences among a myriad of financial report users therefore the quality of the reports will vary greatly depending on user requirement.
An excellent example highlighting the presentation of critical financial information can be seen by examining capital markets. From 1995 to 2000, the US capital market experienced a rapid rise in the equity value of Internet companies (popularly known as dot-coms) due to by market confidence in the future earnings value of these companies and venture capital funding that fed on technological innovations. By March 2010, the bubble burst.
Penman (2002) stated from 1995 to 2000, the financial reporting model used for these dotcoms were not sound and particularly wanting in its recognition of earnings ability, assets and liabilities statements. The study concluded that given failures in financial reporting quality measures, speculative investment momentum and stock market bubbles might happen, again.
After the dot-com bubble, a number of studies were conducted to determine the most accurate definition for financial reporting quality. George (2003) found out that there are different groups espousing different definitions of final quality reporting. One group is the Financial Analysts Federation (FAF), which is a branch of the Association for Investment Management and Research (AIMR). FAF conducts an annual evaluation of about 500 companies from which various financial disclosures are studied and evaluated according to their timeliness, level of detail, and clarity of presented information. The US Financial Accounting Standards Board (FASB) describes financial reporting quality as “a hierarchy of accounting qualities, with relevance and reliability considered the primary ones.” The American Institute of Certified Public Accountants (AICPA) defines “quality of reported earnings” as the measure for reporting firm performance and relevant information. Standard and Poor (S&P), considers accounting quality as “a factor in establishing an industrial bond issue rating. Firms that consistently make timely and informative disclosures are considered less likely to withhold relevant unfavorable information.”
Even without a standard definition, financial reporting must be conducted at the highest possible level of quality by a firm’s management, auditors or other financial service provider. The purpose of this document is to determine if there is a correlation between the earnings quality of a firm, as measured by its dividend policy and the quality of the reported financial performance, as presented by key financial indicators.
Model
The data set analyzed herein is companies from the Kuwait real-estate industry. This industry experienced significant growth from 2000 to 2007 but slowed considerably because of the Kuwaiti government’s proactive move to curb speculation and subsequently, the global economic slowdown. Historical information from fourteen Kuwaiti real estate firms was analyzed. The limitation of the data however is that the number of time-series observations covers only three years (2008 to 2010). The “accuracy” of the model statistically increases as the number of observations increases.
A linear regression analysis was conducted to determine the relationship between the actual dividend paid out and the presented financial items. Linear regression is a statistical method for forecasting. Simply put, if we can plot the dependent variable over an explanatory variable in a graph and draw a line that “best fits” the observations, we will have an estimate of what the future value for the dependent variable could be. This technique of drawing the “best fitted line” provides a reasonably precise and consistent estimate since it seeks to minimize the variances between dependent variable observations.
For our purpose, a simple linear regression was conducted. Simple linear regression looks into the relationship of a scalar dependent variable and one explanatory variable. We assume that the relationship of the explanatory variables to the dependent variable is linear, for instance the movement of the explanatory variable moves the dependent variable by a certain “scale” only.
For simple linear regression analysis, the relationship of the dependent variable Dividends was examined against Net Income, Total
Revenue, Total Assets, Total Liabilities and Cash. The formulae are shown below. For each regression analysis conducted, the goodness of fit (R2) is evaluated to see which individual explanatory variable influences dividends significantly.
1. Dividends = Net Income X1 + error
2. Dividends = Total Revenue X2 + error
3. Dividends = Total Assets X3 + error
4. Dividends = Total Liabilities + error
5. Dividends = Cash + error
Data Analysis
The regression analysis indicates that the best key financial item that predicts dividends is Total Revenue. Total revenue has an R-squared (goodness of fit) measure of 43.85%, and a decrease in 1% in total revenue decreases dividends paid out by 4.7%. The results are intuitive, in that a company that generates bigger revenues can provide dividends to its shareholders, more than a company that does not earn as much.
The second best indicator of divided behavior of firms is the free cash available. Again, this relates to revenue generation. Cash is what would be leftover after all the financial and operating obligations of a firm have been addressed. The high degree of correlation between cash and dividends indicate that if a firm generates enough cash left over after all its financial and operational obligations are met, it will distribute it to shareholders. Therefore, cash is a good indicator of a company’s dividend policy.
Total assets is an interesting predictor of dividends. When total assets increase by 1%, the total dividend paid out can increase by 10.65% (or conversely, a 1% decrease in a firm’s asset value decreases dividends by 10.65%). Total assets as a predictor accounts for 11.69% of the dividend behavior. We can generalize that the bigger the asset base of a company, the more likely it is for that company to give-out dividends.
Net income and total liabilities are two key figures that have little correlation with dividends (only 4.9% and 5.3% goodness of fit respectively).
Conclusion
This study examined the relationship of reported key financial items such as the Net Income, Total Revenue, Total Assets, Total Liabilities and Cash with the Dividend policy of a firm. The key financial items approximate the financial reporting quality, publicly distributed measures of a company’s performance, the directives of its management, and its capacity to compete in a given economic landscape.
Data on fourteen Kuwaiti real-estate companies were collected. Time series data on dividends paid out and the key financial indicators stated above were analyzed using regression analysis. The results showed that of the key financial indicators considered, Total Revenue and Cash best predicts the dispensation of dividends to stockholders. The asset size of a company also provides a prediction of dividends in the future, but is a far third compared to the top two. Of the five key indicators, Total Liabilities and Net Income are the poorest indicators of the availability of future dividends.
If the quality of these financial reports is accurate, capital markets are given reasonably intelligent and reliable indications as to which companies perform, which industries are growing, and which economies are strong. The quality of the information provided therefore has a direct impact on the decisions made by capital market participants. Since capital is a resource that is finite, capital market participants would seek those companies that would provide predictable returns on investments and if the quality of the financial reports of these companies are high, then it would follow that capital would flow to those companies.
Reference
American Institute of Certified Public Accountants: Financial Management & Reporting Publications. Retrieved from http://www.aicpa.org/Publications/FinancialManagementReporting/Pages/FinancialManagementReporting.aspx
Capital Standards (2011). Kuwait Real Estate Sector 2011. Retrieved from http://www.capstandards.com/CSR_RealEstateSectorReport_May-2011.pdf ß
Deloitte, 2011. Financial Reporting Considerations Related to S&P’s Downgraded Credit Rating for US Long-term Sovereign Debt. Retrieved from http://www.corpgov.deloitte.com/binary/com.epicentric.contentmanagement.servlet.ContentDeliveryServlet/USEng/Documents/Deloitte%20Periodicals/Financial%20Reporting%20Alert/FinancialReportingAlert115.pdf
Financial Accounting Standards Board: FASB Accounting Standards Codification. Retrieved from http://www.fasb.org/home
Penman, S. (2002). The Quality of Financial Statements: Perspectives from the Recent Stock Market Bubble. Department of Accounting, Columbia University. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=319262
Standard & Poor. Retrieved from http://www.standardandpoors.com/home/en/ap
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van Beest, F., Braam, G. and Boelens, S. (2009). Quality of Financial Reporting: Measuring Qualitative Characteristics. Nijmegen Center for Economics (NiCE) Institute for Management Research Radboud University Nijmegen. Retrieved from http://www.ru.nl/nice/workingpapers
Wikipedia: Dot-Com Bubble. Retrieved from http://en.wikipedia.org/wiki/Dot-com_bubble
