Sample of Proposal Essay Example

a way for companies to communicate their performance to stakeholders. Companies consider dividend decisions important as they determine how funds are allocated to investors and how much is retained for investment purposes. In simple terms, when profits are made annually, companies must decide the proportion of profit distributed to shareholders as dividends and the amount reinvested. Professional investors in banks generally anticipate receiving income from their investments.

In Islamic terms, dividend is commonly known as profit distribution and can be distributed in two ways - through cash dividend or by repurchasing shares and giving the cash to shareholders. Both distributions and payments fall under the definition of dividend, which also includes releasing a company's assets, including money, to its shareholders if there are accumulated profits. However, Muslim investors must carefully evaluate investments based on two key factors - being free from interest and having a business model that is not haram. This ensures that they only participate in investments that adhere to Islamic principles.

In the context of Islam, dividends are known as profit sharing. This means that investors participate in the profits of the company they have invested in. Unlike passive income like interest, dividends depend on the performance of the company. This research looks into definitions of conventional and Islamic dividends and their importance in investment. Shareholders receive payment when a company generates profit or surplus from its operations or business (Li, W. and Lie, E. 2006). Additionally, this study investigates various factors that influence companies' choices to pay or not pay dividends.

Investors rely on the distribution of dividends to ensure the financial stability of a company and attract

those seeking a consistent income. Dividends also help maintain the market value of shares. To understand how banks distribute dividends, it is crucial to conduct thorough studies on factors that influence this process. Current research predominantly analyzes cash payouts when studying dividend payment patterns. This study aims to explore the determinants of dividend distribution in Malaysian banks and their impact on shareholders.

What are the factors that may impact dividend payments in the Malaysian banking sector?
3. How do profitability, leverage, growth, and collateral capacity affect dividend payments for banks in Malaysia?

The purpose of this study is to investigate the effects of return on assets (ROA), debt ratio (DR), growth of interest income (II), and total fixed assets (TFA) on dividend payments in the Malaysian banking sector. This research collects data annually for seventeen years from ten listed banks in Bursa Malaysia. While previous studies have examined similar topics in other journals, there is currently no evidence specifically for Malaysia.

This study addresses the issue of volatility in dividend distribution within the country and explores various factors that may influence it. Investors interested in becoming shareholders and making investments are particularly concerned about this matter. Dividend payment plays a crucial role as it can enhance shareholder investment and contribute directly to achieving a company's objectives.

The study focuses specifically on examining how profitability (return on assets), leverage (debt ratio), growth (growth of interest income), and collateral capacity (total fixed assets) influence dividend distribution in Malaysian banks.

Below are three research questions addressed by this study:

1. What is the impact of social media on mental health?
2. What factors may impact dividend payments in the Malaysian banking sector?
3. How do profitability, leverage,

growth, and collateral capacity affect dividend payments for banks in Malaysia?1. How does exercise impact cognitive function?
2. What is the correlation between lack of sleep and productivity?

In this study, several research questions have been developed to investigate the problem statement further. These research questions can be divided as follows:
1. Does a higher return on assets of a bank influence higher dividend payments to shareholders?
2. What are the effects of the debt ratio on dividend distribution?
3. Does the growth of interest income impact dividend distribution?
4. Does the total fixed asset of a bank influence dividend payments to investors?

The objective of this study is to determine the factors influencing dividend distribution in banks in Malaysia. There are three main objectives for conducting this research:
1. [Objective 1]
2. [Objective 2]
3. [Objective 3]

The objective of this study is to find the factors that have a significant impact on dividend distribution to shareholders in Malaysian banks. It also aims to examine the correlation between dividend policy distribution and variables such as profitability, leverage, growth, and collateral capacity. Additionally, the study strives to identify the most appropriate model that satisfies all criteria for ensuring an unbiased and efficient ordinary least squares (OLS) estimator. The importance of this research lies in its contribution towards enhancing our understanding of how profitability (return on assets), leverage (debt ratio), growth (growth of interest income), and collateral capacity (total fixed assets) relate to dividend payments through multiple regression analysis.

This research contributes to the current literature on dependent and independent variables in various countries, although limited evidence is available in Malaysia. It provides valuable information for individuals,

investors, and students seeking informed investment decisions pertaining to financial institutions. The study aids in selecting an optimal investment portfolio that can yield higher current income through advantageous stock choices. Furthermore, it offers guidance for managers and board of directors when deciding dividend policy distributions.

The aim of this study is to help managers effectively manage their companies and maximize shareholder wealth by increasing dividend payments, without causing any negative effects on company or bank performance. Furthermore, it is anticipated that this research will serve as a valuable resource for other academics and researchers, offering guidance, references, and future directions. The study focuses on the banking sectors in Malaysia, specifically examining the dividend distribution of banks listed on the Main Board of the Bursa Malaysia. Time series data from 1993 to 2009 is utilized for this research.

This study explores the connections between profitability, leverage, growth, and collateral capacity in relation to dividend payment. It utilizes data from 10 banks listed on the main board in Bursa Malaysia from 1993-2009. The collected data includes dividend per share, return on assets, debt ratio, growth of interest income, and total fixed assets. The objective is to evaluate these relationships using the Multiple Linear Regression Model. However, a limitation of this study is the limited availability of data and information.

Accessing the necessary information is incomplete due to data unavailability. The annual reports of the sample banks, which are the primary sources, often lack available data. Some targeted data was not available based on the date. Therefore, only data from seventeen years of the ten listed banks on the main board of Bursa Malaysia can

be used. This limitation makes it difficult to gather data from other sources as it requires a long period of time and the data may be incomplete, unreliable, or missing from those sources. It is crucial to have ample experience and knowledge for conducting research to ensure accuracy and obtain good results or findings.

The student requires guidance from professionals and lecturers due to the lack of certain aspects. However, continuous effort and attention can help ensure the successful completion of this research. Financial constraints arise from the high costs of collecting data, especially when certain data cannot be found in datastream and can only be obtained from the library of Bursa Malaysia. Additionally, these costs may include printing expenses incurred while gathering various journals, articles, and information for accurate and reliable results. Time constraints pose a challenge as the limited timeframe provided is insufficient to produce the highest-quality research.

The dividend distribution of banks in Malaysia can be influenced by various factors, making it challenging and time-consuming to gather data on these factors.

1.8 DEFINITION OF TERMS
1.8.1 Dividend - a taxable payment declared by a company's board of directors and given to its shareholders. It is the portion of corporate profits paid out to stockholders, with options including cash, stock, or other property.

4.5.6.7.1.2 Dividend policy - a company's approach to distributing profits back to its owners or stockholders, determining how much they will pay out in dividends.

3. Dividend per share (DPS) - the amount of dividends paid per share of common stock over a reporting period.

The return on equity (ROE) is a metric that gauges a company's profitability in

relation to its shareholders' equity. It is determined by dividing the net income by the average shareholders' equity. The ROE formula assesses how efficiently a company utilizes investors' funds to generate profits and is also known as "return on investment".

The paragraph underscores the significance of various financial indicators for assessing a company's financial health. One important indicator is the debt ratio, which is calculated by dividing total debt by total assets and reveals how much a company relies on borrowing to fund its assets. Another critical indicator is interest income, which represents earnings from investments and appears on the income statement. Conversely, net interest income indicates the difference between interest payments received from loans and those made to customers for their deposits. This discrepancy can contribute to an increase in a bank's net profits. Lastly, the paragraph notes that total fixed assets encompass all of a company's long-term assets.

Total fixed assets refer to the assets owned by a corporation that are not consumed or sold during normal business operations. These assets include land, buildings, equipment, machinery, vehicles, leasehold improvements, and other similar items that are necessary for the corporation to carry out its operations. This chapter aims to introduce and provide background information for this study with a focus on the objective and research questions that will be analyzed. Additionally, dividend distributions play a significant role in supporting the business activities of corporations.

The significance of this research is highlighted by the problem statement, which explains the importance of the study. The study utilizes its own approach to examine the significant relationship between the dependent and independent variables. CHAPTER 2

LITERATURE REVIEW INTRODUCTION This study concentrates on banks in Malaysia and their dividend distribution, discussing relevant topics from prior studies. It also presents an empirical theoretical framework for assessing the impact of dividend distributions. Hence, this study strives to accomplish similar goals as previous studies while also comparing factors with a greater influence on dividend distribution.

This chapter provides a comprehensive review of empirical studies that have examined the connection between dependent and independent variables relevant to this research. The study considers profitability (return on assets), leverage (debt ratio), growth (growth of interest income), and collateral capacity (total fixed assets) as independent variables. The primary objective is to investigate the correlation between these variables and the dividend payment of banks in Malaysia. This chapter is crucial in ensuring that important variables with potential impact on the research problem are not overlooked, thus enhancing the ability to test the research findings.

This research review aims to enhance understanding on the issue by discussing key factors that affect dividend policy. Previous studies have identified several factors, including profitability, leverage, ownership structure, firm size, risk, age, and firm growth dividend changes (Eriostis and Vasiliou, 2003; Amidu and Abor, 2006; Al-Malkawi, 2007; Kowaleski, Stetsyuk and Talavera, 2007;). Specifically, Amidu and Abor (2006) found a positive relationship between corporate profitability and dividend payout ratios. Anil and Kapoor (2008) suggest that profitability is commonly regarded as a primary indicator of dividend payout ratio.

According to Al-Kuwari (2009), profitability is a key factor that directly affects dividend policy. Pruitt and Gitman (1991) also found that current and past years' profits, as well as the year-to-year and prior years' dividend,

influence dividend policy. Therefore, it is expected that profitable firms are more likely to pay dividends compared to non-profitable firms (Eriostis and Vasiliou, 2003; and Ahmed and Javid, 2009). Additionally, Kowalski et al (2007) argue that highly indebted firms prefer to pay lower dividends. Al-Kuwari (2009) further confirms that dividend policy is negatively correlated with leverage ratio.

Despite this, the use of debt has been linked to lower agency costs and improved firm profitability, both of which can enhance dividend payment. However, Dhillon (1986) found conflicting evidence on the relationship between dividend payout ratios and leverage. Some industries have a positive correlation between payout and leverage ratios, while others show a negative correlation. Lloyd et al. (1985) and Collins et al. (1996) discovered a statistically significant and negative association between firm risk and dividend payout ratios. Additionally, the growth of interest income can impact dividend payment as firms that have recently experienced revenue growth tend to pay lower dividends (Chen and Dhiensiri, 2009).

According to Higgins (1972), the payout ratio is inversely related to a company's need for capital to fund growth opportunities. Additionally, Bradley, Jarell, and Kim (1984) found that firms with a higher percentage of tangible assets are able to secure debt financing at a lower expense, reducing their reliance on internally generated funds. Consequently, the capacity for collateral is expected to have a favorable effect on a firm's dividend policy. This chapter (Chapter 3) focuses on elucidating the methodology and data collection procedures employed in this research.

This section focuses on data collection and analysis to improve research comprehension. It aims to clarify the study's design elements,

including the purpose, investigation types, setting, unit analysis, and time horizon. The chapter also stresses the significance of constructing a theoretical framework and hypotheses for testing in the subsequent chapter. Furthermore, it provides detailed information about data collection methods that entail obtaining secondary data from diverse sources such as company data, journals, articles, and government publications.

The study utilized variables obtained from the DataStream financial database to identify the influential factors on dividend distribution by banks in Malaysia. It tested hypotheses regarding factors that impact dividend payments using data from 1993 to 2009 and the multiple regression method for analysis. The accuracy and reliability of findings were ensured through careful consideration of the data collection process, which is crucial for analysis, hypothesis testing, and answering research questions.

The study aimed to collect data for testing hypotheses about the factors influencing dividend payment in banks. The data were obtained from secondary sources, which are defined as information gathered and recorded by others for purposes other than the current research. Secondary data can be collected at a low cost. Two types of secondary data were used: Internal Sources, such as annual reports and other bank reports obtained from DataStream at Uitm Segamat, Johor; and External Sources, referring to sources outside the organization.

The research gathered information from a variety of sources, such as textbooks, journals, newspapers, magazines, the internet, brochures, and pamphlets. The specific topics included in the data collection were dividend per share (DPS), return on assets (ROA), debt ratio (DR), growth of interest income (II), and total fixed assets (TFA).

This study focused on Malaysian banks from 1993 to 2009 as the population. The sample

selection was based on data availability in the data stream. Specifically, this research paper chose 10 banks listed on Bursa Malaysia's main board for this research paper based on market capitalization.

The sample selection for this research is focused on achieving the main objective, considering factors such as profitability, leverage, growth, and collateral capacity of the bank. The study uses dependent and independent variables, which are analyzed using regression analysis. The dependent variable is dividend distribution (DPS), calculated by dividing the total amount distributed by the number of ordinary outstanding equity shares. One independent variable is profitability (ROA), indicating how efficiently the bank generates profit per unit of assets. Another independent variable is leverage (DR), measuring the ratio of total debt to total assets. Growth is measured by the growth of interest incomes, while collateral capacity is measured by total fixed assets (TFA). The research design for this study can be found in section 3.4.

This paper aims to investigate the correlation between dependent and independent variables in order to understand the impact of profitability (return on assets), leverage (debt ratio), growth (growth of interest income), and collateral capacity (total fixed assets) on bank dividends in Malaysia. The research design includes the purpose of study, types of investigation, unit of analysis, and time horizon. The purpose of the study is to determine the relationships between dividend distribution (dependent variable) and profitability, leverage, growth, and collateral capacity (independent variables). According to Uma Sekaran (2006), academic research can be exploratory, descriptive, or conducted to test hypotheses. The investigation in this study falls under descriptive research.

The study conducted is a casual study that explains the effects of

profitability (return on assets), leverage (debt ratio), growth (growth of interest income), and collateral capacity (total fixed assets). The unit of analysis in this paper is ten banks, including Maybank, Affin Bank, and Public Bank. The study will use yearly data from 1993-2009. According to the theoretical framework, there is a high correlation between the factors that may influence dividend payment in Malaysian banks. The dependent variable is dividend distribution (dividend per share), while the independent variables are profitability, leverage, growth, and collateral capacity. The schematic diagram illustrates that dividend distribution is determined by profitability, leverage, growth, and collateral capacity. An increase in return on assets and total fixed assets will lead to an increase in dividend payment.

When the debt ratio (DR) and growth of interest income (II) decrease, the dividend distribution of the bank will increase. The study uses the Multiple Linear Regression Model as a statistical tool to analyze the simultaneous effects of several independent variables on a dependent variable that is interval scaled. The Ordinary Least Square (OLS) approach is employed to show that the estimators of the parameter of explanatory variable satisfy statistical properties, including being best, linear, unbiased, and an estimator called BLUE. This study aims to assess the factors influencing dividend distribution to shareholders of banks in Malaysia.

The dividend per share is determined and predicted using multiple regression analysis, specifically a linear regression model represented by the equation DPS = f(ROA, DR, GRO, TFA). The chosen explanatory variables for this study are return on asset (ROA), debt ratio (DR), growth of interest income (GRO), and total fixed asset (TFA). In the equation, Y represents the dependent variable

- dividend distribution. [pic] symbolizes the constant number in the equation, [pic] represents the coefficient Beta value, [pic] stands for the independent variable for ROA, [pic] signifies the independent variable for DR, [pic] denotes the independent variable for growth of interest income (II), [pic] represents the independent variable for log of total fixed asset (TFA), and [pic] shows the error term.

Various factors can influence the dividend distribution of banks, such as return on asset, debt ratio, growth (interest income), and total fixed asset. In chapter four, we will examine these factors as hypotheses to determine their role in contributing to the dividend distribution of banks in Malaysia. To test the applicability of these hypotheses to banks, we propose the following: Hypothesis 1 - H0: There is no significant relationship between dividend per share and return on asset. H1: There is a significant relationship between dividend per share and return on asset. Hypothesis 2 - [No information provided].

The hypotheses being tested in relation to dividend per share are as follows: Hypothesis 1 posits that there is no significant relationship between dividend per share and debt ratio, while Hypothesis 2 argues that there is a significant relationship. Hypothesis 3 focuses on the correlation between dividend per share and growth of interest income, while Hypothesis 4 examines the connection between dividend per share and total fixed asset growth. H0 represents the null hypothesis, while H1 represents the alternate hypothesis.

Table 2 presents the results of the hypothesis testing. The individual tests analyze the specific relationships outlined in Hypotheses 1-3, while the overall/joint test evaluates whether all three hypotheses can be rejected concurrently. In

the individual tests, H0 assumes that each specific relationship is equal to zero, while H1 suggests otherwise. Ultimately, this research should incorporate this hypothesis testing to gain further insights.

There are various methods for conducting Hypothesis Testing, such as the T-test, F-test, P-Value, and Confidence Interval approach. Each method involves two hypotheses - the null hypothesis (H0: ? i = 0) and the alternative hypothesis (H1: ? i ? 0). The null hypothesis assumes no significant relationship between repressors and the dependent variable, while we test the alternative hypothesis using either the T-test approach or P-value approach. If the calculated t-value is higher than the critical t-value, then we reject the null hypothesis. On the other hand, the F-test deals with multiple hypotheses in one null hypothesis by simultaneously testing whether all slope coefficients in an equation are equal to zero.

In regression analysis, the F-statistic is used to test a null hypothesis that involves multiple hypotheses or a single independent hypothesis regarding a group of coefficients. If the estimated F-value is greater than the critical F-value, it means that the null hypothesis should be rejected.

To detect multicollinearity, one can use the Variance inflation factor (VIF), which acts as an indicator for assessing how much multicollinearity exists by determining how much a specific explanatory variable can be explained by all other explanatory variables in the equation. The VIF formula is as follows: VIF (? j) = 1 / (1-Rj? ). A higher value of VIF indicates a stronger degree of collinearity in variable Xj. Severe multicollinearity is typically considered when VIF (? j) exceeds 10.

To detect Heteroscedasticity using the White Test, you need

to estimate regression from the data and obtain residuals. Then, run the auxiliary regression to obtain R squared. If the computed chi-square value exceeds the critical chi-square at the chosen level of significance, there is heteroscedasticity. If it does not exceed, there is no heteroscedasticity.

To detect Autocorrelation using the Durbin-Watson d-test (Dw), you need to compute Dw (d) using the formula: Dw (d) = ? ( u t – u t-1 )? ? 2(1- d/2) ? ut. Firstly, run OLS regression to obtain residuals. Then, compute d.

Find the critical dL and dU values by considering the sample size and number of explanatory variables. Determine if H0 should be rejected or not. Look for evidence of indecision or evidence that is positive or negative for auto.