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# The Factors Determinant Tax Revenue In Malaysia

## INTRODUCTION

Malaysia is a federation of 13 States and the Federal Territories of Kuala Lumpur and Labuan. The Federal Constitution contains special provisions regarding sources of revenue that are assigned to the Federal and the State governments. Those that are assigned to the State governments include revenue fom land, forest, mining, entertainment, water supply, bank interests, returns from investments, fines including forfeitures (other than imposed by Federal Courts) and fees for licences and permits (but not licences relating to motor vehicles and registration of businesses). All other revenues, not specifically assigned to the states, are Federal Government revenues.

Taxation become crucial economic tools to govern economics for any country, especially to developing countries like Malaysia. With the rapid trend toward globalization and internationalization, the pattern of tax revenues and economic growth accross countries has become a significant concern to economists. Recently, Malaysia has also performed well and shows the similar growth pattern in economy. Therefore, fund collected from taxation used by the government to provide facilities for its population and for the development of the nation. Other than that income tax is one of the surest way to make sure the Government fund is available for spending.

Inland Revenue Board (IRB) has play their main role as an agent of Malaysian Government and to provide services in administering, assessing, collecting, and enforcing payment of income tax and other revenue as may be agreed between Government andd the Board. For many years, the Inland Revenue Board (IRB) has presumed that its activities promote better tax collection starting from Official Assessment System (OAS) until Self Assessment System (SAS).

Malaysia Federal Government revenues are broadly classified as tax revenues, non-tax revenues and non-revenue receipts. Tax revenues include both Direct and Indirect Taxes. Direct taxes are collected by the Inland Revenue Board (IRB) and includes taxes such as income tax on individuals and corporations, petroleum income tax, stamp duty and real property gains tax. While for indirect taxes the responsibility of collection is taken by the Royal Customs and Excise Department. Indirect taxes include import duties, export duties, excise duties, sales tax, service tax and last but not least; goods and services tax (GST) that replace sales tax and service tax.

Non-tax revenues of Malaysian Government consists of fees for issue of licences and permits, fees for specific services, proceeds from sale of government assets, rental of government property, bank interests, returns from Government investments (including gains from sales of investments) fines and forfeitures. The non-revenue receipts consist mainly of repayments and reimbursements such as refunds of overpayments in previous years and repayment of loans from the Federal Governmentâ€™s Consolidated Fund (Revenue Account) received from other Federal Government Agencies and State Governments.

The trend of tax collection in Malaysia is inconsistent, changing upward and downward depending upon economic conditions. However, over a 30 period, most years show an increasing incremental in total collection. The exceptions are when there is an abnormal economic condition such as financial crisis, war or increase in world oil prices.

During the early stages of its development which is in year 1960, Malaysia similar with most developing countries relied heavily on indirect taxes accounted for 76.7% (Kasipillai, 2006). However as the economy developed and with the tax reform less reliance was placed on indirect tax which starting from year 1999 the major contribution to government revenue is come from direct tax (69%). In 2008 the collection of direct tax represents 52% of the Government total revenue (Economic Planning Unit, Ministry of Finance and Bank Negara Malaysia). It is believed that the encouraging growth in Gross Gomestic Product (GDP) in 2009 stood at 23% contribute positively to the national revenue collection (9MP).

After brief introduction the remainder of this paper is structured as follow. Chapter 2 provide some sort of literature review regarding all the variables included in this research. Chapter 3 consist of research methodology and design, data collection, theoretical framework, hypothesis statement, and data analysis. Chapter 4 provides data description and result analysis and finally in section 5 gives conclusion and summary of the study.

## BACKGROUND OF STUDY

Tax is the main sources of income for government. Tax is defined as a fee charged (levied) by a government on a product, income, or activity. If tax is levied directly on personal or corporate income, then it is direct tax. If tax is levied on the price of a good or services, then it is called an indirect tax.

Malaysia is a very tax friendly country compared than the others. Income tax comparaly low and many taxes which are raised in other countries, do not exist in Malaysia. All earnings of companies and individuals acccumulated in, derived from or remitted to Malaysia are liable to tax.

Government will used this tax revenues to fund all spending made by government in order to achieve an economic growth and also to promote a sound of economy.

Government will present their budget in Parliament around September each year. Determination of budget is based on estimation of government revenue and spending. An increase in government revenue will increase the allocation for government spending. The tax rate is one of the components in government budget. The government will decide whether to increase or decrease the tax rate or to remain unchage based on the goals of government in each budget every year.

## Definition Of Terms

## Gross Domestic Product (GDP)

Gross domestic product (GDP) is the market value of all final goods and services produced within a country in a given period of time. It is also define as an economic measurement that monitors the overall income and output of a country. It is a way to interpret the overall prosperity of the economy. It is culculated on an annual basis with quarterly updates. The data produced by GDP is interpreted in number of ways. Some use it to measure the productivity of the country, in that it shows how much product was produced and sold. Others use it to measure the general health of the economy and the standard of living of those living in it.

## Inflation Rate

Inflation rate is a measure of inflation, the rate of increase of a price index. It is the percentage rate of change in price level of time. The rate of decrease in the purchasing power of money is approximately equal. The used of inflation rate is to culculate the real interest rate, as well as real increases in wages. When interest rate are high, fewer people and businesses can afford to borrow and it will usually slows the economy down.

## Unemployment

The definition of unemployment is an economic condition marked by the fact that individuals actively seeking jobs remain unhired. Unemployment is an important measure of the economyâ€™s strength. A high unemployment rate generally indicates an economy in recession with few job opportunities, while a low unemployment rate points to an economy running at or near full throttle.

## Openness

The meaning of â€œopennessâ€? has become similar to the notion of â€œfree-tradeâ€?, that is a trade system where all trade distortions are eliminated. Openness also means the extent to which an economy is open to trade, and sometimes also to inflows and outflows of international investment. The openness here means â€œâ€?trade opennessâ€? that consist of imports and exports from a large percentage of GDP.

## PROBLEM STATEMENT

Malaysia is facing budget deficit every year since government expenditure exceed government revenue. If the governmentâ€™s budget are not sufficient, some of the macroeconomic factors canâ€™t be achieved. Government cannot reduce unemployment and inflation rate and also cannot increase the economic growth and promote currency stability if they cannot reach a sufficient budget to cover all the expenditure.

Tax is the main component of government revenue that will use to finance all the government expenditure to stabilize the economy. The expenditure here means the used of governmentâ€™s revenue for the development and operational expenditure that will bring an economic growth.

This study is undertaken to discover factors determinant of tax revenue which are independent variables namely Gross Domestic Product (GDP), inflation rate, unemployment and openness (trade) on dependent variable which is tax revenue. It tries to grasp those variables volatility impact on tax revenue in a given economic environment and horizon.

Besides, this study was brought up to strenghten tho prove of previous similar study. However, due to the changing environmentof the economy, past researchers cannot be deem a suitable for current application. There is a need to revise the findings from the previous researchers, so it is consistent with current economic situation. The horizon of the research will cover from 1995 to the ending 2009. From this, all the indpendent variables are important towards dependent variable.

Therefore the problem statement for this study is which variables that have strongly positive significant relationship towards tax revenue?

## RESEARCH QUESTION

In order to realize the factors determining tax revenue, this question must be taken into consideration.

The question is:

What is the relationship between GDP and tax revenue?

What is the relationship between Inflation rate and tax revenue?

What is the relationship between Unemployment and tax revenue?

What is the relationship between Openness and tax revenue?

This question must be taken into consideration because the questions will answer the overall study and to make sure whether the problem lies within this factor or the others factor.

## OBJECTIVES OF STUDY

## General objectives

The general objective of this study is to identify the factors determine tax revenue in Malaysia from year 1990 to 2009 which is 20 years.

## Specific objectives

To know what are the factors that will increase or reduce the total tax revenue collected by government.

To determine whether growth in GDP significantly affect tax revenue collected by government.

To determine whether inflation in Malaysia significantly affect tax revenue collected by government.

To determine whether unemployment in Malaysia significantly affect tax revenue collected by government.

To determine whether the degree of openness in Malaysia significantly affect total tax revenue collected by the government.

## SIGNIFICANCE OF STUDY

This research study can help the researcher to determine the most significant independent variables to the dependent variable.

From this study, it can help the relevant parties to know which variables can give influence to the tax revenue collected government.

The findings from this research can provide the information to the other researcher for future research that is similar or related with this study.

## SCOPE OF STUDY

The scope of study is as follow:

This study focus on factors determining tax revenue collected by government. The data will be collected from 1990 to 2009 which is twenty years in yearly.

Four variables are choosen which are GDP, inflation rate, unemployment, and openness.

Software that used as a regression tool is Statistical Package for Social Science (SPSS) 16.0.

## LIMITATIONS OF STUDY

## Cost

Cost also becomes one of the limitations in doing this research because the researcher needs to bear all the cost and expenses in completing this research without getting any sponsorship. The cost that incurred such as stationeries expenses, photocopying, printing, transportation expenses and others are fully support by the researcher.

## Choice of Variables

Choice of variables is the other limitation of the study. There have many variables that are determinants tax revenue and the researcher need to choose the exact variables so that it is suitable with the dependent variable. The variables that are choosen in this study are GDP, inflation rate, unemployment, and openness.

## Data Collection

Data collection is one of the limitation of the study. The data covered a period of twenty years which is from 1990 to 2009 in yearly. Besides that, there have difficulties while choosing the exact journal and literature review that are strongly support all the variables.

## Accuracy of Data

Accuracy also become a limitation of the study. Researcher used secondary sources in conducting this stdudy to collect data. The secondary sources such as annual reports, books, article, journal that the researcher found from internet and library. So, the accuracy of data depend from all the secondary sources that found in various materials. It means that, the researcher trying to maintain the originality and quality of the journal but the data needed depend on the materials.

## CHAPTER TWO

## 2.0 LITERATURE REVIEWS

The amount of literature that directly deals with an analysis of factors that determine tax revenue collected by government in Malaysia is fairly limited.

Minea and Villieu (2009), in their research show theoretically that a tighter monetary policy should induce the government to improve institutional quality in order to limit the erosion of tax revenue. The model developed by them exhibits two interesting results. First, by finding an inverse relationship between the level of effort and the inflation target, the authors show that the lower the inflation target is, the higher the governmentâ€™s effort in enhancing the quality of its institutions will be. In other words, by setting a lower inflation target, the â€œsupra-authorityâ€? encourages the fiscal authority to intensify its effort to implement a more efficient tax-collecting administration in order to recoup the loss of seigniorage revenue due to a tighter monetary policy. Effectively, a decrease in the inflation target reduces the interval in which governmentâ€™s effort is minimal and increases the interval in which the effort in improving institutional quality is maximal. To conclude, it is important to note that the incentive of the government to improve the collection of tax revenue could be nonetheless diminished by a significant decrease of inflation rate.

Huang and Wei (2006) extended the model developed by modifying the principal-agent setup and by incorporating an indicator of financial development and social welfare function. They conclude that, conditionally to the cost of institutional reforms, pursue a low inflation target encourages the government to increase the performance of its tax collection system. Therefore the adoption of Inflation Targeting in emerging countries is expected to exert a positive effect on tax revenue collection.

Indeed, empirical literature has provided evidence that tax revenue is negatively affected by inflation, the so-called Olivera-Tanzi effect (Tanzi, 1992). This inverse relationship is usually explained by the fact that the real value of tax revenue is erode by inflation, since it exists for some tax categories a time-lag between the date of imposition and the effective collection of these taxes. Therefore, by theoretically maintaining inflation at low levels, and therefore by increasing the real value of tax revenue, Inflation Targeting may attenuate the governmentâ€™s tax collection effort.

Lucotte (2010), used a methodology suggested by Dehejia and Wahba (1999) which consists of dropping treated observations whose the propensity score is higher than the maximum or smaller than the minimum in the control group. The result shows that the estimated average treatment effect on treated (ATT) are all found to be positive and statistically significant. This suggests that, on average, Inflation Targeting has a quantitatively large and statistically significant impact on increasing public revenue in emerging market economies. This result largely support their hypothesis that the adoption of Inflation Targeting may encourage the government to improve the collection of tax revenue.

Clausing (2007), analyze the impact of the size and the profitability of the corporate sector on revenues from corporate tax. The result of her regression analysis confirm that the share of the value added of the corporate sector, profit level GDP per capita and GDP growth have a positive impact on revenues from corporate tax, whereas the unemployment level has a negative impact.

Kubatova and Rihova (years of study are not stated), found that all of their examined factors (GDP growth, inflation and unemployment) were statistically significant. Along with the growth of GDP comes the growth of revenues from corporate tax. Inflation also has a similar effect. Conversely, higher unemployment leads to a decrease of the revenues from corporate tax.

Qazi (2010), in his paper attempts to search the determinants of tax buoyancy of 25 developing countries. He found that growth in import and manufacturing sectors have positive and significant impact on tax buoyancy which shows with the increase in growth of import sector tax revenue collection increases through import duties, tariff, sales tax on import stage and withholding income tax at import stage.

Saeed, Ahmad and Akhtar (2010), have studied the impact of corruption index on the tax revenues over 27 developing countries and use annual data for the 2002 â€“ 2006 periods found that GDP per capita is positive but it is significance at 12 percent level. The coefficient of the ratio of exports and imports (openness) to GDP is positive but not significance at even 10 percent level.

## CHAPTER THREE

## 3.0 RESEARCH METHODOLOGY AND DESIGN

## RESEARCH DESIGN

## 3.1.1 Purpose of Study

The purpose of this study is to determine the factors determinant tax revenue in Malaysia namely Gross Domestic Product (GDP), inflation rate, unemployment and openness.

## 3.1.2 Research Interference

Most of the data used in this study are obtained from the secondary sources from various resources that have been analyzed. The data are collected from an internet resources.

## 3.1.2.1 Accuracy and Data Reliability

Multiple regression analysis and a correlation research design are selected as the method of this study in order to investigate the variables that are associated with the problem. Two random variables are positively correlated if high values of one are likely to be associated with high values of the other and negatively correlated if high values of one are likely to be associated with low values of the other known as correlation. A statistical method used with one dependent variable and more than one independent variable known as multiple regression analysis. Thus, the accuracy and the data reliability of the data may partly depend on the published materials.

## 3.1.3 Study Setting

Secondary data from various resources have been analyzed. Research here is a field study where it is non contrive setting with minimial interference.

## 3.2 DATA COLLECTION

In completing this study, data is the most important thing needed. From the data collected, the researcher can make analysis and interpret the output to find out the result.

## Secondary Data

It refer to the data collected by someone for some other purposes. The sources include census reports, organizational records, surveys and annual reports. This secondary data used by the researcher to gain the idea and information to develop the literature review and complete this study.

## 3.2.1.1 Internet and website

## Google Search

The major sources that the researcher choose to find and gather journal that related with this study. This website are useful to the reasercher because help the researcher to gain the information about this study.

## 3.2.1.2 Library Research

The researcher find the journal and books through the library reserach. Some of the information from journals and published materials can be used as references to the researcher to get a better picture of the situation.

## THEORETICAL FRAMEWORK

## INDEPENDENT VARIABLES

## GDP

## Tax

## Revenue

## Inflation Rate DEPENDENT VARIABLE

## Unemployment

## Openness

## Figure 1.0: Theoretical Framework

Based on the figure 1.0 above, it shows the relationship between the dependent variable which is Tax Revenue and the independent variables that includes Gross Domestic Product (GDP), Inflation Rate, Unemployment and Openness (trade). All these independent variables will be test to determine the relationship among these independent variables and dependent variables.

## 3.3.1 Priory Relationship

1. GDP and Tax Revenue : if GDP increase, the total tax revenue collected by government will also increase. This two variable have a positive relationship.

2. Inflation Rate and Tax Revenue : if an inflation rate increase, the total tax revenue collected by government will decrease. This two variable have a negative relationship.

3. Unemployment and Tax Revenue : if unemployment increase, the total tax revenue collected by government will decrease. This two variable have a negative relationship.

4. Openness and Tax Revenue : if the degree of openness increase, the total tax revenue collected by government will also increase. This two variable have a positive relationship.

## HYPOTHESIS STATEMENT

The purpose of the hypothesis statement is to illustrates which of the hypothesis is most affect the dependent variable. The hypothesis are:

H0 : GDP is not statistically significant to affect tax revenue in Malaysia

H1 : GDP is statistically significant to affect tax revenue in Malaysia.

H0 : Inflation is not statistically significant to affect tax revenue in

Malaysia

H1 : Inflation is indeed statistically significant to affect tax revenue in

Malaysia.

H0 : Unemployment is not statistically significant to affect tax revenue in

Malaysia.

H1 : Unemployment is indeed statistically significant to affect tax

Revenue in Malaysia.

H0 : Openness is not statistically significant to affect tax revenue in

Malaysia.

H1 : Openness is indeed statistically significant to affect tax revenue in

Malaysia.

## DATA ANALYSIS

In this study, the data analysis need to be explained clearly. The data also consists of independent variable and dependent variable which is GDP, inflation rate, unemployment and openness . Pearson coefficient of correlation is used to the extent of relationship among different variables. All the data has been analyzed by using Statistical package Science for Social (SPSS) program. The data will be examine by:

## Beta analysia (Coefficient)

To find out the relationship between independent variables and dependent variable. Does the relationship exist or not.

## Coefficient of Determination (R-squared)

To know how well the independent variables explain the variation of the dependent variable in the regression.

## T-Statistic

Identify significant relationship of each independent variable with the dependent variable

## F-Statistic

Testing the significance of the overall independent variables with the dependent variable

## Standard Error of Estimation (See)

The objective is to identify whether a particular variableis significant at a certain level of confidence.

## Multiple Regression Analysis

TR = f ( GDP, Inf, Un, Op )This technique will focus on a relationship between a dependent variable and one or more independent variable. The regression analysis help the researcher to understand how the typical value of the dependent variable changes when any one of the independent variable is varied, while the other independent variables are held fixed.

## TR = a + b1 GDP + b2 Inf + b3 Un + b4 Op + É›

Where:

TR = Tax Revenue

GDP = Gross Domestic Product

Inf = Inflation Rate

Un = Unemployment

Op = Openness

The dependent variable in the above equation is tax revenue while the independent variables are GDP, inflation rate, unemployment and openness.

## Beta Analysis (Coefficient)

Beta analysis is a measurement used in order to find out the relationship between independent variables and dependent variable does exist or not. Therefore, if the result is positive that means the independent variables can explain the changes in the dependent variable.

## Coefficient of Determination (RÂ²)

The coefficient of determination is a statistic that will give information the goodness of fit of model. It is a statistical measure of how well the regression line approximates the real data points. Is a descriptive measure between zero and one, indicating how good one term is at predicting another. The value of coefficient of determination is shown below:

## Range of RÂ² Strength of relationship

No relationship with dependent variable

0.1 to 0.5 Weak relationship between independent variables

and dependent variable

0.6 to 0.9 Dependent variable is strongly explained by

independent variables

1 Dependent variable ia perfectly explained by

Independent variables

## T-Statistic

T-statistic is used to determine whether the significance between the dependent variable and the independent variables exists or not. If the computed T-stat is greater than book T-value, the independent variable is statistically significant or vice-versa. In order to get book T-value, the degree of freedom should be culculated at a 95% confidence interval.

The degree of freedom can be calculated as follow:

Degree of freedom = n â€“ k â€“ 1

Where: k = Number of Independent Variable

n = Number of Observation

The results for T-statistic:

Accept H1, reject H0

If the computed t-statistic is greater than the book T-value at a 95% confidence interval.

Reject H1, accept H0

If the computed t-statistic is lower than the book T-value at a 95% confidence interval.

## F-Statistic

F-test is an overall test of the null hypothesis that group means on the dependent variable do not differ. It is used when comparing statistical models that have been fit to a data set, in order to identify the model that best fit the popultaion from which the data were sampled. F-test mainly arise when the models have been fit to the data using least squares. In order to get book F-value, it should be culculated at a 5% significant level.

Formula for book F-value is as follow:

Book F-value = FÎ± (k â€“ 1, n â€“ k)

Where:

Î± = Significant level (5%)

k = Number of Independent Variable

n = Number of Observation

k â€“ 1 = Numerator

n â€“ k = Denominator

The result for F-Statistics:

Accept H1, reject H0

If the computed F-Statistic is greater than the book F-value at 5% significant level.

Reject H1, accept H0

If the computed F-Statistic is lower than the book F-value at 5% significant level.

## 3.5.6 Standard Error of Estimation (See)

It is a measure of the dispersion of tthe data points from the regression line. Itâ€™s objective is to identify whether a particular variable is significant at a certain level of confidence. Standard error can be measured in two ways:

Using T-stat

See = b

t-stat

Degree of freedom

Df = n â€“ k â€“ 1

It is also useful in determining the range in which the dependent variable will point to a specified probability.

## CHAPTER FOUR

## 4.0 DATA DESCRIPTION AND ANALYSIS

This chapter focuses on the data description and result analysis. All the data collected in this study were processed using Microsoft Office Excel and the SPSS program. Microsoft Office Excel was used to describe the performance of dependent variable and independent variables. SPSS program was used to analyze the data from the correlation and regression analysis. The method was used to analyze the data was Multiple Regression Correlation Analysis. A multiple regression analysis involves more than one independent variable.

The process of evaluating is the same with simple regression, but in order to derive the estimated regression, a computer is employed due to the complex nature of data and time required. The presentation of findings is made to examine the relationship among independent variables (GDP, inflation, unemployment and openness) and dependent variable (tax revenue).

This study used Multiple Regression Method Analysis which is the interpretation of Regression Analysis includes Beta Analysis (Coefficient), Coefficient of determination (R-Squared), T-statistics and F-statistics.

## 4.1 DATA DESCRIPTION

## Dependent Variable

## Figure 1

## Independent Variables

## Figure 2

Gross Domestic Product is the value at current prices of the total annual output of final goods and services produced in a country. ........

## Figure 3

Inflation rate is the percentage annual increase in the general price level, commonly measured by the consumer price index (CPI) or some comparable price index. .......

## Figure 4

Unemployment rate is ......

## Figure 5

Openness is ......

## 4.2 INTERPRETATION OF DATA AND FINDINGS

## 4.2.1 Research Analysis

From the data obtained, it shows the result of regression output as stated in Table 1 as follows:

## Table 1

## Variables

## Constant

## GDP

## Inflation

## Unemployment

## Openness

## Beta Analysis

-144980.369

13.481

1657.557

5860.522

-572.845

## T-statistics

8.284

5.562

3.435

2.643

7.017

R-squared : 0.990

F-statistics : 358.696

Standard error of estimation : 6122.50419

## 4.2.2 Regression Equation

From the result obtained, we can derive the regression linear function as follows:

General function:

TR = f ( GDP, Inf, Un, Op )

Multiple Regression Equation:

TR = a + b1 GDP + b2 Inf + b3 Un + b4 Op + É›

TR = â€“ 144980.369 + 13.481 GDP + 1657.557 Inf + 5860.522 Un

â€“ 572.845 Op + É›

## 4.3 RESULT OF FINDINGS

## 4.4.1 Beta Analysis (Coefficient)

Beta analysis is a measurement used in order to find out whether a relationship exists between the independent variables and the dependent variable.

Table 2: The result of beta analysis

## Variables

## Beta Analysis

## GDP

13.481

## Inflation

1657.557

## Unemployment

5860.522

## Openness

-572.845

## Beta analysis for Gross Domestic Product (GDP)

From the results obtained, it shows that when GDP increase by 1 unit, tax revenue will increase by 13.481 units. The increase in GDP will raised the total tax revenue collected by government. It shows that this two variable have a positive relationship and consistent with the economic theory. This is because .....

Beta analysis for Inflation

From the results obtained, it shows that an increase of 1 unit in inflation can explain an increase of 1657.557 units in tax revenue. The increase in inflation will increase the total tax revenue collected by government. It shows that this two variable have a positive relationship and not consistent with the economic theory. This is because .......support dengan LR.

Beta analysis for Unemployment

From the results obtained, it shows that when an unemplyment increase by 1 unit, tax revenue will increase by 5860.522 units. The increase in an unemployment will raised the total tax revenue collected by government. It shows that this two variable have a positive relationship and not consistent with the economic theory. This is because ....... support dengan LR.

Beta analysis for Openness

From the results obtained, it shows that when an openness increase by 1 unit, tax revenue will decrease by 572.845 units. The increase in an openness will reduced the total tax revenue collected by government. It shows that this two variable have a negative relationship and not consistent with the economic theory. This is because ....... support dengan LR.

## 4.4.2 Coefficient of Determination (R-squared)

Coefficient of determination or R-squared measures what percentage of a change in the dependent variable can be measured or explained by the change in the independent variables. It is also explains the level of the explanatory power.

If R-squared = 0 (no explanatory power)

This means that none of the change in the dependent variable can be measured by the change in the independent variables. The estimated equation is useless.

If R-squared = 1 (full explanatory power)

This means 100% of the change in the dependent variable can be explained by the change in the independent variables.

From the results obtained, it shows that R-squared is 0.990. This means that 99% change in the dependent variable can be explained by the change in independent variables. However, 1% can be explained by other variables. This means that the dependent variable is strongly explained by independent variables. Besides, it also has an accepted higher explanatory power by 99%.

## 4.4.3 T-statistic

T-statistic is used to determine whether the significance between the dependent variable and the independent variables exists or not. If the computed T-stat is greater than book T-value, the independent variable is statistically significant or vice-versa. In order to get book T-value, the degree of freedom should be culculated at a 95% confidence interval.

Degree of freedom = n â€“ k â€“ 1

= 20 â€“ 4 â€“ 1

= 15

From the T-distribution table, the book T-value is 2.131 at 95% confidence interval level.

Table 3: The results of T-statistic

## Variables

## T-statistics

## Findings

GDP

5.562 > 2.131

Significant

Inflation

3.435 > 2.131

Significant

Unemployment

2.643 > 2.131

Significant

Openness

7.017 > 2.131

Significant

## T-statistic for Gross Domestic Product (GDP)

From the results obtained, the culculated T-value is higher than the book T-value (5.562 > 2.131) at a 95% confidence interval.

H0 : GDP is not statistically significant to affect tax revenue in

Malaysia.

H1 : GDP is statistically significant to affect tax revenue in

Malaysia.

Therefore, we accept H1 and reject H0 because gross domestic product (GDP) is statistically significant to affect tax revenue in Malaysia.

## T-statistics for Inflation

From the results obtained, the culculated T-value is higher than the book T-value (3.435 > 2.131) at a 95% confidence interval.

H0 : Inflation is not statistically significant to affect tax revenue in

Malaysia

H1 : Inflation is indeed statistically significant to affect tax revenue

in Malaysia.

Therefore, we accept H1 and reject H0 because inflation is indeed statistically significant to affect tax revenue in Malaysia.

## T-statistics for Unemployment

From the results obtained, the culculated T-value is higher than the book T-value (2.643 > 2.131) at a 95% confidence interval.

H0 : Unemployment is not statistically significant to affect tax

revenue in Malaysia.

H1 : Unemployment is indeed statistically significant to affect tax

revenue in Malaysia.

Therefore, we accept H1 and reject H0 because unemployment is indeed statistically significant to affect tax revenue in Malaysia.

## T-statistics for Openness

From the results obtained, the culculated T-value is higher than the book T-value (7.017 > 2.131) at a 95% confidence interval.

H0 : Openness is not statistically significant to affect tax revenue

In Malaysia.

H1 : Openness is indeed statistically significant to affect tax

revenue in Malaysia.

Therefore, we accept H1 and reject H0 because openness is indeed statistically significant to affect tax revenue in Malaysia.

## 4.4.4 F-statistics

F-statistic is used to test the hypothesis that the variation in the independent variables explained a significant portion of the variation in the dependent variable. The formula of book F-value is as follow:

Book F-value = FÎ± (k â€“ 1, n â€“ k)

= F0.05 (5 â€“ 1, 20 â€“ 5)

= F0.05 (3, 16)

Numerator Denominator

From the F-distribution table, the book F-value is 3.06. The culculated F-statistic is 358.696 > 3.06 that means all the independent variables (GDP, Inf, Un and Op) are said to be statistically significant.

H0 : All the independent variables are not significant enough to

affect total tax revenue collected by government in Malaysia.

H1 : All the independent variables are significant enough to

affect total tax revenue collected by government in Malaysia.

From the results obtained, we accept H1 and reject H0 since there is significance for the overall model.

## 4.4.5 Standard error of estimation (See)

It is a measure of the dispersion of the data points from the regression line. Itâ€™s objective is to identify whether a particular variable is significant at a certain level of confidence. Standard error of estimation can be measured in two ways by using T-statistic and degree of freedom.

It also useful in determining the range which dependent variable will point to within a specified probability. From the results obtained, the standard error of estimation is 6122.50419, which means the smaller the standard error, the closer the data points are to the regression line.