FINAL REPORT3

ResearchResearchResearchResearch ProposalProposalProposalProposal (MGT(MGT(MGT(MGT 666648484848))))

TitleTitleTitleTitle :::: DeterminantsDeterminantsDeterminantsDeterminants OfOfOfOf CreditCreditCreditCredit CardCardCardCard DefaultDefaultDefaultDefault inininin

MalaysiaMalaysiaMalaysiaMalaysia

PreparedPreparedPreparedPrepared bybybyby :::: AmirahAmirahAmirahAmirah LiyanaLiyanaLiyanaLiyana bintibintibintibinti AminuddinAminuddinAminuddinAminuddin

StudentStudentStudentStudent IDIDIDID :::: 2012457358201245735820124573582012457358

Class:Class:Class:Class: BMB5AbBMB5AbBMB5AbBMB5Ab

PreparedPreparedPreparedPrepared forforforfor :::: Dr.Dr.Dr.Dr.WahidaWahidaWahidaWahidaAhmadAhmadAhmadAhmad

2

ACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENT

Foremost, I wish to count my blessings and thanked Allah s.w.t for providing me

with the mental and physical to faculties as well as other positive attributes notably

perseverance to complete this research report. Special mention goes to my Research

Methodology lecturer, Dr. Wahida Binti Ahmad for her guidance, supervision and support.

Her constructive comments and suggestions greatly assist in the successful completion of

this research paper.

I also take this opportunity to extend my appreciation to all those who have assisted

in one way or another in the completion of this research paper. Sincere thanks to all my

friends for their understanding, kindness and moral support during the testing time

undertook to complete this assignment. Last but not least, my deepest gratitude to my

beloved parents for their unwavering support, invaluable assistance and sincere blessings.

Thank you.

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ABSTRACTABSTRACTABSTRACTABSTRACT

This paper analyses the relationship between macroeconomic factors and the credit

card default in Malaysia from 2007 to 2013. Credit card default can be defined when the

credit card holders are unable to pay the minimum repayment for three consecutive

months or more. The macroeconomics factors that influence the credit card default in

Malaysia are interest rate, unemployment rate and also industrial production index. The

empirical findings suggest that the credit card default depends on the interest rate and

unemployment rate while industrial production index is independent to credit card default.

This study uses multiple linear regression models to analyze the relationship between

macroeconomic factor and the credit card default. The macroeconomic factors which are

interest rate, unemployment rate and also industrial production index give major impact

towards the credit card default in Malaysia.

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TABLETABLETABLETABLEOFOFOFOFCONTENTSCONTENTSCONTENTSCONTENTS

No. Title Page Number

1. IntroductionIntroductionIntroductionIntroduction

i. Introduction

ii. Background of study

iii. Problem Statement

iv. Research Questions

v. Research Objectives

vi. Scope of Study

vii. Significance of the Study

viii. Limitations of Study

ix. Summary

6

7

8

9

9

9

10

10

11

2. LiteratureLiteratureLiteratureLiterature ReviewReviewReviewReview

i. Introduction

ii. Unemployment Rate

iii. Interest Rate

iv. Level of Income

v. Summary

12

12

13

14

15

3. ResearchResearchResearchResearchMethodologyMethodologyMethodologyMethodology

i. Introduction

ii. Data collection

iii. Variables

iv. Research Design

v. Research Framework

vi. Hypotheses Statement

vii. Sampling Design

viii. Test Consideration for Data Analysis

ix. Summary

16

16

16

18

19

20

20

21

23

4. DataDataDataDataAnalysisAnalysisAnalysisAnalysis

i. Introduction 24

5

ii. Descriptive Statistics

iii. F-Test

iv. Coefficient of Determination

v. Adjusted Coefficient of Determination

vi. Correlations Matrix

vii. Covariance Matrix

viii. Multiple Linear Regressions

ix. Summary Hypotheses Statement

x. Summary of the Result

xi. Summary

24

26

26

26

26

27

28

30

31

32

5 ConclusionConclusionConclusionConclusion andandandand RecommendationsRecommendationsRecommendationsRecommendations

i. Introduction

ii. Discussion

iii. Recommendations

iv. Conclusions

v. Summary

33

33

35

36

37

6 ReferencesReferencesReferencesReferences 38

7 AppendicesAppendicesAppendicesAppendices 41

6

CHAPTERCHAPTERCHAPTERCHAPTER I:I:I:I: INTRODUCTIONINTRODUCTIONINTRODUCTIONINTRODUCTION

1.1.1.1.0000 IntroductionIntroductionIntroductionIntroduction

This study is to examine the factors that influence the credit card default in Malaysia.

This chapter will discuss briefly on the background of the study, problem statement,

research questions, research objectives, significant of study and also provide a summary

of chapter 1. For the research question and research objectives, the researcher divided it

into two sections which are main and specific. Here, an explanation of the dependent and

independent variables is provided and this study to discover the relationship of the

variables mentioned. Specifically, it is to examine the relationship of the selected

macroeconomic variables and the credit card default in Malaysia.

In the background study and as mentioned above, this research will discuss more

about the dependent and independent variables. Dependent variables in our research are

the credit card default in Malaysia while for the independent variables are the selected

macroeconomic factors. The macroeconomic factors that are mentioned above are interest

rate, unemployment rate and industrial production index. It is presumed that the selected

independent variables have a significant influenced on the credit card default in Malaysia.

This relationship is the subject matter of the problem statement of this research whereby

it is to determine the extent of the macroeconomic factors influence.

This research will involve formulation of research questions related to the theoretical

framework of the research. There are two types of research questions. Firstly is the main

research question and secondly are specific research questions. The main research

question is related to the dependent variable that is the nexus or center of the research

study. The specific research questions are aimed at supporting the validity of the outcome

of the main research question.

Furthermore, in this research the objective is divided into two. First is the main

research objective and secondly are the specific research objectives. Here also, the

significance of the study will be highlighted which could provide the credit card

consumers for better understanding before applying for credit card. In this chapter also,

the researcher stated the limitation of the study where the constraint when doing this

research report. Last but not least, the researcher make a conclusion of chapter 1 in a

summary which tell overall about the credit card default..

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1.11.11.11.1 BackgroundBackgroundBackgroundBackground ofofofof StudyStudyStudyStudy

Credit card are widely used as a transactional medium nowadays. The increasing

usage of credit card is because of the convenience and other benefits offered by credit

card. There are three basic type of credit card which are Classic, Gold, and Platinum.

These card will be issued to the card holder based on the income of an individual and

other criteria set by the bank. Credit card can be known as medium of borrowing. This is

because credit card enable the card holders to make purchases on credit term. Interest rate

will be charged from the outstanding balance of the credit card. Usually, credit card offers

high interest rate. According to Bank Negara Malaysia (2007), the interest rate will be

reduced to maximum charge of 18% per year to not more than 15% per year. The ceiling

rate of 18% is still applicable to the card holder. However, some of the credit card issuer

will offer different credit card interest rate. Credit card issuer can charge the interest rate

between 15% to 18%, not more than 18%. Credit card rates have tended to be higher and

stickier than other loans rate. The high interest rate charged on the credit card is because

the interest rate is the credit card issuer's profit. This is why the credit card issuer charged

higher interest rate.

The simple convenience provided by the credit card are the card holders will not

have to worry about the exact amount of available fund when making purchases. Other

than that, credit card are safer from theft compared to cash. This is the reason why elderly

prefer to use credit card. Next, credit card can be a useful medium for travel. The credit

card can be used to reserve hotel, plane ticket, renting car, and others.

Credit card encourage people to spend money that they do not have and spend more

than they earn. When the card holder makes a lot of purchases using credit card, the credit

card outstanding balance will be higher and it will leave people in financial trauma. Other

than that, the late payment for credit card will be charge with higher interest on the

outstanding balance and hence, the outstanding balance will increase. When the

outstanding balance is high, there is a tendency for the card holder to default the credit

card and lastly, it will lead them to bankruptcy.

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Credit card default can be defined as the credit card holders are unable to pay the

minimum payments for three consecutive months or more which the missing payments

are recorded changes over time as the payments are made. (Thomas, Edelman, & Crook,

2002).

In a nutshell, credit card holders need to use their credit card wisely and repay the

minimum amount of the outstanding balance every month in order to avoid the higher

interest rate and credit card default.

1.21.21.21.2 ProblemProblemProblemProblem StatementStatementStatementStatement

Credit card was introduced in Malaysia during mid 1970. Almost twenty thousand

credit cards were issued during that time (Loke, 2007). By owning a credit card, it can

reflect social high status and considered as prestigious. However, the process for applying

and owning credit card is easy as the bank is flexible about the criteria required to own a

credit card for the past ten years. Hence, the flexibility caused the number of cards in

circulation increase to 87.9 million as at 2013 (Bank Negara Malaysia (BNM) Monthly

Statistical Bulletin, 2014).

Credit card can lead the card holders to buy more than they earn. By spending more

than they earn with credit card, it can cause the card holders to delay the credit card

repayment since they are out of money to repay the minimum amount required. Late

repayment on the credit card balance will be charged with higher interest rate on the

credit card balance and the possibility to default the credit card is high.

There are also several factors that leads to credit card default other than higher

interest rate. We need to identify and examine the underlying factors of the credit card

default in order to solve the problem. This can help the credit card holders to manage

their credit card outstanding balance and prevent credit card default. In this research

project, the researcher thinks that macroeconomic factors such as unemployment rate,

interest rate and production index does affect the credit card default.

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1.1.1.1.3333 ResearchResearchResearchResearch ObjectiveObjectiveObjectiveObjective

1.1.1.1.33331111 MainMainMainMain ResearchResearchResearchResearch ObjectiveObjectiveObjectiveObjective

To investigate whether there is a relationship between selected macroeconomic

factors and credit card default.

1.1.1.1.3333.2.2.2.2 SpecificSpecificSpecificSpecific ResearchResearchResearchResearch ObjectiveObjectiveObjectiveObjective

I. To investigate whether there is a relationship between interest rate and credit

card default.

II. To investigate whether there is a relationship between unemployment rate

and credit card default.

III. To investigate whether there is a relationship between industrial production

index and credit card default.

1.1.1.1.4444 ResearchResearchResearchResearch QuestionQuestionQuestionQuestionssss

1.1.1.1.4444.1.1.1.1 MainMainMainMain ResearchResearchResearchResearch QuestionQuestionQuestionQuestion

What are the relationship between the selected macroeconomic factors and credit

card default?

1.1.1.1.4444.2.2.2.2 SpecificSpecificSpecificSpecific ResearchResearchResearchResearch QuestionQuestionQuestionQuestion

I. What is the relationship between interest rate and credit card default?

II. What is the relationship between unemployment rate and credit card default?

III. What is the relationship between industrial production index and credit card

default?

1.51.51.51.5 ScopeScopeScopeScope ofofofof StudyStudyStudyStudy

The main purpose of the study is to analyze the determinants of credit card default

focusing on macroeconomic factors in Malaysia. In this research it will only focus on

selected macroeconomic variables such as interest rate, unemployment rate and industrial

production index. Data selection takes into consideration the availability of data and their

consistency. All the required data were obtained from 2007 to 2013.

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1.61.61.61.6 SignificanceSignificanceSignificanceSignificance ofofofof StudyStudyStudyStudy

The research project done is to obtain information in order to gain better

understanding about the effect of macroeconomic variables towards the credit card

default in Malaysia. In this research, it is assumed that there is a strong relationship

between the macroeconomic variables and the credit card default. The research findings

could provide the basis for a deeper and more accurate understanding of the

macroeconomic factors towards credit card default for the society especially credit card

holders. Other than that, this research will benefit to the future researchers by providing

more knowledge and information. Future researchers can use the findings from this

research paper in order to construct their research and also as a guideline for their future

research in order to enable them to make better analysis.

1.71.71.71.7 LimitationsLimitationsLimitationsLimitations ofofofof StudyStudyStudyStudy

I. LackLackLackLack ofofofof InformationInformationInformationInformation

The information about this research paper is gathered through secondary data

such as journals, and text book. The journals for the topic of interest for this research

paper are limited and therefore, there will be lack of information.

II. DataDataDataData ReliabilityReliabilityReliabilityReliability andandandandAccuracyAccuracyAccuracyAccuracy

Data used in this research is from the secondary data obtained from Trading

Economics and BNM Monthly Statistical Bulletin. Thus, its reliability and accuracy

will depend entirely on the published materials.

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1.81.81.81.8 SummarySummarySummarySummary

In chapter one, the paper introduces the selected macroeconomic variables which are

interest rate, unemployment rate and industrial production index against the credit card

default in Malaysia. Here, the research study highlight the research background as well as

the significant of the relationship between the selected macroeconomic factors and the

credit card default. It then progresses to the problem statement, research questions and

research objectives. The scope of the study and its limitations are given. In this chapter,

the significance of the relationship between the selected macroeconomics factors and the

credit card default is stressed so that the credit card consumer will be aware before

applying for credit card.

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CHAPTERCHAPTERCHAPTERCHAPTER 2:2:2:2: LITERATURELITERATURELITERATURELITERATURE REVIEWREVIEWREVIEWREVIEW


This chapter provided information related to this study which was obtained from

previous literatures to serve for supporting the whole study. In reviewing the literature on

this area of study, it was found that there has been a lot of studies in credit card default

which are related with macroeconomic factors. Actually there are many factors that will

give impact towards credit card default but the most significance is interest rate,

unemployment rate and also industrial production index. This chapter would tell the

broad to the narrow of the research which explain the macroeconomic factors that impact

on credit card default. The findings from the empirical results of the study would explain

the significant relationship of the variables in relation to the credit card default in

Malaysia.

2.22.22.22.2 UnemploymentUnemploymentUnemploymentUnemployment RateRateRateRate

According to World Bank, unemployment can be defined as share of the labor force

which are not working but available for and seeking for employment. Unemployment can

also be considered as unexpected event or shock. For example, when the company is in

the middle of financial crisis which leads to bankruptcy, laying off workers is one of the

way to solve the problem and hence, unemployment happens.

Credit card default is significantly affected by unemployment (Sumit Argawal and

Chunlin Liu 2003, Tony Bellotti and Jonathan Crook 2013). This can be proved that when

individuals is unemployed, they will find it difficult to repay their credit card debt and

hence, the credit card overdue balances and the credit card default rate will be increase.

Other than that, Agarwal and Liu (2003) further studied the impact of unemployment over

time on credit card defaults. Using account level data, for over 700,000 accounts from

1995 to 2001, including the recent recession, they found that credit card default rates

varied with local unemployment conditions over time. Grieb, Hegji, and Jones (2001)

also found that unemployment will leads to the credit card default rates. On the other

hand, Figuera, Glen, and Nellis (2005) found that the credit card balances that are three

months overdue which considered as default is related to the unemployment rate by using

quarterly data for 1993–2001.

13

However, there is previous study shows that unemployment rate does not affect the

credit card default. Gross and Souleles (2002) used a panel data of over 200,000 credit

card borrowers and found out that none of the unemployment rate in the country of

residence is significantly related to delinquency.

Therefore, this research project is considering to use unemployment rate as

independent variable in order to examine whether unemployment rate affect credit card

default or not because previous empirical studies shows that unemployment does affect

and does not affect credit card default.

2.32.32.32.3 InterestInterestInterestInterest raterateraterate

Credit card interest rate tend to be higher than the other types of loan rates. Credit

card is the most profitable business for a bank other than other parts of the bank's

business. Ausubel (1991) found that during the 1980s, bank credit card operations earned

three to five times the rate of return earned overall in the banking industry. Banking

institutions may compensate the default rates of the bank by charging higher interest rates

and fees. Other than that, Ausubel (1991) found that the bank will face a situation which

is credit card holder who accept worse credit card offer are more likely to default their

credit card. Credit card offer are the interest rate, and other fees that need to pay to the

credit card issuer.

Previous studies from Bellotti and Crook (2009) using a sample of credit cards issued

by a United Kingdom (UK) bank between 1997 and 2001 found out that interest rate had

a significant effect on the credit card default. Other than that, according to Joanna Stavins

(2000), using detailed panel data on individual credit card issuers in the United States

between 1990 to 1999, the researcher found out that banks that charge higher interest

rates have higher credit card default rates. However, with the higher interest rate, the

banks tend to have higher revenue than other issuers of credit card. Next, previous

researchers found that higher interest rate will affect the ability of the borrowers to pay

their credit card outstanding balances. When interest rate increased, many of the credit

card borrowers will default their credit cards (Arner, 2009, Crouchy, Jarrow, and Turnbull,

2008). Other than that, Sangkyun Park (1997) conducted a study on the effect of credit

card interest rate on the default of credit card and the result was the credit card interest

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rate have a significant effect on the credit card default. There is also previous researchers

found out that interest rate is significantly negative with credit card default. According to

Grieb, Hegji, and Jones (2001), interest rate is significantly, negatively related to the

current level of interest rate.

However, a study conducted by Sule Alan (2013), found out that there is no effect on

the interest rate increase on the probability of a client to become default. There is

previous researchers found that interest rate

Therefore it can be concluded that interest rate will affect and will not affect the

credit card default. Therefore, this research project will use interest rate as the

independent variable in order to examine whether interest rate are positive or negatively

related with credit card default.

2.42.42.42.4 LevelLevelLevelLevel ofofofof IncomeIncomeIncomeIncome

Income plays an important role in applying credit card. Before banks approve the

applications for credit card, usually banks will take into consideration about the

applicant's income. The minimum income that is applicable for the applicants to apply for

the credit card in Malaysia is RM 24,000 per annum. (BNM, 2014). Income has been

found to have a positive relationship with credit card use (Adcock et al. 1977, Wang et al.

2011, Wasberg et al. 1992). Some researchers found out that lower income families use

credit cards more than the higher income families (Danes and Hira, 1990). Credit cards

provide a line of credit that is easier to access and lower cost to the lower income

families.

Sullivan and Fisher (1988) found a significant effect of income on the risk of debt

repayment difficulty. The lowest income group of 37% of households reported

delinquency but only 7% of the highest income group reported delinquency in debt

repayment. Other than that, during September 2009 in Turkey, the World Bank released

the results of a survey of 2100 households for the effects of the economic crisis on the

welfare of the families. In the report, it stated that almost three quarters of the families

experienced reductions in income between October 2008 and June 2009 (World Bank,

2009). Therefore, with the reductions in income, the level of credit card default have been

rising in Turkey. Moreover, previous studies done by B. Scholnik et al. (2012), they found

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out that poorer individuals fails to repay their credit card debt and hence, leads to credit

card default. On the other hand, according to Tony Bellotti and Jonathan Crook (2012),

with an increase in income of the individuals, the default on the debt repayment will be

decrease as people have more available money to pay off their debts.

However, there are also some researchers that does not agree that level of income is

significantly affect credit card repayment. Previous study done by Canner and Luckett

(1990) found out that income have no significant effect on the debt repayment.

In a nutshell, previous studies shows two different results which are income will

affect and does not affect the credit card default. Therefore, this research project will

focus on level of income as the independent variable in order to examine the relationship

between income and credit card default.

2.52.52.52.5 SSSSummaryummaryummaryummary

In summation, this chapter have tried to review all available literature from previous

researchers finding on the topic as well as the dependent and independent variables

chosen for this research. This review is used as a basis and support for the study.

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CHAPTERCHAPTERCHAPTERCHAPTER 3333 :::: RESEARCHRESEARCHRESEARCHRESEARCHMETHODOLOGYMETHODOLOGYMETHODOLOGYMETHODOLOGY


In this chapter, the focus is on the methodology used in the study. It include the data

collection, data source, variables, research design, theoretical research framework,

sampling design, test consideration for data analysis, hypotheses statements and

conclusion. A total of three selected economic variables namely interest rate,

unemployment rate, and industrial production index and the dependent variable is credit

card default.

3.23.23.23.2 DATADATADATADATACOLLECTIONCOLLECTIONCOLLECTIONCOLLECTION

3.2.13.2.13.2.13.2.1 SecondarySecondarySecondarySecondary DataDataDataData

The researcher is concentrating on using secondary data for this research paper.

The data obtained are from various sources such as Trading Economics and BNM

Monthly Statistical Bulletin. The researcher is using time series data that comprises

from year 2007 to year 2013 for the dependent variable and independent variables.

3.33.33.33.3 VARIABLESVARIABLESVARIABLESVARIABLES

3.3.13.3.13.3.13.3.1 DependentDependentDependentDependent VariableVariableVariableVariable

In this research, the credit card default is the dependent variable where it

indicates the outcome of the changes in the independent variables.

3.3.23.3.23.3.23.3.2 IndependentIndependentIndependentIndependent VariablesVariablesVariablesVariables

Interest rate, unemployment rate and industrial production index are the

independent variables used in the research in order to find the relationship between

dependent and independent variables in order to get the final result of this research.

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VariablesVariablesVariablesVariables NotationNotationNotationNotation UnitUnitUnitUnit DefinitionDefinitionDefinitionDefinition SourcesSourcesSourcesSources

IIIIndependentndependentndependentndependent

Interest Rate IR % Average rate of interest charged on

loans by commercial banks to

individuals and companies.

BNM

Monthly

Statistical

Bulletin

Unemployment

Rate UR %

Labor force that is without work but

available and seeking for employment.

Trading

Economics

Industrial

Production

Index

IPI %

Measures the output of businesses

integrated in industrial sector of the

economy such as manufacturing,

mining, and utilities.

Trading

Economics

DependentDependentDependentDependent

Credit card

default

CD RM

Credit card holders are unable to pay

the minimum payments for three

consecutive months or more which the

missing payments are recorded

changes over time as the payments are

made.

BNM

Monthly

Statistical

Bulletin

For interest rate, the researcher will measured using the average lending rate given by

the banking institutions as proxy. Based on the study conducted by Tony Bellotti and

Jonathan Crook (2009), the study is using base lending rate as to measure the interest rate.

However, the base lending rate data does not varies and therefore, the researcher is using

average lending rate to measure the interest rate. The unit for this independent variable is

percentage of the average interest rate in Malaysia. For unemployment rate, the

researcher follows the study done by Grieb, Hegji, and Jones (2001), using

unemployment rate in order to assess the job market condition. The unit for

unemployment rate will be the percentage of unemployment rate in Malaysia. Industrial

production index is used as proxy to level of income. Based on Tony Bellotti and

Jonathan Crook (2009), level of income is proxy to gross domestic product (GDP).

However, since the GDP data is only for quarterly, therefore, the researcher is using

industrial production index as proxy to level of income. This is because the data for

18

industrial production index available monthly. This can be supported with the study

conducted by Konstantinos Loizos and John Thompson (2001) that used industrial

production index as proxy to real income since the data of GDP is not available monthly.

The unit of industrial production index is in percentage in which it is the percentage of

real output in a base year of 2007. The credit card default are provided in RM million.

The researcher follows the study conducted by Tony Bellotti and Jonathan Crook (2009),

which is using the data of more than 90 days of delinquency for the credit card.

3.43.43.43.4 RESEARCHRESEARCHRESEARCHRESEARCH DESIGNDESIGNDESIGNDESIGN

3.4.13.4.13.4.13.4.1 PurposePurposePurposePurpose ofofofof StudyStudyStudyStudy

The purpose of study for this research is to analyze the cause and effect

relationship of selected macroeconomic factors that influence the credit card default

focusing on interest rate, unemployment rate and industrial production index.

3.4.23.4.23.4.23.4.2 TypesTypesTypesTypes ofofofof InvestigationInvestigationInvestigationInvestigation

The type of investigation that will be used in this research paper is causal

investigation. The effect of the independent variables that cause change or movement

in dependent variable can be shown through the causal investigation.

3.4.33.4.33.4.33.4.3 ResearcherResearcherResearcherResearcher InterferenceInterferenceInterferenceInterference

Since this research paper is using causal studies which is based on the

observations of past data of independent variables and its relationship towards credit

card default, therefore there is minimal interference or no interference at all by the

researcher.

3.4.43.4.43.4.43.4.4 StudyStudyStudyStudy SettingSettingSettingSetting

This study will be conducted in a non-contrived setting or natural environment

where work proceeds normally since this research is using secondary data.

19

3.4.53.4.53.4.53.4.5 UnitUnitUnitUnit ofofofofAnalysisAnalysisAnalysisAnalysis

The unit of analysis for this research paper monthly credit card balance. This is

because this research paper is focusing on how macroeconomic factors affect

monthly credit card balance.

3.4.63.4.63.4.63.4.6 TimeTimeTimeTime HorizonHorizonHorizonHorizon

This research paper will be using the longitudinal studies. This research will use

the dependent and independent variables data for the past seven years. The data is

range from year 2007 to year 2013.

3.53.53.53.5 THEORETICALTHEORETICALTHEORETICALTHEORETICALFRAMEWORKFRAMEWORKFRAMEWORKFRAMEWORK

Dependent Variable

Independent Variables

Figure 1 : Framework of factors affecting the credit card default

The dependent variable is credit card default, which is the variable of primary

interest. The researcher attempt to explain the variance in this dependent variable by the

three independent variables which are interest rate, unemployment rate and industrial

production index.

Interest Rate

UnemploymentRate

IndustrialProduction Index

Credit Card Default

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3.63.63.63.6 HypothesisHypothesisHypothesisHypothesis StatementStatementStatementStatement

3.6.13.6.13.6.13.6.1 MainMainMainMain HypothesisHypothesisHypothesisHypothesis StatementStatementStatementStatement

HO : There is no significant influence by those independent variables.

HA : There is significant influence by those independent variables.

3.6.23.6.23.6.23.6.2 SpecificSpecificSpecificSpecific HypothesisHypothesisHypothesisHypothesis StatementStatementStatementStatement

3.6.2.13.6.2.13.6.2.13.6.2.1 InterestInterestInterestInterest RateRateRateRate

HO : There is no significant relationship between interest rate and credit card

default.

HA : There is significant relationship between interest rate and credit card

default.

3.6.2.23.6.2.23.6.2.23.6.2.2 UnemploymentUnemploymentUnemploymentUnemployment RateRateRateRate

HO : There is no significant relationship between unemployment rate and

credit card default.

HA : There is significant relationship between unemployment rate and credit

card default.

3.6.2.33.6.2.33.6.2.33.6.2.3 IndustrialIndustrialIndustrialIndustrial ProductionProductionProductionProduction IndexIndexIndexIndex

HO : There is no significant relationship between industrial production index

and credit card default.

HA : There is significant relationship between industrial production index and


3.73.73.73.7 SamplingSamplingSamplingSampling DesignDesignDesignDesign

3.7.13.7.13.7.13.7.1 TargetTargetTargetTarget PopulationPopulationPopulationPopulation

The target population of this research paper is credit card holders in

Malaysia.

3.7.23.7.23.7.23.7.2 SampleSampleSampleSample SizeSizeSizeSize

This research paper is using data for the past seven years for all the variables.

21

Therefore, the number of observations in this study will be 73.

3.83.83.83.8 TestTestTestTest ConsiderationConsiderationConsiderationConsideration forforforfor DataDataDataData AnalysisAnalysisAnalysisAnalysis

3.8.13.8.13.8.13.8.1 SoftwareSoftwareSoftwareSoftware

In order to run the data in this research project, researcher will use STATA

software to run the various tests for the data collected.

3.8.23.8.23.8.23.8.2 DescriptiveDescriptiveDescriptiveDescriptive StatisticsStatisticsStatisticsStatistics

This research project will use descriptive statistics for the data analysis such

as the sample mean, min and max, variance, measure of skewness and also measure of

kurtosis.

3.8.33.8.33.8.33.8.3 MultipleMultipleMultipleMultiple LinearLinearLinearLinear RegressionRegressionRegressionRegression FunctionFunctionFunctionFunction

This function is used in order to determine the relationship between interest

rate, unemployment rate, and industrial production index on the credit card default.

Yt= β0+ β1IRt+ β2URt+ β3IPIt+ εt

3.8.43.8.43.8.43.8.4 OrdinaryOrdinaryOrdinaryOrdinary LeastLeastLeastLeast SquareSquareSquareSquareMethodMethodMethodMethod (OLS)(OLS)(OLS)(OLS)

A technique to find the function which most closely approximates the data. It

is a method to fit a straight line through a set of data-points so that the sum of squared

vertical distances from the actual data points is minimized.

3.8.53.8.53.8.53.8.5 CovarianceCovarianceCovarianceCovariance

Covariance will show whether the change in interest rate, unemployment rate,

and industrial production index associates with the changes in credit card default. It will

only shows the direction of the relationship whether there is positive relationship or

negative relationship.

3.8.63.8.63.8.63.8.6 CorrelationCorrelationCorrelationCorrelation CoefficientCoefficientCoefficientCoefficient (r)(r)(r)(r)

Correlation coefficient provides information about the strength and direction

of linear relationship. Table below indicates the strength and direction of the relationship.

22

CCCCorrelationorrelationorrelationorrelation CoefficientCoefficientCoefficientCoefficient InterpolationInterpolationInterpolationInterpolation

-1 Strong negative relationship

0 There is no relationship

1 Strong positive relationship

3.8.73.8.73.8.73.8.7 CoefficientCoefficientCoefficientCoefficient ofofofof DeterminationDeterminationDeterminationDetermination (R(R(R(R2222))))

Coefficient of determinant is to measure total variation. It shows one variable

may affect other variable. The value of R2 can explain the strength of the correlation

between the dependent variable and independent variables. It can be done by squaring the

correlation coefficient in which the proportion of variance in dependent will be explained

by other proportion of independent variable. The value of R2 can only take place between

0 and 1. When the value is close to 1, it explains most of the variation in the values of the

dependent variable and when the value is close to 0, the model is unable to explain the

most of the variation in the values of the dependent variable.

3.8.83.8.83.8.83.8.8 AdjustedAdjustedAdjustedAdjusted CoefficientCoefficientCoefficientCoefficient ofofofof DeterminationDeterminationDeterminationDetermination (R(R(R(R2222))))

Adjusted R2 make an adjustment to R2 to take into account of the number of

independent variables in the regression. R2 as mention above, measure what fraction

of the variation of the dependent variable variable is explained by the regression. In

the case of adjusted R2 when an additional independent variable is added to a

regression, R2 always rises.

3.8.93.8.93.8.93.8.9 F-StatisticF-StatisticF-StatisticF-Statistic

F-statistic can be used to determine whether interest rate, unemployment rate and

industrial production index does or does not have a significant impact towards

dependent variable. The null hypothesis between independent and dependent variable

(H0: β1 = β2 = β3 = β4 = 0) is tested against the alternative hypothesis (H1: Not all β1values are 0) by using F-test approach. When the independent variables are related to

each other and also dependent variable, it is possible that the combined is significant

but the t-value are quite small.

23


This chapter explains the research design that will be applied in the research study.

The purpose of this study is to determine the relationship between the dependent variable

(credit card default) and the independent variables (interest rate, unemployment rate and

industrial production index). A set of monthly observations for each of the variables

beginning from 2007 to 2013 are used. Data for the variables are obtained from the

various source which are from BNM Monthly Statistical Bulletin and Trading Economics.

All the data will be subjected to several empirical tests to investigate the relationship with

credit card default. The test list include, Descriptive Statistics, Multiple Linear

Regression Model, OLS, Covariance, Correlation Coefficient, Coefficient of

Determination, Adjusted R2, and also F-Statistics. The result of the tests will be

highlighted and discussed in the next chapter. The empirical result from the test is

expected to provide insights for answering the hypothesis statement.

24

CHAPTERCHAPTERCHAPTERCHAPTER 4:4:4:4: DATADATADATADATAANALYSISANALYSISANALYSISANALYSIS


In this chapter the empirical result of all the tests conducted will be scrutinized and

analyzed. This is performing with the stated objective of finding the relationship between

the dependent and independent variables. The findings and analysis of the study is

through research using Stata 11 and also Microsoft Excel. At the end of the chapter, a

summary of the findings and results obtained will be presented.

4.24.24.24.2 DescriptiveDescriptiveDescriptiveDescriptive StatisticsStatisticsStatisticsStatistics

VariablesVariablesVariablesVariables NNNN meanmeanmeanmean minminminmin p50p50p50p50 sdsdsdsd maxmaxmaxmax skewnessskewnessskewnessskewness kurtosiskurtosiskurtosiskurtosis

CD 84 20.04 17.72 19.96 1.25 23.37 0.0032 0.026

IR 84 0.053 0.045 0.049 0.007 0.066 0.0080 0.020

UR 73 0.033 0.027 0.032 0.003 0.041 0.0059 0.031

IPI 76 0.016 -0.18 0.024 0.061 0.142 -0.0082 0.042

Table 4.1: Descriptive Statistics for Credit Card Default in Malaysia (2007-2013),

rescaled by hundred

CD or Credit card default can be defined when the credit card holders are unable to

pay the minimum payments for three consecutive months or more which the missing

payments are recorded changes over time as the payments are made. The mean value for

credit card default is RM 2004 million. The maximum value of credit card default is RM

2337 million and the minimum value of credit card default is RM 1772 million. On the

other hand, the standard deviation for the credit card default is RM 125 million. Skewness

is measured as an indicator used in the distribution analysis as a sign of asymmetry and

deviation from a normal distribution. For credit card default, the skewness is equals to

0.32 which is more than 0. When the skewness is more than 0, it is right skewed

distribution, which most values are concentrated on left of the mean, with extreme values

to the right. It is not a normal distribution because the distribution is skewed to the right.

For kurtosis, it is measured as an indicator used in distribution analysis as a sign of

flattening or peakedness of a distribution. The kurtosis for credit card default is 2.6,

which is less than 3. When the kurtosis is less than 3, it indicates that the distribution is

25

flatter than the normal distribution with a wider peak. The probability for extreme values

is less than the normal distribution, and the values are wider spread around the mean.

Next, IR or interest rate can be defined as an average rate of interest charged on loans

by commercial banks to individuals and companies. For interest rate, the mean value is

5.3%. The maximum value and the minimum value for interest rate are 6.6% and 4.5%

respectively. Next, the standard deviation for interest rate is 0.7%. The skewness for

interest rate is 0.8, which is more than 0. Therefore, it is also right skewed distribution,

which is same as credit card default. The kurtosis of interest rate is also less than 3 same

as credit card default which amounted to 2. Therefore, the distribution for interest rate is

flatter than the normal distribution with a wider peak.

UR or unemployment rate can be defined as labor force that is without work but

available and seeking for employment. For unemployment rate, the mean value is

amounted to 3.3%. The maximum value for unemployment rate is 4.1% and the minimum

value for unemployment rate is 2.7%. Next, the standard deviation for unemployment rate

is amounted to 0.3%. the skewness of unemployment rate is 0.59, which is more than 0. It

is also indicates that the distribution is skewed to the right. The kurtosis for

unemployment rate is 3.1, which is more than 3. When the kurtosis is more than 3, it can

be indicates that the distribution is sharper than the normal distribution, which their

values concentrated around the mean and thicker tails.

Lastly, IPI or industrial production index can be defined as measures the output of

businesses integrated in industrial sector of the economy such as manufacturing, mining,

and utilities. The mean for industrial production index is 1.6%. The maximum value for

industrial production index is 14.2% and the minimum value is -18%. The standard

deviation for industrial production index is 6.1%. The skewness value for industrial

production index is -0.82 which is less than 0. When the skewness is less than 0, it is

indicates that it is skewed to the left, which the most values are concentrated on the right

of the mean with extreme values on the left. However, the kurtosis for industrial

production index is amounted to 4.2, which is more than 3. Therefore, it indicates that the

distribution is sharper than the normal distribution.

26

4.34.34.34.3 F-TestF-TestF-TestF-Test

The value of F-statistics shown from the result is 14.65. The p-value of F-statistics is

0.00. This implies that the model as a whole is statistically significant.

4.4.4.4.4444 CoefficientCoefficientCoefficientCoefficient ofofofof DeterminationDeterminationDeterminationDetermination (R(R(R(R2222))))

The value of R2 obtained is 0.39 which means that 39% of the variance in the credit

card default can explained by the variation in the chosen macroeconomic variables which

are interest rate, unemployment rate and industrial production index. The remainder 61%

of the variation is determined by other factors.

4.4.4.4.5555 AdjustedAdjustedAdjustedAdjusted RRRR2222

From the result obtained, it shows that the adjusted R2 is 0.37. This indicates that

37% of the variance in credit card default is explained by the variation in the chosen

macroeconomic variables and the added variables in the research.

4.4.4.4.6666 CorrelationsCorrelationsCorrelationsCorrelations MatrixMatrixMatrixMatrix

CD IR UR IPI

CD 1.000

IR -0.598

0.000

1.000

UR -0.332

0.004

0.287

0.014

1.000

IPI 0.011

0.926

0.002

0.988

-0.306

0.008

1.000

Table 4.3 : Correlations Matrix

From the results, we can see that the credit card default is significantly negatively

correlated to interest rate and unemployment rate. That is, the credit card default is low

when the interest rate is high and unemployment rate is high. However, when the

industrial production index is high, the credit card default will also be high. This is

because based on the results, the industrial production index and also credit card default

have a positive correlation amounted to 0.011%. The probability is 0.926 which is more

27

than 10% significance level and it indicates that it is not significant. Other than that,

based on the correlation matrix, we can see that interest rate is positively correlated with

unemployment rate and also industrial production index amounted to 0.287% and

significant at 1% and also 0.002% and it is insignificant respectively. However,

unemployment rate is found to be negatively correlated with industrial production index

amounted to -0.306% and it is significant at 1%.

4.4.4.4.7777 CovarianceCovarianceCovarianceCovariance MatrixMatrixMatrixMatrix

CD IR UR IPI

CD 16089.4

IR -47.16 0.38

UR -11.87 0.05 0.08

IPI 11.62 -0.02 -0.52 36.36

Table 4.4 : Covariance Matrix

For the covariance matrix, we can see that the covariance between credit card default

and interest rate is negative amounted to -47.16%. This means that the credit card default

and interest rate is covary in a negative way. As the interest rate goes up, the credit card

default tends to go down and vice versa. Other than that, we can see that the covariance

between credit card default and also unemployment rate is negative amounted to -11.87%.

This means that the credit card default and the unemployment rate is covary in a negative

way. As the unemployment rate goes up, the credit card default tends to decrease and vice

versa. Lastly, the covariance between credit card default and industrial production index

is positive amounted to 11.62%. The credit card default and industrial production index is

covary in a positive way. As the industrial production index goes up, the credit card

default will also increase and vice versa.

28

4.4.4.4.8888 MultipleMultipleMultipleMultiple LinearLinearLinearLinear RegressionRegressionRegressionRegression

The multiple linear regression model used is specified as :

Yt= β0+ β1IRt+ β2URt+ β3IPIt+ εtWhere Yt is the dependent variable which is credit card default, and IRt , URt and IPItare the macroeconomic factors where:

IRt= Interest rate

URt= Unemployment rate

IPIt= Industrial production index

VariablesVariablesVariablesVariables CoefficientCoefficientCoefficientCoefficient StandardStandardStandardStandard

ErrorErrorErrorError

T-StatisticsT-StatisticsT-StatisticsT-Statistics ProbabilityProbabilityProbabilityProbability

IR -111.56 20.18 -5.53 0.00

UR -85.11 46.64 -1.82 0.07

IPI -0.95 2.09 -0.45 0.65

Constant 2871.73 158.26 18.15 0.00

Number of Observations 73

F ( 3 , 69 ) 14.65

Probability F-Statistics 0.00

R-Squared 0.39

Adjusted R-Squared 0.37

Table 4.2 : Multiple Linear Regression Model Result

The results obtained from the regression table can be explained by imputing the

result into the economic equation.

Y=Y=Y=Y= 2871.732871.732871.732871.73 ---- 111.56111.56111.56111.56IRIRIRIR---- 85.1185.1185.1185.11URURURUR---- 0.950.950.950.95IPIIPIIPIIPI

Based on the equation, all the independent variables shows a negative relationship

with the credit card default.

29

4.4.4.4.8888.1.1.1.1 InterestInterestInterestInterest RateRateRateRate

The coefficient value of interest rate is -111.56. It indicates that every 1%

increase in interest rate, credit card default will decrease by RM 111.56 million

assuming that all the variables are held constant. The p-value of interest rate is 0.00

which is significant at 1%. The findings reject the null hypothesis and concluded that

there is a significant negative relationship between interest rate and credit card

default.

4.4.4.4.8888.2.2.2.2 UnemploymentUnemploymentUnemploymentUnemployment RateRateRateRate

The coefficient value of unemployment rate is -85.11. It indicates that every 1%

increase in unemployment rate, credit card default will decrease by RM 85.11 million

assuming that all the variables are held constant. The p-value of unemployment rate

is 0.07 which is significant at 10%. The findings reject the null hypothesis and

concluded that there is a significant negative relationship between unemployment

rate and credit card default.

4.4.4.4.8888.3.3.3.3 IndustrialIndustrialIndustrialIndustrial ProductionProductionProductionProduction IndexIndexIndexIndex

The coefficient value of industrial production index is -0.95. It indicates that

every 1% increase in industrial production index, credit card default will decrease by

RM 0.95 million provided all the variables are held constant. The p-value of

industrial production index is 0.65, which is more than 10% significance level. The

findings fail to reject the null hypothesis and concluded that there is no significant

relationship between industrial production index and also credit card default.

30

4.4.4.4.9999 SummarySummarySummarySummary HypothesesHypothesesHypothesesHypotheses StatementStatementStatementStatement

4.4.4.4.9999.1.1.1.1 MainMainMainMain HypothesisHypothesisHypothesisHypothesis StatementStatementStatementStatement

The probability (F-test) is 0.00, which is significant at 1% significance level.

Therefore, the finding reject the null hypothesis statement and accept alternate

hypotheses and can be concludes that there is significant influence by those selected

independent variables.

4.4.4.4.9.9.9.9.2222 SpecificSpecificSpecificSpecific HypothesisHypothesisHypothesisHypothesis StatementsStatementsStatementsStatements

4.4.4.4.9.9.9.9.2.12.12.12.1 InterestInterestInterestInterest RateRateRateRate

The p-value of interest rate is 0.00 which is significant at 1%. The findings reject

the null hypothesis and concluded that there is a significant negative relationship

between interest rate and credit card default.

4.4.4.4.9999.2.2.2.2.2.2.2.2 UnemploymentUnemploymentUnemploymentUnemployment RateRateRateRate

The p-value of unemployment rate is 0.07 which is significant at 10%. The

findings reject the null hypothesis and concluded that there is a significant negative

relationship between unemployment rate and credit card default.

4.4.4.4.9999.2.3.2.3.2.3.2.3 IndustrialIndustrialIndustrialIndustrial ProductionProductionProductionProduction IndexIndexIndexIndex

The p-value of industrial production index is 0.65, which is more than 10%

significance level. The findings fail to reject the null hypothesis and concluded that

there is no significant relationship between industrial production index and also


31

4.104.104.104.10 SummarySummarySummarySummary OfOfOfOf TheTheTheThe ResultsResultsResultsResults

NONONONORESEARCHRESEARCHRESEARCHRESEARCHQUESTIONQUESTIONQUESTIONQUESTION

RESEARCHRESEARCHRESEARCHRESEARCHOBJECTIVEOBJECTIVEOBJECTIVEOBJECTIVE HYPOTHESISHYPOTHESISHYPOTHESISHYPOTHESIS RESULTRESULTRESULTRESULT

1111 What is the relationshipbetween interest rateand credit card default?

To investigatewhether there is arelationshipbetween interestrate and creditcard default.

HO : There is nosignificantrelationshipbetween interestrate and creditcard default.

HA : There issignificantrelationshipbetween interestrate and creditcard default.

AcceptAlternateHypothesis

2222 What is the relationshipbetween unemploymentrate and credit carddefault?

To investigatewhether there is arelationshipbetweenunemploymentrate and creditcard default.

HO : There is nosignificantrelationshipbetweenunemploymentrate and creditcard default.

HA : There issignificantrelationshipbetweenunemploymentrate and creditcard default.

AcceptAlternate

3333 What is the relationshipbetween industrialproduction index andcredit card default?

To investigatewhether there is arelationshipbetween industrialproduction indexand credit carddefault.

HO : There is nosignificantrelationshipbetweenindustrialproductionindex and creditcard default.HA : There issignificant

RejectAlternateHypothesis

32

relationshipbetweenindustrialproductionindex and creditcard default.


All the empirical result from this study has been shown clearly in this chapter. In

the research testing, the researcher have closely followed the recommended steps in

treating and analyzing multiple linear regressions. Based on the results, it shows that

interest rate and unemployment rate have positive relationship with the credit card

default. However, industrial production index does not have a significant relationship

with credit card default. In accordance to testing a regression model with time series

data, the researcher has tested the regression model for the variables. Accept for

correlation coefficient test, all other test have fulfill the underlying assumptions for a

time series multiple regression model. The results obtained from this chapter will

give a clear view for the researcher to make conclusion and recommendations which

is the basis of the next chapter.

33

CHAPTERCHAPTERCHAPTERCHAPTER 5:5:5:5: CONCLUSIONCONCLUSIONCONCLUSIONCONCLUSIONANDANDANDAND RECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONS


In this chapter, the empirical results of the entire test conducted will be summarize.

This is to get the general view of the relationship between interest rate, unemployment

rate and industrial production index with credit card default. The result will be discussed

and concluded. The outcome of the study will be summarized in the discussion. Thus, the

recommendation will be suggested for the upcoming study regarding this topic. This

chapter will provide the information needed by the credit card consumer and researcher

for them to study.

5.5.5.5.2222 DiscussionDiscussionDiscussionDiscussion

Empirical results from this study have provided valuable insights for answers to the

problem statement and hypothesis statements of this research paper. Using the basis of

5% significance level, it can be concluded that interest rate and unemployment rate plays

a significant negative relationship with credit card default. With regards to the other

independent variable which is industrial production index, it does not appear to have any

significant relationship with credit card default.

The outcome of the study which indicates that interest rate has a significant negative

relationship with credit card default is consistent with the findings of of the research done

by Bellotti and Crook (2009). This finding is also supported by the research done by

Sangkyun Park (1997) who concludes that the interest rate have significant effect on the

credit card default. The significant negative relationship indicates that when the interest

rate is higher, the credit card default will be decrease. The significant negative

relationship between interest rate and credit card default can be supported by the research

done by Grieb, Hegji, Jones (2001) which found that interest rate is significantly

negatively related with the current level of interest rate.

The negative relationship found in this research can be explained in the keynesian

theory. The supply curve reflects the amount of credit lenders which are willing to

provide at various rates. The curve slope upward because lenders costs, including the cost

of funds increase as more credit is supplied. At the same time, higher interest rate offers

an incentive for the savers to provide more credit at higher rates of interest than at lower

34

rates. In the competitive market, as borrowers increase their demands for limited supply

of credit, they compete with one another and thus, bidding up interest rate. But when the

interest rate increase, lenders will want to provide more credit and increase their supply to

satisfy the demand. However, as the interest rate increase, the demand for will generally

decrease. This can be apply to the credit card case. When the interest rate high, people

will not demand to use credit card because they afraid that they cannot pay their

outstanding balances and thus, credit card default happen.

The findings indicates that other researchers place interest rate as an important

determinant that will influence credit card default. Interest rate is important to the

banking institutions because the interest rate is treated as the profit to the banking

institutions. Therefore, banking institutions will charged higher interest rate to the credit

card consumer since the interest rate is the profit for the banking institutions.

Next, the results of the study shows that unemployment rate has a significant

negative relationship with credit card default. This result can be supported by the findings

done by the previous researchers. Sumit Argawal and Chunlin Liu 2003, Tony Bellotti

and Jonathan Crook, 2013 in which they found that credit card default is significantly

affected by unemployment rate.

Unemployment is found to have negative relationship with credit card default. This

means that when the unemployment level increase, the credit card default will be

decrease and vice versa. This is surprising since the researcher is expecting both of the

variables will have positive relationship with each other. This negative relationship

between unemployment and also credit card default is because according to Erin Turinetti

(2011), an increase in unemployment rate will implies a tighter budget for the households.

Therefore, when unemployment rate high, households will consume less and thus, borrow

less. This xplains why both variables have negative relationship.

Unemployment rate can be considered as an important determinant that will affect

the credit card default in Malaysia. This is because employment gives people income and

money to survive and also to buy their needs and wants. However, when the person

become unemployed, they will no longer have continuous income to support their daily

life expenses. Therefore, unemployment rate is said to be an important determinant that

will affect the credit card default based on the above logic.

35

Lastly, based on the findings, it is found that industrial production index does not

have any significant relationship with credit card default. The researcher is using

industrial production index as proxy to level of income since gross domestic product is

not available monthly. This findings is supported by Canner and Luckett (1990) that also

found level of income does not have significant relationship with debt repayment. The

reason for insignificance is because credit card holder's occupation and the acquisition

channel. Event though the bank sets the credit card holder to high risk category, which

means that there is high possibility that the credit card holder will default the payment, if

the credit card holder is willing to maintain a good credit status and pay the monthly

credit card repayments on time, it will not result in credit card default.

Based on the results of the research, it is shown thar industrial production index is

not an important determinant to credit card default. There are other important

determinants that should used in analyzing the cause of credit card default in Malaysia.

5.5.5.5.3333 RecommendationsRecommendationsRecommendationsRecommendations

Performing this research study has created a realization on how future researchers

could further expand the knowledge horizon to obtain more reliable results and

comprehensive study.

5.5.5.5.3333.1.1.1.1 AddAddAddAdd moremoremoremore externalexternalexternalexternal variablesvariablesvariablesvariables

As can be observed from the study, the three selected macroeconomic variables

accounts for only 39% explanation of the dependent variables. More variables need

to be considered such and included in the future research. Inclusion of other variables

other than interest rate, unemployment rate and industrial production index would

provide the researcher a broader base of understanding.

5.3.25.3.25.3.25.3.2 UseUseUseUse differentdifferentdifferentdifferent datadatadatadata structurestructurestructurestructure

Future researchers are encouraged to use other types of data structure such as

panel data. Used of other types of data structure would enable researchers a new

perspective on their research study which then could be compared with existing

36

studies for the purpose of knowledge expansion. Additionally, different frequency of

the data set such as daily, weekly, quarterly and annually could be used instead of

monthly data set to test the consistency of the findings as well as increase the

reliability of the futures.

5.5.5.5.3333.3.3.3.3 UseUseUseUse primaryprimaryprimaryprimary datadatadatadata insteadinsteadinsteadinstead ofofofof secondarysecondarysecondarysecondary datadatadatadata

The future researchers can use primary data other than secondary data in order to

get more accurate data. By using primary data, more variables can be used for further

research such as the consumption of credit card every month, the education level, and

also awareness of credit card risk as the variables for the research if the future

researchers using primary data.

5.5.5.5.3333....4444 ResearchResearchResearchResearch onononon bankingbankingbankingbanking instutionsinstutionsinstutionsinstutions ofofofof otherotherotherother countriescountriescountriescountries

Prospective researchers should also conduct similar research on other developed

and emerging countries or markets. Result from such studies would be very

beneficial because not only will it show the trend in different countries but it could be

segregated into regional, develop and emerging countries. The information generated

from the research study would be beneficial and valuable not only to credit card

holders but also to other parties.

5.5.5.5.3333....5555 HaveHaveHaveHave moremoremoremore comprehensivecomprehensivecomprehensivecomprehensive teststeststeststests

Future researchers are advice to have more comprehensive test for validity and

reliability. Some of the tests that can be considered are Unit Root test,

Multicollinearity test, Normality test and others.

5.45.45.45.4 ConclusionConclusionConclusionConclusion

This study shows that interest rate and also unemployment rate are significant with

credit card default. Therefore, it is advisable for the bank to restrict their credit screening.

Which means that before the bank approve the credit card application, they need to screen

and examine the applicants carefully. This is done in order to avoid high credit card

default that will happen. Other than that, credit card holder is advised to use the credit

37

card only when needed or during emergency. Do not use credit card in order to satisfy our

wants. When credit card holder consume more than their income, they will have problem

to pay their outstanding balance and thus, credit card default will happen.


In this chapter, all the result of test were combined and concluded. From the report, it

can be found that only two variables accepted the alternate hypothesis which is interest

rate and unemployment rate. It is found that interest rate and unemployment both have

significant negative relationship with credit card default while the last variable which is

industrial production index have no significant effect towards the credit card default. The

researcher also suggest some recommendations to help future researchers as their

reference to done study related with credit card default in Malaysia. One of the

suggestion is should add more external variables and widen the period to have better

result. Not only that, future researchers also can do more comprehensive test such as

Multicollinearity test and also Normality test. To see the performance of our banking

institutions and other banking institutions in different countries, future researchers can

using panel data on other countries to measure the credit card default.

38

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APPENDICESAPPENDICESAPPENDICESAPPENDICES

1.1.1.1. DataDataDataData ofofofof StudyStudyStudyStudy

Y = Credit card defaultX1 = Interest RateX2 = Unemployment RateX3 = Industrial Production Index

MONTHLYMONTHLYMONTHLYMONTHLY YYYY X1X1X1X1 X2X2X2X2 X3X3X3X3200701 1793 6.57 NA NA200702 1914 6.54 NA 0.8200703 1846 6.54 3.4 1.7200704 1956 6.44 3.4 0.3200705 1896 6.44 3.4 7.3200706 1917 6.49 3.4 1.5200707 1824 6.34 3.4 1.2200708 1859 6.35 3.4 0.4200709 1929 6.30 3.1 1.2200710 1921 6.26 3.1 3.5200711 1909 6.31 3.1 2.5200712 1928 6.29 NA NA

200801 1856 6.27 NA NA200802 1958 6.27 NA 9.7200803 1904 6.21 3.6 9.9200804 1866 6.19 3.6 3.1200805 1861 6.13 3.6 4.7200806 1897 6.08 3.5 2.5200807 1801 6.02 3.5 2.3200808 1790 5.98 3.5 4.8200809 1776 5.96 3.1 1.8200810 1912 6.01 3.1 -0.9200811 2009 5.98 3.1 -2.6200812 1996 5.86 NA -7.5

200901 2016 5.77 NA NA200902 2082 5.49 3.8 -18200903 2071 5.16 4.1 -12.7200904 2007 5.11 4 -13200905 1996 5.02 3.8 -11.8200906 1978 5.04 3.6 -11200907 1858 4.96 3.2 -9.7200908 1854 4.90 3.5 -7.9

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200909 1895 4.91 3.5 -6.9200910 1772 4.91 3.6 -6.1200911 1968 4.91 3.4 0.8200912 1881 4.83 3.5 -0.8

201001 1857 4.85 NA NA201002 2084 4.85 3.6 13.8201003 1992 4.96 3.6 4.9201004 1933 4.93 3.6 14.2201005 1954 5.01 3.2 10.6201006 1992 5.05 3.3 12.3201007 1968 5.19 3.7 9.4201008 1995 5.22 3.3 3.2201009 2111 5.19 3.1 4201010 2022 4.99 3.1 5.6201011 2180 4.85 2.9 3201012 2068 4.91 3.1 5.1

201101 1982 4.95 NA NA201102 2240 4.96 3.4 1201103 1965 4.95 2.9 5201104 1998 4.97 3 2.4201105 2059 4.94 3 -2.2201106 2051 4.93 3 -5.1201107 2036 4.88 3.2 1201108 2091 4.89 3 -0.5201109 2188 4.89 3.1 3201110 2203 4.88 3.3 2.5201111 2337 4.91 3 2.8201112 2071 4.83 3.1 1.8

201201 2225 4.87 NA NA201202 2276 4.88 3 0.2201203 2090 4.74 3.2 7.5201204 2209 4.88 2.9 0.6201205 2037 4.80 3 3.2201206 1870 4.88 3 7.6201207 1990 4.71 3 3.7201208 2035 4.72 3.1 1.4201209 2166 4.76 2.7 -0.7201210 2007 4.78 3.2 4.9201211 2090 4.71 3.2 5.8201212 2028 4.70 2.9 7.5

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201301 1983 4.69 NA NA201302 2089 4.72 3.3 5.2201303 2136 4.70 3 -5.2201304 2195 4.80 3.3 -0.1201305 2057 4.72 3 4.6201306 2102 4.51 3.3 3.4201307 1984 4.46 2.8 3.3201308 2070 4.54 3 7.6201309 2200 4.55 3.1 2.3201310 2064 4.54 3.1 1201311 2178 4.56 3.3 1.7201312 2216 4.56 3.4 4.4

2.2.2.2. ResultResultResultResult fromfromfromfrom DataDataDataDataI.I.I.I. DescriptiveDescriptiveDescriptiveDescriptive StatisticsStatisticsStatisticsStatistics

ipi 76 1.563158 -18 2.35 14.2 6.07416 -.8211705 4.194965 ur 73 3.268493 2.7 3.2 4.1 .2817981 .591024 3.071294 ir 84 5.269048 4.46 4.945 6.57 .6562886 .803967 2.030383 dp 84 2004.405 1772 1995.5 2337 125.96 .3240641 2.59905 variable N mean min p50 max sd skewness kurtosis

II.II.II.II. CorrelationCorrelationCorrelationCorrelation TestTestTestTest

0. 9 2 6 0 0 . 9 88 2 0 . 0 0 8 6 i p i 0. 0 1 0 8 0 . 0 01 7 -0 . 3 0 5 6 1 . 00 0 0 0. 0 0 4 1 0 . 0 13 7 u r - 0. 3 3 2 1 0 . 2 87 4 1 . 0 0 0 0 0. 0 0 0 0 i r - 0. 5 9 7 7 1 . 0 00 0 d p 1. 0 0 0 0 d p i r u r i p i

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III.III.III.III. MultipleMultipleMultipleMultiple LinearLinearLinearLinear RegressionRegressionRegressionRegression

_cons 2871.729 158.2618 18.15 0.000 2556.006 3187.453 ipi -.9470785 2.087443 -0.45 0.651 -5.111413 3.217256 ur -85.10936 46.63695 -1.82 0.072 -178.1475 7.92882 ir -111.5639 20.18024 -5.53 0.000 -151.8224 -71.30547 dp Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1158435.32 72 16089.3794 Root MSE = 101.27 Adj R-squared = 0.3625 Residual 707700.27 69 10256.5256 R-squared = 0.3891 Model 450735.045 3 150245.015 Prob > F = 0.0000 F( 3, 69) = 14.65 Source SS df MS Number of obs = 73

IV.IV.IV.IV. CovarianceCovarianceCovarianceCovariance

ipi 11.6182 -.016653 -.519326 36.3637 ur -11.87 .050225 .07941 ir -47.1565 .384512 dp 16089.4 dp ir ur ipi

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