This paper intends to determine the factors affecting bankruptcy cases in Malaysia. The data ranges from 1999 to 2012 on a yearly basis consist of the independent variables such as non-performing loans, unemployment, per capita income and bankruptcy cases as dependent variable. The result shows that non-performing loan and unemployment has statistical significant relationship towards bankruptcy case in Malaysia. However, per capita income has no statistical relationship towards bankruptcy case in Malaysia. The results suggest that Malaysians fails to repay loan due to inability to settle their debt and also loss of work or being unemployed. This research is done in the context of Malaysia as single entity instead of a pool of countries or states/counties and the variables are all statistically analyzed. Also, the current research gives perspective and insight from academic point of view to assist government in their decision making as far as bankruptcy is concern

A. Fahami, Norasyikin

Hilmy, Hilwa

Mohd Z., Shaliza A.

Universiti Teknologi MARA Institutional Repository

International Journal of Undergraduates Studies, 2(3), 4-8, 2013 
ISSN: 2289-4242 
 
4 
 
FACTORS AFFECTING BANKRUPTCY: THE CASE OF MALAYSIA 
 
Hilwa Hilmy,2 · Shaliza A. Mohd Z.2 · Norasyikin A.  Fahami1 
1Universiti Teknologi MARA, Tapah Campus, Malaysia 
2Universiti Teknologi MARA, Perlis Campus, Malaysia 
 
 
ABSTRACT 
This paper intends to determine the factors affecting bankruptcy cases in Malaysia. The data ranges from 
1999 to 2012 on a yearly basis consist of the independent variables such as non-performing loans, 
unemployment, per capita income and bankruptcy cases as dependent variable. The result shows that non-
performing loan and unemployment has statistical significant relationship towards bankruptcy case in 
Malaysia. However, per capita income has no statistical relationship towards bankruptcy case in Malaysia. 
The results suggest that Malaysians fails to repay loan due to inability to settle their debt and also loss of 
work or being unemployed. This research is done in the context of Malaysia as single entity instead of a pool 
of countries or states/counties and the variables are all statistically analyzed. Also, the current research 
gives perspective and insight from academic point of view to assist government in their decision making as 
far as bankruptcy is concern. 
Keywords: Bankruptcy, non-performing loans, unemployment and per capita income 
 
INTRODUCTION 
According to Malaysia Department of Insolvency, a bankrupt person is someone who has officially being 
declared that he unable to pay what he owes. In Malaysia, the minimum outstanding debt amount to declare 
as bankruptcy person is RM30,000. Issues of bankruptcy case have gained increasing attention from many 
parties in the past few decades, as data shows an increasing form.  
 
 
 
Figure 1: Causes of Bankruptcy from 2005 to 2012. 
Source: Malaysia Department of Insolvency 
 
 
From the article of New Straits Times dated 18 February 2013, the Finance Ministry discussed with the 
Department of Insolvency to resolve the problems of bankruptcy among youths aged 25 and below. The 
government views bankruptcy among youths as a serious problem not only it makes their life troubled, but 
also a loss to the country. Inability to pay car loans is the major contributor to the statistics followed by 
other loans and also personal loans and housing loans. This is due to fact that those youthswho just started 
working unable to commit for the large amount of monthly car installment. On the other hand, Malaysia 
Legal Resources reported that bankruptcy gives negative impacts to individuals because it involves the 
closing down of the business, deactivated of bank account, restriction on withdrawal of money and open up a 
new account or use existing account and also unable to obtain new loans. Bankruptcy also damages 
individual‟s standing in the community. 
International Journal of Undergraduates Studies, 2(3), 4-8, 2013 
ISSN: 2289-4242 
 
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Bankruptcy is no longer a taboo to the society. Lately, it is not unusual to be declared bankrupt before 30 
years old. The reckless spending and the “pressure” of having a luxurious lifestyle have been identified as 
among the factors that trigger this problem. On the other hand, the availability of the facilities provided by 
the financial institutions do not do any justice for this problem. For instance, it was announced that the 
incidence of bankruptcy from car loans alone was extremely high accounting for about 24% of the total 
80,370 cases between 2005 and May 2010 (Malaysia Insolvency Department). Hence, this paper mainly 
intended to examine factors affecting bankruptcy in Malaysia namely; non-performing loans, unemployment 
and per capita income. The data is analysed on yearly basis throughout year 1999 to 2012. For years, many 
economists and researchers have serious debates on what actually lead to a rising personal bankruptcy rate. 
Earlier researchers used surveys and cited adverse events, such as loss of job, divorce, serious illness as the 
leading causes (Sullivan et al, 2000). While, by using the debt data from the banks, White (2007) found that 
recent studies on personal bankruptcy indicated that revolving debt, specifically credit card debt, as the 
primary culprit that causes rising bankruptcy rates among people in a country. He said that when the 
amount in the credit card was high, they faced difficulties to pay the debt due to increasing interest rates 
and the usage of credit card may lead people to file for bankruptcy. Meanwhile, earlier study by, Godwin 
(1999) concluded that the borrowers of the loan from the banking and financial institutions were having 
difficulties repaying their debt due to inability to pay the interest rates that increased from day to day. With 
the availability and loose requirement of such facilities, financial institutions should be lenient in the paying 
back terms. However, since this is not the case, it intrigued this research to select Non-Performing Loan 
(NPL) as a variable.Technically, NPL provisions were regarded as a controlling mechanism over expected 
loan losses and previous practices showed that provisions were triggered by default incidents on loans. 
Higher level of non-performing loans was associated with high rates of provisioning (Hasan and Wall, 2004). 
Brownbridge (1998) found that most of the bank failures were caused by non-performing loans (NPLs).  
With reference to loan data from banks, Delgado and Saurina (2004) stated that a high growth of 
credit was associated with an increase in the non-performing loan ratio; hence this non-performing loan will 
lead to bankruptcy among individuals. Existing findings like Moorman (2006),pointed out that in certain 
countries like America, some consumers would go to the extent of abusing the country‟s bankruptcy 
protection due to financial problem. In addition, a distinction study by Gregoriou, Healy and Tsitsianis 
(2008) between high income with low income group in adapting to unemployment showed that low income is 
more prone due to the lack of social capital.In language, unemployment is the unavailability of job 
opportunities for able and desired people to work and it was the most serious problem that threatens the 
stability of nations and countries. On the other hand, Warren (2004) stated that the adverse events in the 
labour market, such as job loss or unemployment and pay cut will lead to the bankruptcy case in a country. 
He gave the opinion that the people will have insufficient income when the unemployment and pay cut 
occurred.Sullivan et al (2000) and Domowitz and Sartain (1999) reported that overwhelmingly large 
proportion of those filing for bankruptcy have recently experienced a job loss or unemployment.Previous 
studies by Gropp et al (1997) and White (1998) have pointed out that the bankruptcy case is affected by 
economic condition. Despite the fact that past studies concluded that revolving debt and loan are the culprit 
of personal bankruptcy (White,2007) found that adverse events do play a role in personal bankruptcy filings 
under the severe economic conditions. Earlier, Keeton and Morris (1987) managed to determine that local 
economic conditions along with the poor performance of certain sectors explain the variation in loan losses 
recorded by the banks.However, Garette and Ott (2005) suggested that both per capita income and 
unemployment have a negative relationship with personal bankruptcy filings. Their findings on Eighth 
District states of U.S also found that at a given point in time, lower-income individuals may be more likely to 
file for bankruptcy, given relatively less financial literacy and less diversification of fewer financial assets. 
 
RESEARCH METHODOLOGY 
The data were retrieved from Bank Negara Malaysia, Department of Statistics Malaysia and also 
Department of Insolvency Malaysia. The software used to analyze the data is Statistical Packaged for Social 
Science which also known as SPSS. The SPSS has the capability to perform analysis such as multiple linear 
regressions, coefficient of determination or R2, F-test, T-test and also Spearman‟s Correlation.  
 
International Journal of Undergraduates Studies, 2(3), 4-8, 2013 
ISSN: 2289-4242 
 
6 
 
Multiple Linear Regressions 
Regression analysis is a powerful procedure for analyzing associative relationships between dependent 
variable and one or more independent variables.Multiple linear regressions are used to see whether a 
relationship exists and to determine whether the independent variables explain a significant variation 
towards the dependent variable.Besides that, it is also used in order to see the strength of the relationship 
and to determine the variation in the dependent variables that can be explained by the independent 
variables.The equation model for this research is: 
 
 Bnk = α+ B1NPL + B2UnEm + B3IncPC + e 
 
Coefficient of Determination, R2 
R2 is the measure of correlation and it indicates the proportion of the variance in the criterion variable which 
is accounted by the model. The general form for R2 is: 
 
Coefficient of determination = RSS  
SST 
   Where, RSS  =  regression sum squares     
  SST =  total sum of squares 
 
The higher the coefficient of determination, the variance that the dependent variable is explained by 
the independent variable is better. The coefficient of determination shows the overall measure of the 
usefulness of a regression. The coefficient of determination represents that 0 ≤ r2 ≥ 1 and it determines the 
strength of the linear association between x and y.  
 
F-Test 
F-test is used for testing the significance of the regression model. By using F-test, the appropriateness of 
the multiple regression models as a whole can be tested. A significant F indicates a linear relationship 
between dependent variable and at least one of the independent variable.In F-test, the F-values are always 
all non-negative and the distribution is non - symmetric. The mean is approximately 1. According to the F-
statistics distribution table is:   
Degree of freedom for numerator  = k – 1 
Degree of freedom for denominator = n – k 
   Where,   
     k = number of independent variables 
     n = number of data 
 
 The general formula for F-test is: 
F = (RSSR – RSSU) / r 
RSSU / dfU 
 
T-Test 
T-test shows whether the means of two groups are statistically different from each other. Generally, t-test is 
a test of significance procedures by which sample results are used to verify the truth or falsity of a null 
hypothesis. The main idea behind tests of significance is that from the test statistic (estimator) and the 
sampling distribution of statistic under the null hypothesis.The formula for t-distribution table is: 
     T = (n – k) – 1 
    
 The general formula for T-test is: 
t =β2 – β2 =  estimator - parameter               
se (β2) estimated standard error of estimator 
 
 = β2 – β2   
  ᵟ   
International Journal of Undergraduates Studies, 2(3), 4-8, 2013 
ISSN: 2289-4242 
 
7 
 
The null hypothesis, H0 is expressed as no relationship between two variables. The alternate hypothesis, H1 
represents a statement expressing a relationship whether it is a positive or negative relationship between 
two variables. The decision to accept or reject H0 is made on the basis of the value of the test statistic 
obtained from the data.When the value is less than 0.05, it shows significant, which means reject null 
hypothesis which is H0 and accept alternative hypothesis which is H1 and vice versa. 
 
FINDINGS AND ANALYSIS 
The results of the study are presented and discussed in this chapter.  By conducting theabove-mentioned five 
tests, the decision to accept or reject the null hypothesis can be made. The results are tabulated in Table 1, 
Table 2and Table 3. 
 
Based on the result the equation is as follows: 
   
Bankruptcy = α+ B1NPL + B2UnEm + B3IncPC + e 
  Bankruptcy  = - 2.935 – 0.368 NPL + 1.192 UnEm + 0.157 IncPC 
        (4.013)        (0.146)        (0.386)         (0.141) 
 
Based on the regression equation, the value of the Beta for non performing loan is -0.368. The negative sign 
indicates that non performing loan has a negative relationship towards bankruptcy. Whereby, another two 
variables indicates positive sign towards dependent variable. For the coefficient of determination (refer 
Table 1), the result for R2 is 0.827. It means that 82.7% of dependent variable (bankruptcy) is explained by 
the independent variables (non performing loan, unemployment and per capita income). The remaining 
value, 17.30 % is explained by other factors that are not included in this research.  
 
Table 1: Model Summaryb 
Model R R Square Adjusted R Square Std. Error of the Estimate 
1 0.931a 0.867 0.827 0.0916349 
a. Predictors: (Constant), Income, NPL, Unemployment 
b. Dependent Variable: bankruptcy 
 
The result for F-test is significant as tabulated in Table 2 thus indicates that dependent variable 
(bankruptcy) is statistically affected by the independent variables (non performing loan, unemployment and 
per capita income).It means that null hypothesis which states that dependent variable (bankruptcy) is not 
affected by  the independent variables is rejected. Therefore, this model can be said as significant and it can 
be used for forecasting method.  
 
 
Table 2: Results of ANOVAb 
Model Sum of 
Squares 
df Mean Square F Sig. 
Regression 0.546 3 0.182 21.677 0.000a 
Residual 0.084 10 0.008   
Total 0.630 13    
a. Predictors: (Constant), Income, NPL, Unemployment 
b. Dependent Variable: bankruptcy 
 
For the t-distributed table (refer Table 3), the value is 2.228, therefore non performing loan and 
unemployment have significant relationship towards dependent variable (bankruptcy) as their computed t-
statistics are higher compared to t-distributed table. For per capita income, the computed t-statis lower 
than t-distribution table. Therefore the result between a dependent variable and independent variable (per 
capita income) is not significant. Hence, null hypotheses for the first two variables are rejected while the 
other variableis accepted. 
 
International Journal of Undergraduates Studies, 2(3), 4-8, 2013 
ISSN: 2289-4242 
 
8 
 
Table 3: Coefficientsa 
 
 
Model 
Unstandardized 
Coefficients 
Standardized 
Coefficients 
 
 
t 
 
 
Sig. 
Collinearity 
Statistics 
B Std. Error Beta Tolerance VIF 
(Constant) -2.935 4.013  -0.731 0.481   
NPL -0.368 0.146 -0.363 -2.525 0.030 0.645 1.550 
Unemployment 1.192 0.386 0.561 3.084 0.012 0.403 2.482 
Income 0.157 0.141 0.234 1.118 0.290 0.304 3.291 
a. Dependent Variable: bankruptcy 
 
CONCLUSION  
Bankruptcy case has become one of the major problems in Malaysia nowadays. This is because the statistics 
of bankruptcy is increasing from year to year. Therefore, this study is conducted in order to determine 
whether non-performing loan, unemployment and economic condition affect the bankruptcy cases in 
Malaysia.Based on the findings, both non-performing loan and unemployment have statistically significant 
relationship with bankruptcy. While, the unemploymentis not significant towards bankruptcy.The model for 
this study has a high explanatory power as it indicates that the combination of non-performing 
loans,unemployment and economic condition explain a high portion towards the variation of 
bankruptcy.Estimated results also show that there is a significant relationship between all independent 
variables and dependent variable. Hence this model is said to be significant and can be used for forecasting 
methods. The government can use this research in order to know the factors that affecting bankruptcy so 
that the government can take action to reduce the bankruptcy case in Malaysia. The financial institutions or 
banking sector must give the loans for those who only have potential to pay back the loan by enforce the 
financial institutions or bank law.While, for further research, it is recommended to use quarterly or monthly 
data and also lengthen the number of years study in the analysis. 
 
REFERENCES 
Bernama.„Ministry to Resolve Bankruptcy Among Youths‟. Retrieved June 10th 2013 from 
http://www.nst.com.my/latest/ministry-to-resolve-bankruptcy-among-youths-1.220711 
Brownbridge M. (1998) The Causes of Financial Distress in Local Banks in Africa and Implications for 
Prudential Policy, United Nations Conference on Trade and Development (UNCTAD), Geneva 
Delgado J. and J. Saurina (2004) Credit risk and loan loss provisions: an analysis with macroeconomic 
variables, Working Paper, Banco de Espana. 
Domowitz, I. and Sartain, R. L. (1999). Determinants of the consumer bankruptcy decision, Journal of 
Finance 54(1): 403–420. 
Garrett T. A. and Ott L. S. (2005) Up, Up and Away: Personal Bankruptcies Soar!,The Regional Economist, 
Federal Reserve Bank of St. Louis, 10-11               
Godwin D. D. (2009) Predictors Of Households' Debt Repayment Difficulties, Financial Counseling and 
Planning, 10(1), 67 – 78. 
Gropp, Reint, John Scholz, and Michelle White (1997). “Personal Bankruptcy and Credit Supply and 
Demand,” Quarterly Journal of Economics, 112, 217-251. 
Hasan, I. and L.D. Wall, (2004) Determinants of the Loan Loss Allowance: Some Cross-Country 
Comparisons.Financial Review. 39(1), 129–152. 
Keeton, William and Charles S. Morris (1987) Why Do Banks‟ Loan Losses Differ? Federal Reserve Bank of 
Kansas City, Economic Review, 3-21. 
Sullivan, Teresa A., Warren E., and Westbrook J. L. (2000) The Fragile Middle Class: Americans in Debt. 
New Haven, CT: Yale University Press. 
Warren E. (2004) Growing Threat to Middle Class Families, 69 Brook, L. Rev. 401 (2003-2004), 401-424. 
White M. (1997) Why don‟t more household file for bankruptcy?,Working Paper, University of  
 Michigan 
White M. J. (2007) Bankruptcy Reform And Credit Cards, NBER Working Paper Series, Working Paper 
13265, National Bureau Of Economic Research. 


Factors affecting bankruptcy : the case of Malaysia / Hilwa Hilmy, Shaliza A. Mohd Z and Norasyikin A. Fahami

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