1.0       BACKGROUND OF STUDY                                                                    


The purpose of this study is examine and extend the existing knowledge towards the factors that affecting the number of consumer bankruptcy in Malaysia by specifically among public servants in Selangor. In Malaysia, bankruptcy is one of the leading factors that contribute in the tendency of people to be affected with financial risk. Financial risk can be seen as a major issue since it affects individual, the organisation and also the country itself. Hence, the awareness towards factors influencing bankruptcy is very important.

Nowadays, the issue of bankruptcy has become more serious to many countries. The number of bankruptcies has consistently increased from 13, 238 in 2007 to 13, 907 in 2008, 16, 228 in 2009 and 18, 119 in 2010, 19, 167 in 2011, 19, 575 in 2012, 21, 984 in 2013, and 22, 305 in 2014.  Even though the number decrease to 18, 457 in 2015 (“Bankruptcy Statistic December 2016,” 2016) .  Therefore, the number of bankruptcy declared in Malaysia is still at a worrying level.


Figure 1: The Number of bankruptcies in Malaysia from 2007 to 2015

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1.1       Definition of Bankruptcy

Bankruptcy is officially proclaiming that he or she cannot pay the outstanding debt (Nair, Paim, Sabri, & Rahim, 2016). Bankruptcy filing specifications vary widely among different countries.  According to the Malaysian Bankruptcy Amendment Act 2017, an individual does not need to owe millions to be bankrupt. Having a minimum amount of RM50,001 in outstanding debt can initiate bankruptcy (Law of Malaysia, 2017).

            1.2       Problem Statement

                The Accountant General’s Department of Malaysia stated that 61,726 out of 1.59 million public servants receiving net income of less than 40 percent of their monthly emoluments (“Penjawat awam bankrap meningkat,” n.d.). Besides, Minister in the Prime Minister’s Department Datuk Seri Azalina Othman Said said the number of public servants declared bankrupt in 2016 increased by 13 percent which is 1,093 compared to 960 in  2015, 606 people in 2014 and 617 people in 2013 (“3,276 penjawat awam diisytihar bankrap,” 2017). Bankruptcy is one of the signs of economic illness according Xioa (2013).

            There are many studies has been conducted regarding bankruptcy topics.  Claessens and Klapper (2002) tabulated the number of bankruptcy in different countries such as Australia, Hong Kong, Ireland and Russia. Based on the results, the top five countries with high number of bankruptcy are the United States, United Kingdom, France, Germany and Japan.  But there are less studies has been conducted regarding bankruptcy topics in Malaysia.

In short, consumer bankruptcy is a serious issue not just in Malaysia but also to other countries.  Hence, this study will examine the factors that affecting the number of consumer bankruptcy among public servants in Selangor




             2.1 Lending Rate

Lending rate can be defined as additional charge of borrowing where this rate influence the demand and supply of loanable funds.  Increasing in lending rate will increasing the supply of loanable funds, however, it will decreasing the demand for loanable funds as it gives disadvantages to debtors which the loan payment will be high compared to the principal they get.  The high loan payment could lead people to the bankruptcy as some of researchers have found lending rate is one of the factor to the number of bankruptcy.  According to Feldstein (1998), an increasing in prevailing lending rate will increasing the monthly debt payments and vice versa.  His found that, in 1993 and 1994, the bankruptcy rate fall after the declining in lending rate and then the bankruptcy rates rise back when the lending rate are increasing in later 1994 and 1995.  In addition, White (2007), found that people face difficulties to repaying their debt due to an increasing in lending rates which it may lead people to bankruptcy.  This is due the lending rate will increasing the monthly debt payment where the debt payment will exceed their capabilities to pay the debts.

Besides that, some of researchers found that high lending rate will decrease demand of borrowing while lower lending rate could lead to bankruptcy.  According to Livshits, MacGee and Tertilt (2010), higher interest rates makes demand of borrowing declines.  This is due the fact that people are less likely to borrow money when the interest rate are high.  Nakajima and Ríos-Rull (2014), also found the same result where the consumer consumption are 20 percent more volatile when credit available during recession.  However, lower lending rate making borrowing more attractive and it will lead economic growth and inflation might happen.  When inflation happens, it might increase the burden of consumers who are holding many debts and might lead to the increase of bankruptcy.  Furthermore, Fieldhouse, Livshits and MacGee (2015), stated that increase in the cost of borrowing during recession limits ability of households to smooth their financial shocks over time, and lead them to fall in debt and increase in bankruptcy filings during recession.  Therefore, we postulate that there is a relationship between lending rate with the bankruptcy rate.

2.2 Unemployment Rate

Unemployment is a word that describe a person with no job where its rate is one of the factor influencing the bankruptcy rates.  According to Hilwa Hilmy, et al. (2013), found that unemployment rate has significantly relationship toward bankruptcy.  The author found Malaysian people who have insufficient income to pay their debts due to job loss are more likely to lead to a bankruptcy case in a country.  In another research done by Komoto (2014), the author study the correlation between the gamblers pathologist`s clinical characteristics and suicide attempts and history of bankruptcy. The result imply that gamblers who file for insolvency are be more likely unemployed as unemployment rate are positively correlated with bankruptcy rate.

Furthermore, other researchers also found the unemployment rate is one of the factor people filing for bankruptcy.  According to Jacoby et al. (2003), households that experienced unemployment are 30% more likely to file for bankruptcy besides unexpected expenses and difficulties paying medical bills.  In addition, according to Chakravarty and Rhee (1999), they also found that unemployment problems have a positive significant to the probability of bankruptcy filing.  They states that family with an unemployed-head is 23% more likely to file for insolvency for job loss.  National Longitudinal Survey Youth (NLSY) also indicates similar results that households are over three times more likely to file for insolvency in the year at once following a job loss (Benjamin, 2015).  The author also found that 1000 employment losses is  linked with a tripling of the country insolvency rate.  Thus, the country with higher living rate have higher risk of bankruptcy for consumers living in that country (Agarwal, S. et al., 2008). 

According to Desai (2015), the expected bankruptcy rate of portfolio increases with its beta.  This is a research based on 25 portfolios by using country level data on unemployment and.  The results shows that the highest number of bankruptcy filings per 1000 population is in the portfolio with the lowest income growth and the highest unemployment rate.  Thus, increase in unemployment rate causes an increase in personal bankruptcy filings.

However, there is a studies that found working people have tendency to bankruptcy compared to unemployed people.  Garret and Ott (2005) found unemployment rate has negative relationship to the bankruptcy rate.  They stated that lower income group are likely to filing bankruptcy where these group have less financial literacy.  In addition, Uzzi (1988), found working group are likely to filing bankruptcy.  The author shows that the white collar workers which is the largest working population are filing personal bankruptcy more than the group of people who are unemployed, disabled and retired.   This is due the working group have high debt compared to unemployed group where these working group are likely to have high standard of living.  Therefore to afford these standard, they might increasing the demand for loan or usage of credit card.  Thus, the working group also contribute to bankruptcy rates. 

2.3 Medical Debt

Medical debt incurred when people have insufficient fund to pay their medical bill by their own. Usually, medical debt happen when medical cost rise and put consequences to people do not have medical coverage or unaware of the benefit of health insurance.  According to Feldstein (1998), he found that rise in medical cost put uninsured people in at a greater default risk.  According to Census Bureau, some 40 million Americans have no health insurance and they found that percentages of the population lacking health insurance have positive correlation to the state-level bankruptcy (as cited in Feldstein, 1998). 

Furthermore, according to Chakravarty and Rhee (1999), the authors found that there are significant determinants of the probability of filing for bankruptcy due to health reason.  The author added people filing for bankruptcy due to health reasons have health problems and do not have Medicare/Medicaid coverage.

According to Fan and Yavuzoglu (2013), there are three possible explanations of choosing to stay uninsured where lack of financial resources is one of the reasons.  Secondly, healthy people may choose to stay uninsured due to unfair insurance market in United States.  Lastly, bankruptcy can be used as an implicit health insurance.   Implicit health insurance can be defined as opportunity cost when people declared bankruptcy.  Mahoney (2012), stated that people declared bankruptcy can receive implicit health insurance as stated in bankruptcy exemption law.  Based on this research, the author found that households who do not have insurance with more assets are likely to have health insurance, and are likely to be affluent households. Thus, based on these research, we can implied that medical insurance/cost has significant to bankruptcy rate due to people filing bankruptcy to obtain implicit insurance.

Besides that, the country that have higher population with no medical coverage is positively contribute to the bankruptcy rate in one states which supported by Agarwal, et al. (2008), Agarwal and Liu (2003). There is a great deal of recognition that medical expenses contribute to an increase in personal liabilities. These included Laos, Belgium, (where out-of-pocket expenditure on health care is more than 60%) and Malaysia (which reported that there was a medical bankruptcy case among credit card holders who paid the hospital fee with credit card).  Next, Vietnam reported that being unable to cover medical expenses is the cause of disability because there was no bankruptcy application system. There are 2002 studies is estimated that 6% to 8% of families are facing disasters in medical expenses and In a recent survey, disaster medical expenses have been identified as major causes of family concerns in regional studies (Sarah, 2010).  In addition, according to the survey done by Austin (2014), debtor responses medical bills as the largest reasons they filed for bankruptcy.  Based on the survey, 26 percent of the surveyed people choose medical debt as cause of consumer bankruptcy followed by job loss (20 percent) and other expenses (19 percent).

Furthermore, United States has introduced medical crowdfunding in order to help people have funds to settle medical cost.  According to Burtch and Chan (2015), they found medical crowdfunding has significant impact to the bankruptcy rate as it reduce bankruptcy rate. This implied that rising in medical debt has contribute to the rate of bankruptcy.


                This study attempt to answer the following questions:

(i)    Does lending rate, unemployment rate, and medical debt play an important role in influencing the number of consumer bankruptcy among public servants in Selangor?


(ii)  What is the best predictor for the number of consumer bankruptcy among public servants in Selangor?


4.0       Hypothesis

            Hypothesis 1

 : Number of bankruptcy in Malaysia is not affected by lending rate

 : Number of bankruptcy in Malaysia is affected by lending rate

            Hypothesis 2

 : Number of bankruptcy in Malaysia is not affected by unemployment rate

 : Number of bankruptcy in Malaysia is affected by unemployment rate

            Hypothesis 3

 : Number of bankruptcy in Malaysia is not affected by medical debt

 : Number of bankruptcy in Malaysia is affected by medical debt


5.0       RESEARCH             OBJECTIVES

The main objectives of this study is to investigate the relationship of lending rate, unemployment rate, and medical debt to the number of consumer bankruptcy among public servants recorded in Selangor.  Thus, the specific aims of this study are:

                     i.        To analyze the relationship of lending rate, unemployment rate, and medical debt to the number of consumer bankruptcy among public servants in Selangor.


                    ii.        To identify the best predictor for the number of consumer bankruptcy among public servants in Selangor.



            For research purposes, this framework is the basis for creating variables    related to the problem. The Figure 1 shows three independent and dependent     variables. The independent variables in this research are lending rate, unemployment rate and medical debt. These independent variables will affected the dependent variable which is affecting the number of consumer bankruptcy among public servants in Selangor.

Figure 1: Theoretical Framework

Adapted: Cheang, W. C., Tsen, E. J. Y., Low, H. C., Ng H. S., Ong, M. L. (2015). Factors of Consumer Bankruptcy: A Case Study in the United States.

Argawal, S., and Liu, C. (2003). Determinants of Credit Card Delinquency and Bankruptcy. Journal of Economics and Finance, Vol. 27, Number 1.

Hilwa Hilmy, Shaliza A. Mohd. Z., Norasyikin A. Fahami. (2013). Factors Affecting Bankruptcy : The Case of Malaysia. International Journal of Undergraduate Studies, 4-8.

White, M. J. (2007). Bankruptcy Reform and Credit Cards. NBER Working Paper Series, Working Paper 13265, National Bureau of Economic Research.



            Each research has its own research design as a guide to process flow. This design may include a research plan to achieve the purpose. The direction of this survey is to investigate factors affecting consumer bankruptcy in Malaysia specifically public servants in Selangor . Several facts are known through exploration research, but more information is needed to create a viable theoretical framework. In such a case, before researchers develop models and do strict design for thorough investigation, the extensive preliminary work needs to be done to gain familiarity with the phenomena in the situation. Furthermore, the unit analysis  will be public servants in the Secretary Office of State of Selangor. Questionnaires are distributed and collected after field work. The time of this session is short because there is no comparative study. Researchers conduct natural surveys or on-site investigations (correlation studies) with minimal intervention.



            In this survey there are two sections of the questionnaire, and part I (A) and part II consists of four subparts (B, C, D, E). In Part I, the measurement scale used is the nominal measurement scale. The nominal scale is used for variable labels. In our questionnaire, part I (A) contains all demographics information of respondents and questions such as age, sex, marital status, educational level, race, work experience, and income. To date, in the nominal scale type, the question that has only two categories (male / female) is called “dichotomy”. For part II (subparts: B, C, D), the scale of the measure to use is the interval scale. This is because the given question is used likert scale. Respondents will rate the question from 1 to 10. Another example of the interval measure is a time scale as it is a good example, as the increase is known, measurable and constant.



            The validity and reliability of data collection equipment plays an important role in quantitative research as a measure of the validity of how instruments estimate construction. Also, guarantee that the question is subjective and not biased (error free). The reliability of the data scale is tested using Cronbach’s alpha test to determine if the existing structures are designed to be consistently consistent with each other. The scale reliability range of the alpha coefficient is 0 to 1.


10.0    SAMPLING

            Sample size is the amount of sampling selected for research purposes. According to Saunders, Lewis and Thorhill (2009), researchers need to acquire large samples in order to lower or reduce the error that contained in sample size. This survey will be conducted in a series of questionnaires given to Selangor Public Servants. The target population is a public servants of Selangor. The sample size was taken from the staff of Secretary Office of State of Selangor. A total of 377 samples were determined using the tables of Krecjie and Morgan as sample size (n) by 17,000 staff of Selangor (Krecjie and Morgan, 1970). Simple random sampling is used as probability sampling. Questionnaires are randomly distributed to officials working at the Secretary Office of State of Selangor..










Total Sample of Public Servants That Work At Secretary Office of State of Selangor
(377 workers)







            Distribution of questionnaires to the public servants especially staff at Secretary Office of State of Selangor will be a method of data collection in this research. We will create a questionnaire based on the following framework. A flow process consists of concepts, dimensions, and elements. To create a questionnaire we start with an important part which is the main concept of this research. Then, the dimension is determined based on the above main concept, and the last part is to create elements of the question. The figure as shown below are the concept, the dimension and the elements for this research


The table as shown below are the questionnaires that consist of 4 parts with        different

scale. The questionnaire was a formulated written set of question and the respondents will answer their question, usually within rather closely defined alternatives (Sekaran and Boungie, 2009). Actually, it can be an effective collection mechanism as the researcher could as what is exactly they needed and how to measure the variables of interest The Likert scale will be used with starting number with 1 for “Strongly Disagree” to rating number 10 for “Strongly Agree”. The questionnaires will be shown In Appendix part.




            After conducting the field survey through the survey session, the data obtained from the questionnaire was analyzed using the Statistical Package for Social Science (SPSS) and the results were obtained. The results are evaluated based on the hypotheses developed in the previous section. There are some tests and analyzes will be used such descriptive statistics, normality tests and reliability, and validity tests on SPSS Ver. 21. As mentioned above, the survey result was obtained from the questionnaire distributed to 377 respondents. According to Sekaran and Bougie (2010), this survey is accepted as the sample size we are looking for is a sample size of 30 or more but less than 500 samples. Since the question in Section I (A) is based on demographic information, the data is displayed and sorted in a table of percentage of circles according to the categories shown in the demographics information. For questions on Section II (B, C, D and E), we will obtain the results from the SPSS tool for descriptive purposes. Descriptive statistics can be defined as a collection of concise descriptive coefficients giving a concise description of a series of data that can represent the entire population or the entire sample. To extend the description of this data analysis, analyze the relationship between dependent variables and independent variables using Pearson correlation coefficients. This analysis tool is useful because it is a process of analyzing analysis. FIG. 5 shows an analysis of Pearson correlation coefficients based on previously analyzed and studied independent and dependent variables.



            This research is expected to provide input and information for the development of knowledge by expanding broader research by future researchers. The purpose of this research is to review and expand the factors that affect Malaysian consumers’ bankruptcy, in particular the existing knowledge of public servants in Selangor. Indeed, this problem can be explained more because many people are involved such as the government, universities, and other relevant agencies.



            In conclusion, this problem is increasing every year, and it become so silent nowadays since there are lack of studies on this issue. Because of its impact on economic growth, there must be some precautions to address this issue. That is why this research focuses on public servants in Selangor State and checks if they understand this problem. Based on the above independent variables, there is a high possibility that it will affect consumer bankruptcy. As for future studies, It is highly recommended to explore deeply on this issue. This is not only for the future of our economy but also for the development of the nation.


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