IJERD – International Journal of Environmental and Rural Development (2011) 2–1

Research article
erd

Impacts of Micro-credit on Household Economics
SIVCHOU TENG
University of Battambang, Battambang, Cambodia
Email: sivchouteng@yahoo.com

SOKHAK PRIEN
University of Battambang, Battambang, Cambodia

NARA MAO
Royal University of Agriculture, Phnom Penh, Cambodia

BUNHOR LENG
Royal University of Agriculture, Phnom Penh, Cambodia
Received 17 December 2010

Accepted 25 January 2011

Abstract This research was conducted to investigate the impacts of micro-credit on local
household economics in Prek Norin Commune by focusing on people who took a loan
from microfinance institutions and continue to use it. This study mainly focuses on threeobjectives, socio-economic factors of households using credit, the status of using microcredit and effects of micro-credit on household economics. Data were collected via survey,
using face to face interviews with a hundred and forty two household heads. Simple
random sampling method was used to select the samples from two villages (Prektachreng
and Prek Krouch) in Prek Norin Commune, Ek Phnom district, Battambang province.
Therefore, the accuracy of the analysis heavily relies on the data provided by interviewees.
The result of this study revealed that those using micro-credit have better living standards
than before because of income and asset growth. In addition, using micro-credit also
creates more job opportunities and variety of economic activities, provides more jobs for
women,   and   improves   household   education,   women’s   status,   and   family   welfare.   It   also  reduces income inequality in the villages. However, micro-credit has negative impacts on
people’s  feeling  because  most  people  are  more  concerned  about  paying  back  the  loan.
Keywords impacts, micro-credit, economics

INTRODUCTION
Microfinance is a development program related to the provision of financial services to people with
low incomes; these services are credit, saving and insurance (Khan and Rahaman, 2007; Wanchoo,2007 and Bakhtiari, 2006). Microfinance is recognized as the most essential tool for poverty
alleviation in many developing countries (Brandsma and Chaouli, 1998; ADB, 2000; Emilia, 2005;
Posner, 2007 and Shastri, 2009), and microfinance is an effective instrument that can improve onmost  important  things  for  poor  people  such  as  households’  welfare,  education,  economics,  people’s  living standards and empowerment of women (Felix, 2007 and Singh, 2004). Even though some ofthe studies showed that microfinance can reduce poverty, people who used credit did not know how
microfinance could help to alleviate poverty (Khan and Rahaman, 2007).
Most of the research studies showed that microfinance could provide a lot of positive resultson peoples household economy such as creating more job opportunities, increasing householdincomes,   building   up   women’s   abilities,   improving household education and family welfare;however, microfinance could also be a heavy responsibility for people too. When people usedfinancial service, they could increase household income more easily than before, buy morehousehold’s   assets,   and   improve their living standards. Especially the group of poor households
who have used microfinance to change their daily livelihood by preparing their future plans such,© ISERD108

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as household investment and income, building and fixing their houses, improving family welfare
and education (Bakhtiari, 2006 and Felix, 2007).
In Cambodia, the number of Microfinance institutions (MFIs) has increased significantly,
especially in this last decade. A number of people borrowed funds from those MFIs to set up theireconomic activities, but up until now there has been no research study that shows how micro-credit
affects  people’s  lives.  Therefore,  this  study  was  conducted  to  find  out  the  impacts  of  micro-credit
on   people’s   living   status.   According   to   this   research   objective,   a   hypothesis was set that microcredit  provided  positive  results  to  the  people’s  way  of  living.
METHODOLOGY
Quantitative research was applied, so that structured interviews were used to interview a hundredand forty two households heads by selecting them from two villages, Prek Tachreng and Prek
Krouch, in Prek Norin Commune, Ek Phnom District, Battambang Province.
This study relied on two types of data; primary data and secondary data. Primary data whichwere collected from people through questionnaires was used as the most important data in thisresearch. Therefore, the questionnaires were pre-tested in order to correct some difficult questions.
A lot of documents such as the last research thesis, journal, and paper were used as secondary datato compare with the similar research all over the world.
The sample size was defined by using non-probability sampling method, selecting only thepeople who took a loan from institutions and continue to use it. Purposive sampling method wasused to select the research location and the simple random sampling method was used to selecthousehold heads using credit from the list given by both village chiefs.
Data collected from interviewees was coded and entered into Ms Excel and SPSS for analysis.
The data were analyzed in two ways, qualitative and quantitative data analysis. Descriptive andinferential statistics were used in data analysis, which were Time Series Regression, ANOVA, Chisquare Test, Gini Coefficient, Lorenz Curves, Graphic and Charts.
RESULTS AND DISCUSSION
Profiles of households using micro-credit
Interview status was focused on gender, age, marital status, education and time duration of living inthis study area and the main annual income of every household using micro-credit. The results inTable 1 showed that 93 percent of families using credit were women, and only 7percent were men.
The majority of credit borrowers were over thirty years old; besides this, they were in the age groupof eighteen to thirty years old. Among all borrowers, most of them did not have high education,
which 17 percent never having gone to school, 59 percent studied in primary school, 23 percent
studied in secondary school, and only 1 percent studied in high school.
In addition, the result showed that 23.50 percent of seventy-one households were the families
having a main job as doing business, 23.50 percent selling labor, 14.70 percent feeding animals,
10.30 percent rice farmers, and 11.80 percent having other jobs. The result of this study also
illustrated that 41 percent of household using micro-credit could earn incomes between 15 to 10
million riels in a year, and only 7 percent could earn incomes over 20 million riels per year fromhouseholds’  main  jobs.
Income distribution during 2008-2009
Fig. 1 indicated that household income distribution curve in 2008 moved away from the perfectequality; it means that income distribution of people in 2008 had inequality between group ofpeople having high incomes and low incomes. Whereas, the Lorenz curve represented for income© ISERD

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distribution in 2009 had moved toward the perfect equality line than in 2008; it showed that income
inequality of each household in 2009 was in low level. Moreover, Gini coefficient of incomes in2009 (Gini=0.3484) fell down by comparing with 2008 (Gini=0.3847). This fall also illustrated that
income inequality in 2009 was better than the last year, so micro-credit could help to reduceincome inequality of people living in this study area.
Table 1 General status of interviews
Variables
Gender (n=71)
Age

Education

Main jobs in family

Annual Incomes (Main jobs)

Categories
Male
Female18 to 30 years old
31 to 40 years old
Over 40 years old
Illiteracy
Primary school
Secondary school
High school
Doing Business
FarmerLabor selling
Animal feeding
Other jobs
1 to 5 million riels
5,000,001 to 10,000,000 riels
10,000,001 to 20,000,000 riels
Over 20,000,000 riels

Percentage
7.00
93.00
20.00
21.00
59.00
17.00
59.00
23.00
1.00
38.00
28.00
11.00
10.00
13.00
38.00
41.00
14.00
7.00

Income distribution during 2008-2009
The Fig. 1 represented that households income distribution curve in 2008 moved away from theperfect equality; it means that income distribution of people in 2008 had inequality between groupof people having high incomes and low incomes. Whereas, the Lorenz curve represented forincome distribution in 2009 had moved toward the perfect equality line than in 2008; it showed that
income inequality of each household in 2009 was in low level. Moreover, Gini coefficient ofincomes in 2009 (Gini=0.3484) fell down if comparing with 2008 (Gini=0.3847). This fall also
illustrated that income inequality in 2009 was better than the last year, so micro-credit could help toreduce income inequality of people living in this study area.

Fig. 1 Income inequality between 2008 and 2009

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Status of using micro-credit
The Fig. 2 indicated that the total loan size of those borrowers in this area had increased from 2005
to 2009 according to the function of time series regression: y = 23,240,000 x -46,581,806,000,
which x demoted the year, and y represented the total loan size in year x. The result displayed thatthe total loan size had grown up 23,240,000 riels per year, and this loan size had related to the year
significantly (ANOVA: p = 0.0066**), which this model could be used to forecast the total loan
size of sampling households to be 130,594,000 riels in 2010.

Fig. 2 Comparison of total loan size from 2005 to 2009
Impact on household’s  incomes
The study on impact of micro-credit on incomes was observed by the different important types ofmain jobs such as doing business, agriculture, labor selling and other jobs from 2006 to 2009. It
indicated  that  the  mean  of  households’  incomes  increased  consequently  during  this  period  (Fig.  3).

Fig. 3 Increase of income in different job sectors from 2006 to 2009

Fig. 4 Time series regression of increasing assets© ISERD

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Impact on household’s  assets
The  study  on  households’  asset  status  in  this  area  was  focused  only  on  the  important  assets  such as
TV, motorbikes, bicycles and telephones and the other assets. According to the time series
regression analysis of asset growth, it showed  that  the  amount  of  households’  assets  in  this  study  area had increased after using micro-finance until now. Through the function of time series
regression  analysis  on  households’  asset,  it could be estimated that the asset growth in 2010, which
TV would increase to 53, motorbikes to 60, bicycles to 65 and telephones to 63 (Fig.4).
Impact on household’s  job opportunities
The result in Table 2 showed that the job opportunities had changed a lot, starting from having only
one job to more jobs in each household after using micro-credit. In fact, during 2006 most ofpeople had one job, and only a few people had two jobs in their families. However, in 2009 themajority of households had two jobs in the family, and the minority households had three jobs.
Table 2 Comparison of job opportunities of people from 2006 to 2009
Year
2006
2007
2008
2009

Percentage of households
Two Jobs
25
36
49
62

One Job
70
56
41
21

Three Jobs
5
8
10
17

Impact on women, education and welfareThis study had shown that most of people using micro-credit were women who had right to makedecision  on  households’  problems.  In  addition,  all  of  those women had a lot of job opportunities,
and  had  been  involved  in  income  generating  activities  for  households’  living.  
The result also proved that using micro-credit could empower the level of education throughborrowing   loans   to   pay   children’s   school   fees and earning incomes for sending their children toschool. Surely, 72 percent of households brought up children to school and left opportunities forthem to get training. Furthermore, women also had more ability to supply food and nutrition forhouseholds’ daily living. Therefore, using micro-credit could not only helped to increasehouseholds’   income,   assets   and   job   opportunities,   but   it   could   help   to   empower   women   to   be  involved   in   society,   provide   household   members’   educational   opportunities   and   make   family’s  welfare better, too.
Impact on feelingAccording to the results of interviews, the interviewees had observed that 34 percent of them wereconcerned about repayment the loan such as, paying late and having not enough money on the due
date of the capital repayment. Some households were worried about confiscation of their lands,
houses and assets by microfinance institutions they borrowed from. Some of other household wereconcerned about getting sue by institutions when they had no abilities to pay the loan in order toreceive their mortgage-able things back. Moreover, most of those people did not want to beembarrassed or loss of reputation. All the above reasons revealed some negative impacts on
people’s feeling using micro-credit.
According to the result of hypothesis testing through ANOVA analysis on annual incomes, themeans  of  those  household’s  annual  incomes  had  increased  consequently  from  2006  to  2009  in  the  level of significant testing at 10 percent, which p=0.086*. This result indicated that using microcredit could help people to increase their incomes as the same as result of last researchers such as
Dieckman, (2007); World Bank, (1998); Yunus, (2006); Yunus, (1999); Doocy et al., (2003);© ISERD112

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Goldberg, (2005); Ottogenghi, (2008); Shetty, (2006); Rahman et al., (2009); Ghalib, (2007);
Pathirange, (2005); Rajat, (2007); Hassan, (2006).
The  testing  on  household’s  assets  by  using  time  series  regression  model  focused  on  only  the  very important assets of people using micro-credits. The result of analysis showed that the amountof televisions, motorbikes, bicycles and telephones increased strongly in statistic at
p=0.000***<0.001, which means that the increase of all above assets had strong correlation withthe year when those assets were bought. This revealed that after using micro-credits,  household’s  assets could increase, and it was the same as the findings of some last researchers such as ADB,
(2007); Kaboki and Townsend, (2002); Zaman, (2000).
Women

WelfareEducation

Affect FeelingMicro-credit
Increased Assets

Provided Job
Opportunities

Household’s Economics

Increased
Savings

Increased
Incomes

Increased Expense

Decreased Incomes
Inequality

Fig. 5 Summary diagram of impact of micro-credit on household’s economics
Furthermore,  the  study  showed  that  using  credit  could  improve  households’  living  and  other  expenditure abilities such as spending on medical treatment to be helthier, and this study was thesame as the result of Datar et al.,(2008), which indicated that microfinance had positive impacts on
livelihoods and welfare when income increased. Additionally, micro-credit also helped to provide
job opportunities for women, empowered women and provided educational opportunities forchildren, that was similar with the findings of Sayasene (2007); and Maldonado (2002).
CONCLUSION
According to the overall results of this study, it can be concluded that micro-credit was strongly
related to the improvement of household’s   economics.   In   addition, micro-credit had improved
household’s   living   to   be   better,   because   it   could   increase   household’s   incomes,   assets,   job  opportunities, the empowerment of women, education and family welfare to those people using
microcredit. However, data also showed that micro-credit created some negative impact such as thestress of borrowing. Despite this, we can say that microfinance is an effective tool for poverty
alleviation in Cambodia.
ACKNOWLEDGEMENTS
We would like to give our regards to local authorities. The Prek Norin Commune leader, Prek Tachreng
village leader and Prek Krouch chiefs, who gave a lot of information and documents related to peopleusing micro-credit in this study area. Especially, we would like to say thanks to the people using microcredit in both villages who had spent their value time to give interviews for our study.

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