Impact evaluation of micro-credit on welfare and poverty on the Vietnam rural household.pdf

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES
HO CHI MINH CITY THE HAGUE
VIETNAM THE NETHERLANDS
VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
IMPACT EVALUATION OF MICROCREDIT ON
WELFARE OF THE VIETNAM RURAL
HOUSEHOLD
BY
PHAM TIEN THANH
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
HO CHI MINH CITY, OCTOBER 2012

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES
HO CHI MINH CITY THE HAGUE
VIETNAM THE NETHERLANDS
VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
IMPACT EVALUATION OF MICROCREDIT ON
WELFARE OF THE VIETNAM RURAL
HOUSEHOLD
A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
By
PHAM TIEN THANH
Academic Supervisor:
DR. PHAM BAO DUONG
HO CHI MINH CITY, OCTOBER 2012

i
DECLARATION
I certify that the contents of thesis have been carried out and written by me to the
best of my knowledge and with the support in preparing this paper from many
different sources.
I certify that this thesis has not been submitted to any other programs or journals.
HCMC, October 15th
, 2012
PHAM TIEN THANH

ii
ACKOWLEDGEMENTS
This thesis is impossible to be achieved without the support and assistance of the
following people:
Firstly, I would like to express my greatest gratitude to Dr. Pham Bao Duong, my
academic supervisor, who advised and instructed and supported me during the
process of this thesis. His expertise and his suggestions have provided a good basis
for the improvement of my research. His enthusiasm and encouraging is also a
motivation for me to achieve me thesis.
I would like to give my special thanks to Prof.Dr. Nguyen Trong Hoai, Dean of
Vietnam–The Netherlands Programme and Dr. Pham Khanh Nam, Academic
Director of Vietnam –The Netherlands Programme. Their knowledge and
enthusiasm has supported me a lot during my thesis writing process.
This is also a good opportunity to express my appreciation to all the lecturers who
equipped me with valuable knowledge during my study at Vietnam –The
Netherlands Programme.
I would also like to appreciate Mr. Nguyen Khanh Duy, Lecturer at the Faculty of
Development Economics, University of Economics, Ho Chi Minh City. His support
with data as well as using econometrics software is a great contribution to the
completion of my thesis.
Lastly, I am grateful to my beloved parents who gave moral support and encouraged
me to finish my thesis during writing process.

iii
ABSTRACT
This research evaluates the impact of microcredit on the welfare of
households living in the Vietnam rural areas, especially the poor. The research is
analyzed based on a data of the Vietnam household living standard survey
(VHLSS) in the year 2008. The difference of the research in comparison with the
previous studied about the relationship between microcredit and welfare is the
employment of propensity score matching (PSM) method, thus it reflects the impact
of microcredit on rural households’ living standard better and more precisely. The
result shows that microcredit will result in better welfare of rural households via a
greater increase in the income and consumption per capita per month of the
participating households. However, the result about the poor rural households
showed that microcredit does not result in a higher increase in income of the
participants than that of the nonparticipants, but contributes to a greater rise in the
consumption.
The research also showed the determinants on the accessibility to microcredit
programs of the households living in rural regions.
The results found out that the probability of accessing the microcredit
sources of the rural households in Vietnam is still low. Moreover, the proportionate
of accessibility to microcredit of the poor household is even less that of the non-
poor households, which means microcredit programs mistarget the poor households.
From those results, the research gives policy recommendations to improve
microcredit programs in rural areas as well as to support more poor households to
access to microcredit sources.

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TABLE OF CONTENT
DECLARATION................................................................................................................ i
ACKNOWLEDMENTS ................................................................................................... ii
ABSTRACT ..................................................................................................................... iii
TABLE OF CONTENT .................................................................................................. iv
LIST OF ABBRIVIATIONS .......................................................................................... vi
LIST OF TABLES AND FIGURES ............................................................................. vii
CHAPTER I .......................................................................................................................1
INTRODUCTION..............................................................................................................1
1.1. Problem Statement .......................................................................................................1
1.2. Objectives of the study .................................................................................................4
1.3. Research questions .......................................................................................................4
1.4. Organization of the research ........................................................................................5
CHAPTER II .....................................................................................................................6
LITERARTURE REVIEW ..............................................................................................6
2.1. Overview of Poverty ....................................................................................................6
2.1.1. Definition ..................................................................................................................6
2.1.2. Method of defining poverty ......................................................................................7
2.2. Overview of Microcredit...............................................................................................8
2.2.1. Some definitions ........................................................................................................8
2.2.2. Characteristics of Microcredit ...................................................................................9
2.2.3. Overview of rural credit market in Vietnam ..........................................................11
2.2.4. Overview of microcredit program in Vietnam .......................................................12
2.3. Empirical Study ..........................................................................................................17
2.3.1. Impact of micro credit on welfare/ living standard of the rural households ...........17
2.3.2. Determinants of the accessibility to microcredit programs ...................................24

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CHAPTER III ..................................................................................................................30
RESEARCH METHODOLOGY AND DATA DESCRIPTION ...............................30
3.1. Model of determinants of access to credit .................................................................30
3.2.Impact Evaluation techniques .....................................................................................34
3.2.1. Some Definition ......................................................................................................34
3.2.2. Impact evaluation using PSM technique .................................................................34
3.2.3. Impact evaluation using DID technique...................................................................38
3.3. Data Description .........................................................................................................41
3.3.1. Survey area ..............................................................................................................41
3.3.2. Data sources ............................................................................................................41
3.3.3. Sample selection ......................................................................................................41
CHAPTER IV ..................................................................................................................44
RESULT ...........................................................................................................................44
4.1. Descriptive Statistics ..................................................................................................44
4.2. Determinants on microcredit participation ...............................................................46
4.3. Impact of microcredit on welfare of rural households using PSM .............................51
4.4. Impact of microcredit on welfare of the rural poor using PSM..................................52
4.5. Impact of microcredit on welfare of rural households using DID with fixed
effect...................................................................................................................................55
4.6. Comparison between the results of PSM and DID method ........................................56
4.7. Comparison with previous studies .............................................................................57
CHAPTER V ...................................................................................................................59
CONCLUSION, POLICY RECOMMENDATION AND LIMITATION ................59
5.1. Conclusion ..................................................................................................................59
5.2. Policy Recommendation ............................................................................................62
5.3. Limitation ...................................................................................................................64
REFERENCES.................................................................................................................65
APPENDIX .......................................................................................................................63

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LIST OF ABBREVIATIONS
GSO General Statistics Office
MOLISA Ministry of Labor, Invalids and Social Affairs
DOLISA Department of Labor, Invalids and Social Affairs
MFIs Micro Finance Institutions
VBA Vietnam Bank for Agriculture and Rural Development
VBSP The Vietnam Bank for Social Policies
WB World Bank
UN The United Nations
PSM Propensity Score Matching
VHLSS Vietnam household living standard survey
NN Nearest neighbor
PSM Propensity Score Matching
DD or DID Difference in Difference or Double Difference

vii
LIST OF TABLES AND FIGURES
List of Tables
Table 2.1: Poverty Rate in Vietnam ...................................................................................7
Table 2.2: Characteristics of Microcredit Programs in Vietnam from 2005 to 2011 .........12
Table 2.3: Main Characteristics of the MFIs in 2011 .......................................................14
Table 2.4: Characteristics of Microcredit Programs by VBSP from 2005
to 2011 ............................................................................................................16
Table 2.5: Summary of Some Main Findings about the Impact of Microcredit
Programs on Welfare/ Living Standards ..........................................................20
Table 3.1: Descriptions of the Determinants on Accessibility to Microcredit ...................31
Table 3.2: Variables in the Analysis of the Impact of Microcredit using DID...................40
Table 3.3: Characteristics of Comparison Groups in 2008 ...............................................43
Table 4.1: Impact of Microcredit on Income/Consumption of Rural Households
using Independent Sample T-Test Methods......................................................44
Table 4.2: Impact of Microcredit on Income/Consumption of the Rural Poor
using Independent Sample T-Test Methods......................................................44
Table 4.3: Distribution of Eligibility with respect to Treatment Households ...................45
Table 4.4: Credit Access with respect to Eligible Households .........................................45
Table 4.5: Probit Estimations of Determinants on Accessibility to Microcredit ...............47
Table 4.6: Probit Estimation of Model 3 with Marginal Effect ........................................48
Table 4.7: Impact of Microcredit on Income of Rural Households using PSM..................51
Table 4.8: Impact of Microcredit on Consumption of Rural Households using PSM .......52
Table 4.9: Impact of Microcredit on Income of the Rural Poor using PSM.....................53
Table 4.10: Sector of Production and Business on Which the Loan was Spent ...................53
Table 4.11: Reasons of Unchanged or Worse Living Condition..........................................54
Table 4.12: Impact of Microcredit on Consumption of the Rural Poor using PSM ............54
Table 4.13: Impact of Microcredit on Welfare of Rural households using
DID with fixed effect.......................................................................................55
Table 4.14: Result Comparison between PSM and DID Method ........................................56
Table 4.15: Results from the Previous Studies....................................................................57

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List of Figures
Figure 2.1 : Gross Loan Portfolio of microcredit in Vietnam from 2005 to 2011 ...............13
Figure 2.2 : Characteristics of Microcredit Programs by VBSP from 2005 to 2011 ............15
Figure 2.3 : Determinants on Accessibility to Microcredit and Welfare Indicators ..............29
Figure 3.1 : Illustration of Impact Evaluation Using DID Method ......................................39

1
CHAPTER I
INTRODUCTION
The purpose of this chapter is to present chapter introduction of microcredit program as
well as scope of the research such research methodology, research data, research
objectives, and research questions.
1.1.Problem Statement
Vietnam is considered one of the few countries that has obtained the
remarkable achievement in poverty reduction. As annual reports by GSO showed, the
poverty rate has declined from 37.4 percent in 1998, to 18.1 percent in 2004 to 13.4
percent in 2008. In a report by GSO (2008), the poverty rate in rural areas (16.1
percent) was higher than that in urban areas (6.7 percent). A large number of farmers in
Vietnam are still living in poverty and under poor living standards. Moreover, they
have difficulties with accessing to credit sources especially, formal credit sources. As a
result, they mostly borrow from informal sources for financing their production as well
as for consumption. That results in the fact that they may fall into deeper debt and
default debt. Therefore, in order to gain the more preeminent achievement of hunger
eradication and poverty reduction as well as to help the poor escape from poverty, the
Vietnam Government have invested a great number of capital as well as provided
financial services to support the rural households, especially the poor in rural areas via
credit programs. One of the special credit programs that the Government applied the
program is microcredit.
As the definition by Microcredit Summit (1997), microcredit program is a
program which provides small loans to poor people so that they can generate income to
improve their living standard.
Many countries have applied microcredit programs as a tool of poverty
reduction as well as a channel of providing credit to rural households. Microcredit has
been popularly applied and its impact on welfare or living standard of households has

2
been studied by many authors. However, there are two mixed opinions about the
impact of microcredit as follows:
 On the bright side, Khandker, S. R. (1998), Yunus (2009) considered
microcredit as the tool for the purpose of poverty alleviation and hunger
eradication. To reaffirm this statement, the study by Alexander (2011), Zaman
(1999), Kumar (2005), and Sarangi (2007) showed that microcredit program has
positive impacts on the household’s welfare via increasing their income and
consumption.
 On the limited side, some researchers argued that microcredit insignificantly
affects welfare of households. Coleman (1999) stated that there is no evidence
of the microcredit program impact on the living standard which is reflected via
assets and income.
However, in Vietnam, does this program actually have impacts on welfare and
poverty of the rural households, especially the poor rural households as well as target
these poor households?
In Vietnam, there have been also many researches about the impact of
microcredit program on the households, especially the households in rural areas and the
poor rural households. Cuong Nguyen (2008) proved that VBSP microcredit programs
enhance the incomes and expenditures of the rural households in Vietnam. Also in his
research, microcredit program is found to decrease the poverty-gap and poverty-
severity indexes as well as contribute to poverty reduction of the participating
households positively. However, he found that among the participating households, the
proportion of the non-poor is higher than that of the poor. Tra Pham (2011)
reconfirmed that participation in microcredit programs by VBSP have positive effect
on self-employment profits of rural households. Moreover, she found that participation
in microcredit program results in the higher increase in income of the poorest
households than that of the medium-income households in Vietnam rural regions, then

3
this leads to the positive impact on poverty alleviation. In a research on the case of the
Vietnam rural households by Nadine R. & Peter P. M. (2012), microcredit program
was founded to improve the quality of water supply and the sanity system reflected via
safer removal of human waste.
The research is conducted in order to evaluate the impact of microcredit on
welfare of rural household, as well as the poor in rural areas. This research mainly
focuses on PSM method using cross-sectional data, and applies DID method with fix
effect technique using panel data to compare the results of PSM method. The
feasibility of PSM method is that there is no need pre- and post- program survey as
required in as Difference in Difference (DD) method. PSM method only requires the
post program survey, so it is very useful when there is not pre-program surveyed data.
Meanwhile, DID method with fixed effect regression can measure the difference in an
outcome pre – post attendance in the program, measure the difference in outcome
among factors at the same time (separate the impact of microcredit and other factors on
welfare), and the difference in outcome of impact of the program over time.
The analysis of this research relies on data collected by the General Statistical
Office of Vietnam (GSO), namely the Vietnam household living standard survey
(VHLSS) in the year 2006 and 2008. The microcredit loans in this research are only
derived from formal credit sources granted by VBSP, which is considered as the
greatest providers of microcredit and the most typical representative of financial
institution of the Government in anti-poverty program. In Vietnam, most of the poor
households are living in the rural areas; therefore, the research mainly focuses on
analyzing households in rural areas, as well as the poor rural households.
In addition to present the impact of microcredit on welfare or living standard of
the households, the research also presents the determinants on the accessibility to
microcredit programs of households living in the rural areas as well as the targeting of
this program.

4
Based on the results, relevant policies will be carried out to improve microcredit
programs, and to support the poor.
1.2. Objectives of the study
The general objective of this study is to evaluate the impact of the programs on
the welfare of the households living in the rural areas, especially the poor.
In order to achieve the overall goal, the research must meet the following
specific objectives:
i. Investigating whether microcredit programs have significant positive effects on
the living standards of the household living the rural areas.
ii. Investigating whether microcredit programs truly targets the poor rural
households.
iii. Investigating the determinants on the microcredit programs participation of the
rural households.
iv. Suggesting policy implications to develop this program as well as to support the
accessibility to microcredit programs of the rural households.
1.3. Research questions
In order to capture the research objectives, the research should answer the
following questions:
i. Does microcredit program have a significant positive impact on household’
welfare via income/ consumption per capita per month?
ii. Does microcredit program target the poor household in rural area?
iii. What is the determinants on households’ access to microcredit programme ?

5
1.4. Organization of the research
In order to achieve the above objectives, the structure of the research is
constructed as follows:
Chapter I : This chapter gives introduction about the microcredit program, research
methodology, research objectives, and research questions.
Chapter II : This chapter presents literature review and empirical studies about the
issues related to the research such as poverty, credit market in Vietnam
rural areas, impact of microcredit on welfare of the poor, as well as
determinants on the participation in microcredit programs.
Chapter III : The first part of this chapter presents methodology applied in the
research, especially focusing on the PSM technique. The second part
gives description of data used for analysis.
Chapter IV : This chapter shows the result of the research such as descriptive
statistics; the determinants on the participation of microcredit programs;
and the most important, the result of the impact of microcredit programs
on the welfare of the household via income per capita and consumption
per capita.
Chapter V : This chapter presents conclusions of main findings in the research,
suggests policy recommendations, and mentions limitations of the
research.

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CHAPTER II
LITERARTURE REVIEW
This chapter presents literature review and empirical studies about the issues related to
the research. The first part discusses about the overview of poverty regarding definition
of poverty and methods of defining poverty. The second part presents overview of
microcredit regarding definition, characteristics, microcredit market in Vietnam rural
areas and the operation of microcredit program in Vietnam, especially the case of
VBSP. The last part discusses the impact of microcredit on welfare of housholds, as
well as determinants on participation in microcredit programs by previous studies.
2.1. Overview of Poverty
2.1.1. Definition
There is no one single definition of poverty. Poverty can be defined as follows:
"The most commonly used way to measure poverty is based on incomes. A
person is considered poor if his or her income level falls below some minimum level
necessary to meet basic needs. This minimum level is usually called the "poverty line".
What is necessary to satisfy basic needs varies across time and societies. Therefore,
poverty lines vary in time and place, and each country uses lines which are appropriate
to its level of development, societal norms and values." - (The World Bank)
“Poverty is a situation in which a proportion of the population does not enjoy
the satisfaction of basic human needs that have been recognized by the society
depending on the level of economic and social development and local customs and
practices.” (Asia-Pacific Conference on Poverty Reduction by ESCAP, 1993).
There are many ways to define poverty. In general, poverty is expressed via
three main aspects:
1. The income is lower than the average income of whole population.
2. Living standard is below some minimum level necessary to ensure basic needs.
3. There is no opportunity to join or integrate to the development of society.

7
In Vietnam, the Government accepted the definition of poverty by Asia-Pacific
Conference on Poverty Reduction held by ESCAP (1993). Many methods to define
poverty have been developed by GSO and MOLISA. This research employed the
Regional Rating Method by MOLISA to define poverty as well as the poor households.
2.1.2. Method of defining poverty.
2.1.2.1.Expenditure / Consumption Method
This method specifies the poor via their expense on the goods baskets including
food and non-food good, in which the expense on food products must ensure the level
of 2000 kalo/capita/day. When the household cannot obtain this level, they are living in
poverty. This method is used and developed by The General Statistics Office of
Vietnam (GSO).
2.1.2.2.Income Method
This method specifies the poor via their minimum income in order satisfy their
minimum basic needs. The International poverty rate (by World Bank) states that
people with income less than 1USD/day are considered as living in poverty.
Meanwhile, the poverty rate in Vietnam has been calculated as follows:
Table 2.1: Poverty Rate in Vietnam
Region
Urban
(VND)
Rural
(VND)
Period
2004 218,000 168,000
2006 260,000 200,000
2008 370,000 290,000
2011 - 2015 450,000 35,0000
Source: Report by GSO and MOLISA (2010)
However, this method is not applied homogenously by each region. To obtain
the precise information on true income of households is very difficult because they
often have tendency to under-declare their income.

8
2.1.2.3.Regional rating Method
This method is applied and developed by MOLISA. To execute this, MOLISA
has employed such methods as investigation and reviewing in combination with quick
identification method, quantitative method and evaluation method under the
participation of households (Official Dispatch 3461/LD-TBXH-BTXH, 2011) . Then,
the households will be interviewed by Commune staff about such criteria as income,
expenditure, assets, house condition, dependency ratio, sanity condition, etc,.
Following these standards given by MOLISA, the local authorities at village level will
evaluate and choose which households are poor, then make a list and send to commune
authority. Then, the commune authority will review the list and send to DOLISA at
District-level for being issued “Certificate of poverty”.
Households with “Certificate of poverty” that will answer “YES” when being
question about their state of poverty are classified as the poor households in this
research.
2.2. Overview of Microcredit
2.2.1. Some definitions
a. Rural finance is defined as 'financial services offered and used in rural areas by
people of all income levels', and agricultural finances 'a sub-set of rural finance
dedicated to financing agriculture-related activities, such as input, supply,
production, distribution and wholesaling, and marketing'. (The Consultative
Group to Assist the Poor (CGAP) )
b. Rural credit is the credit which is given to the farmers for agriculture and other
purposes relating to rural activities. Rural credit makes up to 90 percent of
activities of rural finance market.

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c. Microfinance is defined as providing to the poor and low-income people with
variety of small-size financial services such as savings, credit and other basic
financial services. (United Nations).
d. Microcredit
“Microcredit is a program which extend small loans to very poor people for self-
employment projects that generate income, allowing them to care for themselves and
their families” (The Microcredit Summit, 1997).
Microcredit is defined as provision of thrift, credit and other financial services
and products of very small amount to the poor in rural, semi-urban and urban areas for
enabling them to raise their income levels and improve living standards”. (Reserve
Bank of India - Master Circular, 2011)
Microcredit programs have been considered as an effective tool for hunger
eradication and poverty reduction. Microcredit has been developed by the Grameen
Bank under the leadership of Prof. Muhammad Yunus, who received the Nobel Peace
Prize in 2006.
2.2.2. Characteristics of microcredit
In order to be considered as microcredit, the loan should include the such
characteristics as :
(1) The small loan size : The term "small loan" may vary in each country. As
Microfinance Institutions (MFIs), the amount ranges between $30 and $200.
In Bangladesh, the average loan size of microcredit is 393.55USD. A report by
Microcredit fund (MCF) showed that average size of microcredit loans is
795USD. In this research, the amount to be considered as microcredit is the
average loan size from VBSP at 444USD (Source: www.mixmarket.org in
2008).

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(2) The high interest rate: The rate may vary from 15 to 35 percent per year
(Microfinance Institutions).
(3) Targeting the poor: Du (2004) found that microcredit targets the poor and low-
income households.
(4) The purpose of improving living standard: The main objective of microcredit is
to eradicate hunger and reduce poverty. This objective can be achieved via
income and employment generation.
(5) No collateral: Collateral is often considered as a good tool of reducing default
risk incurred by the lenders. However, it causes difficulty for the poor because
of their lack of precious assets for collateral. Therefore, microcredit is an
innovative lending service that provides the poor with loans without the need of
collateral and only based on trust (Xia Li, 2010).
(6) Group-lending scheme: Without collateral, microcredit program controls
borrows via using scheme such as group-lending. The main mechanism of this
scheme is that the members of group will monitor one another and be
responsible for the repayment of the other members. If one group member
defaults, the whole group will have less opportunity to access to the program in
the future. Anderson and Nina (2000), Besley and Coate (1995) stated that
group-lending scheme is considered as a “social collateral” which can help
lenders to minimize default risk as well as reduce cost of monitoring.
(7) Targeting women: In their research, Cheston and Kuhn (2002) stated that the
proportion of female borrowers all over the world is about 74 percent.
In this research, the microcredit loans are extracted based on the definition of
microcredit by Microcredit Summit (1997) and the information of microcredit loan size
by VBSP. Therefore, microcredit needs to meet such characteristics as:
(1) The loan is granted and provided by VBSP. The reasons to focus on only the
case of VBSP are : (i) VBSP is the major provider of credit for the rural

11
households as well as the poor; (ii) VBSP is the most typical financial institution
that best represents the Government in hunger eradication and poverty reduction
campaigns; (iii) Nowadays, VBSP is the greatest provider of microcredit in
Gross Loan Portfolio as well as the number of borrowers (Table 2.3), and these
numbers tend to increase more and more (Table 2.4).
(2) The average loan size is about 444USD (7,360,00VND in term of exchange rate
in 2008 at 16580VND/USD) (Source : www.mixmarket.org in 2008);
(3) The purpose of borrowing is to run production or self-business in such
industries as Agriculture, Forestry, Fishery, Business and Trading, Services, etc.
2.2.3. Characteristics of rural credit market in Vietnam
“The formal rural credit is defined as the credit that provided by the Vietnam
Bank for Agriculture and Rural Development (VBARD) and access to such a form
kind of credit referred to ability to obtain a loan” (Vien, 2006). Besides VBARD, the
Vietnam Bank for Social Policies (VBSP) and the Vietnam Bank for the Poor (VBP)
are also the major sources of credit for rural households. The main functions of these
banks are targeted in struggling with hunger eradication and poverty alleviation as well
as becoming a major credit source for the poor, minority ethnic groups.
The semi-formal credit sector provides loans through sociopolitical unions in
the rural areas. Some unions that have efficient operation in this sector include
Women’s Union Farmers’ Association, or The People’s Credit Funds (PCF),
Informal credit sources have been traditional providers of credit in rural areas
and are the result of an underdeveloped formal credit market. In Vietnam, informal
credit market has played a significant role in providing credit to rural households in the
past. The characteristic of this sector are specified as:
The research only focuses on the formal credit sector with microcredit loans
from VBSP.

12
2.2.4. Overview of microcredit program in Vietnam
2.2.4.1. Microfinance institutions and performance of microcredit program.
In Vietnam, microcredit program was first applied by Tinh Thuong (TYM) fund
in 1992. TYM was established in 1992 based on the model of Grameen Bank of
Bangladesh and managed by the Vietnam Women's Union (VWU). After that, some
more MFIs were established such as Binh Minh CDC, CEP, etc... However, at that
time, the operation of microcredit programs by TYM as well as most of MFIs was not
adjusted and controlled under a legal framework. Most of MFIs at that time were only
considered as political social organization. Without legal framework, the MFIs had
difficulty in mobilizing capital.
After the promulgation of the decree 28/2005/ND-CP that prescribes the
establishment of small-sized financial institutions and the decree of 165/2007/ND-CP
that amends and implements decree 28/2005/ND-CP, microcredit has been remarkably
improved and increased in great quantity.
Table 2.2: Characteristics of Microcredit Programs in Vietnam from 2005 to 2011
Year
Average loan
per borrower
Gross Loan Portfolio
(USD)
Number of active
borrowers
2000 86 1,940,888 22,568
2001 98 3,693,409 37,661
2002 101 4,912,074 48,620
2003 187 630,602,241 3,371,273
2004 226 864,943,591 3,820,166
2005 260 1,103,533,447 4,251,506
2006 241 1,169,333,228 4,858,491
2007 378 2,208,590,097 5,848,567
2008 435 3,059,283,932 7,028,691
2009 510 3,979,270,468 7,805,106
2010 550 4,652,328,963 8,453,818
2011 610 5,476,680,085 8,976,422
Source : www.mixmarket.org

13
Figure 2.1 : Gross Loan Portfolio of Microcredit in Vietnam from 2005 to 2011
Source : Calculated from the data at www.mixmarket.org
Table 2.2 and figure 2.1 showed the trend of microcredit from 2000 to 2012.
From the year 2000 to 2002, the operation of microcredit was ineffective, the gross
loan portfolio was small and increased very slightly. From 2003 to 2006, the operation
of the program was improved, but there was only a moderate increase in the gross loan
portfolio. From 2007 to 2011, since the decree 28/2005/ND-CP and 165/2007/ND-CP
took affected, there has been a remarkable increase in gross loan portfolio.
Table 2.3 presented the most updated information (in 2011) about the number
of microfinance institutions as well as their operation via three indicators such as
average loan per borrower, gross loan portfolio and number of active borrowers . This
table showed the outstanding role of main microfinance providers such as VBSP,
CPCF, CEP, TYM and M7, in which VBSP is the greatest providers of such kind of
lending service nowadays. Therefore, this research analyses the impact of microcredit
programs provided by VBSP only.
0
1,000,000,000
2,000,000,000
3,000,000,000
4,000,000,000
5,000,000,000
6,000,000,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

14
Table 2.3: Main Characteristics of the MFIs in Vietnam in 2011
MFI name
Average loan
balance per
borrower
(USD)
Gross Loan
Portfolio
(USD)
Number of
active
borrowers
VBSP 579 4,932,544,460 8,519,497
CPCF 8,814 457,581,075 51,914
CEP 231 44,647,899 193,238
TYM 274 19,965,308 72,958
M7 210 5,334,193 25,407
WU (Ha Tinh, Son La) 113 2,659,580 23,607
Dariu 161 2,243,715 13,936
NMA 92 1,964,721 21,369
Fund for Women Development -
HCM
181 1,723,535 9,528
Microfinance Fund, Hai Phong --- 1,692,635 ---
CAFPE BR-VT 148 1,522,332 10,300
TCVM Thanh Hoa 138 1,469,763 10,650
WV Vietnam 183 1,221,721 6,690
Binhminh CDC 188 835,079 4,449
BTWU 121 264,780 2,189
Chi-Em 76 231,459 3,032
MCDI 95 185,449 1,950
Women Development Fund 239 157,428 660
BTV 160 157,185 983
CSOD 95 123,776 1,300
VietED MF 617 98,147 159
STU 345 55,483 161

15
2.2.4.2. Microcredit program by VBSP
In 1995, the State announced the establishment of the Vietnam Bank for the
Poor (VBP) with the purpose of poverty reduction. Later, in 2003, the VBP was re-
organized and renamed the Vietnam Bank for Social Policies (VBSP). The VBSP
continued the mission of fighting poverty. Since its establishment, VBSP has operated
effectively via providing various lending service to support the poor. One of the most
effective lending service that VBSP provides is micro credit program. Table 2.4 and
figure 2.2 showed the operation of microcredit program by VBSP from 2005 to 2011.
Figure 2.2: Microcredit Program Operation by VBSP
Source: Calculated from the data at www.mixmarket.org
0
1,000,000,000
2,000,000,000
3,000,000,000
4,000,000,000
5,000,000,000
6,000,000,000
2005200620072008200920102011
Gross Loan Portfolio
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
2005 2006 2007 2008 2009 2010 2011
Number of active borrowers

16
Table 2.4: Characteristics of Microcredit Programs by VBSP from 2005 to 2011
Indicator
Year
2005 2006 2007 2008 2009 2010 2011
Offices 665 665 610 677 681 677
Personnel 6088 7155 7501 7809 8370 8800 8900
Number of
active
borrowers 4,125,264 4,695,986 5,648,140 6,792,978 7,536,960 8,166,287 8,519,497
Gross Loan
Portfolio
(USD) 1,087,403,356 1,149,164,276 2,181,692,164 3,017,866,034 3,929,035,635 4,588,944,354 4,932,544,460
Average
loan
balance per
borrower
(USD) 264 245 386 444 521 562 579
Cost per
borrower
(USD) 14 9 14 31 36 21
Borrowers
per staff
member 678 656 753 870 900 928 957
Borrowers
per loan
officer 2829 3402 3884 3326 2827 2850

17
2.3. Empirical Study
2.3.1. Impact of microcredit on welfare/ living standard of the rural households.
2.3.1.1. Dependent variables
In a case study of Grameen Bank and BRAC, Malin Johansen and Carola
Nilsson (2007) mentioned living standards/ welfare of a household via indicators such
as income, consumption, accessibility to clean water, accessibility to education, having
electricity, health indicators (maternal health and child care, nutrition care), food status
(more food intake, better-quality food), etc.
In his research about the impact of microfinance in Thailand, Brett E. Coleman
(2002) mentioned households’ welfare including various factors such as wealth, assets,
livestock, self-business sales, expenses (medical expense, school expenses, etc.,..).
In this research, income/consumption is used to reflect welfare/ living standard
of households. More income or more consumption means that the poor have better
welfare or higher living standards.
2.3.1.2. Independent variable :
Many empirical studies showed that there are various factors that affect welfare
of the poor in rural area. Among these variables, microcredit plays a very significant
role. Microcredit has significant impact on many aspects of welfare of households such
as income, consumption, health, schooling, poverty reduction level, etc…
Pitt & Khandker (1998) stated that microcredit has positive impact on living
standard of the poor households via increasing their consumption. Research of
Grameen Bank by Pitt et al (2003) also had the same conclusion that the participation
in microcredit has effect on the health status of children. R.Khandker (2005) found in
his research in Bangladesh that microfinance loan helps to improve the households’
welfare such as consumption. Moreover, Yasmine F. Nader (2008) also concluded that
microcredit play a significant role in helping the poor to escape poverty via affecting

18
their children’s education, income and assets. The research by Xia Li (2010) supported
that microcredit can significantly foster the welfare of the participants by raising their
income and consumption. To re-affirm the above statements, in the case of India, the
Reserve Bank of India (2011) proved that microcredit enables the poor to raise their
income and improve their living standards.
In contrast, many researches argued that participation in microcredit program
has no significant impact on welfare of households. Coleman (1999) stated that there is
no evidence of the microcredit program impact on the living standard which is
reflected via assets and income. Moreover, Kazushi et al. (2010) found that there is no
relationship between microcredit and households’ income and expenditure. Also in
their research, microcredit was proved not to effect poverty reduction instantly.
In the case Vietnam, Cuong Nguyen (2008) proved that microcredit programs
have positive impact on welfare via incomes and expenditures as well as poverty
reduction of the participating households in rural regions. Also, Tra Pham (2011) found
that participation in microcredit programs help to enhance on self-employment profits
of the poor and increase income of the poor as well as contribute to poverty reduction
of the rural households. Nadine R. & Peter P. M. (2012) confirmed that microcredit
programs positively contribute to the households’ accessibility clean water as well as
the advanced and safer sanity system.
Table 2.5 summarized some main findings on the significant impacts of
microcredit programs on welfare and living standard of the rural households and the
poor in rural areas.
There are also many different arguments over pros and cons about microcredit
that can be summarized as follows:
 Pros : Microcredit is found to improve the households’ welfare or living
standards as well as fight against poverty. Moreover, microcredit contributes a

19
new channel of providing credit services to population with low income,
especially the poor (CGAP, 2002).
 Cons : Microcredit is not considered as a “one size fit all” program for the poor
or low income households: (1) With respect to the targeting, microcredit may
not be suitable for the nomads and people with illness (CGAP, 2002); (2) With
respect to the impact on welfare, in some specific cases, other alternative
programs should be taken into consideration to better support the households
(Xia Li, 2010). Moreover, the participating households may not benefit from the
program due to the misusages, and then they may even get into deeper debt
(CGAP, 2002).
This research only focuses on the impacts of microcredit on the two indicators:
(1) income, and (2) consumption of households in rural area.

20
Table 2.5: Summary of main findings about the impact of microcredit on welfare/ living standards.
Author Key variables Methodology Sample Selection Findings
Khandker
(1998)
Microcredit,
Consumption,
Poverty rate
DID between
participants and non-
participants
Bangladesh (Grameen,
BRAC) in 1991/1992
and 1998/1999
Microcredit reduced poverty rate by 5
percent with respect to the participants.
Moreover, microcredit increases their
consumption.
Pitt and
Khandker
(1998)
Microcredit, labor
supply,
consumption,
schooling, assets
DID between
treatments and
controls
In 87 villages of 29
districts in rural
Bangladesh (BRAC.
BRDB. Grameen
Bank) during 1991-
1992
Program participation increase weekly
consumption per capita, nonland assets
and labor supply.
The participation in Grameen Bank
Programs has positive impact on
schooling of girls
Brett E.
Coleman
(April,
2002)
Microfinance loans,
Various measures
of households'
welfare
Tobit regression;
Weighted logit
regressions; Ranking
Method
Northeast Thailand in
1995-1996.
The results found that microfinance has
positive effect on household welfare for
only for the wealthy members, while its
impact is insignificant for the poorer.
Khandker
(2003)
Microfinance,
income, Poverty
rate
1) Fixed effect Tobit
estimation
2) Panel data fixed
effects estimation
Bangladesh (Grameen
bank. BRAC. BRDB)
in 1991/1992 and
1998/1999
Microfinance reduces poverty rate (18
percent for very poor households and
8.5 percent for moderate poor
households over 7 years).

21
Pitt et al
(2003)
Microfinance,
Health of boys
and girls
Maximum likelihood
estimation
Bangladesh (BRAC.
BRDB. Grameen Bank) in
1991/1992
Microfinance has positive impact on
health of both boys and girls.
Owuor G.
(2009)
Microcredit ,
Productive
incomes
PSM medhod using
such techniques as
NN, Radius, Kernel,
Stratified
Two districts in Kenya,
namely Nakuru - high
tropics and Kakamega -
the Low tropics.
Microcredit program help to increase
households’ productive incomes about
200 USD – 260 USD in a single
production period.
K.S. Imai
et al
(2010)
Microfiance
productive loans,
welfare
indicators
Tobit and PSM
models via using
Nearest neighbor,
Kernel
Cross-sectional data in
India in 2001 collected by
EDA Systems for Small
Industries Development
Bank of India.
Microfiance productive loans have
significant positive impact on welfare
indicators.
Xia Li
(2010)
Microcredit,
Income,
Consumption
DID method, logistic
regression model
Primary data: Surveyed in
Hubei Province, China in
2005. Secondary data:
From the Rural Credit
Cooperative.
Microcredit has significant positive
impacts the households’ income and
consumption.

22
Kazushi et
al (2010)
Microcredit,
Income/ Profits;
Expenditure;
Asset; Sales
PSM and DID
method using panel
data
Gresik District of
Indonesia in 2007 and
2008
Moreover, Kazushi et al. (2010) found
that microcredit has no impact on
households’ income and expenditure,
but sales of nonfarm enterprises and
schooling expenditures. Also in their
research, microcredit was proved not
to have poverty-reducing impact
instantly.
Cuong
Nguyen
(2008)
Microcredit,
Incomes and
Expenditures
Fixed-effect
regression using
panel data
In Vietnam rural areas in
2002 and 2004, using
VHLSS data set collected
by GSO, focusing on VBSP
case.
There is positive relationship between
microcredit programs and of
households’ welfare via incomes and
expenditures, which results in the
positive effect on poverty reduction
(Specifically reduces poverty indexes
by 20 percent)

23
Tra Pham
and Robert
L. (2011)
Microcredit,
Household Self-
employment
Profits
Fixed-effect
regression using
panel data
In Vietnam rural areas in
2004 and 2006, using
VHLSS data set collected
by GSO, focusing on VBSP
case.
Microcredit increases self-
employment profits of participating
households.
Moreover, microcredit programs
contribute to poverty alleviation effect
positively, reflected via the higher
increase in the income of the poor.
Nadine R.
& Peter P.
M. (2012)
Microcredit;
Water
Supply;
Sanitation
Qualitative method
based
on semi-structured
interviews
Four rural districts in Can
Tho in Vietnam in 2008
Microcredit program has a positive
impact on improving the quality of
water as well as the sanity system via
the advanced and safer toilet system.
However, microcredit was found to
have poverty reducing impact on
only better-off households.

24
2.3.2. Determinants of the accessibility to microcredit programs
Credit (including microcredit) procedure consists of two stages. In the first stage
(demand side), the borrowing households who demand credit apply for a certain
amount of loan from formal or informal credit sources (the lenders). In the second
stage (supply side), the lenders choose who can be granted credit and how much the
loan size is, based on eligibility of the households.
In a study of accessibility to formal rural credit in Northern Nicaragua, Vaessen
(2001) found that accessibility to credit was affected by the characteristics of supply-
side (behaviors of banks or financial institutions) and demand-side (behaviors of
households). In the case of Vietnam, Duong Pham (2002) analyzed the accessibility to
rural credit via focusing on the determinants of borrowing of households (demand-side)
and the determinants of credit rationing by the formal lending institutions (supply-side)
This research analyzes the determinants of accessibility to microcredit based on
demand-side. The determinants in this research will be classified into three levels: (1)
Household head/ Individual level (e.g. gender, age, square term of age, education,
marital status, official status); (2) Household level (e.g. ethnic, dependency ratio, land
size per capita, house value (which is considered as a precious source of collateral); (3)
Commune/village level (e.g. Distance to bank, facilities of the commune, dummies for
regions).
2.3.2.1. Education level of the household head
In the previous studies, there are many contrasting ideas about the impact of
education on the accessibility to credit of households. Education level is reflected via
the years of schooling.
Yehuala (2008), Okunade (2007), Okurut (2006), Vaessen (2001), educational
level is founded to foster the probability of households’ accessibility to microcredit
program. Xia Li (2010) also proved that households with head’s education level at
secondary school or lower are more likely to access to microcredit programs than those

25
without educated head. However, Khandker (2001); Khandker (2005), Thaicharoen,
Ariyapruchya & Chucherd (2004) stated that higher education level of household head
results in lower probability of microcredit participation.
In the case of Vietnam, Cuong H. Nguyen (2007) also argued that the higher
education level of the household head will lower the probability of accessibility to
microcredit. His research found that the households with head's education level at
primary and lower secondary school are more likely to borrow from microcredit
programs.
2.3.2.2. Age
There are many contrasting conclusions about the relationship between age and
the accessibility to credit. Moreover, it seems to be complicated to interpret this factor
because of its ambiguous characteristics. M. Anjugam and C. Ramasamy (2007)
showed that households with older head will less likely to borrow from credit program
including microcredit. Similarly, Okurut (2006) and Mohamed (2003) reconfirmed
that the probability of accessing to credit sources decreases as the age of household
head increase. However, in the case of Vietnam, Tinh (2010) argued that the age of
household heads has a significant positive effect on the accessibility to credit.
2.3.2.3. Marital Status
A research by Kenya National FinAccess (2009) shows that single individuals
have less opportunities to access to credit, while the divorced/separated or widowed
individuals have more opportunity to borrow from credit programs. Moreover, the
probability of participating in credit program is highest when individuals are married or
live with their partners. In a research in Vietnam by Tinh Doan (2010), it is found that
marital status has affected the accessibility to credit. Single households are often
considered as disadvantaged group, so they think they have difficulties in social
networks. Therefore, it results in the less likelihood of credit participation.

26
2.3.2.4. Gender of household head
Bruno Crépon et al. (2011) proved that there is a high proportion of men
accessing to micro credit in the rural areas in Morocco. Similar to Bruno Crépon et al.
(2011), a research result by Banerjee et al (2010) also showed that men are only
borrowers from the microcredit program. However, in a research by Owuor George
(2009), it was found that women get more attracted to microcredit program.
2.3.2.5. Official Status
Cheng (2006), Xia Li (2010) claimed that members working as official has
higher demand for credit including microcredit to do investment and run their own
business. Moreover, official status also reflects the social status of households in their
village or commune, which results in their closer connection with banks or financial
institutions. Therefore, that will help to foster the probability of accessing to credit.
2.3.2.6. Household Size
The impact of this factor is ambiguous and varies from study to study, and thus
there are contrary opinions about this factor.
Schreiner & Nagarajan (1998), Ho (2004) and Vaessen (2001) stated that
number of members in a household has positive effect on the likelihood of accessing
credit program including microcredit. In the case of Vietnam, Tinh Doan (2010),
Cuong H. Nguyen (2007) also concluded that household size may inﬂuence the
probability of credit access positively. In contrast, Xia Li (2010) argued that the
higher household size will lower the probability of households’ accessibility to
microcredit.
2.3.2.7. Economic dependency ratio
Husain (1998) stated that households with higher dependency ratio are less
likely to access to microcredit programs because of their less capability of repayment.
Meanwhile, Xia Li (2010) found that there is a positive relationship between

27
dependency ratio and the probability of participating in microcredit. In the case of
Vietnam, Duong Pham (2002) confirmed that the larger the number of dependents, the
higher opportunities of accessibility to credit because of the greater probability of
being poor. Therefore, they demand more capital for mostly smoothing consumption.
2.3.2.8. Ethnic of household
In the researches by Becker (1971), Yinger (1998) and Fafchamps M. (2000),
main ethnic groups may have higher probability of participation in credit program
including microcredit. From the hypothesis, applied to Vietnam case, it may be found
that Kinh or Chinese households have more probability to access to microcredit.
2.3.2.9. Land/ Farm Size
Mohamed (2003), Ravi (2003), Davis et al (1998) stated that households with
larger farm scale have greater demand for credit in order to run farm production, and
thus they are more likely to participate in credit program including microcredit.
Nevertheless, Khandker (2001), Khandker (2005), Thaicharoen et.al. (2004) argued
that households with greater farm size are found to have less probability of accessing to
microcredit program. In the case of Vietnam, Cuong H. Nguyen (2007) and Duong
Pham (2002) concluded that land also positive effects on the participation in credit.
2.3.2.10. Total value assets
Total value assets may be reflected via factors such as house value, fixed assets
value, etc. In the research in Malawi, Aliou Diagne (May, 1999) found out that total
value of assets has negative impact on accessibility to microcredit participation. The
reason is that households with more total assets may be considered as the non-poor, so
they have less demand for credit. In contrast with Aliou Diagne, Cheng (2006) and
Ruiz-Tagle (2005) stated the households with more assets may think that they are rich
and then consume more, which results in higher demand for credit including
microcredit. This research uses house value as a factor of total value assets.

28
2.3.2.11. Distance to credit institutions or banks.
From the previous studies, credit access is also determined by distance to
financial institutions or banks. Ho (2004), Vaeseen (2000), Xia Li (2010) showed that
the farther from banks the rural households live, the less they are likely to access to
microcredit programs. because they may incur more time spending and high borrowing
costs resulting from such expenses as travelling, postal service or telecommunication.
Esther Duflo et al., (2008) reaffirmed that the villages in which distance to the bank is
also significantly lower have higher participation than the other villages.
2.3.2.12. Geographic location
Sharma and Zeller (1999) stated that geographic location is considered as a
determinant of households’ accessibility to microcredit. For instance, households in
mountainous areas are found to have lower probabilities of accessing microcredit due
to the shortage of information and disadvantages in transportation. In the case of
Vietnam, Duong Pham (2002) also had the same conclusion that region has impact on
the accessibility to credit of rural households.
2.3.2.13. Facility/ Condition of Commune
Khandker (1998) stated that the facility and condition of the communes may
support accessibility to microcredit of households living in those communes/villages .
These facilities and condition may include the facts that whether there is any post
office; or road to the commune/ villages; or radio broadcasting station
Based on the previous study, Figure 2.3 summarizes the determinants on
participation to microcredit Programs as well as indicators that reflect welfare of
households. The figure present some welfare indicator, but this research only focuses
on income and consumption per capita per month. The reason for choosing these two
indicators is that the purpose of microcredit is to do business and run production for

29
generating income, so income and consumption will be a suitable measurement to
reflect the results from business and production activities.
Figure 2.3: Determinants on Accessibility to Microcredit and Welfare Indicators

30
CHAPTER III
RESEARCH METHODOLOGY AND DATA DESCRIPTION
The objective of this chapter is to discuss the methodology and data set that will be
applied to analyze. The first part presents methodologies such as probit model to
analyze the determinant on accessibility to microcredit program; and PSM as well as
DID to analyze the impact of microcredit on welfare, especially focusing on the PSM
technique. The second part discusses the issues related to data set used for analysis
such as data survey, data source and sample size.
3.1. Model of determinants of access to credit
In order to identify the groups for comparison, we conduct a model to forecast
the determinants on the households’ accessibility to micro credit programs, which can
be interpreted as the propensity score of each households.
There are two common modeling methods to determine the credit accessibility:
logistic regression models by Evans et al., (1999); Aghion and Morduch (2005);
Coleman (2006); M.Duvedack and R.Jones (2011); Xia Li et al., (2011), and probit
models by: Umoh (2006); Katsushi S. Imai et al (2010); Kazushi et.al. (2009).
Caliendo and Kopeinig (2005) stated that the results from logistic and probit
models are very similar. In this research, in order to determine the probability of
accessing to microcredit of households, a probit model is conducted to estimate.
The dependent variable (Credit) is binary (1 if households participate in
microcredit program; and 0 otherwise).
The independent variables are divided into three groups as:
 The group 1 consists of variables reflecting characteristics of household head:
gender, age, square term of age, education, marital status, and official status.
 The group 2 includes characteristics of household level such as: ethnic,
dependency ratio, land size per capita, house value (which is considered as a
precious source of collateral).

31
 The group 3 reflects characteristics of commune/village level such as: distance
to bank, facilities of the commune (reflected via the fact that the commune has
radio broadcasting station, automobile road to access commune, post office, or
not), dummies for regions.
The following model was formulated and developed based on the researches by
Coleman (1999), Alexander (2001), A. Aghion and Morduch (2005), Coleman (2006):
( )
Where: Crij : participation in microcredit program of households
Iij : vector of group 1 variables
Hij : vector of group 2 variables
Vij : vector of group 3 variables
Probit (CREDIT) = F(gender, age, education, square of education, marital status,
official status, ethnic, dependency ratio, land size, house value,
distance to bank, facilities of the commune , dummies for regions)
Based on strategy of simple to general, the research constructs various models to
investigate the determinants on accessibility to microcredit. Then, using criteria as R2
,
Percentage of Correct Prediction as well as multicolinearity test, the best model will be
chosen.
Table 3.1: Descriptions of Determinants on Accessibility to Microcredit
Independent
Variables
Name Description
Expected
Sign
Hgender
Gender of
household head
Dummy variable, coded as:
HGEN =0 : if female
HGEN =1 : if male
Positive
AGE
Age of household
head
Actual age of household head
in year (Continuous).
Positive

32
AGE2
Square Age of
household head
Square actual age of household
head in year (Continuous).
Positive
HEDU
Education level of
household head
Calculated by the years of
schooling (Continuous).
Positive
HMAR
Marital Status of
household head
= 0 : Single; Divorced /
Separated; Widowed;
= 1 : Married/ living with
partners.
Positive
OST
Official Status of
household head
Dummy variable, coded a:
= 0 : Not having official status
= 1 : Having official status
Positive
ETHNIC
Ethnic of
household
Dummy variable:
=0 : Other ethnic groups
=1 : Kinh and Hoa
Positive
HHSIZE Household Size
Scale of household or number
of members in the household
(Continuous).
Positive
DEPRATE Dependency ratio
The proportionate of non-
working member over working
member (Continuous).
Positive
LANDPERCA Land per capita
Land per capita in meter square
(Continuous).
Positive
HVAL
Total value of
assets (house value)
House value in thousand dong
(Continuous).
Positive
DISTANCE
Distance to credit
institutions or
banks
Distance in kilometer
(Continuous).
Negative

33
GEOF1
Coastal or Midland
Regions
Geof1 : =1 If Coastal or
Midland; =0 if other regions
Negative
compared to
GEOF3
GEOF2 Plain Region
Geof2 : =1 If Plain Region; =0
if other regions
Negative
compared to
GEOF3
GEOF3
Mountainous
Region
Geof3 : =1 If Mountainous
Region; =0 if other regions
Positive
compared to
GEOF1 &
GEOF3
GEO2
Geographic
location
Dummy variable, coded as
follows : =0 :Not far-off
region; =1 :Far-off region
Negative
RBS
Facility of the
commune (With or
without Radio
Broadcast Station)
=0 : Without Radio Broadcast
Station
=1 : With Radio Broadcast
Station
Positive
CA2
Facility of the
commune (With or
without Road for
automobile to
access commune)
follows :
=0 : Without Road for
automobile
=1 : With Road for automobile
Positive
PO
Facility of the
commune (With or
without Post
Office)
follows :
=0 : Without Post Office
=1 : With Post Office
Positive

34
3.2. Impact Evaluation techniques
3.2.1. Some Definition
Impact evaluation basically measures the benefit received participants based on
the participation in the program (Khandker et al., 2010).
Propensity score matching (PSM) predicts the probability of program
participation of comparison groups based on certain observed characteristics (usually
obtained by Logit or Probit model), and then the participants (the treatment group) are
matched to the nonparticipants (the control group) on the basis of this probability
(propensity score). The impact of the program participation is the mean difference in
outcomes between the treatment and control group (Khandker et al., 2010).
The DID method also evaluates the program impact via the estimates of
difference in the outcome between the participating units and nonparticipating units.
However, this is difference overtime between pre and post program intervention
between these two groups.
3.2.2. Impact evaluation using PSM technique
3.2.2.1. Procedures of PSM technique
Based on the procedure of impact evaluation using PSM method developed by
Khandker et al. (2010), Sascha O. Becker and Andrea Ichino (2002), and Duy Luong
(2010), the following steps should be conducted:
Step 1 : Collecting the samples of participant (treatment group) and non-
participant (control group). Then the state of microcredit program take-up will be
estimated based on the similar observed characteristics X that determine the
participation in microcredit program and are not affected by the program participation
Step 2 : Conducting a probit model in which indicates that :
 Dependent variables are treatment group (D=1) in comparison with control
group (D=0)

35
 Independent variables may include determinants on the accessibility to
microcredit program such as characteristics of household head (age, education
level, marital status, ethnic); characteristics of household (household size,
dependency ratio, house value, land size per capita); and characteristics of
commune (distance to bank, facilities, geographical regions)
Step 3 : Estimating the participation equation using regression method for probit
model. The predicted value of D can be estimated from this equation. The results
indicate the estimated probability of participation or propensity score which ranges
from 0 to 1. Each participant and non-participants have their own estimated propensity
score, of which the equation is written as:
( ) ( )
Where : D : Indicator of participation in the program
X : Multidimensional vector regarding determinants on the
accessibility to microcredit
Step 4 : Specifying the common support region in which there is overlap of
distribution of propensity scores for treatment group and control group. Also in this
step, some observations of control group may be dropped out because they fall outside
the common support region, which mean they have too high or too low estimated
probability.
Step 5 : Matching each participant with one or some non-participants based on
single propensity score that represents the closet probability of accessibility to
microcredit program. Then, based on this probability, the criteria such as income per
capita and expenditure per capita should be compared between each participant and
non-participant. Various techquiques of matching can be employed to match these two
groups such as Nearest-neighbor, Caliper or radius , Stratification or interval. The
resulting difference from this comparison reflects the impact of the microcredit
program with respect to each participant, or individual gain.

36
 Nearest-neighbor (NN) matching. This technique is most commonly applied
among matching techniques. Following this method, each participant is matched
to the non-participants based on the most similar propensity score. This method
is conducted with replacement, which means a control unit can be used as a
match for more than one treatment unit.
( )
Where : pi : Estimated value of propensity score of participants i
pj : Estimated value of propensity score of non-participants j
C(i) : Set of participants matching to non-participant i with a value of pi
However, in NN matching, the difference of propensity scores between a
treatment unit and a closest control unit may be sometimes very high because it is
difficult to find households belong to two groups with the exact propensity score. This
situation causes the risk of bad matches among two groups.
 Caliper or radius matching. In other to solve the problem of NN matching , this
technique employs a tolerance level on the maximum distance of propensity
score, namely caliper/ radius. Therefore, this technique is conducted with
replacement, among propensity scores within the caliper/ radius.
( )
Where: pi : Estimated value of propensity score of participants i
pj : Estimated value of propensity score of non-participants j
C(i) : Set of participants matching to non-participant i with a value of pi
r : Certain radius or caliper from pi
 Stratification or interval. In this technique, propensity scores are divided into
different intervals (or strata) in which the treated units and the control unit have
similar values. Within each interval, the mean difference in outcomes between
treatment and control units will be calculated to generate interval impact values.

37
Using the proportionate of treatment units in each strata as weighed, the
program impact (or average treatment effect of the program) is the weighted
average of the interval impact values.
Step 6 : Calculating mean value of all individual differences to capture general
mean value which reflects the impact of microcredit program with respect to the
participants.
Average effect of Treatment for the Treated (ATT) can be estimated as follows:
ATT = E(Y1i – Y0i|Di = 1) = E(Y1|Di=1) – E(Y0i|Di=1)
Where: Y1i : Potential outcome of treatment units
Y0i : Potential outcome of control units
Step 7 : The outcomes encounter the problem of standard errors to be estimated
incorrectly. In order to overcome this problem, estimating standard errors with PSM
via using of the Bootstrap is employed. This technique draws repeated samples form
original sample, and then re-estimates the properties such as standard error and bias
with each sample.
3.2.2.2.Advantages and disadvantages of PSM technique
Propensity score matching technique is widely applied and highly appreciated in
the impact evaluation of program or project. PSM has become an widely accepted
practice in credit program and policy research.
i. The preeminent feature of this method is its feasibility. Unlike the other
methods such as reflexive comparisons or Difference in Difference that require
pre- and post- program survey with respect to the participant, PSM method only
require the post program survey. Therefore, the method is very useful when
there is not pre-program surveyed data.
ii. Reduced selection bias. PSM is one of the best techniques to reduce the
selection biases when making estimations.

38
However, it results in some disadvantages of the PSM method :
i. PSM does not measure the difference in an outcome pre–post attendance in the
program overtime.
ii. A small sample in PSM often encounters the unbalanced distribution of
covariates. Therefore, PSM method requires large samples, which results in
higher cost and more time spending.
iii. Hidden bias may still exist because PSM only covers observable characteristics.
3.2.3. Impact evaluation using DID technique
3.2.3.1. DID method
Based on DID method developed by Khandker et al., (2010) and Thanh Nguyen
(2006), the following model should be applied to evaluate the impact of microcredit:
Where: Yit : the welfare of the household i at time t
Cr = 1 : Households participating in the program ;
Cr = 0 : Households not participating in the program
T = 0 : Survey in 2006; T=1: Survey 2008
Zit : Other determinants on household’ welfare: demography,
education, gender, production capacity, etc. However, this
research only use simple model, so these factors are not taken
into account.
: Error term
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39
Year 2006 (T = 0) Year 2008 ( T = 1) Difference
Control Group
(Cr = 0)
E(Y00) =
̂ ̂
E(Y01) = ̂ ̂
̂
E(Y01) – E(Y00) =
̂
Treatment Group
(Cr = 1)
E(Y10) = ̂ ̂
̂
E(Y11) = ̂ ̂
̂ ̂ ̂
E(Y11 ) – E(Y10) =
̂ ̂
Difference
E(Y10) - E(Y00) =
̂
E(Y11) - E(Y01) =
̂ ̂
Difference in
Difference
Therefore, the impact of micro-credit on households’ welfare equals:
= {E(Y11) –E(Y10 )} –{E(Y01) – E(Y00)} = ̂ = DID Estimation
Where :
E(Y00) : Welfare of households not participating in the program (Cr=0) in 2006 (T=0)
E(Y10) : Welfare of households participating in the program (Cr=1) in 2006 (T=0)
E(Y01) : Welfare of households not participating in the program (Cr=0) in 2008 (T=0)
E(Y11) : Welfare of households participating in the program (Cr=1) in 2008 (T=1)
Figure 3.1 : Illustration of Impact Evaluation Using DID Method
Source: Thanh Nguyen (2006)
Y00
[Cr=0
]
Y01
[Cr=0
]
Y10
[Cr=1
]
Y11
[Cr=
1] DID
T = 0 T = 1
Y
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40
This research only apply basic simple model of DID method using fixed effect
technique as follow:
Table 3.2: Variables in the Analysis of the Impact of Microcredit using DID
Independent
Variables
Description
Cr
Dummy variables of two comparison group :
Cr = 1: Households participating in the program ;
Cr = 0 Households participating not in the program
T
Dummy variable about time of survey
T = 0 : Survey in 2006; and T=1: Survey 2008
T*Cr
Interaction variable between groups and time. It reflects the impact
of microcredit program on households’ welfare (income /
consumption)
Instead of using DID with ordinary least squared, this research applied DID
with fixed-effects regression. Therefore, this research should only consider the
coefficient (which means the impact of the pre and post program overtime) because
there may be perfect correlation between Cr variable and other dummy variables of
household that are generated when using fixed-effect regression.
3.2.3.2. Advantages and Disadvantage of DID methods
DID Method measure the difference in an outcome pre – post attendance in the
program; the difference in outcome among factors at the same time (Separate the
impact of Microcredit and other factors on welfare); and the difference in outcome of
impact of the program over time. DID method using panel data can control the
unobserved and time-invariant variables.
Meanwhile, the drawback of DID Method is that it still does not measure the
impact of loan size on welfare.
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