Determinants of accessibility to microcredit in term of formal sector and informal sector

UNIVERSITY OF ECONOMICS, HO CHI MINH CITY
VIET NAM – NETHERLANDS PROGRAMME FOR M.A. PROGRAM IN
DEVELOPMENT ECONOMICS

DETERMINANTS OF ACCESSIBILITY TO
MICROCREDIT IN TERMS OF
FORMAL SECTOR AND INFORMAL SECTOR
----------o0o--------TRAN THI NGOC ANH MAI

Academic Supervisor:

DR. CAO HAO THI

Dec – 2014


ABSTRACT
Microcredit is an emerging concept helping the poor out of poverty situation. This
dissertation attempts to investigate the determinants affecting the probability of
participation in different types of credit sectors in terms of formal sector and
informal sector. Using a sample size of 1,522 households participate in credit
market from The Vietnam Access to Resources Household Survey (VARHS) 2012,
bivariate probit model is employed to explore the determinants of household credit
demand due to the binary nature of the dependent variables. Various explanatory
variables include age, gender, marital_stt, edu, hhsize, income, savingamount,
landsize, agriculture_act, network and location that influence probability of
accessibility to different sectors of credit. Furthermore, relationship between
dependent variables is accounted in this research. Results reveal that factors
affecting formal credit participation are different from factors affecting informal
credit participation. Additionally, the result indicates that there is negative
correlation across two sectors of credit.

ACKNOWLEDGEMENT

I would like to express my deepest thankfulness to my advisor, Dr. Cao Hao Thi
who spent lots of his precious time to support and guide me throughout this
research and continuously led me to the right way.
I would also like to extend my appreciation to the teachers working on Vietnam
Netherlands programme who gave great lectures and invaluable knowledge for us
to complete the course.
I am grateful to my parents and my siblings that always encourage and support me
in my study and in every aspect of life.
I also want to express my gratitude to my friends for sharing with me the
difficulties and giving me the ideas, knowledge and materials for the study and for
all the time we were at Master in Development Economics 19.


LIST OF FIGURES
Figure 2.1 Probability of success and expected returns to borrowers ................... 9
Figure 2.2 Return to the bank ............................................................................... 11
Figure 3.1 Microfinance Systems in Vietnam ..................................................... 22
Figure 4.1 Process of research ............................................................................ 30
Figure 4.2 Participation in credit sector ............................................................... 33

LIST OF TABLES
Table 2.1 Definition of Variables......................................................................... 18
Table 3.1 Microfinance Institutions in Vietnam .................................................. 20
Table 3.2 Comparison between formal and informal lenders .............................. 28
Table 4.1 Summary of Participation in different credit sectors ........................... 32
Table 4.2 Conditional and Unconditional Credit Participation Probabilities ...... 33

Table 4.3 Summary statistics ............................................................................... 34
Table 5.1 Determinants of accessibility to formal and informal credit sector ..... 38
Table 5.2 Marginal effects for conditional probability of
formal sector participation .................................................................. 44
Table 5.3 Marginal effects for conditional probability of
informal sector participation .............................................................. 46


TABLE OF CONTENTS
CHAPTER 1: INTRODUCTION ................................................................................. 1
1.1. Problem statement ................................................................................................. 1
1.2. Research objective ................................................................................................. 3
1.3. Research questions ................................................................................................ 4
1.4. Research Structure ................................................................................................. 4
CHAPTER 2: LITERATURE REVIEW ..................................................................... 5
2.1. Concept of credit ................................................................................................... 5
2.2. Theory of demand for credit .................................................................................. 6
2.3. Credit rationing theory .......................................................................................... 7
2.4. Determinants of participation in microcredit programs ...................................... 11
CHAPTER 3: OVERVIEW OF MICROFINANCE SYSTEM............................... 19
3. 1. The history of Microfinance ............................................................................... 19
3.2. The role of government in microfinance: ............................................................ 21
3.3. Overview of credit market in Vietnam ................................................................ 22
3.3.1. The formal credit market............................................................................... 23
3.3.2. The semi-formal credit market: .................................................................... 26
3.3.3. The informal credit market ........................................................................... 26
CHAPTER 4: RESEARCH METHODOLOGY ...................................................... 30
4.1. Research process ................................................................................................. 30
4.2. The data ............................................................................................................... 31
4.3 Data Analysis Method .......................................................................................... 35

CHAPTER 5: RESULTS AND DISCUSSION ......................................................... 38
5.1. Estimation of determinants of microcredit participation ..................................... 38
5.2. Estimation of conditional marginal effects.......................................................... 44
CHAPTER 6: CONCLUSION .................................................................................... 48
6.1. Research Findings ............................................................................................... 48
6.2. Policy implications .............................................................................................. 49
6.3. Limitations ........................................................................................................... 50
REFERENCES ............................................................................................................. 52
APPENDIX ................................................................................................................... 57


CHAPTER 1: INTRODUCTION
1.1. Problem statement
There are about 1.22 billion people (21 percent of population) in the world living on
less than $1.25 a day in 2010 (World Bank). Focusing towards poverty reduction
and finding ways to improve living condition have taken a lot of attention of public
policies in the world. The rate of poverty in Vietnam decreases remarkably in recent
years. According to annual report shown by GSO, the poverty rate declined from
15.5 percent in 2006, to 13.4 percent in 2008, to 10.7 percent in 2010. In a report of
GSO in 2010, it also revealed that poverty level in rural area (13.2 percent) is much
higher compared to that in urban area (5.1 percent). How to distribute the benefits
of economics growth, especially to rural area is one of the challenges remained.
Therefore, rural economy deserves more attention and support to reduce inequality
between rural and urban area.
According to McCarty (2001) and Pham & Lensink (2002), lack of ability to obtain
the fund for the purpose of working capital and investment is one of the reasons
among other things that lead to poverty in developing countries. Providing a
channel to ease the credit constraints for the poor rural household is the primary
object in poverty alleviation strategy of developing countries, including Vietnam.
Farmers need an instrument such as credit to enhance productivity and promote

standard of standard of living because of their seasonal activities and uncertainty
they are facing (Ololade & Ologunju, 2013). Accessing to microcredit is recognized
as a potentially effective tool out of under poverty line situation and improve living
standards (ADB, 2000a; Morduch and Haley, 2002; Khandker, 2003). Agricultural
credit plays an important role in sustainable achievement in any country in the
world Microfinance industry has been known in many decades in developing
countries, and its role was further attended with rapid growth worldwide when
Mohammad Yunus who pioneered the principle of microfinance and microcredit

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received Nobel Peace prize in 2006 (Tra Pham and Robert Lensink, 2007). And a
variety of previous researches demonstrated the position of microfinance in poverty
reduction by focusing on the effect on household welfare. The demand for rural
credit has increased sharply due to the decollectivization of agriculture launched in
Vietnam in the year 1986. Hence, the spread of microfinance with amendment of
regulations on banking operation in Vietnam plays an important component in
fighting again poverty over the last decades. Vietnam has introduced several of
microcredit programs via a lot of channels such as banks, credit funds, money
lenders and advance input providers to supply credit for a variety of clients.
Despite the importance of credit to the poor, the poor family that lacks ability to
access to adequate financial service leads to the fact that they do not have prospects
for increasing their productivity and living standard. And the fact that commercial
banks have no interest in allocating credit to the poor because of their lack of viable
collateral. Because of these reasons, governments in developing countries have set
up credit programs that aim at improving the process of rural household access to
formal credit during the past four decades (Diagne, 1999). However, the lending
mechanisms as well as the nature of the credit market which are highly regulated by
government intervention such as controls of interest rates and credit quota allocation

do not function well.
Similarly, Robinson (2001) and Gonzalez Vega (2003) also indicated that most of
microfinance institutions have been not sustainable in developing countries. Credit
subsidized interest rate provided by “Agricultural development banks” which
established by commercial banks to extend credit to rural household not considered
creditworthy. However, majority of these credit programs have failed to reach their
targets both to be sustainable credit providers and serve the poor (Adams, Graham,
and von Pischke 1984; Adams and Vogel 1986; Braverman and Guasch 1986).
Risk management and transaction costs associated with Asymmetric information are
the most problematic features facing by lenders and borrowers (Pham & Lensinnk,

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2007). It is also well know that different forms of credit market serve different
group of borrowers, it is difficult for large number of poor households to access to
credit sources. Households often face limited access to credit because of rationing
of credit demand that leads to the poor and low income households are
generally excluded from the formal credit sector (Stiglitz & Weiss, 1981). In fact
that formal provider, semi-formal provider and informal provider exist side by side
in Vietnamese financial market. To deal the level of information asymmetry
between borrowers and different lenders, many government microcredit programs
are accompanied by the local Peoples Committees in terms of lending process to
assist microcredit market operation.
In respect of this, narrowing gaps in term of whom it serves and the service it
provides, improving the efficiency and effectiveness of microfinance system is the
main challenge of policy makers as well as program organizers.
With data collected from The Vietnam Access to Resources Household Survey
2012 (VARHS) which supplements and extends the VHLSS (Vietnam household
Living Standards Survey) by repeating surveys of the same household with data

from VHLSS and asking more questions about income, expenses, land, agriculture,
asset, investment, migration, climate change, social welfare and so on; VARHS
received assistance from University of Copenhagen, CIEM, ILSSA (Institute For
Labor Science and Social Affair), and IPSARD (Institute of Policy and Strategy for
Agricultural and Rural Development), econometrics techniques are employed in this
research to explore the factors that affect access to credit in terms of formal credit
and informal credit.

1.2. Research objective
The objective of this thesis is to empirically investigate the determinants that
influence on the probability of household accessing to different types of credit

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sectors as well as the relationship between formal credit participation and informal
credit participation at the same time.
Additionally, marginal effects of each independent variable on the choice of credit
source are also shown in this research.

1.3. Research questions
This research is to answer two central questions:
What are determinants affecting the probability of household accessing to different
types of credit sector?
Is there any evidence of a correlation between participating in formal credit and
participating in informal credit at the same time?

1.4. Research Structure
This dissertation is organized as follows. In chapter one, problem statement and
objectives of this research are presented. Chapter two provides concepts related to

this research, discusses theory for demand credit and credit rationing theory and
introduces explanatory variables. Chapter three presents the history of microfinance
as well as the role of government in microfinance. It also provides insight into the
structure of credit market in Vietnam. Chapter four presents research structure, data
description and methodology method used in this research. Chapter five gives
empirical models and the estimated results. Finally, conclusion, policy suggestions
and limitations are highlighted in chapter six.

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CHAPTER 2: LITERATURE REVIEW
This chapter presents the overview of theory and discusses previous studies relate to
the research topic. The first part mentions about microcredit regarding concept of
credit. The second part discusses about theory for demand credit and credit
rationing theory. The last part discusses about the determinants affecting credit
accessibility.

2.1. Concept of credit
There are several and various definitions regarding the word credit as follows:
Credits are referred as loans which permit consuming in the present, in exchange for
an agreement to make repayment at sometimes in the future (Pischie et al., 1983).
Obtaining credit was considered as the process of controlling over the use of money,
goods and services based upon a promise to repay at a future day (Adegeye &
Dittoh, 1985).
Ololade & Ologunju (2013) defined credit as a mean for temporary transfer of
assets to individuals or organizations that has not them from individuals or
organizations that has. This process required evidences of debt obligation in return
for a loan, in the case of transaction between friends or relative which based on
good relationship excluded.

Microcredit which is a component of microfinance provides small loan to the poor
for self –employment. That generates income, helping them care for themselves and
their family (The Microcredit Summit, 1997).
To raise income level and improve living standard of semi-urban and urban areas
are considered as targets of microcredit by providing of thrift, credit, other financial
services and products of every small amount to the rural household (Reserve Bank
of India- Master Circular, 2011).

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The definition of Microfinance differs from person to person, but microfinance can
be defined as small assistance to low-income individuals (CGAP). These assistances
come in variety of forms including savings, money transfers, payments, remittances,
and insurance, from others to low-income people (Christen R.P., 1997). All services
aim at primarily focus on reducing poverty (Khan & Rahama, 2007).
Microfinance is also defined as a development approach, which is composed of
financial and social intermediation to benefit for the poor (Legerwood, 1999).
Microfinance institutions (MFIs) provide not only credit but also services such as
group formation, development of self-confidence, and training in financial literacy
and management capabilities among members of a group.
Microcredit is widely used interchangeably as microfinance but microcredit, as a
part of microfinance, is a provision of loans to the poor. Microfinance, on the other
hand, has broader category of services such as loans, saving and insurance.

2.2. Theory of demand for credit
According to life circle model (Franco Modigliani, 1966), individuals cannot
maintain consumption at an acceptable level when the size of family changed with
uncertainties of future. To maximize time life utility, income should be reallocated
inter-temporally (Morduch, 1995a). Consumers can afford their purchases by using

saving from past or present income or by accessing to credit funds which help
borrowers to make inter-temporal choice. By borrowing money, borrowers have
additional spending power in the present and duty to pay loan and interest rate in the
future in exchange (Soman & cheema, 2002).
The inter-temporal model of life circle hypothesis and permanent hypothesis which
explain the consumption behavior of individuals were also discussed by Modigliani
in1986. It is assumed that borrower have opportunity to borrow in perfect market in
Modigliani’s model.

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In model of Chen and Chiivakul (2008), current household‘s consumption level not
only depends on the current income but also depends on household’s life time
characteristics (behaviors of household on participation in credit market).
Additionally, it is argued that current consumption depends on expected
consumption in the future period (consumers firstly estimate their ability to afford
consumption in long run) which depends on their saving or demand for loan (Hall,
1978).
Moreover, in Cobb Douglas function: Y = ALαKβ, capital is viewed as a production
input factor, accessible and affordable inputs; profit from production depends on
labor (L) and capital (K) with given technology (Zellne at al., 1966). Cobb Douglas
showed how two factors (Capital and Labor) effect on production function and how
income distribution is effected by production output (Felipe and Adams, 2005). This
capital can be provided by a variety of credit sources at different interest rates (cost
of capital).

2.3. Credit rationing theory
In 1981, Stiglitz and Weiss based on two assumptions to introduce theory of credit
rationing:

(1) There is unable to differentiate level of risk associated with safe and risky
borrower, and
(2) Loans are subjects to the ability of repayment ability of borrower at the end of
investment period.
There are two types of problem including adverse selection and moral hazard in
microcredit market due to the presence of asymmetric information. The former
relates to the screening process where transaction costs (interest rate) is various
between good and bad borrowers while the latter arises in the monitoring and
enforcement mechanism where the borrowers do not make every effort to repay for

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lenders because they know the risk is shared by lenders ( Pham & Lensink, 2007).
In general, lenders judge borrower’s creditworthiness basing on a set of information
that they have.
The model of Stiglitz and Weiss (1981) assumes that expected return of projects (Ei)
is identical but the probability of success (𝑝i) is different. Eis and Eif present for
return of project in the case of success and failure respectively. The bank offers loan
(B) to every borrower with the same rate (r).
In the case of success, the return of project is greater than the money that borrowers
must pay for bank, (1+r)*B, while the return in the case of failure is lower than the
repayment giving to lender. The project is feasible if expected return is higher than
the opportunity cost (Ci) (Stiglitz & Weiss, 1981). Expected return of project as
follows:
Ei = 𝑝i*Eis + (1-𝑝i)*Eif

(2.1)

Additionally, in the case of success, the return to borrower is higher than

opportunity cost:
π(𝑝i , r) = 𝑝i [ Eis – (1+r)*B] ≥ Ci

(2.2)

From (2.1) and (2.2), (2.3) is obtained:
π(𝑝i,r) = Ei – Eif + 𝑝i [Eif – (1+r)*B] ≥ Ci

(2.3)

Taking derivative of the function (2.3), (2.4) is obtained:
𝜕𝜋(𝑝𝑖,𝑟)
𝜕𝑝𝑖

= Eif – (1+r)*B < 0

(2.4)

The first derivative of the function is lower than zero, so expected return function is
a decreasing one. It implies that expected return of project decreases when the
probability of success increases.

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From equation (2.2), using the implicit function theorem to differentiate r respects
to pi:
𝜕𝑟
𝜕𝑝𝑖

=−

𝜕𝜋(𝑝𝑖,𝑟)/𝜕𝑝𝑖

(2.5)

𝜕𝜋(𝑝𝑖,𝑟)/𝜕𝑟

Equation (2.5) shows that an increase in interest rate charged by lender leads to a
decrease in probability and vice versa.
Marginal borrowers are the persons who expect the return of project is zero, it
means π(𝑝i, r*) = 0. At interest rate (r) is higher than r*, the marginal borrowers will
withdraw from the market. At a result of this phenomenon, new marginal borrowers
face the increase in interest rate. This effect is depicted as below:

E

Borrowers with 𝑝im’≤𝑝i≤𝑝im out of
the market

𝑝im’

𝑝im

Ci’
E1

Ci

𝑝i

E3
E2

Figure 2.1

Probability of success and expected returns to borrowers

Figure 2.1 illustrates the effect of interest rate and opportunity cost on expected
returns to the borrowers. E1 is expected returns to a marginal borrower at 𝑝im which
is the probability of success of marginal borrowers. As shown before, an increase in
interest rate (r) leads to a decrease in expected return to the borrower from E1 to E2

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which is lower than the opportunity cost. Hence, marginal borrowers drop out of the
market. E3 is expected return of new marginal borrower, with the probability of
success is 𝑝im’which is lower than the previous pim.
According to Quach (2005), there is the same effect of opportunity cost on expected
return.
From the perspective of the bank, the expected return is:
κ(𝑝i,r)= 𝑝i(1+r)B + (1-𝑝i)Eif

(2.6)

Differentiating function (2.6) with respects to pi:
𝜕𝜅(𝑝𝑖,𝑟)
𝜕𝑝𝑖

= (1+r)B - Eif

(2.7)

The first derivative of the function is greater than zero. It implies that an increase in
probability leads to an increase in expected return to the bank.
If the interest rate increases:
(1) The value of component (1+r)*B increase.
(2) The value of pi decrease (according to function 2.5 shown above), which leads to
lower expected return as result of withdraw of lower-risk borrowers (Stiglitz &
Weiss, 1981).
Stiglitz and Weiss (1982) mentioned about critical equilibrium interest rate; at that,
if the current interest rate is lower than critical equilibrium interest rate, interest rate
of the bank can be increased without any significant withdraw of borrowers and
income of the bank is higher. If the interest rate increases over critical equilibrium
interest rate, lower risk borrowers will drop out credit market that leads to a
decrease of lender’s profit. In this case, credit is allocated at critical equilibrium
interest rate by bank.

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Figure 2.2 demonstrates relationship between returns to the lenders and interest rate
(r). At critical equilibrium interest rate rra where the supply of fund meets the
demand for fund, expected return of the bank is maximized without rationing.
E

r
rra

Figure 2.2

Return to the bank

2.4. Determinants of participation in microcredit programs
When income and wealth to increase purchase are insufficient, households borrow
money as a way to finance their consumption (Kirchler et al., 2008). There are two
stages in process of getting loan. First, the households who demand credit apply for
a certain amount of loan for a type of credit sector which they want to borrow from.
Second, the providers choose which applicants are met requirements for loan based
on household’s information and availabilities of the lenders.
Stiglitz and Weiss (1981) showed that behavior of accessibility to credit is
explained by demand theory (demand side) and rationing process of credit (supply
side).
Vaessen (2002) pointed out that accessibility to credit in Northern Nicaragua was
resulted in the interaction between demand side (characteristics of household) and
supply side (characteristics of financial institutions). Duong Pham (2002) also

11


focused on characteristics of both demand side and supply side in determining
factor that influence on accessibility of rural credit in Vietnam.
However, in this analysis, I focus on demand side’s characteristics to consider the
probability of access to credit. The determinants of microcredit participation include
age,

gender,

marital_stt,

edu,

hhsize,

income,

savingamount,

landsize,

agriculture_act, network and location.

2.4.1. Age
According to the life circle hypothesis, the age is negative relationship with the
decision to get loan. It is also confirmed in research of M. Ajugam and C.
Ramasamy (2007). Similarly, Okurut (2006) and Mohamed (2003) pointed out that
the possibility to access to credit resources decrease when they get older. Younger
persons more likely to borrow than the elderly because of elements of personal risk
level (Fabbri and Padula, 2004; Zeller, 1994; Magri, 2002; Abdul- Muhmin, 2008;
Del- Rio and Young, 2005); additionally, the young tend to spend more on a variety
of activities while the old maybe less (Mpuga, 2008).
In contrast, some studies showed accessibility to credit positively related to age. For
example, Tinh (2010) demonstrated that age of household head has a significant
positive relationship with getting a loan. It was also proven in research in 2010 of
Tang et al.

2.4.2. Gender of household’s head
Banerjee et al. (2010) Bruno and Cre1pon et al. (2011) prove that there are a
majority proportion of male borrowers from the microcredit programmes.

Moreover, Nwaru (2011) and Bendig et al (2009) also proven that demanding in
loan negatively related with being female.
However, contrary to mentioned studies, Owuor George (2009) stated that being a
female headed household increases probability of joining financial activities.

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2.4.3. Marital status
A vast of previous studies showed that married individuals are likely to get loans
than unmarried individuals because of the level of needs (Kamleitneir and Kirchler,
2007; Bridges et al., 2004; Chen and Jensen, 1985; Duca and Rosenthal, 1994;
Magri, 2002). Similarly, in a research by Kenya National Fin Access (2009)
indicated that the probability of credit program participation is the highest with
married persons. It is explained that there is difficult to access to credit for single
household due to lack of social network (Ferede, 2012).

2.4.4. Level of household head’s education
Education was an important factor that influences the probability of accessibility of
microcredit programmes (Tang et al., 2010). Quach (2005) demonstrated that
education level had a positive relationship with demanding in loan. Moreover,
education level was founded as a determinant that fosters the accessibility to
microcredit programme thanks to their awareness of financial market system
(Yehuala, 2008; Okunade; 2007; Vaessen, 2001; and Okunade, 2007).
On the other hand, Khandker (2001) and Khandker (2005) demonstrated that higher
education level of household head would less likely to borrow from microcredit
program. Similar to Khandker’s finding, Cuong H. Nguyen’s research (2007) also
proves that household head with higher education has lower chance of accessibility
to credit sector in Vietnam which composed of high proportion of borrowers with
education level at primary and lower secondary school.

It is interesting that the impact of this variable on various source of credits are
different. Bendig et al. (2009) stated that better educated individuala tend to access
to formal financial sector. Moreover, there was an inverse relationship between
education and informal loan.

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2.4.5. Household size
The ideas of relationship between household size and accessibility of credit are
different from studies to studies.
Schreiner & Nagarajan (1998), Vaessen (2001), Ho (2004) and Quach (2005)
indicates that the number of members in a family were significantly positive
relationship with household borrowing. It is explained that more loans are
demanded by large-size household or that more credits are allocated to household
with more members. That idea was the same in research in the case of Nguyen
(2007) and Tinh Doan (2010).
In contrast, Bendig at al. (2009) argued that household size has negative impact on
probability to credit in a research of demand for financial service. This is due to the
assumption that there are more dependent members including children and elderly
people who would consume a large share of income in their family and had higher
risk of default (Tang et al., 2010).
However, household size did not effect on getting loan in Greece (Mitrakos and
Simiyiannis, 2009).

2.4.6. Household’s income
Income is the most common measurement used to define the poor (The World
Bank); hence, household with high income is not considered as the poor whereas the
primary target of microcredit is to provide credit to the poor who will provided
credit to increase income (World Bank, 2010). Therefore, applicants with higher

income have lower chance to get loan. This idea was proven in the research by
Pham & Lensink (2007) and Li et al. (2011) that household’s income negative
correlation with probability of participation in credit program including microcredit.
It is also explained that marginal utility of consumption of poor household is high,
leading to more demand for credit of the poor (Ferede, 2012).

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In contrast, many researches argued that high-income household more likely access
to loan than low-income household (Crrok, 2001; Lin and Yang, 2005; Jappelli and
Pistaferri, 2007). The reason for that is due to assumption that high-income
households hold mortgage (Ambrose et al., 2004).

2.4.7. Saving amount
Saving amount is identified as collateral to reduce adverse selection and moral
hazard arising from lending process between lenders and borrowers. Compared to
others, saving amount is more liquidity. Therefore, applicants with bigger saving
amount have more opportunities for accessing credit sector. It means that
relationship between household saving and possibility to lend credit is positive.
However, total saving is considered as a determinant of household’s demand for
credit; hence, saving amount is negatively related to probability to approach credit
sector (Tang et al., 2010). It is explained that households with larger saving amount
tend to borrow less because they have money for affording their spending at
acceptant level, they are non-poor.

2.4.8. Land size
For household’s characteristics, Phan (2012) found that land ownership had
negatively significant relationship with demand for credit. It was similar to finding
by Phan (2012). Quach (2005) also pointed that household which own more land

tended to borrow less than those with smaller land size. The reason is that
household with more land is considered as non-poor household who less demand for
loan; therefore, there is a little of credit is allocated to them. Moreover, Khandker
(2001) and Khandker (2005) proved that there was an inverse relationship between
land own and probability of accessibility to microcredit sectors. It is also
appropriate in the case of Vietnam (Cuong H. Nguyen, 2007 and Duong Pham,
2002).

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In contrast, finding by Okurut (2006) revealed that land endowment has a positive
correlation with household’s probability to borrow credit. Land title may be
considered as collateral for household’s borrowing, so it is easier for household with
bigger land size to get loan from formal sector (Sai et al, 2010). This result is in the
line with the finding by Vu (2002) and Zeller (2001) that Land is the most important
variable to measure the household’s ability to get credit, especially credit from
formal sector. Additionally, some empirical research states that households with
large own land scale which is the basic source of livelihood of the farmer demands
for more credit in order to run production activities (Mohamed, 2003; Ravi, 2003
and Davis et al., 1998; Svay et al, 2006).

2.4.9. Social network
Relationship between probability of accessibility to credit and social capital has
been a controversial issue. A vast of literature has revealed that social capital play a
crucial role in credit accessibility, particularly in developing countries (Okten and
Osili, 2004; Fafchamps, 2000). Social network is considered as social collateral in
order to obtain credit and there is a strong positive relationship between social
collateral and credit borrowing shown (Karlan et al, 2009). Bui (2010) also
indicated that social capital also play an important factor on credit ration. This result

is consistent with the finding by Grootaert (1999) that social capital has positively
influence for accessing to credit. Additionally, borrowers rely on social network to
lower uncertain information lead to a better flow of information between lenders
and borrowers, so demand for credit increase (Thierry, 2000). Considering the role
of social network on credit obtaining, it is expected that social capital is a
determinant of credit transaction.
Different from previous result, some indicates that social network does not
guarantee poor households participate in rural credit (World Bank, 2000).

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The objective of this research is to find out the effect of social network not only on
overall credit but also on types of credit, informal sector and formal sector.

2.4.10. Location
The main objective of rural credit is to help the rural poor household out of poverty
situation, so it is assumed that households in rural area have higher probability to
get credit compared to that located in urban area.
However, Consultative Grove to Assist the Poor (CGAP) demonstrated that the
probability of accessibility to credit source in rural area is probably significant
lower than in urban area. Microfinance for rural areas is not sustainably provide
financial services for rural populations; only densely populated areas benefit from a
widespread microfinance services. Therefore, households in remote area have less
chance to access to credit services. This might be due to opportunity costs of time
spending, transaction costs to travel to financial institutions and deficiencies in
communication with lenders because of long distance (Zeller & Sharma, 2000).
This negative relationship between location and demand for credit supported the
result of research by Balogun and Yusuf (2011).
In this research, I examine how location variable does affect the possibility to

approach credit source of household.

2.4.11. Rural activities
One target of microcredit is to help the poor on rural farming activities. Therefore, it
is assumed that households have more probability of accessibility to rural credit if
the households take part in rural activities
All variables in this econometrics research are defined in the Table 2.1.

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Table 2.1 Definition of Variables
Variables

Age

Gender

marital_stt

Edu

Type

Continuous

Explanation
Age measures the age of household’ head and it is
performed over 18 years old

Gender is sex of household head. This is dummy variable
Binary
which takes a value one if the household head is female
and zero if the household head is male
Marital status is divided into two categories including
married if the household head is married and single
Binary
otherwise. Marital status would be coded as 1 for married,
and 0 for single.
Edu is education level of household head. This variable is
Continuous measured by number of schooling year of household head
attending.

Hhsize

Continuous

Household size is considered as the number of member in
family.

Income

Continuous

Income is the total income of household (1,000,000
VND).

Savingamount

Continuous

It is measured in 1,000,000 VND.

Landsize

Continuous

Landsize is is the size of land owning by household. It is
measured in 1,000 m2.

agriculture_act Binary

1- Household takes part in agricultural activities
0- Otherwise

Network

Binary

Network variable is zero-one dummy variable presenting
with the value of 1 if the household is member of any
Association/ Union/Cooperative/Group/ Political Party, 0
otherwise.

Location

Binary

1- household is located in rural area
0- other wise

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CHAPTER 3: OVERVIEW OF MICROFINANCE SYSTEM
The first part of this chapter presents the history of Microfinance. The second part
discusses the role of government in Microfinance. In the last part, the overview of
Vietnamese microfinance system is mentioned.

3. 1. The history of Microfinance
According to Robinson (2001) and Otero (1999), microcredit and microfinance are
relatively new terms in the field of development, first coming to become
prominence in the 1970s. Since 1980, financial institutions such as Grameen Bank
and Bank Raykat Indonesia started to offer loans to the poor and organizations
without subsidies or funding from governments. Since then, the term microcredit
has become quite popular.
There are an increasing number of microfinance institutions coming into operation
in the 1900s. In addition, microfinance services have grown out to various kinds of
forms such as savings, pensions and so on.
The first microcredit Summit was organized in 1997 proving the importance of
microfinance to the development of the world. During the summit, the board has
agreed to put the plan to assist 175 million poorest families around the world.
Vietnam currently has a variety of Microfinance Institutions offering loans and
others services to a number of poor households. Table 3.1 presents loan portfolio
(in VND) and number of active borrowers provided by Vietnamese Microfinance
Institution in the recent years 2012 and 2013.

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Table 3.1 Microfinance Institutions in Vietnam

MFI name
An Phu Development Fund
Binhminh CDC
BTV
BTWU
CAFPE BR-VT
CEP
Chi-Em
Childfund Hoa Binh
CPCF
CSOD
Dariu
Fund for Women Development –
HCM
Ha Tinh Women Development
Fund
M7 Can Loc
M7 DB District
M7 DBP City
M7 Dong Trieu
M7 Mai Son
M7 Ninh Phuoc
M7 Uong bi
Small Credit Fund For Housing
Refurbishment, Da Nang
Soc Trang Fund for Poor Women
STU
TCVM Thanh Hoa

TYM
VBSP
VietED MF
Women Development Fund, Lao
Cai
Women Development Fund,
Quang Binh
WU Ha Tinh
WV Vietnam

Gross Loan Portfolio

Number of
borrowers
2012
2013
702
755
4,800
4976
1,463
1974
5,920
8500
10,400
10800
218,031 242725
3,389
3447
7,991

7662
50,874
#N/A
1,350
1570
11,334
14368

2012
151,282
944,211
254,622
698,523
1,880,640
55,471,876
506,509
712,268
311,345,856
153,600
2,683,618

2013
165,919
1,002,755
296,054
1,156,181
2,120,962
67,617,536
566,329
850,847

#N/A
232,084
3,196,935

1,479,004

2,312,577

5,798

15022

2,778,429
736,469
322,337
639,079
1,782,234
965,293
474,242
1,403,035

#N/A
925,202
350,418
867,883
#N/A
#N/A
481,176
#N/A

20,142
2,169
2,494
2,257
5,778
2,438
5,224
4,201

#N/A
2295
2635
2640
#N/A
#N/A
5352
#N/A

1,127,760
221,374
196,547
2,379,078
23,238,183

#N/A
#N/A
421,371
3,371,883
28,556,438

5,468,211,995
78,157

5,773,396,452
#N/A

1,650
3,184
855
14,687
78,818
7,100,00
0
533

#N/A
#N/A
1441
15328
91004
710000
0
#N/A

238,511

407,918

1,219

1632

1,550,803
2,778,429
1,804,441

1,896,247
2,930,831
2,591,050

12,710
20,142
8,626

7921
18660
11156

Source: www.mixmarket.org

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