------VU DUC CAN RISK PREFERENCES, SOCIAL CAPITAL, AND MICROCREDIT RISKS: AN EXPERIMENTAL STUDY IN THE MEKONG DELTA REGION OF VIETNAM Major: Finance – Banking Code: 9340201 SUMMARY OF
Trang 1- -VU DUC CAN
RISK PREFERENCES, SOCIAL CAPITAL, AND MICROCREDIT RISKS: AN EXPERIMENTAL STUDY IN THE MEKONG DELTA REGION OF
VIETNAM Major: Finance – Banking Code: 9340201
SUMMARY OF DOCTORAL THESIS IN
ECONOMICS
HOCHIMINH CITY, 2019
This thesis is completed at University of Economics Ho ChiMinh City
Trang 3The aim of this study is to empirically analyze social anddemographic factors related to microfinance borrowers in order tomeasure their effects on microcredit risks as undergone bymicrofinance institutions (MFIs) in the Mekong Delta Region ofVietnam Further, the study looks at risk preferences, social capital,and others with respect to microfinance borrowers’ behavior toestimate their impact on microcredit risks facing MFIs
In this study, a series of economic experiments was conductedwith the participation of microfinance borrowers in six provinces
of the Mekong Delta Region to capture the effects of riskpreferences and social capital on microcredit risks, which was welljustified by the findings Specifically, those who seek more risk areless likely to have bad debt, while those being more risk aversesuffer more Given social capital, mutual support in the communityand trust impact positively on microcredit risk These results form
a firm basis for devising feasible policies in direct relation tomicrofinance lending activities involving MFIs
Keywords: microfinance, risk preferences, social capital, risk
seeking, risk averse
Chapter 1: INTRODUCTION 1.1 Problem statement.
Microfinance has come into existence and gone through a longhistory of development, thus establishing its significant role andinfluence on economic growth in general and poverty alleviation inparticular Vietnam, however, has seen its advancement onlyrecently, and activities of formal MFIs are still limited According
to the State Bank of Vietnam (SBV), up to late 2018, there have
Trang 4been 16 financial firms, among which six are subsidiaries of a fewbanks The current period has seen a boom in financial companies
in Vietnam to exploit the untapped consumer lending segment,which has yet to satisfy market needs According to an SBV’sreport, by the end of 2018, the total outstanding loans of the entireeconomy reached around VND7.2 million billion, and theaggregate informal outstanding loans accounted for more than20% Nevertheless, the supply of formal credit has not well metpeople’s needs, especially small loans or those without collaterals,thus resulting in the growing demand for illegal lending, literallyknown as ‘black credit’, which made inroads into socioeconomicwell-being Hence, addressing the issue of risks as well as theimpact of microcredit risks on microfinance activities is urgent andessential to the current context of Vietnam
1.1.1 Risk preferences and microcredit risks.
In this study microfinance is understood as small loans (nolarger than VND100 million), and microcredit is one of theservices offered by MFIs As such, microcredit is a lending product
in credit activities as conducted by credit institutions; it is apredominant service provided by MFIs in Vietnam The prospecttheory, developed by Tversky and Kahnerman, suggested that thevalue function is determined by gains and losses in relation to thereference point Wen et al (2014) concluded that risk preference isrelated to attitudes toward risks Thus, it is evident that riskpreference is a tendency toward risk decisions as can be made byindividuals and investors to obtain the highest possibleprofitability Handa (1971) argued that risk preference is the choicebetween a high-risk asset and low-risk asset to gain higher returns.Charness et al (2013) and Eckel et al (2010) concluded that in
Trang 5economics emphasis can be put on suggestive methods inanalyzing risk preferences, and the suggested preferences can beaffected by the measures used According to Stiglitz and Weiss(1981), borrowers are motivated, and have a tendency, to invest inrisk-ridden projects This means that borrowers with bad debts arewilling to take high risks The experiments carried out by Zeballos
et al (2014) showed that borrowers having no bad debtsdemonstrate more risk-seeking behavior than those with bad debts.Stiglitz and Weiss (1981) hypothesized that people investing inless risky projects are those suffering bad debts The poor cannotrepay their loans because they refuse to face risks, so theeffectiveness is low (Zeballos et al., 2014)
In Vietnam, Vieider et al (2013) concluded that farmers are onaverage risk neutral and that income is negatively associated withrisk aversion The studies of Nguyen et al (2016) and Tanaka et al.(2010) in northern and southern villages accentuated the impact ofrisk attitudes and risk and time preferences on trust and reliability,and risk aversion and patience So, which specific behavioralcharacteristic of microfinance borrowers has influence onmicrocredit risks? Do risk preferences differ in microfinancepractices between rural and urban regions? These are also theresearch gap for this paper to fill
1.1.2 Social capital and microcredit risks.
To date social capital is regarded as a real form of capital andthus substantially influences microcredit risks Trust and reliabilityare two major concepts embedded in personal social capital, andsocial capital takes a crucial part in different fields in an economyand society Still, how does it manifest itself and in what waywould it be measured when it comes to the issue of risk in
Trang 6microfinance activities? This also receives special attention in thisstudy.
1.2 Research topic.
In Vietnam there has yet to be any comprehensive, systematicresearch that examine risk preferences and social capital with theireffects on microcredit risks as well as the progress of microfinanceactivities in Vietnam Risk is commonplace in decision makingprocesses, and risk preference is measured by the level of risktolerance of a single individual From this respect, this study is to
be carried out with the title “Risk preferences, social capital, and
microcredit risks: An experimental study in the Mekong Delta Region of Vietnam”.
1.3 Research objectives.
The principal objective of this study is to examine the effects
of microfinance borrowers’ behavior on microcredit risks in theMekong Delta Region As such, through data collection andanalysis derived from field experiments, the study identifies theextent to which behavioral factors such as risk preference andsocial capital, along with other social and demographic factorsinclusive of the difference between rural and urban borrowers,have effect on microcredit risks To obtain the informed objective,the following questions are to be brought up: (i) How doborrowers’ risk preferences and other social, demographic factorsaffect microcredit risk of MFIs? and (ii) How do borrowers’ socialcapital and other social, demographic factors influence microcreditrisks of MFIs?
1.4 Research methods.
Several research hypotheses are proposed based on the review
of related literature and relevant theoretical framework as well as
Trang 7the results of previous studies Field experimental method isadopted to collect the data Regression analysis with BinaryLogistic is performed to process the data, along with the use ofProbit technique to test the robustness of the results obtained Theresults are then screened, discussed, and interpreted to put forwardpolicy implications, and limitations are also outlined as a basis forfuture research.
The technique proposed by Eckel and Grossman (2002) isadopted to conduct the experiment of eliciting risk preferences.Concerning social capital, the study suggests the Game ofcontributions to community, and Camerer and Fehr’s (2003)method is employed to investigate trust and reliability
1.5 Research participants and scope.
- Participants: microcredit borrowers of microcredit providers,including both formal and semi-formal institutions
- Scope: A total of 176 microfinance borrowers residing in bothrural and urban areas in six provinces of the Mekong Delta Region,namely Kien Giang, Hau Giang, Vinh Long, Tien Giang, Ben Tre,and Long An All six surveys and experiments were undertakenfrom May through October 2017
1.6 Contributions of the study.
1.6.1 Theoretical contribution.
Selectively applied in this investigation are the three-Gameexperimental technique suited to the reality of Vietnam as well asthe study locations to consider the impact of different factors onmicrocredit risks in the Mekong Delta Region, and thus to addsome theoretical basis on behavioral finance as regards riskpreferences and social capital with their diverse effects onmicrocredit risks in urban and rural areas
Trang 81.6.2 Contribution to practice.
In this study the author draws critical conclusions on riskpreferences and social capital that influence microfinanceactivities Those who contribute much to the community and whomuch willingly donate their money to partners are less likely tosuffer bad debt, and the reverse is also true When the size of theloan is high, the level of bad debt abates, and no difference can befound in bad debt levels between urban and rural areas Further, thestudy provides policy implications regarding microfinanceactivities and constructive suggestions as to the advancement of theVietnam’s microfinance industry at large
1.7 Organization of the study.
Chapter 5: Result discussion and policy implications
Chapter 2: RISK PREFERENCES, SOCIAL CAPITAL, AND
MICROCREDIT RISKS 2.1 Risk preferences and microcredit risks.
In human society risk is perceived to exist in all kinds ofactivities Attitudes of people toward risk remarkably differ;therefore, it can be used to speculate on their economic behaviorand decisions The impact of risk is direct and diverse, fromborrowers’ behavior and activities to investment, manufacture, and
Trang 9consumption and behavior toward risk Other effects arise fromdemographic, financial, or physical factors and social capital.
2.1.1 Prospect theory.
As the basis for behavioral science, Tversky and Kahnerman(1979) with the prospect theory posited that people sometimesshow either risk aversion or show risk seeking tendenciesdepending on the nature of the prospects (Ackert & Deaves, 2013).Tversky and Kahneman’s theory centered around thesefundamental points: (i) In the light of the nature of the prospects,human behavior sometimes implies not just risk aversion (riskavoidance) but sometimes risk loving (risk seeking) People’schoices, thus, are made on the basis of gains and losses; (ii) Aperson assesses gains and losses against a reference level, whichnormally corresponds to his current condition; and (iii) People willlikely lose because the loss impacts more powerfully on theiremotions than the gain
2.1.2 Risk preferences in microfinance lending activities.
The credit market is imperfect, and always reflects anasymmetry between borrowers and lenders Stiglitz and Weiss(1981) argued that borrowers with bad debts are willing to riskgetting high-interest loans According to Zeballos et al (2014),borrowers without non-performing loans seek more risk than thosewho have Eckel and Grossman (2008) found that female studentsare more risk averse than their male counterparts WhileBinswanger (1980) detected no difference in risk compared to thescope of investment between the rich and poor, Vieider et al.(2015) showed that unmarried people are less risk averse, whereaswomen and the elderly are more risk averse
Trang 10In brief, studies on risk preferences concern a wide range ofsubjects and areas The results also indicated many differences insubjects, areas, and fields of study However, the impact of riskpreferences on risks involving microcredit lending andmicrofinance activities in Vietnam has not been studied at length.
So, how do risk preferences as well as other social, demographicfactors of microfinance borrowers affect the risks in microfinancelending activities of credit institutions engaging in microcreditlending and MFIs?
2.2 Social capital and microcredit risks.
2.2.1 The role of social capital.
Social capital is seen as a kind of capital Social capital is acomparatively sustainable social network, exhibiting itself withsympathy, understanding, and interaction among members(Bourdieu, 1986; Fukuyama, 2001, 2002; Coleman, 1988; Portes,1998) According to Karlan (2005), social capital of an individual
is the ability to obtain information, their communication, and socialrelations to get to grips with imperfect information-relatedproblems Economists held that trust is a critical constituent ofsocial capital As revealed by Karlan (2005), the more faith peoplehave in others, the more economical they are; the more reliablethey are, the less credit risk they are exposed to, and the morepeople contribute to the community, the less credit risk they face.According to Knack and Keefer (1997) and Karlan (2005),countries and cultures with more mutual trust achieve highergrowth rates Glaeser et al (2000) maintained that people who aremore trusted are more reliable
2.2.2 Social capital in microcredit lending activities.
Trang 11Feigenberg and Field (2010) highlighted lending to the group
of low non-performing loans without mortgage Akram andRoutray (2013) suggested that social capital index has negligibleinfluence on microfinance participation Trust as a measurefacilitates borrowing from a group based on microfinanceprograms Poor households can use their social capital as collateralfor loans According to Karlan (2005), the higher the social capital,the better the ability to repay loans and the more economical it is.Greiner and Wang (2009) exhibited an information asymmetrybetween lenders and borrowers
2.2.3 Studies on social capital in Vietnam.
In a study by Nguyen Tuan Anh and Thomése (2007), socialcapital was shown to well handle troubles involving landconsolidation in agriculture Nguyen Van Ha and Kant (2004)indicated that social capital has a strong and positive influence onhousehold income Tran Huu Dung (2003) pointed out therelationship between social capital and economic policy; betweensocial capital and economic growth Social capital has a profoundimpact on the quality and rate of human capital accumulation DinhHong Hai (2013) noted the dark side of social capital Ngo ThiPhuong Lan (2011) believed that social capital helps minimizerisks in the transition from rice cultivation to shrimp farming in theMekong Delta Nguyen Hong Thu (2018) concluded thatmicrofinance has an impact on the income of poor households,which, as argued by Mai Thi Hong Dao (2016), is affected by suchfactors as age, household size, rate of dependency, total assets,microcredit, and regions affect the income of poor households.Phan Dinh Khoi (2013) concluded that working for localauthorities, being members of loan groups, education level, skilled
Trang 12labor, and inter-commune roads affects the accessibility tomicrofinance Dinh Phi Ho and Dong Duc (2015) asserted thathousehold characteristics, residential locations, and shocks ofenvironmental risks have influence on farm households’ incomeand expenditure.
Accordingly, it is conceivable that social capital has asubstantial impact on many sectors in an economy or society Still,considering the matter of risks in microfinance practices, how does
it represent and how can we measure it? This merits specialattention
2.3 Measuring risk and effectiveness of microfinance practices 2.3.1 Definition of microfinance.
The term ‘microfinance’ denotes the models of financialservices provided for the poor that helps them with their ownbusiness development and life improvement
2.3.2 Measuring and assessing microcredit risks.
2.3.2.1 Effectiveness of microfinance practices.
Indicators of performance and sustainability of a microfinance
institution are varied, including: (1) Institutional self-sustainability (ISS); (2) Operational self-sustainability (OSS); (3) Financial self-
sustainability (FSS) (Ackert & Deaves, 2010; Le Dat Chi et al.,2013)
2.3.2.2 Risks in microfinance practices.
Objective risks: natural environment, socio-economic
environment, legal environment
Subjective risks:
MFIs: administration capacity, lending procedure and policy,
⁕ MFIs: administration capacity, lending procedure and policy,
loan inspection and supervision, service and ethical quality ofcredit staff
Trang 13Microfinance borrowers: education level, production and
⁕ MFIs: administration capacity, lending procedure and policy,
business capacity, ethical issues
2.3.3 Measuring microcredit risks in the study.
2.3.3.1 Definition of bad debt and related views.
Bad debt can be referred to as ‘doubtful debt’ or performing loan’ WB defined it as substandard loans that may beoverdue, or doubts arise over the repayment capacity as well as therecoverability of capital, frequently occurring in the event that thedebtor has been declared bankrupt or detected with propertydispersion According to IMF, “a loan is nonperforming whenpayments of interest and/or principal are past due by 90 days ormore, or interest payments equal to 90 days or more have beencapitalized, refinanced, or delayed by agreement, or payments areless than 90 days overdue, but there are other good reasons—such
‘non-as a debtor filing for bankruptcy—to doubt that payments will bemade in full.’
Risks in microfinance lending practices
Figure 2.2: Research framework.
(Source: from theoretical bases and overview of literature)
2.3.3.2 Bad debt in Vietnam.
Pursuant to SBV’s Circular 02 (2013), bad debts are thosefrom Group 3 (91 days or more overdue) to Group 5
- Trust
- Reliability
- Contribution tocommunity
- Social relations
- Social network
Bad debt
Trang 142.4 Research framework (Figure 2.2.)
Chapter 3: RESEARCH DESIGN 3.1 Data and methodology.
3.1.1 Qualitative method.
Direct interviews were carried out with 176 microfinanceborrowers on-site, along with consultation provided by experts,SBV’s senior leaders and other credit institutions
3.1.2 Quantitative method.
Based on the data collected from the experiments, statisticaldescription was given, in addition to Binary Logistic regression,Probit analysis performed to test the robustness of the regressionresults in order to analyze the models suggested
3.1.3 Basis for location and sample selection.
This is a key area of the southern region of Vietnam, full ofdistinct characteristics of ecosystems, industries, and ethnic groups.The author has over 20 years’ experience in the banking industryfor proper selection of participants Given the total number of 176participants, 33.5% was selected from Vietnam Bank for SocialPolicies (VBSP), and the remaining 66.5% from local commercialbanks
3.2 Selecting experimental methods in economics.
3.2.1 Eliciting risk preferences.
Several experimental techniques have been developed to delveinto attitudes toward personal risks, including Balloon AnalogueRisk Task (BART), questionnaires, methods as proposed byGneezy and Potters, Eckel and Grossman, and selection based onprice lists
3.2.2 Measuring social capital.
Trang 15The methods applied comprise Trust Game and Public Goods
Game
3.2.3 Assessing and selecting methods.
The author employed Eckel and Grossman’s technique, Trust
Game, and Public Goods Game
3.2.4 Organization and role assignment.
The author first collected demographic information and
decided on the locations for Risk Game (Game 1) In Games 2 and
3, each assigned group is composed of one group leader, one
secretary, and one assistant
3.2.5 Basis for determining rewards.
Table 3.2: Average income and expenditure per capita per day
Unit: VND
Whole country
(Source: Statistical Yearbook of Vietnam 2016 and author’s calculations)
3.3 Methods and steps taken for experiments.
Experiment 1: Eliciting risk preferences.
Each participant received VND100,000 and would have to
make a random selection of one of the six Scenarios as detailed in
Table 3.3 Then, they were instructed to cast either of the two lots
labelled “win” and “lose”
Table 3.3: Game options
Unit: VND
Scenario Amount
subtracted Amount received Selection Result
Trang 16(Source: Author’s selection).
Experiment 2: Public Goods Game.
Groups of 10–15 participants were formed, and they eachreceived VND50,000 The Game operator then asked if theydecided to donate or not A participant’s acceptance means that hewould have to give the operator VND30,000, and the players in thesame group would each receive VND5,000 upon the end of theGame His refusal to donate the money means the amount obtained
by the others in the group remained unchanged
Experiment 3: Trust Game.
The operator asked if the number 1 players would love to givetheir money to those with number 2 No money given means theend of the Game The money, if given, must be held by theoperator; it was then doubled before received by the number 2players Next, the operator asked the number 2 players if theyagreed to give the money back to the number 1 players
3.4 Research models.
3.4.1 Regression equation for risk Game experiment:
Y 1=β0+ β1 X1+ β2 X2+ β3 X3+ β4 X4+ γ Z
where Y 1i is a dependent variable, equaling 1 if the participant has
bad debt and 0 otherwise Independent variables:X1 represents
participant’s selection; X2 represents age; X3 represents gender;
X4 represents education level.
- Z is a control variable denoting living area
Trang 173.4.2 Regression equation for public goods Game experiment:
Y 2=β0+ β1 X1+ β2 X2+ β3 X3+ β4 X4+ γ Z
where Y 2i is a dependent variable, and X1is an independent
variable representing the participant’s intention to donate
3.4.3 Regression equation for trust Game experiment:
Y 3=β0+ β1 X1+ β2 X2+ β3 X3+ β4 X4+ γ Z
where Y 3i is a dependent variable,X1 is an independent variable
denoting percentage of the amount given to his partner by theparticipant
3.4.4 Regression equation for all three experiments (robustness check):
Y 4=β0+ β1 X1+ β2 X2+ β3 X3+ β4 X4+ β5 X5+ β6 X6+ γ Z
where Y 4i is a dependent variable,X1 represents participant’s
selection, X2 represents intention to donate, X3 represents
percentage of the amount given to partner, X4 represents age, X5
represents gender, X6 represents education level, and Z is a
control variable denoting living area
3.5 Research hypotheses.
3.5.1 Behavioral hypothesis concerning Risk Game:
H 1 : Those who seek more risk have less bad debt, while those being more risk averse suffer more.
3.5.2 Behavioral hypothesis concerning Public Goods Game:
H 2 : Those who donate are less likely to have bad debt, while it is more likely for those with no contribution.
3.5.3 Behavioral hypothesis concerning Trust Game:
H 3 : The larger the percentage of the amount a participant gives his partner, the less likely it is for him to be burdened with bad debt.
Trang 18Conversely, the smaller the percentage, the more likely he suffers bad debt.
3.6 Regression technique.
Primarily employed in this research was Binary Logisticregression method Further, Probit analysis was performed to checkthe robustness of the results obtained using the regression method
Chapter 4: ANALYSIS OF EFFECTS OF DIFFERENT FACTORS
ON MICROCREDIT RISKS: RESULTS OF SURVEY, STATISTICS, AND EXPERIMENTS IN THE MEKONG DELTA
REGION 4.1 Statistical description of data sample.
4.1.1 Overall statistics on participants’ characteristics.
4.1.1.5 Locations of households’ bank loans.
33.5% of the loans are requested at Vietnam Bank for SocialPolicies and 66.5% at local joint stock banking institutions
Trang 194.1.1.6 Principal income sources.
There is a relatively even distribution of households’ sources
of income (ranging from 23.3% to 29.5%)
4.1.1.7 Quantitative indicators.
The average age is 46.9 along with the most advanced of 85and the earliest of 20 Standard deviation is 12.4 Averagehousehold size is 4.5 people (max is 12, and min is 1) The averagepercentage of household members with employment is 68.7% Theaverage loan rate is VND23.58 million per household Theduration of loans repayment is about 15.8 months, ranging from 1
4.1.2.2 Public Goods Game.
81.8% of the participants make donations, and 18.2% do not
4.1.2.3 Trust Game.
92% agree to give money to their partners
4.1.3 Detailed statistics on characteristics of experiments.