寮國的銀行貸款違約的決定因素 - 政大學術集成

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(1)國立政治大學商學院國際經營管理英語碩士學位學程 International MBA Program College of Commerce National Chengchi University. 碩士論文 Master’s Thesis. 學. ‧ 國. 立. 政治大. ‧ y. Nat. er. io. sit. 寮國的銀行貸款違約的決定因素 n. Determinants of Loan Defaults al i v in Laos. Ch. n U engchi. Student: Morxay Vongnakhone Advisor: Jason Tsai. 中華民國一○九年五月 May 2020. DOI:10.6814/NCCU202000789.

(2) 寮國的銀行貸款違約的決定因素 Determinants of Loan Defaults in Laos. 研究生：方楠冠. Student: Morxay Vongnakhone. 指導教授：蔡政憲. Advisor: Jason Tsai. 立. 政治大國立政治大學. ‧ 國. 學. 商學院國際經營管理英語碩士學位學程. A Thesis. io. sit. Nat. y. ‧. 碩士論文. er. Submitted to International MBA Program. n. aNational iv l C Chengchi University n hengchi U in partial fulfilment of the Requirements for the degree of Master in Business Administration. 中華民國一○九年五月 May 2020. DOI:10.6814/NCCU202000789.

(3) Acknowledgements I am indeed indebted to my academic advisor, professor Jason Tsai for his insightful comments and support. I would like to sincerely thank Zong Yi Lin, an assistant of my professor who also supports me on the technical part of my thesis. Furthermore, I would like to thank my colleagues from the Saving and Credit Union Champa Phatthana for their support and cooperation during the survey providing the data and also participating in the interview session. Special thanks to my boss, Mr. Khammon Sitthideth for his support in setting up the survey team to conduct the survey for me. I would like to thank. 政治大 Champa Phatthana who always supports and inspires me to challenge myself. Moreover, I 立 would like to thank the International Cooperation and Development Fund Taiwan (ICDF to Mr. Friedrich Herbert Lechermann, a development advisor of the Saving and Credit Union. ‧ 國. 學. Taiwan) for the financial support during my study in Taiwan and special thanks to an excellent program manager at National Chengchi University, Emily Huang for her great assistance on. ‧. every matter of my campus life.. Nat. sit. y. In addition, I would like to thank my friend, Miss Vilasouk Phongphaekham for her. al. n. for always supporting me.. er. io. assistance with my data entry. Finally, I would like to thank my beloved parents and brothers. Ch. engchi. i Un. v. i DOI:10.6814/NCCU202000789.

(4) Abstract Determinants of Loan Defaults in Laos By Morxay Vongnakhone This study investigates the determinants of loan defaults of the village banks in Laos. I use a questionnaire and a semi-structured interview to collect data. This research is based on 293 microcredit loans granted by the village banks under the supervision of the microfinance institution (Saving and Credit Union Champa Phatthana). By applying statistical methods, I. 政治大 less than 1million LAK, no agriculture land holding, loan size (ln), and loan diversion rate less 立 than 35% have positive relations with loan default. Conversely, commute time to the financial. find that marital status (widowed), family members who earn the living, expenses on festivals. ‧ 國. 學. institution office, loan diversion rate more than 50%, and construction loan factors have. ‧ y. Nat. io. n. al. er. Keywords: Microfinance, Village Bank, Loan Default, Laos. sit. negative relations.. Ch. engchi. i Un. v. ii DOI:10.6814/NCCU202000789.

(5) TABLE OF CONTENTS 1. Introduction ............................................................................................................................ 1 1.1. Country Brief of Laos .................................................................................................. 1 1.2. Overview of Microfinance in Laos .............................................................................. 4 1.3. Microfinance Providers in Laos ................................................................................... 5 1.3.1.. Formal Microfinance Sector ....................................................................... 5. 1.3.2.. Semi-Formal Microfinance Sector ............................................................. 6. 1.3.3.. Informal Microfinance Sector .................................................................... 7. 立. 政治大. ‧ 國. 學. 2. Literature Review and Conceptual Framework ...................................................................... 8. ‧. 2.1. Literature Review ......................................................................................................... 8. sit. y. Nat. io. n. al. er. 2.2. Conceptual Framework .............................................................................................. 15. i Un. v. 3. Village Bank and SCU Champa Phatthana .......................................................................... 17. Ch. engchi. 3.1. Village Bank Organizational Structure ...................................................................... 17 3.1.1.. General Assembly of Members ................................................................ 17. 3.1.2.. Village Bank Committee (VBC) .............................................................. 18. 3.1.3.. Village Bank Advisor ............................................................................... 18. 3.1.4.. Financial Services of Village Bank .......................................................... 19. 3.2. Brief of the Saving and Credit Union Champa Phatthana ......................................... 21. iii DOI:10.6814/NCCU202000789.

(6) 4. Methodology......................................................................................................................... 25 4.1. Research Approach .................................................................................................... 25 4.2. Data Source and Type ................................................................................................ 25 4.3. Target Population ....................................................................................................... 25 4.4. Model Specification ................................................................................................... 25 4.5. Description and Measurement of Variables ............................................................... 28. 治政大 4.6. Questionnaire ............................................................................................................. 29 立 ‧ 國. 學. 5. Findings ................................................................................................................................ 36 5.1. Defaulters’ Perspectives ............................................................................................. 36. ‧. sit. y. Nat. 5.2. Non-Defaulters’ Perspectives ..................................................................................... 40. n. al. er. io. 5.3. Borrowers’ Experiences before Village Bank (VB) Exist ......................................... 43. i Un. v. 5.4. Perspectives of SCU’s Personnel ............................................................................... 47. Ch. engchi. 5.4.1.. Staff’s Perspectives .................................................................................. 47. 5.4.2.. Manager and Development Advisor’ Perspective of the SCU ................. 51. 5.4.3.. Stories of Borrowers (Defaulters)............................................................. 53. 5.5. Summary of Variables ................................................................................................ 54 5.6. Regression Results ..................................................................................................... 64 6. Conclusions and Recommendations ..................................................................................... 72. iv DOI:10.6814/NCCU202000789.

(7) 6.1. Conclusions ................................................................................................................ 72 6.1.1.. Borrowers’ Perspectives ........................................................................... 72. 6.1.2.. Staff and Management’ Perspectives. ...................................................... 73. 6.1.3.. Binary Logistic Regression Results.......................................................... 73. 6.2. Recommendations ...................................................................................................... 74 6.3. Further Research ........................................................................................................ 75. 治政大 7. References ............................................................................................................................ 76 立 ‧. ‧ 國. 學. 8. Appendix .............................................................................................................................. 81. n. er. io. sit. y. Nat. al. Ch. engchi. i Un. v. v DOI:10.6814/NCCU202000789.

(8) List of Figures and Tables Figure 1: Type of Microfinance in Laos ..................................................................................... 6 Figure 2: Conceptual Framework of the Study ........................................................................ 16 Figure 3: Village Bank Organization Structure ........................................................................ 17 Figure 4: Operating Mechanisms of the Village Bank System ................................................ 19. 政治大 Figure 6: Marital Status Distribution........................................................................................ 56 立 Figure 5: Organization Chart .................................................................................................... 24. ‧. ‧ 國. 學. Figure 7: Education Distribution .............................................................................................. 57. Table 1: Literature Review (outside of Laos) ........................................................................... 11. Nat. sit. y. Table 2: Literature Review (in Laos) ....................................................................................... 14. n. al. er. io. Table 3: Types of Loans and their Terms ................................................................................. 21. Ch. i Un. v. Table 4: Variable Descriptions ................................................................................................. 28. engchi. Table 5: Main Reasons of Causing Defaults ............................................................................ 36 Table 6: Defaulters’ Choices in Problem Solving .................................................................... 37 Table 7: Defaulters’ Worries .................................................................................................... 38 Table 8: Defaulters' Lessons Learned ....................................................................................... 39 Table 9: Defaulters’ Needs ....................................................................................................... 40 Table 10: Main Factors of Non-Default ................................................................................... 41 Table 11: Non-Defaulters’ Needs ............................................................................................. 42 Table 12: Feeling on Loan Default ........................................................................................... 42 vi DOI:10.6814/NCCU202000789.

(9) Table 13: Non-Defaulters’ Choices in Problem Solving if They Would Default .................... 43 Table 14: Sources of Loans ...................................................................................................... 44 Table 15: Borrowers’ Experiences on Late Payments.............................................................. 45 Table 16: Interest Rate Charged by Moneylenders .................................................................. 45 Table 17: Benefits of Obtaining Loans from the Village Bank ................................................ 46 Table 18: Disadvantages of Obtaining Loans from the Village Bank ...................................... 47 Table 19: Age Distribution ....................................................................................................... 55. 政治大. Table 20: Distribution of Gender.............................................................................................. 55. 立. Table 21: Family Size Distribution .......................................................................................... 57. ‧ 國. 學. Table 22: Employment Status .................................................................................................. 58. ‧. Table 23: Travel Time during Dry Season (minute) ................................................................ 58. sit. y. Nat. Table 24: Travel Time during Rainy Season (minute) ............................................................. 59. n. al. er. io. Table 25: Agricultural Land Value (USD) ............................................................................... 59. v. Table 26: Construction Land Value (USD) .............................................................................. 60. Ch. engchi. i Un. Table 27: Value of Livestock per Family (USD) ..................................................................... 60 Table 28: Expenses Distribution on Festivals (USD) ............................................................... 61 Table 29: Loan Purpose ............................................................................................................ 61 Table 30: Loan Amount ............................................................................................................ 62 Table 31: Loan Diversion Rate ................................................................................................. 62 Table 32: Financial Literacy Training ...................................................................................... 63 Table 33: Default ...................................................................................................................... 63 Table 34: Descriptive Statistics of Explanatory Variables ....................................................... 64. vii DOI:10.6814/NCCU202000789.

(10) Table 35: Univariate Analyses ................................................................................................. 65 Table 36: Regression Results of Binary Logistic Regression Model ....................................... 69 Table 37: Alternative Results of Binary Logistic Regression Model ....................................... 70. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i Un. v. viii DOI:10.6814/NCCU202000789.

(11) List of Abbreviations ADB. Asian Development Bank. AFC. Asian Financial Crisis. AFP APB. Microfinance in Rural Areas - Access to Finance for the Poor Agricultural Promotion Bank. BOL. Bank of Lao PDR. CGAP. Consultative Group to Assist the Poor. DTMFIs. Deposit Taking Microfinance Institutions. GDP. Gross Domestic Product. GDP. Domestic Product. National Economic Research Institute. National Growth and Poverty Eradication Strategy. io. NGPES. Non-Deposit Taking Microfinance Institutions. y. NERI. Ministry of Planning and Investment. Nat. NDTMFIs. Microfinance Institutions. ‧. MPI. Microfinance Association. sit. MFIs. 學. MFA. er. MDGs. ‧ 國. Lao PDR. 政治大 Lao People’s Democratic Republic 立 Millennium Development Goals. al. UN. United Nations. UNDP. United Nations Development Program. UNFPA. United Nations Population Fund. UNICEF. United Nations Children's Fund. VB. Village Bank. VBC. Village Bank Committee. WB. World Bank. SCUs. n. SDC. iv n C Savings & Credit h eUnions ngchi U Swiss Agency for Development and Cooperation. NGPES. National Growth and Poverty Reduction Strategy. ix DOI:10.6814/NCCU202000789.

(12) 1. Introduction 1.1. Country Brief of Laos The country of Laos, officially named the Lao People's Democratic Republic (Lao PDR). Laos is located in Southeast Asia and has no direct access to the sea or a landlocked country. Laos is bordered by 5 neighboring countries. Thailand borders Laos to the Southwest and west while Cambodia also lies to the Southwest; China and Myanmar (Burma) are from the northwest boundary while Vietnam is to the east. Laos is one of the poorest countries in East Asia and is classified by the United Nations. 政治大 has a population of 6,492,288. The population is relatively young: 4% of the population aged 立. (UN, 2015) as a Least Developed Country (LDC). With a land area of 236,800 square km, it. 65 years and over, 32% aged 0-14 years and 64% being the working age between 15-64 years. ‧ 國. 學. (United Nations Fund for Population Activities [UNFPA], Swiss Agency for Development and Cooperation[SDC], World Bank [WB], and United Nations Children's Fund [UNICEF], 2015).. ‧. Laos was established in 1975. It has a moderately centralized political system grounded. y. Nat. sit. on the principle of “democratic centralism” that supports the idea of bottom up deliberation but. al. er. io. top down decision making. The system has been balanced by a process of decentralization and. v. n. entrusting some authority to the provincial level. Even though policy is centrally decided,. Ch. i Un. provincial governors and ministers who are party members share the same political rank and. engchi. have significant independence in administering and implementing policy. There are 11-person politburo who lead the Lao People’s Revolutionary Party (LPRP) that is the only political party and policy making body of the nation. From the mid-1970s to early 1980, the Laos implemented a centrally planned economy where the economic decision was highly controlled by the government. During this period the county was extremely poor and isolated. However, the government introduced market-oriented reforms under New Economic Mechanism (NEM) in 1986. In the early stage of NEM, there were many changes such as removing price controls, unifying exchange rates, expanding foreign and inter-provincial trades, and supporting private enterprise in both agricultural and manufacturing sectors. In the 1990s, a legislative program continued to reform in order to. 1 DOI:10.6814/NCCU202000789.

(13) provide the foundation for market-oriented rules and private sector development (Asian Development Bank [ADB], 2013). The reforms produced significant results, from 1990 to 1997, before the Asian Financial Crisis (AFC), Gross Domestic Product (GDP) growth rate was about 6.4% on average per year. Even though the economic growth was affected by the AFC in 1998, it had recovered by 1999. Sustained growth produced an impressive outcome on GDP per capita by increasing its value more than two times from $227 in 1990 to $592 in 2011(ADB,2013). Laos has significant natural resources like forestry, minerals, and hydro-electric power, which also play a significant role in economic growth. From 2014 – 2018 the economy had strong growth with an average. 政治大 [BoL] ,2018). However, the proportion of the population below the national poverty line is still 立. of approximately 7%, which generates the estimated per capita of US$2,599 (Bank of Lao PDR. high, 29% in 2015 (The ASEAN Secretariat, 2017).. ‧ 國. 學. Globally, approximately 736 million people lived under the international poverty line or. ‧. below $1.90 a day (WB, 2020). About 10% of the global population live in extreme poverty and face difficulties in receiving the basic needs for instance healthcare, education, access to. y. Nat. sit. clean water, sanitation, and so on (UN, 2015). About 3.8 billion people or 69% of adults. er. al. n. 2017).. io. worldwide have a bank account, but 1.7 billion adults remain unbanked (World Bank Group,. Ch. engchi. i Un. v. In Laos, about 47% of adults use at least one regulated financial service (World bank[WB], 2018). Financial access helps households and businesses plan for their long-term goals and unexpected circumstances, expand businesses, invest in education or health, manage risks, which can enhance the standard of living (WB, 2018). As quoted by the late Milton Friedman, Nobel Prize winner in the Economics 1976, “The poor stay poor not because they are lazy but because they have no access to capital”. Microfinance is a significant accelerator for poverty alleviation. It allows poor people to access financial services, to generate income, and to enhance their ability to pay for social services, their quality of living can thus be improved (Consultative Group to Assist the Poor, 2010). Referring to the United Nations Capital Development Fund (UNCDF, 2005), microfinance not only underpins the achievements of many Millennium Development Goals 2 DOI:10.6814/NCCU202000789.

(14) (MDGs) but also is a significant key role in many MDGs strategies. These are because microfinance can nurture financially self-sufficient private sectors domestically and generate wealth for low-income people. The UN launches the International Year of Microcredit aiming to support poor and low-income people to have more access to financial services by providing greater access to credit, savings, insurance, money transfer, and other financial services in the effort of moving forwards to more secure life and flourishing futures (UN,2005). The UN also aims to raise public awareness on microcredit and microfinance as well as to promote innovative partnerships among governments, donors, international organizations, nongovernmental organizations, private sector, academia and microfinance clients to recognize. 政治大 In the following year 2006, Muhammad Yunus and the Grameen Bank of Bangladesh 立. how significant microfinance can help people to get out of poverty.. jointly received Nobel Peace Prize for pioneering the provision of small loans to millions of. ‧ 國. 學. poor people—also known as microcredit. He stated that “I firmly believe that we can create a poverty-free world if we collectively believe in it. In a poverty-free world, the only place you. ‧. would be able to see poverty is in the poverty museums”. Kofi Annan, United Nations. y. Nat. Secretary-General also quoted " Microfinance has proved its value, in many countries, as a. n. al. Ch. er. io. especially the lives of those who need it most.". sit. weapon against poverty and hunger. It really can change peoples’ lives for the better. i Un. v. While international communities have been working on poverty reduction by using. engchi. microfinance as one of the significant tools, the government of Laos has also been working on implementing the 8th National Socio – Economics Development Plan (NSEDP) 2016-2020 to reduce poverty. This implementation may help Laos graduate from being a Least Developed Country because poverty reduction is one of the significant issues that needs to be solved. The government has afforded much effort to improve the microfinance sector. The government also believes that microfinance can boost economic growth and poverty reduction. Hence, in the framework of the National Growth and Poverty Eradication Strategy (NGPES), the microfinance sector was pushed into the top development programs in the agriculture and forestry sectors for the purposes of economic sustainable and poverty reduction (NGPES, 2004).. 3 DOI:10.6814/NCCU202000789.

(15) 1.2. Overview of Microfinance in Laos Financial Institutions are a main element in the finance sector which is under the management of the bank of Lao PDR. These include: commercial banks, financial institutions and non-bank institutions. Among those financial institutions, microfinance has been operating actively for more than two decades. The starting point of microfinance development in Laos went back to the beginning of the 1990s when the country started to open up and to evolve toward a market economy. The starting point was the support by multilateral and bilateral organizations for establishing village-. 治政大 partners that supported this organizations (NGOs) were the most significant development 立 sector. By 1996, there were more than 20 international organizations involved in credit funds based credit schemes and revolving funds. During 1994 to 1996, non-governmental. ‧ 國. 學. in the rural areas over the country. Projects were implemented by the cooperation between international organizations and the local government at the district level such as the Lao Women. ‧. Union office, agriculture and forestry office, and other related local government offices (Ministry of Planning and Investment, National Economic Research Institute, and Bank of the. y. Nat. er. io. sit. Lao PDR [MPI, NERI & BOL], 2012).. The villages in Laos are relatively small. Many of them have less than 100 households on. n. al. Ch. i Un. v. average. Therefore, mostly the credit fund was small. By the support of donors, the number of. engchi. credit schemes and revolving funds increase rapidly. According to the national survey of financial access which was conducted in 1997 by the United Nations Development Program (UNDP)/UNCDF, there were 1,640 village funds by the middle of 1996 and accounted for approximately 15% of all villages in Laos. Those village banks included more than 1,000 rice banks, livestock banks, and revolving credit funds. Because the degree of monetization of the rural economy was relatively low, most credit was in kind (MPI, et al., 2012). The rapid growth of the number of village funds caused both the government and the donor to concern about sustainability and viability. Hence, a microfinance Roundtable Meeting between the government and donor agencies was held by the coordination of UNDP/UNCDF. During 1995 and 1996, there were 3 conferences held. The two main issues discussed at that. 4 DOI:10.6814/NCCU202000789.

(16) time were enhancing saving mobilization and improving the regulatory environment to support microfinance service (MPI, et al., 2012).. 1.3. Microfinance Providers in Laos Microfinance providers in Laos can be categorized into three categories, namely, formal sector, semi-informal, and informal sector.. 1.3.1. Formal Microfinance Sector This sector consists of state-owned commercial banks and microfinance institutions. State-owned commercial banks include Agriculture Promotion Bank and Policy Bank. 政治大 Deposit Taking MFIs (NDTMFIs), 立 and Savings & Credit Unions (SCUs).. (NAYOBY bank). Microfinance institutions include Deposit Taking MFIs (DTMFIs), Non-. ‧ 國. 學. Agriculture Promotion Bank (APB) established on 18/08/1993 under prime minister Degree No: 90/PM, dated 19/06/1993. The purpose of establishing APB was to provide loans. ‧. for farmers, particularly to those who live in the remote areas and have difficulties in accessing. y. Nat. finance. As one of the largest banks in terms of clients and branches, it has the headquarter. sit. located in Vientiane capital with 17 branches and 98 units serving clients all over the nation. n. al. er. io. (Agriculture Promotion Bank, n.d.).. Ch. i Un. v. Policy Bank (NAYOBY bank) which was established on 15/09/2006 under Decree Law. engchi. No: 03/BoL in 2006. Its headquarter is located in Vientiane capital as well, and it has 10 branches all over the nation. Policy Bank has its own special rule for the special purpose of poverty reduction, operating purpose. The state set up Policy Bank to serve 47 poor districts in Laos, it mainly focuses on giving loans with lower interest rates on social economic development. The goal is to turn the natural economy into a market-oriented economy in the field of small-scale agriculture, handicraft, and services in rural areas (NAYOBY bank, n.d.). In the middle of the year 2016, the implementation guidelines were established, with number 01/BOL for DTMFI and NTMFI to implement the decree 460, for the SCUs the regulation number 03. During the period of 2015-2017, the MFIs were blooming rapidly, especially NDTMFI, due to low registered capital of about US $ 25,000. The state concerns. 5 DOI:10.6814/NCCU202000789.

(17) much about this; it therefore issued a notification to stop authorizing a temporary license since 18 May 2017 to ensure effectiveness of the supervision. On the other hand, the degree needs to be improved to ensure the sustainability of the existing established microfinance institutions (MFA, n.d.). The number of microfinance institutions has been increasing significantly. Refer to Figure 1, by the end of 2017, there are 123 MFIs all over the country including 19DTMFIs (24%), 74 NDTMFIs (60%)and 30 SCUs (16%). The majority of NDTMFIs are located in the capital city which accounts for 73.68% (14 MFIs) and the rest were located in other big provinces. The MFIs located outside of the capital city accounts for 26.32% (5 MFIs) only. DTMFIs account. 政治大 most of the SCU‘s locations are in the provinces: 86.67% (26 SCUs). Those 123 MFIs 立. for about half or 51.35% (38 MFIs) of all MFIs are located in the capital city. On the other hand,. microfinance institutions served approximately 247,000 clients with 62,000 active borrowers. ‧ 國. 學. with a total loan amount of about US $88 million (Lao Microfinance Association [MFA], n.d.).. ‧. n. al. y. er. io. sit. Nat. MFIs in Laos (123). 24%. C h16% 60% U n i engchi. v. NDTMFI DTMFI SCU. Figure 1: Type of Microfinance in Laos. 1.3.2. Semi-Formal Microfinance Sector This sector has been supported by both the international organizations and the government through many different channels for more than two decades. Semi-microfinance sectors include village funds, and local authority programs such as Lao Women Union Credits.. 6 DOI:10.6814/NCCU202000789.

(18) Many of the microfinance institutions are developed and shifted from village funds with the technical and financial support from both government and international organizations. The semi-formal microfinance sector saw rapid expansion around the country and also has been playing an important role in terms of poverty reduction. The bank of Lao PDR thus created new regulations for three types of microfinance institution namely Deposit Taking MFIs (DTMFIs), Non-Deposit Taking MFIs (NDTMFIs), and Savings & Credit Unions (SCUs).. 1.3.3. Informal Microfinance Sector This sector includes moneylenders, rotating savings and credit schemes (local people. 政治大 scheme can offer them an emergency financial resource. In the rural area where people find it 立 hard to access to informal financial sources, moneylenders are the very significant financial. known as Houay). Traditionally, Houay is popular among the local people because this kind of. ‧ 國. 學. sources for them even the interest is relatively high (ranging from 5% to 20% per month) because local people have limited choices they can rely on (Seibel and Kunkel, 1999).. ‧. Moneylenders are indeed considered to be illegal, but they are regarded as the first and only. y. Nat. choice for local people when there are no legal channels. In 2014, 60% of adults used. er. io. al. sit. unregulated financial services (world bank, 2018).. n. ADB (2006) conducts a survey on rural finance in Laos. They classified the informal. Ch. i Un. v. finance providers into the following groups: households, moneylenders, and Houay.. engchi. Households made an estimated 217,415 loans to friends and family with about the amount of US$ 38.34 million and 136,159 loans to other households in the same village and other villages. The total estimated loan amount made by households is about US$ 62.2 million and 76% of these are provided by the richest quartile households. Moneylenders make loans to about 25,300 rural households with the estimated amount of US$2.57 million. About 3,100 rural households participated in Houay, rotating savings, or credit schemes; the estimated lending amount to their members is about US$ 1.74 million.. 7 DOI:10.6814/NCCU202000789.

(19) 2. Literature Review and Conceptual Framework 2.1. Literature Review The ability of borrowers in repaying their microcredit loans is an important issue that needs high attention. Borrowers can either make the payment of their loan or decide to default their loan. Borrowers who fail to repay their loan may be voluntary and involuntary (Brehanu and Futa, 2008). Involuntary defaults on borrowed funds may be caused by unexpected situations. For instance, natural disasters and borrowers’ sickness which may lead to the capability of the borrower’s repayment. On the contrary, voluntary defaults, borrowers have the. 政治大. capability to repay the borrowed funds but choose to default because the institution has poor level enforcement mechanisms.. 立. ‧ 國. 學. Most previous research that investigated the determinants of loan default in the microfinance area apply the logistic regression model to identify significant variables. For. ‧. instance, Mokhtar, Nartea, and Gan (2012) investigate the determinants of microcredit loans repayment problem in Malaysia. They find that borrowers' characteristics (age, gender, type of. sit. y. Nat. business) and microcredit loan’s features (mode of repayment, repayment amount) are the. io. er. influential factors contributing to the problem of loan repayment. Nanayakkara and Stewart (2014) conduct a study on gender and other repayment determinants of microfinancing in. n. al. Ch. i Un. v. Indonesia and Sri Lanka. They point out that age has a positive correlation coefficient with the. engchi. dependent variable. Interest rate, agriculture loan and gender (female) also have positive correlation coefficients, but they are not statistically significant. Unexpectedly, the sign of coefficient of training is positive and is significant statistically. Ellis Kofi and Portia (2015) conduct research on the determinants of business loan default in Ghana. They find a positive relationship between extra income, diversion of loan purpose, and multiple borrowing on loan default. On the other side, location or distance between borrower and lending institution are statistically insignificant. Yibrie and Ramakrishna (2017) conduct a study on the determinants of loan repayment performance in ACSI. They find out that sex, age, education level, loan size, interest rate, loan tenure and training are statistically significant affecting loan default. Jote (2018) study on the determinants of loan repayment in Gedeo Zone. He points out that education level, nearness of borrowers to institution and training are the significant variables associated 8 DOI:10.6814/NCCU202000789.

(20) positively with loan repayment whereas family size has a negative relation with loan repayment. Loan size, loan diversion rate and celebrating and participating in social festivals are not statistically significant though. Authors use different statistical methods to find out the influential determinants on repayment performance in the microfinance sector such as Mota, Moreira, and Brandao (2018), they study on determinants of microcredit repayment in Portugal by using an ordered logistic regression (OLR). They conclude that the relationship between educational level, marital status (being married), employment status has a positive sign. Conversely, marital status (being single) has a negative sign on loan repayment performance but it is not statistically significant. Berhanu. 政治大 among small-scale farmers in Ethiopia. The authors employ a two-limit Tobit model in their 立. and Fufa (2008) examine the repayment rate of loans on semi-formal financial institutions. study, they conclude that, total land holding size (for agriculture activities), income from off-. ‧ 國. 學. farm activities affect the loan repayment rate of farmers statistically significant and positively. On the contrary, age, education level, gender and expenditure on festivals variables are. ‧. statistically insignificant. Siaw, Ntiamoah, Oteng, and Opoku study on loan default rate of. sit. y. Nat. microfinance institutions in Ghana 2014, by using correlation and regression to obtain the empirical results, they strongly confirm that schedule of repayment has a positive correlation. io. n. al. er. coefficient, meaning that this factor influences loan repayment significantly. Mwaka (2014). i Un. v. investigated the factors influencing repayment among microfinance loan consumers in Makueni. Ch. engchi. county. He employs inferential statistics, the findings indicate that customers’ literacy, off-farm income and utilization of loan have a positive sign associated with loan repayment. However, a researcher also finds that gender, marital status, repayment duration is statistically insignificant. Muthoni (2016) conducts a study on assessing borrower’s and business’ factors causing microcredit default in Kenya. He uses a multiple regression model and Pearson correlation to establish relationships among the variables, the study reveals that loan diversion, family size, gender(male) have a positive relationship with repayment performance. on the other side, the association between age (older group), marital status (married) and business experience are statistically significant. Muthoni, Mutuku, and Kamau (2017) conduct the study on a comparative analysis of microfinance institutions and financial intermediaries. They apply a 9 DOI:10.6814/NCCU202000789.

(21) multiple regression model and Pearson correlation to find out the association among the variables. The results of the study indicate that loan amount, and loan payment duration have a positive relationship with loan default significantly statistically. Moreover, Adurayemi, Sunday, and Abiola (2019) study Microfinance banks’ loan size and default in Lagos state, Nigeria. The linear regression is the statistical tool of their study to find out the relationship among the variables. The findings show that loan size contributes to loan default significantly. Selvaraj, Karim, Rahman, and Chamhuri (2019) study the determinants of microcredit quality in Malaysia. They apply a static panel technique to examine the relationship among the variables, the result shows that females have a negative relationship but household’s income has a positive. 政治大. relationship on microcredit quality. Overall, the loan repayment performance factors can be categorized into three categories, namely borrower characteristics, loan characteristics and. 立. business characteristics.. ‧ 國. 學. Alternatively, some researchers use different statistical methods to find out the factors that influence loan repayment problems. For example, Korankye (2014) studies cause and. ‧. control of loan default/delinquency in microfinance institutions in Ghana. His research. sit. y. Nat. instrument includes questionnaire and interview guide, he finds that unfavorable payment terms, inadequate loan sizes and lack of training for the clients before and after disbursement are the. io. n. al. er. causes of load default enumerated by the clients. Boateng, Amoah, and Anaglo (2015) also. i Un. v. examine the influence of demographic factors, products and service characteristics of. Ch. engchi. microfinance institutions on microfinance in eastern region, Ghana by using Chi square statistics to assess the relationship between variables. The result reveals that the default rate is higher among males (78%) in comparison with females (51%), in terms of age (ages were categorized into 14-40, 41-60 and 61+), the authors also find that defaulters are younger than non-defaulters on average. The default rate is higher for clients with no formal educational background compared with clients who received formal education, and also the default rate is lower if clients revived training compared to those clients who have not received any training. Murthy & Mariadas (2017) investigate an exploratory study on the factors contributing loan repayment default among the loan borrowers in microfinance institutions in Shah Alam, Selangor. They use a 5-point Likert scale to find out the relationship among the variables, they find that the unit increase in age of borrowers influence the loan repayment default positively. 10 DOI:10.6814/NCCU202000789.

(22) and as the increase of a unit repayment schedule also result to an increase in loan repayment default; however, both variables (age and repayment schedule) are not statically significant.. Table 1: Literature Review (outside of Laos) Topic Repayment rate of loans from semiformal financial institutions among small-scale farmers. 立. Mwaka (2014). Factors influencing repayment among microfinance loan consumers. Findings Total agricultural land holding size, income from off-farm activities affect the loan repayment rate of farmers statistically significant and positively. 政治大 Logistic regression model. Malaysia Sample size: 472. Inferential statistics. Kenya Sample size: 400. Borrower’s characteristic (age, gender and type of business involved) and microcredit loan’s characteristics (mode of repayment, repayment amount) are factors contribute to microcredit loan repayment problem Customers’ literacy, offfarm income and utilization of loan have a positive sign associated with loan repayment. Conversely, gender, marital status, repayment duration is statistically insignificant In Sri Lanka: Time approves and disburses the loan, loan cycle, gender and age, a group/ individual borrower, loan purpose and visiting frequency by the loan officers influence loan payment statically significant. In Indonesia: Only time to approve and disburse the loan, interest repayment. ‧. ‧ 國. Determinants of microcredit loans repayment problem. Context /Sample Ethiopia Sample size: 157. 學. Mokhtar et al. (2012). Theoretical Model Two-limit Tobit model. io. n. Nanayakkara Gender and other and Stewart repayment (2014) determinants of microfinancing. Ch. engchi. Logistic regression model. sit. y. Nat. al. er. Author/ Date Berhanu and Fufa (2008). i Un. v. Sri Lanka & Indonesia Sample size: 1,109. 11 DOI:10.6814/NCCU202000789.

(23) frequency and gender variables influence loan payment statically significant. Siaw et al. (2014). Loan default rate of Correlation microfinance and institutions regression. Ghana Sample size:561. Korankye (2014). Causes and control Descriptive of loan statistic default/delinquency in microfinance institutions. Ghana Sample size: 254. Boateng et al. (2015). The influence of demographic factors, products and service characteristics of microfinance institutions on microfinance. Ghana Sample size:126. Ellis Kofi and Portia (2015). Determinants of business loan default. Muthoni (2016). Assessing borrower’s and business’ factors causing microcredit default Influence of loan characteristics on microfinance default. 政治大. 立. ‧ 國. ‧. n. al. Yibrie and Determinants of Ramakrishna loan repayment (2017) performance. er. io. sit. y. Nat. Muthoni et al. (2017). 學. Chi square statistics. High interest rate and Unrealistic term and schedule of repayment variables have positive correlation coefficient with loan default. Unfavorable payment terms, inadequate loan sizes and lack of training for the clients before and after disbursement are the causes of loan default Default rate is higher among males (78%) in comparison with females (51%). Default rate is higher among males (78%) in comparison with females (51%), higher with clients with no formal educational background and lower with clients who receive training. Influence factors on loan default include Extra income, diversion of loan purpose, and multiple borrowing Loan diversion, family size, gender(male) have a positive relationship with repayment performance. Ghana i v n C hLogistic regression iSample U e n g c h size: 224 model Multiple regression model and Pearson correlation Multiple regression model and Pearson correlation Logistic regression model. Kenya Sample size: 125 Kenya Sample size: 38 India Sample size: 400. Loan amount, loan payment duration have a positive relationship with loan default significantly statistically Sex, age, education level, loan size, interest rate, loan tenure and training factors. 12 DOI:10.6814/NCCU202000789.

(24) Murthy, and Mariadas (2017). An exploratory 5-point study on the factors Likert contributing loan repayment default among the loan borrowers in microfinance institutions. statistically significant affect loan default The unit increase in age of. Malaysia. borrowers influences the loan. repayment. positively. and. increase. of. default as a. the unit. repayment schedule also results an increase in loan repayment. 立. (age. and. repayment. schedule) are not statically. ‧ 國. significant.. Ethiopia Sample size: 364. sit. n. al. er. io. Education level, nearness of borrowers to institution and training are the significant variables associated positively with loan repayment whereas family size has a negative relation with loan repayment. Loan size, loan diversion rate and celebrating and participating in social festivals are not statistically significant though The relationship between educational level, marital status (being married), employment status has a positive sign. Conversely, marital status (being single) has a negative sign on loan repayment performance but it is not statistically significant. y. Logistic regression model. ‧. Determinants of loan repayment. Nat Mota et al. (2018). however, both variables. 學. Jote (2018). 政治大. default;. Determinants of microcredit repayment in Portugal. Ch. engchi. Ordered logistic regression (OLR).. i Un. v. Portugal: Sample size: 752. 13 DOI:10.6814/NCCU202000789.

(25) Adurayemi et al. (2019) Selvaraj et al. (2019). Microfinance banks’ loan size and default Determinants of microcredit quality. Linear regression. Nigeria Sample size: 182 Static panel Malaysia technique Sample size: 80. Loan size contributes to loan default significantly. Females have a negative relationship but household’s income has a positive relationship on microcredit quality. In Laos, recently, there are many authors study determinants of loan default in the area of microfinance in different countries by using both quantitative and qualitative methods to obtain the relationship among the variables. In recent years, there are also some empirical studies about. 政治大. microfinance in Laos (Table 2). For instance, Sayvaya (2012) conducts a study on does. 立. microfinance reduce poverty in Laos. Phonesavanh (2015) studies on the impact of. ‧ 國. 學. microfinance on poverty reduction in Oudomxay, Northern province, Laos. Chansathith et al. (2011) discuss Should Microcredit B a Right for the Poor? Credit Demand of Poor Households. ‧. in Laos. Chaleunsinh et al. (2015) conduct a study on an Analysis on Borrowing Behavior of Rural Households in Vientiane Municipality.. y. Nat. io. sit. We can conclude that most of the studies about microfinance in Laos focus on the impact. n. al. er. of microfinance on defaults. There is no empirical research on the determinants of loan defaults.. i Un. v. Hence, we conduct this study to investigate the determinants of loan defaults in the. C microfinance institutions in Laos. h. engchi. Table 2: Literature Review (in Laos) Author/ Date Chansathih et al. (2011). Topic Should microcredit be a right for the poor? credit demand of poor households in Laos. Theoretical Model Probit and Tobit model. Context /Sample Laos Sample size: 684. Findings Poorer households are more likely to be borrowers, the ratio of labor on household members is less likely to have correlation with credit demand. The poor who are non-farm self-employed tend to borrow and ones who work in non-farm wage/salary paid are less likely to have a demand for loan.. 14 DOI:10.6814/NCCU202000789.

(26) Sayvaya (2012). Does Microfinance Reduce Poverty in. Ordinary Least Square. Laos Sample size: 361. Phonesavah (2015). Impact of microfinance on poverty reduction. Fixed-effect model. Laos Sample size: 381. 立. ‧ 國. Laos, Vientiane. Sample size: 684.. ‧. An analysis on A structured borrowing questionnaire behavior of rural households in Vientiane municipali. 學. Chaleunsin h et al. (2015). 政治大. n. al. er. sit. y. Nat. io. Village Development Funds program does not have significant impact on outcome as household income, expenditure and saving A highly positive and significant effect of microfinance loans on household yearly income and expenditure over the years. Difference and change in household yearly income and expenditure between member and non-member are totally large over the years Formal banks provide loans exclusively for production purposes, while informal lenders do for coping with emergencies. Savings groups fall between them. Though poor households are reluctant to be a savings group member but rich households actively participate in the group. For saving group’s members, nearly 40% of the loans use for product i on purpos es specially in agriculture.. Ch. engchi. i Un. v. 2.2. Conceptual Framework This section presents a conceptual framework of determinants affecting loan payment performance. It assesses the research variables derived from literature to test whether there are significant associations diagrammatically between dependent variable and independent variable. This study adopts the conceptual framework Jote (2018) to demonstrate the relationship between loan dependent variable (loan repayment) and the independent variables which demonstrates in Figure 2.. 15 DOI:10.6814/NCCU202000789.

(27) Borrower’s characteristics: age, gender, education, marital status, and family member who earn the living.. Borrower's financial conditions: no agriculture land holding, agriculture land value, employment status, livestock, land size, and additional income (remittance).. 政治大. 學. ‧ 國. 立. Loan Repayment. ‧. Culture: expenses on festivals less than 1million LAK, and loan diversion rate.. sit. y. Nat. n. al. er. io. Loan features: agriculture loan, construction loan, loan size, and loan period. Ch. engchi. i Un. v. (Dependent Variable). Others: commute time to financial institution office, loan from moneylender, and training.. (Independent Variables) Figure 2: Conceptual Framework of the Study. 16 DOI:10.6814/NCCU202000789.

(28) 3. Village Bank and SCU Champa Phatthana 3.1. Village Bank Organizational Structure Figure 3 presents an Organizational Chart of a Village Bank. The village bank consists of three bodies: the general assembly of the member, the village bank committee, and the village bank advisors.. SCU Champa Phathana. 政治大. 立. Frame regulations Takes decisions Elects committee and advisors. Nat. n. Ch. Village Bank Advisor -. engchi. er. io. al. Representation Day-to-day management. sit. y. ‧. ‧ 國. 學. Member Assembly -. Village Bank Committee -.  Set up and Supervision of VB  Representation & Coordination  Financial Services. Internal control Problem Solving. i Un. v. Compulsory & Voluntary Savings Microcredits. Figure 3: Village Bank Organization Structure. 3.1.1. General Assembly of Members The general assembly is the main governing body of the village bank that consists of all members of the village bank. Assembly meetings are held at least once per year. Its decisions are made by a simple majority of the present members on the following issues:. 17 DOI:10.6814/NCCU202000789.

(29) a. To approve or reject the annual village bank report that was prepared by the village bank committee. b. To agree on profit distribution, normally depositors receive at least 60%, the allowance payment to the village bank committee at least 4%, but not more than 20%, the general reserve and any other purposes that the assembly might agree upon. c. To decide on actual savings and lending conditions, such as minimum monthly savings rate, savings ceiling, loan purposes, loan interest rates, maximum loan ceilings, maximum loan terms, loan collateral requirements and the introduction of new loan and savings products. d. To elect the village bank Committee by ballots and to confirm or reject the appointment of. 政治大. village bank advisors and also to dismiss individual members or the whole village bank committee.. 立. e. To decide on other changes to the VB bylaws not covered in financial product conditions,. ‧ 國. 學. including its key operational policies.. 3.1.2. Village Bank Committee (VBC). ‧. The VBC is elected by the general assembly to be in charge of the general administration of the VB such as savings and credit operating and any other things related to village banks.. Nat. sit. y. The number committee normally depends on the size of the village bank. It usually has 4-6. al. n. following responsibilities:. er. io. members and at least 2 members of such a committee must be female. The VBC has the. Ch. i Un. v. a. To organize regular (minimum monthly) village bank operating days and to accept and. engchi. register new members according to membership conditions. b. To promote and to inform members about the village bank’s objectives and operations. c. To collect and manage the savings of the members and carry out loan appraisal, disbursement and follow-up. d. To manage and safeguard the village bank’ assets including its cash stock and its external accounts with SCU Champa Phatthana.. 3.1.3. Village Bank Advisor Village bank’s advisors consist of at least two village bank advisors. They are confirmed by the general assembly upon selection by the village and local village administration. The. 18 DOI:10.6814/NCCU202000789.

(30) advisors are usually highly respected representatives and they responsible for the following tasks: a. To support the VBC in case of disagreement or in case of problems, like repayment problems. b. To control and monitor the VBC whether the village bank is operating according to its mission, its statutes and comply with village bank bylaw. c. To attend the meeting regularly to keep themselves well-informed about village bank operations.. 3.1.4. Financial Services of Village Bank. 政治大 Figure 4 illustrates an overview of operating mechanisms of a village bank system. 立 Firstly, members save money at the village bank. Next, those savings are used to make loans. ‧ 國. 學. to members. Then, interests and repayments are paid to the village bank by borrowers. Finally, dividends are distributed to members.. n. al. sit er. io Saving. y. ‧. Nat. Credit. Ch. engchi. i Un. Village Bank. Borrowers. v Interest. Repayment. Dividend Member Figure 4: Operating Mechanisms of the Village Bank System. 19 DOI:10.6814/NCCU202000789.

(31) a. Village bank set the minimum amount of compulsory savings at around 10,000 LAK (approximately $US1.25) per account. Compulsory savings are to make members come to use VB service regularly and to increase the village bank’s capital. b. Village bank accepts unlimited voluntary savings from its members because the savings increase the village bank’s capital for credit disbursement. If there is a demand for credit, a village bank would encourage savings actively. All types of savings can be withdrawn during the service day or in the urgent circumstances outside of the service day. c. Even though both village bank and traditional bank’s profits are mainly generated through. 政治大. its credit lending activity, the return on savings of village banks is not a fixed interest rate like commercial banks. Members of village banks receive return on savings once a year in. 立. terms of dividends. Dividends are calculated based on an average annual savings balance. ‧ 國. 學. and how much saving members can get. They are also based on how great the village bank could perform. Village banks paid to its members about 15.70% dividends on average (SCU. ‧. annual report, 2018).. sit. y. Nat. d. Village bank loan is normally disbursed in a bullet loan form with monthly interests’ payment, and the principal repayment is due at the end of the loan contract. Borrowers can. io. n. al. er. opt to pay back their loans earlier than their contracts’ maturities. The following table. i Un. v. represents the typical credit conditions which are usually set in the first year. Village bank. Ch. engchi. members can vote to change the conditions at the annual meeting in following years. e. Technically, there are 8 types of loan in the village bank and all village banks under the support of SCU Champa Phatthana have these 8 different loans (Table3). However, the interest rate, loan period and loan ceiling of the village bank can be set differently by each village, and they are set during the annual general meeting of each village bank. Technically, the interest should be in the range that is recommended by the staff from SCU Champa Phathana. The majority of the village banks set the lending period to be within one year. We cannot compare the interest rate charged by village bank and commercial bank because they are different in loan sizes and operating costs per client. The interest income charged from clients will be distributed in the form of dividend to village banks’ clients (if village bank has profit) at the end of business years.. 20 DOI:10.6814/NCCU202000789.

(32) Table 3: Types of Loans and their Terms Interest rate Loan Period Loan Loan type. (month). (month). Ceiling. (US$). Emergency. 1.0%. 5. 560. House (build/ improve). 1.5%. 12. 1,130. Consumption. 2.0%. 6. 560. Agriculture production (crops). 2.5%. 10. 1,130. Agriculture Production (livestock). 2.5%. 10. 2,260. Non- agriculture -production. 2.5%. 12. 2,260. 12. 5,640. 12. 1,670. Trading Other / services. 立. 2.5% 政治 2.0% 大. ‧ 國. 學. 3.2. Brief of the Saving and Credit Union Champa Phatthana. ‧. SCU champa phatthana is located in Soukhouma district, Champasack Province, the southern part of Laos. Champasack is one of the biggest provinces in Laos which has 649,023. Nat. sit. y. inhabitants. The province consists of 10 districts, 643 villages, 121,865 households (of which. al. er. io. 775 households or 6.35% are poor households). In 2018, GDP growth of this province is 8%. n. and GPD per capita is US$ 3,153. Service sector is the biggest component of GPD which. Ch. i Un. v. accounts for 54.16%, followed by industry 22.94% and agriculture 22.96%. The fastest growing. engchi. sector is service, industry and agriculture with the growth rate at 13.64%, 2.60% and 2.53%, respectively (Champasack Province Statistic Center, 2018). Microfinance in Rural Areas - Access to Finance for the Poor (AFP) was established in 2009 and has been supporting the development of village banks in the Laos since its establishment. AFP has been operating its activities in 6 provinces and 21 districts. AFP is implemented by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, commissioned by the German Federal Ministry of Economic Cooperation and Development (BMZ), and co-financed by the Australian Department of Foreign Affairs and Trade or DFAT. In August 2013, AFP expanded its project to Champasack province and established the Network Supporting Organization (NSO) to start establishing village banks. It started in 21 DOI:10.6814/NCCU202000789.

(33) Soukhouma district and then continued to expand to Monlapamok district in the following month. to Champasack district in 2016, and to Pathoumphone district in 2019. In March 2016, the Annual General Meeting founded the Saving and Credit Union Champa Phatthana (SCU Champa Phatthana/SCU) that replaced the NSO. In September 2016, SCU Champa Phatthana officially received a full bank license from the bank of Lao PDR and an enterprise license from the department of industry and commerce, Champasack province. On September 27, 2016, SCU was officially opened (SCU Champa Phatthana annual report, 2017). According to SCU Champa Phatthana 2017 annual report, SCU’s core business is supervising the activities of the VBs. The supervisions are categorized into two categories. 政治大 building, SCU provides various training for VBCs such as training on bookkeeping, fraud 立. including technical support on capacity development and financial services. For capacity. prevention, credit and delinquency management, peer-to peer exchange, responsible lending. ‧ 國. 學. and also on-job-coaching. SCU also provides training for VB members in various topics like financial literacy, responsible borrowing.. ‧. Another key core activity offered to VBs is financial service. If village banks have more. y. Nat. sit. savings, they can deposit these with the SCU and get the interest comparable to the commercial. al. er. io. bank rate. One the other side, if they do not have enough capital to disburse loans to their. n. members, they can get loans from SCU. Additionally, SCU offers syndicated loans to village. Ch. i Un. v. bank clients in case the credit amount exceeds the ceiling of the village banks (SCU Champa Phatthana annual report, 2017).. engchi. Through the above business model, SCU was able to cover its expenses by December 2017 without any financial support from donors. SCU’s main expenditure includes salary, capacity development for SCU’s staff, VBCs, and VB members, and interest payments to village banks. On the other side, SCU’s revenues mainly come from service fees based on the outstanding loans of the village banks. These fees are collected on a monthly basis when staff from SCU go to the village to support the village bank activities. SCU also generates its revenue from the interest of disbursed loans to village banks. (SCU Champa Phatthana annual report, 2017). 22 DOI:10.6814/NCCU202000789.

(34) Within half a decade, the village banks have growth significantly in terms of the number of members and the business size. By the end of December 2019, there are 165 village banks under SCU’s supervision. These village banks have 812 village bank committee members (39% are females) who serve 25,221 members, and approximately 77% of the total households in those 165 villages are members of village banks. Total savings of all village banks are about US$8,935,000 and credits outstanding are about US$ 7,170,000; the total number of loans outstanding is 8,633 and the credit overdue is around 2.05% (SCU Champa Phatthana annual report, December 2019). The Annual General Assembly (AGM) of members is the highest body of a Savings and. 政治大 of directors. The rights and responsibilities of AGM include to hear the board of directors 立. Credit Union. The AGM of members is held at least once per year by the decision of the board. (financial statements, budget and action plan for the upcoming year), to hear the report of the. ‧ 國. 學. auditor, to approve the distribution of dividends and the reserves, to elect or remove members of the board of directors, and to authorize the board of directors to perform a special task.. ‧. Additionally, AGM also elect the credit and audit committee.. y. Nat. sit. The board of directors are elected or removed by AGM which has the following. al. er. io. responsibilities: to report the activities of the SCU Champa Phatthana, to propose the profit. n. distribution, to appoint the chairman of the board of directors, to appoint and dismiss or remove. Ch. i Un. v. the manager, to decide the objectives and business strategies, to approve business plans and to. engchi. fulfil other rights and responsibilities as defined in the bye-laws of SCU Champa Phatthana. The rights and responsibilities of the manager include managing and deciding all matters of the business within the range assigned by the board of directors, representing the SCU Champa Phatthana in contacts and contractual dealings, recruiting or dismissing personnel, implementing the payroll, personnel beneficial package as approved by the Board of Director, awarding and promoting personnel or applying disciplinary sanctions against offenders, performing other rights and responsibilities assigned by the board of directors. The manager has a deputy manager and the manager assistant to help him on different tasks. Another important person is the development advisor. SCU Champa Phatthana has always been receiving technical support from at least one development advisor who works in 23 DOI:10.6814/NCCU202000789.

(35) the office of SCU Champa Phatthana, and he is hired by the German Federal Ministry of Economic Cooperation and Development (BMZ). A technical advisor always works closely with the management team on the important tasks. For instance, strategic business planning, developing and implementing new policies, setting up a quality control system, setting up a benefit package for personnel, implementing the MIS system and so on. SCU Champa Phatthana’s business covers 4 districts. Soukhouma district, Monlapamok district, Champasack districtand Pathoumphone district (Figure 5). Each district has their own district manager who is mainly responsible for the performance of the village banks in their own responsible district and they have their own field stuff under his/her supervision.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i Un. v. Figure 5: Organization Chart. 24 DOI:10.6814/NCCU202000789.

(36) 4. Methodology 4.1. Research Approach In this paper, there are two types of research approaches we use in order to solve the research problem which include the qualitative and the quantitative approaches. We use the quantitative method to test research hypotheses and qualitative research to uncover trends in thought and opinions that related to the research problem.. 4.2. Data Source and Type One of the significant features of research is the decision making about to collect the. 政治大. research data, from and in what ways the data should be collected. In this study, we use both primary and secondary data.. 立. For the primary data, the researcher uses a questionnaire as the main tool for collecting. ‧ 國. 學. data for the analysis. The questionnaires of this research include both close and open-ended questions. We prepare the questionnaires in English first before translating to Lao and we also. ‧. conduct a pre-tested by the pilot study before conducting the survey for the whole sample.. y. Nat. Additionally, we conduct qualitative data through semi-structured, face to face interviews with. sit. field staff/village bank consultant, manager and development advisor of the Saving and Credit. n. al. er. io. Union Champa Phatthana in order to get an in-depth understanding of the problem. For the. i Un. v. secondary data, the materials include microfinance history, and the number of microfinance institutions and its clients.. Ch. engchi. 4.3. Target Population The population for this research is borrowers of the village banks under the support of the Saving and Credit Union Champa Phatthana (SCU). The target group includes both defaulters and non-defaulters of the village banks’ clients.. 4.4. Model Specification Loan repayment is a dependent variable, while different borrower’s characteristics, borrower's financial conditions, culture, loan features, travelling time from SCU office to clients and borrower’s experience with moneylenders are the independent variables. In this research, the dependent variable assumes values 0 and 1, which is 1 is a defaulter and 0 if the borrower. 25 DOI:10.6814/NCCU202000789.

(37) is a non-defaulter. Consequently, we treat loan repayment as a dichotomous dependent variable and a non-continuous dependent variable which does not fit the key assumption in the linear regression analysis. Statistically, logistic regression or logit model is a regression model where the dependent variable(DV) is categorical that the output can take only two values, “0” and “1”. For example, the outcome can be pass/fail, win/loss, default/non-default. However, there are some cases where the dependent variable has more than two outcome categories, researcher may use multiple logistic regression, or if the multiple categories are in order, researcher may apply the ordinal logistic regression to analyze the data.. 政治大 outcomes but the logic model is the best fit for this study because the logit model best fits the 立 Even though there are several methods we can use to analyze the data involving binary. non-linear relationship between the dependent and independent variables and it has only two. ‧ 國. 學. outcomes. Moreover, a logistic model has its simplicity of calculation and its probability lies between 0 and 1. The probability comes near zero indicates an unlikely event or the value of. ‧. the explanatory variable gets smaller and the probability near 1 indicates a likely event or the. sit. y. Nat. value of the explanatory gets larger, (Jote, 2018).. io. er. David Cox is the statistician who developed the logistic regression in 1958. The binary logistic model is used for the estimation of probability of a binary response based on one or. n. al. Ch. i Un. v. more predictors (variables). It allows one to say that the present of a risk factor increases the. engchi. odds of a given outcome by a specific proportion. Since the dependent variable of this research (loan repayment) has binary outcomes (defaulter and non-defaulter); hence, in this the binary logistic regression is the best fit for this study. The analysis of determinants of the loan repayment problem uses a binomial logistic model, interest lies primarily in the response probability. 𝑃(𝑦 = 1|𝜒) = 𝑃(y = 1|𝑥1 , 𝑥2 … , 𝑥𝑘 )|. (1). 𝑃(𝑦 = 1|𝜒) is the probability that y=1(defaulting) given x (independent variable), y represents loan repayment and X denote the full set of explanatory variable that include. 26 DOI:10.6814/NCCU202000789.

(38) borrower’s characteristics, borrower's financial conditions, culture, loan features, travelling time between borrowers and MFI and loan from moneylenders. 𝑃(𝑦 = 1|𝜒) = 𝐺(𝛽0 + 𝛽1 , 𝑥1 … + 𝛽𝑘 , 𝑥𝑘 ) = 𝐺(𝛽0 + 𝑥𝛽). (2). where G is a function taking on values strictly between zero and one: 0 <G(z)<1, for all real numbers z. This ensures that the estimated response probabilities are strictly between zero and one. We write 𝑥𝛽 = 𝛽1 𝑥1 + ⋯ + 𝛽𝑘 𝑥𝑘 . Logistic function is a non-linear function used for the function G in order to make sure that the probabilities are between zero and one. In the logit model, G is the logistic function which is between zero and one for all real numbers z. This is the cumulative distribution function for a standard logistic random variable.. 立. 政治 𝐺(𝑧)大= exp(𝑧) /[1 + exp(𝑧)]. (3). where Z = X𝛽= 𝛽1 , 𝑥1 … + 𝛽𝑘 , 𝑥𝑘 . The goal of a logistic model is finding the best fitting (yet. ‧ 國. 學. biologically reasonable) model to describe the relationship between the dichotomous characteristic of interest (dependent variable or outcome variable) and a set of independent. ‧. (predictor) variables. Logistic regression generates the coefficients (and its standard errors and significance levels) of a formula to predict a logit transformation of the probability of presence. Nat. Logit(p) = 𝛽0 + 𝛽1 𝑥1 + 𝛽2 𝑥2 … + 𝛽𝑘 , 𝑥𝑘. n. al. er. io. sit. y. of the characteristic of interest.. i Un. v. Logit(P) can be transformed back to p by the following formula: -. Ch. engchi. When one binary variable and one independent variable is included: 1. P(Y) = 1+𝑒 −(𝛽0+𝛽1 𝑥1) When one binary variable and several independent variable is included in the study:. 𝑒 𝛽0 +𝛽1 𝑥1 +𝛽2 𝑥2 …+𝛽𝑛 ,𝑥𝑛. P(Y)= 1+ 𝑒 𝛽0+𝛽1 𝑥1+𝛽2 𝑥2…+𝛽𝑛 ,𝑥𝑛 where, P(Y) is probability of Y occurring, e is natural logarithm base (e≈2.71828), 𝛽0 is interception at y-axis, 𝛽𝑛 is regression slope coefficient of 𝑥𝑛 , 𝑎𝑛𝑑 𝑥𝑛 is a predictor or independent variable that predicts the probability of Y. P(Y). =. 𝑒 𝛽0 +𝛽1 𝐺𝐷+𝛽2 𝑀𝑆+𝛽3 𝐴𝐺+ 𝛽4 𝐸𝐷𝑈+𝛽5 𝐹𝑀𝐿+𝛽6 𝐸𝑆+𝛽7 𝐸𝑆+𝛽8 𝐶𝑇+𝛽9 𝐴𝐿𝑃+𝛽10 𝑁𝐴𝐿+𝛽11 𝐿𝑆 1+𝑒 𝛽0 +𝛽1 𝐺𝐷+𝛽2 𝑀𝑆+𝛽3 𝐴𝐺+ 𝛽4 𝐸𝐷𝑈+𝛽5 𝐹𝑀𝐿+𝛽6 𝐸𝑆+𝛽7 𝐸𝑆+𝛽8 𝐶𝑇+𝛽9 𝐴𝐿𝑃+𝛽10 𝑁𝐴𝐿+𝛽11 𝐿𝑆. 27 DOI:10.6814/NCCU202000789.

(39) ++𝛽12 𝐿𝑃+𝛽13 𝐿𝐷𝑅𝐹𝑇+𝛽14 𝐴𝐿𝑃+𝛽15 𝐶𝐿+ 𝛽16 𝐴𝐼+𝛽17 𝐿𝑀+𝛽18 𝑇𝑁+𝛽19 𝐿𝑆𝑃𝐹𝑀+𝛽20 𝐿𝐴𝑃𝐹𝑀 ++𝛽12 𝐿𝑃+𝛽13 𝐿𝐷𝑅𝐹𝑇+𝛽14 𝐴𝐿𝑃+𝛽15 𝐶𝐿+ 𝛽16 𝐴𝐼+𝛽17 𝐿𝑀+𝛽8 𝑇𝑁+𝛽19 𝐿𝑆𝑃𝐹𝑀+𝛽20 𝐿𝐴𝑃𝐹𝑀. (4). 4.5. Description and Measurement of Variables Referring to the theoretical and literature, traditional observable characteristics about the factors that may affect the probability of loan payment performance, we can summarize in the following table. Table 4: Variable Descriptions Variable. Symbol. Expected sign/Hypotheses. 政治大. Dependent variable. io. Education EDU Family member who earn the living FML. n. al. Employment status. ES. - (Higher age, low probability of default). y. AG. + (Widowed, high probability of default). sit. ‧ 國. MS. Nat. Age. GD. Explanatory variable + (If head of household is male, lower probability of default). ‧. Marital status. 立. 學. Gender (male). LP. - (High education, low probability of default) - (More members who earn the living, low probability of default). er. Loan default. Ch. engchi. i Un. v. Agriculture land value. ALV. Land holding. NAL. - (Government staff, low probability of default) + (High expenses on festivals, high probability of default) + (More commute time to financial institution, high probability of default) - (High value of agriculture land holding, low probability of default) + (No agriculture land holding, high probability of default). Loan size. LZ. + (Higher loan size, high probability of default). Loan period. LP. (+/-) The probability of default can be both signs. Expenses on festivals EF Commute time to financial institution office CT. 28 DOI:10.6814/NCCU202000789.

(40) Loan diversion rate. LDR. - (Higher loan diversion rate, low probability of default). Agriculture loan. ALP. + (Agriculture loan, high probability of default). Construction loan Additional income (remittance). CL. + (Construction Loan, high probability of default). AI. - (Additional income, low probability of default). Training. TN. - (Obtain training, low probability of default). Livestock. LSPFM. - (High livestock value, low probability of default). Land size. LAPFM - (More land size, low probability of default). 立. 4.6. Questionnaire. 政治大. ‧ 國. 學. Purpose of the Survey. Mr. Morxay Vongnakhone works for the Saving and Credit Union Champa Phatthana.. ‧. He is currently pursuing his master’s degree in Taiwan and conducting this survey for his. sit. y. Nat. graduation thesis. This survey will be very useful not only for the graduation purpose but also for the Saving and Credit Union Champa Phatthana in terms of policy making and service. io. n. al. er. improvement to its village bank clients. Your input will be protected and used for study purpose solely.. Ch. engchi. i Un. v. The interview will be conducted with the head of the household or his/her representative who is a member (beneficiary) of the Village bank.. General Information Province: Champasack……………………………... District: ……………………………………………. Village: ……………………………………………. Name of Client: …………………………………. Book Account Number: …………. 29 DOI:10.6814/NCCU202000789.