Households Access To Informal Rural Credit- An Analysis From Vhlss 2008.Pdf

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM NETHERLANDS PROGRAMME FOR M A IN DEVELOPMENT ECONOMICS HOUSEHOLD ACCESS TO INFORMAL RURAL[.]

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS HOUSEHOLD ACCESS TO INFORMAL RURAL CREDIT: AN ANALYSIS FROM VHLSS 2008 By LE ANH THU MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, August 2012 UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS HOUSEHOLD ACCESS TO INFORMAL RURAL CREDIT: AN ANALYSIS FROM VHLSS 2008 A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LE ANH THU Academic supervisor: Dr LE VAN CHON HO CHI MINH CITY, August 2012 ACKNOWLEDGEMENT This thesis would not have been accomplished without the kind assistance and enthusiastic guidance of several individuals who have in one way or another contributed toward to the formation and fulfillment of this paper First of all, I would like to express my utmost gratitude to Dr Nguyen Trong Hoai and Dr Pham Khanh Nam for sharing their practical profound insights and steadfast encouragement in term of theoretical literature and techniques that are helpful to this study I would like to express my special thanks to Dr Tran Tien Khai and Dr Ha Thuc Vien who have inspired initiatives and passion of rural credit in me to carry out this interesting study I would like to express my deep and sincere gratitude to Dr Le Van Chon for his scientific guidance, patient encouragement and invaluable advice, which he has provided throughout the time of preparation and accomplishment of this paper I sincerely would like to thank all my loved classmates in class MDE17 and staff in the VNP office, who always give me their restless assistance when I was in trouble; especially Nguyen Thi Thuy Thanh, Dinh Thi Thu and Phan Thach Truc for creating motivation for me due to their brilliant talent I would like to express my special massive thanks to my bosses MA Nguyen Duc The and Mrs Van Thi Le who have given me opportunities and spiritual assistance to accomplish this study Last but not least, I must express my most gratitude to my parents and my wife, Bui Thi Thanh Thuy, for their enduring understanding and spiritual assistance which help me overcome the hard times [i] ABSTRACT It is said that credit is the essential source to finance production and consumption expenditures in rural provinces in Vietnam It also plays a critical role in poverty alleviation, livelihood diversification and in reducing household vulnerability Although credit contributes substantially to the rural development, household access to credit sources has not been given proper attention The purpose of this paper is to examine household access to informal financial markets in Vietnamese rural areas It applies the theoretical framework of asymmetric information to investigate the rural credit markets in Vietnam This paper explores determinants that influence loan amounts borrowed by rural households from the informal sources using the Heckman two-step model and the data in the Vietnam Household Living Standard Survey which was carried out in the year 2008 It is found that household expenditure, household assets and number of working earners strongly and positively impacts on probability of credit access; gender of household head highly negatively influence credit accessibility Notwithstanding, informal loan appears almost in household’s activities for both consumption and production purposes, they still mainly rely on relationship of friends and relatives rather than fully make use of informal credit institutions and other sources Key words: Informal rural credit; cross section; Heckman model; VHLSS 2008; Vietnam [ ii ] TABLE OF CONTENTS ACKNOWLEDGEMENT i ABSTRACT ii CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objectives 1.3 Research questions 1.4 Justification of the thesis 1.5 Organization of the thesis CHAPTER 2: LITERATURE REVIEW 2.1 History and origin of the rural credit 2.2 Theoretical review of rural credit markets 2.2.1 The theory of monopoly 2.2.2 Asymmetric Information 2.2.3 Indirect screening mechanism 2.2.4 Direct screening mechanism 10 2.3 Empirical studies 11 2.4 Conceptual framework 19 2.5 Chapter summary 22 CHAPTER 3: DATA AND RESEARCH METHODOLOGY 24 3.1 Background of rural credit markets in Vietnam 24 3.2 Data 28 3.3 Research methodology 29 3.3.1 Descriptive analysis 29 3.3.2 Econometric model 29 3.4 Chapter summary 32 CHAPTER 4: ANALYSIS RESULTS 34 4.1 Rural credit markets 34 4.2 Intention of loans 35 4.3 Different loan amounts analysis 36 4.4 Descriptive statistical analyses 38 4.4.1 Univariate analysis 38 [ iii ] 4.4.2 Bivariate analysis 39 4.4.2.1 The nexus of loan amount and age of household head 40 4.4.2.2 The nexus of loan amount and gender of household head 41 4.4.2.3 The nexus of loan amount and education of house head 41 4.4.2.4 The nexus of average loan amount and number of dependents 42 4.4.2.5 The nexus of average loan amount and number of adults 43 4.4.2.6 The nexus of average loan amount and expenditure 44 4.4.2.7 The nexus of loan amount and total value of asset 44 4.4.2.8 The nexus of average loan amount and expense on livestock 45 4.4.2.9 The nexus of average loan amount and cultivated areas 46 4.5 Empirical results 47 4.6 Chapter summary 51 CHAPTER 5: CONCLUSIONS & POLICY IMPLICATIONS 53 5.1 Conclusions 53 5.2 Policy implications 54 5.3 Limitations and directions for further studies 55 5.3.1 Limitations 55 5.3.2 Directions for further studies 55 REFERENCES 57 APPENDICES 60 [ iv ] LIST OF TABLE Table 2.1: Early empirical studies on rural credit 15 Table 3.1: Sample size by region 22 Table 3.2: List of variables 32 Table 4.1: Status of household’s access to rural credit markets 34 Table 4.2: Loan distribution over financial sources 35 Table 4.3: Loan distribution over loan intention 36 Table 4.4: Different amount of loan on rural markets 37 Table 4.5: Different loan amount on the informal sector 38 Table 4.6: Univariate analysis 39 Table 4.7: The Heckman two-step model for informal loan amount 47 [v] LIST OF FIGURES Figure 2.1: The vicious circle of poverty Figure 2.2: Unorganized financial markets in LDCs Figure 2.3: Monopoly & competitive markets Figure 3.1: Rural loan in the formal sector 25 Figure 3.2: Rural loan in the semi-formal sector 26 Figure 3.3: Rural loan in the informal sector 27 Figure 3.4: Sample size 29 Figure 4.1: Gender of household heads 39 Figure 4.2: The nexus of average loan amount and age of household head 40 Figure 4.3: The nexus of average loan amount and gender of household head 41 Figure 4.4: The nexus of loan amount and education of household head 42 Figure 4.5: The nexus of average loan amount and number of dependents 43 Figure 4.6: The nexus of average loan amount and number of adults 43 Figure 4.7: The nexus of average loan amount and expenditure 44 Figure 4.8: The nexus of loan amount and total value of asset 45 Figure 4.9: The nexus of loan amount and expense on livestock 45 Figure 4.10: The nexus of loan amount and cultivated areas 46 [ vi ] ABBREVIATION CCF: The Central Credit Fund LDCs: Less developed countries GSO: The General Statistics Office of Vietnam HH: Household ROSCAs: Rotating Savings and Credits Associations OLS: Ordinary Least Squares PCFs: The People’s Credit Funds SBV: The State Bank of Vietnam VBARD: The Vietnam Bank of Agriculture and Rural Development VBP: The Vietnam Bank for the Poor (formerly) VBSP: Vietnam Bank for Social Policies VFA: The Vietnamese Farmers’ Association VHLSS: Vietnam Household Living Standard Survey VWU: The Vietnamese Women’s Union WB: The World Bank [ vii ] CHAPTER 1: INTRODUCTION 1.1 Problem statement The absence of formal credit sources for the rural household is a critical constraint to agricultural development in many developing countries It is due to information asymmetry in the relationship of lenders and borrowers leading to problems of adverse selection and moral hazard (Stiglitz & Weiss, 1981), (Jung, 2000); the consequence is often that the rural lending is perceptibly undetermined Moreover the imperfect information appears in many government policies supporting credit for rural households The formal credit does not satisfy demand for financing projects or expenditure (George & James, 2010) In addition, formal institutions respond late to small loan amount (Lipton, 1976) Therefore, borrowers seek credit in the informal sector (private moneylender, parents, relatives, friends, etc.) to satisfy their production and consumption (Pham & Izumida, 2002), Mpuga (2010) The poor household in rural areas inevitably relies mainly on the expensive informal credit to finance their production, expenditure, tuition fee, wedding, funeral etc; for that reason informal credit plays a crucial role in rural development with evidences from (Adams & Graham, 1981), (George & James, 2010) The operations of informal financial sectors are concerned with many diversified aspects including the supply of rural formal credit market is not able to satisfy the growing demand of rural households and many borrowers turn to informal credit markets for their production and consumption needs (Takashi, 2009); almost characteristics of the rural farm households are risky and uncertainty, usually dealing with small scale of debt, while the supply of the formal sector often concentrates on large scale projects (Barslund & Tarp, 2008), (Takashi, 2009); transaction cost of the formal credit is higher than the cost implied so informal lenders provide financial services with the competitive cost (Adams & Graham, 1981), (Guirkinger, 2008), (Mpuga, 2010) [1] CHAPTER 3: DATA AND RESEARCH METHODOLOGY Literature review and conceptual framework of rural credit have been reviewed in the previous chapter The Vietnamese financial system has experienced with formal sector, semi-formal sector and informal sector Each sector reveals its contribution to different aspects of the picture of rural credit in Vietnam This chapter presents an overview of rural credit market in Vietnam, data used for this study and research methodology 3.1 Background of rural credit markets in Vietnam Before Doi Moi in 1986 in Vietnam, the State Bank of Vietnam (SBV) was the solitary credit provider This bank played a role as either a central bank or a commercial bank In this period, with the association of the SBV, credit cooperatives intensively handled the credit needs of individuals, cooperatives and communes Rural credit needs existed but at the cooperative level rather than the household level since a cooperative was the smallest unit of production and management After Doi Moi, the household was introduced as an unit of agricultural production; and economic reforms policies were implemented to spur developement of social economics in general and financial sector in particular The household credit demand has risen sharply In order to catch up the movement of commercial and financial activities, the SBV was divided into two state owned commercial banks: (i) the Agricultural Development Bank, and (ii) the Commercial Bank of Vietnam However, these banks served only state owned enterprises; in addition, the credit needs of farmers and rural households were still neglected This result led towards a growth of credit cooperatives by offering high rates of interest on savings Due to the unsuccesful of the collective production system, the collapsed of credit cooperatives and banking system were took place in 1990 - 1991 The Agricultural [ 24 ] Development Bank changed to the Vietnam Bank for Agriculture and Rural Development (VBARD) and worked mainly as a credit provider for rural households In 1995, in keeping with the program of Hunger Eradication and Poverty Reduction, the Bank for the Poor (VBP) was established as a new complementary funding institution from the VBARD The objective of this bank was to provide the rural poor with the interest credit subsidies In 2003, the VBP separated from the VBARD and nominated as the Vietnam Bank for Social Policies (VBSP) (Takashi, 2009) Beside VBARD and VBSP, People’s Credit Funds network was mentioned as a third financial institution in 1993 Three of these financial institutions are essential formal credit suppliers in Vietnamese rural credit markets and concentrating on asset accumulation and loans with production purposes (Barslund & Tarp, 2008) The amount of loan is used in the formal sector is as the figure 3.1 The formal financial sources are the main credit providers for rural credit markets in Vietnam Figure 3.1: Rural loan in the formal sector 50.000 45.000 40.000 VND million 35.000 30.000 25.000 20.000 15.000 10.000 5.000 2004 2006 2008 Source: Author’s calculation in VHLSS 2004, 2006, 2008 & 2010 [ 25 ] 2010 Next to the formal sector, there exists microfinance organizations, such as the Vietnamese Women's Union (VWU) and the Vietnamese Farmers' Association (VFA), which offering the rural poor, ethnic minorities and women access to fundamental finance services including savings and loans These organizations were called the semi-formal sector (Takashi, 2009) (APEC, 2011) The distribution of loan amount in the semi-formal sector is as the figure 3.2 The semi-formal sector essentially concentrates on saving mobilization Its mechanism often operates in rural areas and provides financial services with short-term and small amount of loans Figure 3.2: Rural loan in the semi-formal sector 4.500 4.000 VND million 3.500 3.000 2.500 2.000 1.500 1.000 500 2004 2006 2008 2010 Source: Author’s calculation in VHLSS 2004, 2006, 2008 & 2010 The informal sector has appeared to contribute to the complete picture of the rural credit market in Vietnam This financial source comes from Group Lending, Moneylenders, Rotating Savings and Credits Associations (ROSCAs), relatives and friends (Pham & Izumida, 2002) Under central planning, the informal financial markets in Vietnam has been suppressed, information about them are very scant The Financial liberalization, which taking place in 1989, contributed to a revival and growth of the informal financial markets Recent studies have revealed the fact that the informal source provides a large number of financial intermediaries In the [ 26 ] Vietnam context, there are four types of major informal financial participation (Tran, 1998), (Pham & Izumida, 2002) and (Takashi, 2009): (i) Mutual finance is among family members, relatives, neighbors and friends This kind of credit usually is small amount of money and using for contingencies rarely for buying input material (ii) Self-help group is spontaneously established by members to help each other in production and life It operates under the form of ROSCA The other type of self-help group is collaborates with local formal institutions to reduce transaction costs and enhance peer monitoring loan among groups (iii) Moneylenders are characterized as monopoly lenders because of the absence of an effective formal financial system Experience shows that where access to formal financial sector is limited, the loans are in shortage, they can charge exorbitant interest rates The size of loan is usually small amount; procedures are simple and convenient; no collateral is needed and they often operate locally And (iv) traders often use the form of advancing inputs They advance inputs and receive the products with prefixed negotiated rate at harvest In some communes, cooperatives play the role of such traders The informal loan taking part in the informal credit markets is as the figure 3.3 Figure 3.3: Rural loan in the informal sector 18.000 16.000 VND million 14.000 12.000 10.000 8.000 6.000 4.000 2.000 2004 2006 2008 Source: Author’s calculation in VHLSS 2004, 2006, 2008 & 2010 [ 27 ] 2010 The informal credit sector still play a essential role in rural credit markets since (i) the rural poor cannot be affordable for market interest rates, (ii) commercial lenders usually exclude demand of small loans due to high transaction cost, and (iii) collateral is to signal creditworthiness of borrowers to commercial lenders in term of asymmetric information 3.2 Data All data of the thesis were acquired from the Vietnam Household Living Standard Survey which was carried out in the year 2008, conducted by the General Statistics Office of Vietnam (GSO), and also got helps on technical support of the World Bank (WB) The data for the study only obtained rural population, with total of 4837 households including 1103 households have credit access and 3734 households not access to credit, which is representative for the whole country and rural population presented as figure 3.4 The information of the survey was collected through household questionnaires Household information consists of basic demography, education, number of dependents, labor force participation, expense on livestock, expenditure on consumption and non-production, fixed assets and durable goods, cultivation areas, participation of households in informal credit markets, and especially the information of informal loans had been borrowed during the last 12 months before the interview took place Data on cultivation areas, expenditure on consumption and non-production used a lot of small questions in details Cultivation areas were summed up from areas of rice cultivation, annual crops, perennial plants and fruit trees Expenditure on consumption and non-production were aggregated from food, foodstuff, selfproduced products, education, healthcare, contingencies, commodities, energies and water supply and sewage system [ 28 ] Figure 3.4: Sample size 1103 Access to credit Not access to credit 3734 Source: Author’s calculation in VHLSS 2008 3.3 Research methodology 3.3.1 Descriptive analysis In this section, the analysis consists of calculation and comparison of rural credit markets, borrower characteristics, loans and terms of loan by using descriptive statistics The descriptive statistics analysis also provides some insight of various factors relevant to the use of loans, which will be beneficial to analyses and estimations of the econometric model discussed in the following section 3.3.2 Econometric model Farm household characteristics of credit access are analyzed in this section Due to using non-randomly selected samples in the VHLSS data set to examine loan amounts of households, the result could be biased estimates by using the OLS analysis because of a missing data problem The Heckman two-stage model (1979), which is to correct the error of sample selection, is used to test hypotheses about the relationship between the dependent and independent variables The conventional sample selection model (Heckman, 1979) can be written as the form: [ 29 ] 𝑧𝑖 = 𝛾𝑤𝑖 + 𝜀𝑖 i=1 N 𝑑𝑖 = 𝑖𝑓 𝐸(𝑑𝑖∗ |𝑧𝑖 > 0) = 𝛽𝑥𝑖 + 𝑢𝑖 > 𝑎, 𝑑𝑖 = 𝑖𝑓 𝐸(𝑑𝑖∗ |𝑧𝑖 = 0) = 𝛽𝑥𝑖 + 𝑢𝑖 ≤ 𝑎 (1) i=1 N Where 𝑧𝑖 : Informal loan amount 𝑤𝑖 : Observed variables relating to the ith characteristics of loan amount, 𝑧𝑖 is observed only for households who received loans already from the informal sector 𝑎: The minimum criterion for getting a loan If total characteristics of borrowers (𝑥𝑖 ) are below the condition, those people cannot borrow money from informal lenders 𝑑𝑖 : - access to credit, - cannot access to credit 𝛾 𝑎𝑛𝑑 𝛽 : Unknown parameter vectors 𝜀𝑖 𝑎𝑛𝑑 𝑢𝑖 : Zero mean error terms With the assumption that 𝜀𝑖 𝑎𝑛𝑑 𝑢𝑖 follow a bivariate normal distribution and then applied a two-stage estimation procedure purposed by Heckman (1979) The sample selection model in (1) comprises two equations; the outcome equation representing the desired relationship in the population, the selection equation is to take into account of the non-representative nature of the non-random sample According to the literature (Heckman, 1979), in order to facilitate the identification purpose, the vector 𝑥𝑖 should contain at least one variable which does not appear in vector 𝑤𝑖 The outcome equation describes the relationship between an outcome in interest 𝑧𝑖∗ and a vector of covariates 𝑤𝑖 and the selection equation describing the relationship between a binary participation decision 𝑑𝑖∗ and another vector of covariates 𝑥𝑖 In order to estimate 𝛾 𝑎𝑛𝑑 𝛽 parameters in the model (1), there are two approaches widely used to estimate the sample selection models under this distribution assumption: the Heckman maximum likelihood estimation procedure and the Heckman two-step procedure [ 30 ] The method frequently used for the sample selection model and also is the best alternative to maximum likelihood is the two-step procedure introduced by Heckman (1979) (Lola et al., 2009), (Cameron & Trivedi, 2009) In the Heckman two-step model, the first step is to estimate the binary selection equation through probit over the whole sample in order to obtain estimates of 𝛽̂ Recall model (1), considers the bivariate normal distribution for the error terms which implying independence of the errors and regressors 𝑧𝑖 = 𝛾𝑤𝑖 + 𝜀𝑖 𝑑𝑖 = (𝛽𝑥𝑖 + 𝑢𝑖 > 𝑎) (2) 𝑑𝑖 = (𝛽𝑥𝑖 + 𝑢𝑖 ≤ 𝑎) 𝜎2 (𝜀𝑖 , 𝑢𝑖 ) ~𝑁 (0, ( 𝜀 𝜎𝜀𝑢 𝜎𝜀𝑢 )) With 𝑧𝑖 observed only for 𝑑𝑖 = and since the third row in model (2) by assumption where 𝜎𝑢2 is normalized to and it is not identified in the selection model; moreover 𝜀𝑖 𝑎𝑛𝑑 𝑢𝑖 are assumed independently of 𝑥𝑖 ; hence the model (2) can be rewritten to: 𝑧𝑖 = 𝛾𝑤𝑖 + 𝜎𝜀𝑢 (𝛽𝑥𝑖 ) + 𝜉𝑖 𝑑𝑖 = (𝛽𝑥𝑖 + 𝑢𝑖 > 𝑎) (3) 𝑑𝑖 = (𝛽𝑥𝑖 + 𝑢𝑖 ≤ 𝑎) With (𝛽𝑥𝑖 ) is the inverse Mill's ratio which implied by the bivariate normality of (𝜀𝑖 , 𝑢𝑖 ): 𝜑(𝛽𝑥 ) (𝛽𝑥𝑖 ) = 𝛷(𝛽𝑥𝑖 ) 𝑖 𝛷(𝛽𝑥𝑖 ) and 𝜑(𝛽𝑥𝑖 ) are cumulative distribution function and the univariate probability density respectively of the standard normal distribution N(0,1) and 𝜎𝜀𝑢 is the covariance between 𝜀 and u [ 31 ] (i) The probit step: Probit (d = 1|x) = 𝛷(𝛽𝑥 ) = 𝛽0 + 𝛽1 𝑙𝑛𝑎𝑠𝑠𝑠𝑒𝑡 + 𝛽2 𝑙𝑛𝑙𝑎𝑛𝑑𝑠𝑧 + 𝛽3 𝑎𝑔𝑒 + 𝛽4 𝑒𝑑𝑢 + 𝛽5 𝑑𝑒𝑝 + 𝛽6 𝑙𝑛𝑒𝑥𝑝 +𝛽7 𝑙𝑛𝑙𝑠𝑡𝑘+𝛽8 𝑔𝑒𝑛𝑑𝑒𝑟+𝛽9 𝑓𝑎𝑟𝑚𝑖𝑛𝑔+𝛽10 𝑓𝑎𝑟𝑚𝑙𝑎𝑛𝑑+𝛽11 𝑓𝑎𝑟𝑚𝑙𝑖𝑣 + 𝑢 (ii) The OLS step: 𝐸(𝑙𝑛𝑙𝑜𝑎𝑛𝑠𝑧|𝑥𝑖 ) = 𝛽𝑥𝑖 + 𝜎𝜀𝑢 𝜑(𝛽𝑥𝑖 ) 𝛷(𝛽𝑥𝑖 ) = 𝛽0 + 𝛽1 𝑙𝑛𝑎𝑠𝑠𝑠𝑒𝑡 + 𝛽2 𝑙𝑛𝑙𝑎𝑛𝑑𝑠𝑧 + 𝛽3 𝑎𝑔𝑒 + 𝛽4 𝑒𝑑𝑢 + 𝛽5 𝑑𝑒𝑝 + 𝛽6 𝑎𝑑𝑢𝑙𝑡 + 𝛽7 𝑙𝑛𝑒𝑥𝑝 + 𝛽8 𝑙𝑛𝑙𝑠𝑡𝑘+𝛽9 𝑔𝑒𝑛𝑑𝑒𝑟+𝛽10 𝑓𝑎𝑟𝑚𝑖𝑛𝑔+𝛽11 𝑓𝑎𝑟𝑚𝑙𝑎𝑛𝑑+𝛽12 𝑓𝑎𝑟𝑚𝑙𝑖𝑣 + 𝜎𝜀𝑢 (𝛽𝑥𝑖 ) + 𝜉𝑖 Table 3.2: List of variables Variable Description Expected sign d access to credit, otherwise N/A lnloansz Natural log of loan amount N/A lnlandsz Natural log of land size + age Age of household head –/+ edu Education of household head + gender if household head is male, otherwise + lnexp Natural log of expenditure of households + adult Number of people who are between 15 and 64 + dep Number of people who are less than 14 or greater than 64 – lnasset Natural log of total value of fixed and durable assets + lnlstk Natural log of expense on livestock + farming if occupation of household head is farming, otherwise – farmland Natural log of land size used for farming – farmliv Natural log of land size used for livestock farming + 3.4 Chapter summary This chapter has presented the data and research methodology As for the data, the study collects the secondary cross-sectional data in VHLSS 2008 As for [ 32 ] the research methodology, the study employs the Heckman two-stage model The first stage is the probit model estimating the whole sample The second stage is the OLS model only focusing on observations which accessed to credit [ 33 ] CHAPTER 4: ANALYSIS RESULTS In this chapter, the general picture of rural credit markets, consisting of applicants, loanable sources, term of loans and size of loans, is fully described to facilitate as the strong evidences for further analyses Then univariate and bivariate analyses are deployed to present the impacts among explanatory variables The Heckman two-stage model is used to test the hypotheses; and the discussion of results is also shown in the end of this chapter 4.1 Rural credit markets In the 2008 VHLSS survey, there is a large likelihood of households could not touch to the financial market comprising formal, semi-formal and informal sources; it takes the share of 51.4%; the remaining is divided into three of formal, semi-formal and informal sources are 28.7%, 4.7% and 15.2% respectively There are 3524 households taking part in credit markets (formal: 2082 households, semiformal: 339 households and informal: 1103 households) The rest who have no demand and no access to credit markets is 3734 families (table 4.1) Table 4.1: Status of household’s access to rural credit markets Status of households Number of households Access to formal credit Percentage 2082 28.7% 339 4.7% Access to informal credit 1103 15.2% No demand/access to credit 3734 51.4% Total 7258 100% Access to semi-formal credit Source: Author’s calculation in VHLSS 2008 It is obviously that informal financial services still play an important role in the rural financial market More than one third rural farmers borrow from informal sources to smooth their consumption and contingencies Table 4.2 will show a more detail picture of loan distribution among credit service providers In the informal [ 34 ] financial sector, rural farmers tend to rely mainly on major sources from friends and relatives (70.2%) since the interest rate is low compared to monopoly lenders, sometimes it could be zero for close friends and relatives, and the individual lenders also share a large proportion of informal markets (22.7%) Table 4.2: Loan distribution over financial sources Item I Source of loan Number of loans Percentage Formal sector VBSP Bank 1102 46.4% VBARD Bank 1183 49.8% Other Banks 90 3.8% 2375 100 30 8.2% Total II Semi-formal sector National Fund for Employment Credit Institutions 141 38.6% Social & Political Institutions 194 53.2% Total 365 100 III Informal sector Individual Lender 285 22.7% Friends & relatives 883 70.2% Others 90 7.2% 1258 100% Total Source: Author’s calculation in VHLSS 2008 4.2 Intention of loans According to table 4.3, almost loans coming from formal financial institutions are for production purposes and take the share of 62.22% including current asset (37.11%) and fixed asset (25.10%) However it could not deny the role of informal credit sources, just with one-third of the total shares of loan distribution, it still take part in mostly activities of rural households People demand for credit essentially from the informal sector for non-production purposes (67.71%) There is [ 35 ] a large percentage of loan using for house purchase, medical treatment, general consumption and repayment as 27.25%, 8.04%, 5.41% and 5.37% respectively Table 4.3: Loan distribution over loan intention Formal Item Loan intention Amount (VND mil) I II Production Informal % Amount (VND mil) Total % Amount (VND mil) % 28,099.58 62.22 5,413.83 32.29 33,513.41 54.11 Current asset 16,761.90 37.11 2,502.93 14.93 19,264.83 31.11 Fixed asset 11,337.68 25.10 2,910.90 17.36 14,248.58 23.01 17,065.43 37.78 11,351.52 67.71 28,416.95 45.89 Non production Repayment 3,332.00 7.38 899.92 5.37 House purchase 4,259.31 9.43 4,567.95 27.25 334.52 0.74 167.60 1.00 502.12 0.81 1,646.90 3.65 428.36 2.56 2,075.26 3.35 577.40 1.28 1,347.22 8.04 1,924.62 3.11 2,120.60 4.70 906.97 5.41 3,027.57 4.89 28.00 0.06 20.09 0.12 48.09 0.08 746.10 1.65 442.90 2.64 1,189.00 1.92 129.00 0.29 25.18 0.15 154.18 0.25 198.50 0.44 23.50 0.14 222.00 0.36 3,693.10 8.18 2,521.83 15.04 45,165.01 100 Wedding/funeral Schooling Medical treatment 4,231.92 6.83 8,827.26 14.25 General consumption Food consumption Durable stuff Quality of water improvement Sanitation 10 improvement 11 Others Total 16,765.35 100.00 6,214.93 10.04 61,930.36 100 Source: Author’s calculation in VHLSS 2008 4.3 Different loan amounts analysis Tải FULL (82 trang): https://bit.ly/3Xngtzv Dự phòng: fb.com/TaiHo123doc.net Table 4.4 shows that the larger amount of loan, the smaller of number of applicants for both informal and formal sectors For the amount less than or equals [ 36 ] to million VND, the likelihood of the informal sector is larger than the formal, and also is the biggest share (38.7%) meaning that rural households demand for credit mainly on informal sources for consumption, wedding, funeral and schooling For the amount greater than 50 million VND, they tend to seek financial sources in the formal sector or from friends and relatives since the interest rate of informal lenders is so high than formal markets or they don’t have enough collateral, assets and other criteria Tải FULL (82 trang): https://bit.ly/3Xngtzv Dự phòng: fb.com/TaiHo123doc.net Table 4.4: Different amount of loan on rural markets Loan amount Formal Informal Total (VND million) ≤1 No of Loans % No of Loans % No of Loans % 17 0.7 145 11.5 162 4.5 – 634 26.7 487 38.7 1121 30.9 – 10 912 38.4 287 22.8 1199 33.0 10 – 20 452 19.0 165 13.1 617 17.0 20 – 50 259 10.9 122 9.7 381 10.5 50 – 100 58 2.4 35 2.8 93 2.6 100 – 500 39 1.6 17 1.4 56 1.5 Over 500 0.2 0.1 2375 100 3633 100 Total 1258 100 Source: Author’s calculation in VHLSS 2008 According to table 4.5, generally people tend to borrow money from friends & relatives for all sections because it is the cheapest loan, interest rates may be zero in some cases For the loan amount from to million VND, the amount of friends & relatives take the biggest share as 337 applicants of the total, and then are individual lenders and others as 116 applicants and 34 applicants accordingly Although with the extortionate interest rate of private lenders, there is still 23% households borrow money from this source; this could be understood that welltimed availability and service quality, in many cases, are more important to farm [ 37 ] households than the level of lending rate In general, individual moneylenders don't claim for collateral and have no complicated administrative procedures and regulations to follow prior to getting a loan Table 4.5: Different loan amount in the informal sector Loan amount (VND million) ≤1 Individual Lenders No of Loans % Friends & Relatives No of Loans % Others No of Loans % Total No of Loans % 39 13.7 93 10.5 13 14.4 145 11.5 – 116 40.7 337 38.2 34 37.8 487 38.7 – 10 62 21.8 194 22.0 31 34.4 287 22.8 10 – 20 37 13.0 123 13.9 5.6 165 13.1 20 – 50 20 7.0 97 11.0 5.6 122 9.7 50 – 100 2.8 26 2.9 1.1 35 2.8 Over 100 1.1 13 1.5 1.1 17 1.4 285 100 883 100 90 100 1258 100 Total Source: Author’s calculation in VHLSS 2008 4.4 Descriptive statistical analyses 4.4.1 Univariate analysis In this study, there are 4837 rural households including 1103 families borrowing money from the informal sector and 3734 families that not access to financial institutions The standard deviations of expenditure, asset, livestock, land size and amount of loans are big; it could be explained that these variables varies across farm households (table 4.6) In 4837 rural households, 3791 household heads are male and 1046 household heads are female, presented as figure 4.1 [ 38 ] 6674161 ... farmers’ access to credit Another view of Mpuga (2010), he employed a panel data analysis of the Uganda household surveys conducted in 1992/1993 and 1999/2000 to study the accessibility to and the... institutions Meanwhile, the distance of formal sector, transaction cost, corruption and bribe tend to move the farmer from formal to informal sector Similarly, Menkhoff and Rungruxsirivorn (2011) analyzed... borrowing money from the informal sector and 3734 families that not access to financial institutions The standard deviations of expenditure, asset, livestock, land size and amount of loans are big;