(Luận văn) determinants on households’ partial credit rationing an analysis from varhs 2008

t to INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS ng UNIVERSITY OF ECONOMICS hi ep w n lo ad ju y th yi VIETNAM-NETHERLANDS pl PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS n ua al va n DETERMINANTS ON HOUSEHOLDS’ PARTIAL CREDIT RATIONING fu ll AN ANALYSIS FROM VARHS 2008 oi m at nh z z k jm ht vb By om l.c gm NGUYEN VAN HOANG an Lu Academic Supervisor: n va ey t re Dr TRAN TIEN KHAI th HO CHI MINH CITY, NOVEMBER 2013 t to AKNOWLEDGEMENT ng hi ep I am indebted to many individuals for their enthusiastic support and guidance while doing this thesis This paper would be impossible to accomplish without their unlimited support w n lo Firstly of all, I would like to express my great appreciation with Dr Tran Tien Khai, my ad supervisor, for the whole support to help me constructing ideas, structure, advices and y th comments, from the beginning to the end ju yi May thanks for Prof Dr Nguyen Trong Hoai, Dean of Vietnam – The Netherlands Programme pl who has provided necessary assistance and motivation for me to achieve this thesis ua al n I would like give my special thanks for Dr Pham Khanh Nam, Academic Director of Vietnam – n va The Netherlands Programme Without his introduction for VARHS 2008, an important data set ll fu used in this research, this paper would be impossible to complete oi m Many thanks for Dr Truong Dang Thuy, Chair of the Department of Economics - Faculty of nh Development Economics, who has passionately cooperate with me to solve issues related to at econometric techniques z z Last but not least, I must express my most gratitude to my parents and my aunt’s family for vb k jm ht providing comfortable condition during hard time, so that I can finish this thesis om l.c gm an Lu n va ey t re th t to List of Tables and Figures ng hi ep LIST OF TABLES w Table - VARHS 2008 Survey Questions 27 n lo Table - Model Specification 44 ad ju y th Table - Determinants of Credit Accessibility 54 Table - Determinants of Partial Credit Rationing Probability 56 yi pl Table - Determinants of Partial Credit Rationing Degree 60 n ua al n va LIST OF FIGURES ll fu Figure – Credit Supplier Expected Return 15 m oi Figure - Rationing in Credit Market 17 nh at Figure - Identify Case of being Credit Rationed 20 z z Figure - Survey Site Mapping for VARHS 2008 Source: IPSARD (2006-2008) 26 vb jm ht Figure - Sample Distribution Source: Author Calculation from VARHS 2008 29 Figure - Analytical Framework 38 k gm Figure - Credit Access & Credit Ration Source: Author’s calculation from VARHS 2008 45 l.c Figure - Credit Access & Household Head Age Source: Author’s calculation from VARHS om 2008 46 an Lu Figure 10 - Household Head Age & Credit Ration Source: Author’s calculation from VARHS ey from VARHS 2008 48 t re Figure 11 - Credit Access & Household Head Education Level Source: Author’s calculation n va 2008 47 th t to Figure 12 - Household Head Education Level & Credit Ration Source: Author’s calculation from ng VARHS 2008 49 hi ep Figure 13 - Credit Access & Loan Purposes Source: Author’s calculation from VARHS 2008 50 Figure 14 - Loan Purposes & Credit Ration Source: Author’s calculation from VARHS 2008 51 w n lo Figure 15 - Credit Access & Credit Institutions Source: Author’s calculation from VARHS 2008 ad 52 y th Figure 16 - Partial Ration & Credit Institutions Source: Author’s calculation from VARHS 2008 ju yi 53 pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th t to Abstract ng hi ep This study aim to identify key factors affected the partial credit ration’s probability and its degree in rural area of 12 provinces in Vietnam including Ha Tay, Nghe An, Khanh Hoa, Lam w n Dong, Phu Tho, Quang Nam, Long An, Dac Lac, Dac Nong, Lao Cai, Dien Bien, Lai Chau lo ad period 2006-2008 Based on VARHS 2008 data set, the research has employed Heckman sample y th selection bias model to investigate the determinants of partial ration’s degree, and bivariate ju probit with sample selection model to examine the determinants of partial ration’s probability yi Besides that, the impact of credit accessibility’s determinants, as a supplement outcome from the pl ua al two regression models, were also revealed n The result showed that households who have following characteristics - Kinh ethnicity, large va household size, high land value, suffering shock at household level (economic shock, illness, n ll fu unemployment, etc.), holding social position (at least one member working for government, local oi m authority unit) tend to have higher chance of credit access, while those who have high nh dependency ratio, and older household, tend to have negative correlation with credit at accessibility z z Formal credit institutions appeared to have higher rate of partial credit rationed than the informal vb jm ht sector, and those who requested a large size of loan were likely to be partial rationed as well In contrast, households who own larger house, borrowed for investment purposes (build/buying k gm house, land and other assets) or holding social position had a lower chance of being partial l.c rationed om The finding also uncovered the negative correlation between the degree of partial credit ration an Lu and following factors - Household head age, dependency ratio, house size and collateral value On the contrary, household size, loan size applied, loan for consumption purposes negatively n va affect the degree of partial credit ration th due to inherent sample selection problem in the data set ey selection bias or Heckman two stages regression are applied, the regression result might be bias t re The regression result also shown that unless treatments such as bivariate probit with sample t to Table of Contents ng Chapter Introduction hi ep 1.1 Research Context w 1.2 Research Problem 10 n lo 1.3 Research Objectives 11 ad y th 1.4 Research Questions 11 ju 1.5 Scope of Study 11 yi pl 1.6 Thesis Structure 12 al n ua Chapter Literature Review 12 n va 2.1 Rural credit 12 ll fu 2.1.1 Definition 12 m oi 2.1.2 Characteristics of rural credit market 12 nh 2.1.3 Types of rural credit 13 at z 2.2 Asymmetric Information and Credit Rationing 14 z vb 2.2.1 Asymmetric information 14 jm ht 2.2.2 Problems of lenders in context of asymmetric information 15 k l.c gm 2.2.3 Screening mechanism in lending 17 2.3 Credit Rationing 18 om 2.3.1 Types of Credit Rationing 18 an Lu 2.3.2 Identify Credit Rationing 19 va 2.3.3 Impact of Credit Rationing in Rural Area 21 n th ey 2.4.1 Factors of Credit Demand 22 t re 2.4 Empirical Studies 21 t to 2.4.2 Factor of Credit Supply 23 ng hi Chapter Methodology 25 ep 3.1 Data Source and Features 25 w 3.2 Issue of Data Bias (Sample Selection Problem) 28 n lo 3.3 Heckman Two-Stages Model 30 ad ju y th 3.3.1 Sample Selection Bias vs Omitted Variables Bias 30 3.3.2 Heckman Two Stages Procedures 32 yi pl 3.3.3 Application to study & Model Specification 33 al n ua 3.4 Bivariate Probit with Sample Selection Model 34 n va 3.4.1 Model Review 34 ll fu 3.4.2 Application to study & Model Specification 36 m oi 3.5 Multicollinearity Test 37 nh 3.6 Analytical Framework 38 at z 3.7 Hypothesis 40 z vb 3.7.1 Hypothesis for the probability and degree of partial credit rationing 40 jm ht 3.7.2 Hypothesis for the probability of access to credit 42 k l.c gm 3.8 Model Specification 44 Chapter Results and Discussion 45 om 4.1 Characteristics of Borrowers by Credit Rationing 45 an Lu 4.2 Determinants of Credit Accessibility 54 va 4.3 Determinants of Partial Credit Rationing Probability 56 n th ey 4.5 Multicollinearity Test 61 t re 4.4 Determinants of Partial Credit Rationing Degree 58 t to Chapter Conclusions and Policy Implications 62 ng hi 5.1 Conclusions 62 ep 5.1.1 Findings, answers for research questions 62 w 5.1.2 Conclusions on degree of solving research objectives 62 n lo 5.1.3 Limitation of the study 63 ad ju y th 5.2 Policy implications 63 5.2.1 Policy implications 63 yi pl 5.2.2 Research perspectives 65 n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th t to Chapter Introduction ng hi ep “Credit rationing is not necessary the source of poverty trap, but it reinforce them ” (Ping, Heidhues, & Zeller, 2010) w n 1.1 Research Context lo ad Since 1986, Vietnam Government has initiated the economic reform that has transformed the y th nation from the central planning to market oriented economy Major achievements in terms of ju economic growth and poverty reduction have been attained as a result of the reform However, yi pl the large gap between rural and urban areas has still existed To ensure the sustainability of al ua economic development and the stability of political environment, rural and agriculture n development are therefore considered as a priory goal in the nation development strategy va n Providing access to finance to the poor or microfinance has been considered as a tool for ll fu economic development and poverty reduction (Morduch & Haley, 2002; Khandker, 2003) It is oi m the interest of many policy makers and researchers in recent years Thus, in this strategy, rural nh credit, which aims at ensuring rural households having access to financial services, is regarded as at an important component The Government has launched many credit programs supporting the z z development of rural area such as preferential credit for the poor, agriculture forestry and fishery ht vb encouragement through special state own banks or government agencies The credit program has jm some significant impact to economic development of Vietnam rural areas; however there still k exist some issues such credit rationing in the program When credit rationing occurs, credit gm suppliers ignore to offer loan to some borrowers to avoid the risk of default, thus it limit the l.c credit accessibility of the poor Due to it implication to the economic development in general, om and to the effectiveness of Government credit for the poor program in particular, this paper will an Lu aim at examining the factors that affect to credit rationing, particularly focus on the cases of partial credit ration, with the hope of revealing some potential implications for policy makers n va ey t re th t to 1.2 Research Problem ng hi Rural credit market is an importance factor that helps to foster the economic development in ep rural areas, thus improving the poor living standard and supporting poverty alleviation One of its function is funding household’s credit demand w n lo However, the degree to which rural credit impacts on the rural area welfare depends on how well ad the rural credit market operates, however the problem of credit rationing could have negative y th effect on the performance of rural credit market Credit rationing could be described as the cases ju in which credit lenders refuse to offer loan to borrowers, or offer an amount of loan that is less yi pl than borrower’s request, even though the borrowers willing to accept higher level of interest rate al ua to help the lender to cover the default risk (Barham, Boucher, & Cater, 1996; Buchenrieder, n 1996; Heidhues & Schrieder, 1998; Zeller, 1993) The higher the probability of credit rationing, va the more difficulties for household to satisfy their credit demand In other word, if credit n ll fu rationing is a common practice in the area, it may lead to the inefficiency of the credit market in oi m the area as a consequence at nh As Stiglitz, J and A Weiss (1981) pointed out, asymmetric information is an explanation for the problem of the credit rationing In rural credit market, which is characterized by numbers of poor z z households and the difficulties to evaluate their credit worthiness, is concealed by a fog of vb jm ht asymmetry information between lenders and borrowers In other word, lenders are reluctant to lend as they are uncertain about the loan repayment probability To overcome this problem, k gm lenders require different kinds of information about their borrowers such as household’s l.c dependency ratio, household size, land value, social position, etc., to assess their repayment ability and make a basis for lending decision om an Lu As such kinds of information may affect to the probability and the degree to which a borrower be credit rationed, a question has been raised by many researchers is that what factors determined ey credit rationing – especially for the case of partial credit ration, concentrating on 12 provinces Ha t re under examination of a study For this paper, the research aim to examine the determinants of n va lenders’ decision of credit ration The answers are different depending on the period and location th 10