UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS COLLATERAL LIQUIDITY AND LOAN DEFAULT RISKS: THE CASE OF VIETNAM BY NGUYEN LE HIEU MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, Dec 2016 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 COLLATERAL LIQUIDITY AND LOAN DEFAULT RISKS: THE CASE OF VIETNAM A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN LE HIEU Academic Supervisor: Dr. LE HO AN CHAU HO CHI MINH CITY, Dec 2016 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com DECLARATION By these statements, I declare that the thesis titled “Collateral liquidity and loan default risks: the case of Vietnam” is result of my own works and efforts. All the contents in this thesis are my study based on reviewing some previous papers which are clearly indicated in references. In addition, this thesis has not been submitted to get any other degrees or certifications.
Signature NGUYEN LE HIEU December 2016 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ACKNOWLEDGEMENTS I desire to express my sincere gratitude to my supervisor Dr. Le Ho An Chau for her devotion to this thesis completion. Her recommendations really help to improve the quality of this study very much. My special thanks for all lecturers who taught me many profound and useful knowledge.
Thanks all VNP office employees who supported me so much during my master course. Besides, I really appreciated unforgettable memories that I have experienced with all my classmates in VNP class 21. This friendship will be maintained and developed deeply in future. Lastly, I would like to show my thankfulness to my family who really supported me so much and therefore I am enabled to finish this course.
LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ABSTRACT This thesis investigates the impact of the liquidity level of collaterals on the probability of default of individual loans and examines the channels through which collaterals affect default risks. Following the approach of Jiménez and Saurina (2004), binominal logit model is applied on the data from individual loan accounts of a medium – size commercial bank in Vietnam. The empirical results suggest the significant and negative impact of collaterals’ liquidity on loans’ probability of default, supporting the dominance of borrower selection effect and risk shifting effect over lender selection effect. Moreover, the finding also implies that bank has not applied carefully and thoroughly screening process on loans that are fully secured by low liquid collaterals and therefore impaired the credit quality of loan portfolio.
LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com CONTENTS CHAPTER 1. Research background and motivation. Research objectives and research questions. Research Methodologies and Data.
Structure of thesis .1 Theoretical review of relationship between collaterals and loan risks .2 Empirical review of relationship between collaterals and loan risk .1 Descriptive Statistics and Pre-estimation tests .1 Main findings & conclusion.3 Research limitation and further research .42 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com LIST OF TABLES AND FIGURES Table 1: Summary of variables. 21 Table 2: Summary of loans characteristics. 23 Table 3: Summary of default loans according to liquidity levels of collaterals. 24 Table 4: Summary of default loans according to varied amounts of loans.
24 Table 5: Summary of loans default according to rate of protection. 25 Table 6: Summary of loans default according to loan time. 25 Table 7: Estimation results of Logit model. 26 Table 8: Estimation results of Logit model (exclude interest and loan time factors).
27 Table 9: Estimation results of second logit model for robustness test. 31 Table 10: Estimation results of the third logit model for robustness test. 33 Figure 1: NPL rate of Viet Nam for the period from Dec-2012 to Jun-2013 .2 Figure 2: NPL of Viet Nam for the period from Jun-2014 to Dec-2015 .3 Figure 3: The transmission channels of collaterals on loan risk .7 Figure 4: Screening cost prorated.9 Figure 5: House price index of HCM city from 2009 to Q3-2016. 36 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com CHAPTER 1 INTRODUCTION 1.
Research background and motivation Non-performing loans (NPL) are a severe problem for the whole economy of the world since they lead to the financial crisis in East Asian countries, America and Sub-Saharan Africa (Farhan, Satta, Chaudrhy & Khalil, 2012). Therefore, finding out the main determinants of NPL plays an important role in policy making in order to prevent the future bad debts (Adebola, Wan Yusoff, & Dahala (2011) in Farhan et al (2012)). Previous studies identify that macro-economic conditions, bank and borrowers specific characteristics, loans characteristics, relationship banking1, and collaterals are key drivers of default risks and hence NPL. The relation between collateral characteristics and loan default is investigated in many studies over the world.
However, the findings are inconsistent among different papers, some of which show positive relationship while the others provide evidence of a negative effect. Berger, Frame and Ioannidou (2011) find a positive relationship between collaterals pledge and ex-post NPL in Bolivia for the period from 1998 to 2003. This result is supported by Jiménez and Saurina (2004) for Spain. Berger and Udell (1990) in Leitner (2006) shows that borrowers who pledge collaterals tend to be worse and therefore are riskier.
Leitner (2006) explains that this finding is due to collaterals’ requirement of banks for riskier borrowers. In contrast, John, Lynch and Puri (2003) investigate the yield difference between secured and unsecured loans in US and conclude that higher yield is decided by secured loans. This result implies that borrowers who pledge collaterals are more efficient than others. Kugler and Oppes (2005) investigate the impact of collaterals2 on loans risk in case of group lending in a developing country and find that collaterals are used by individuals to prevent loans default under joint borrowing.
1 Banks who supply more services in long time for customers will have more private information of their customers according to Argawal et al (2009). 2 Collateral in this paper is defined as equity capital of individual dedicated to investment projects. 1 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Berger et al. (2011) argue that the diversified findings about this relationship arise from the variation of data samples which include different types and characteristics of collaterals.
Moreover, previous papers investigate only the impact of collaterals on NPL by comparing the default risk (probability of default) between secured loans and unsecured loans. To my knowledge, there is very limited work on the impact of different collateral types and characteristics on default risk. Berger et al. (2011) find that liquid collaterals decrease the probability of default when compared to non-liquid collaterals.
However, previous papers mainly focus on loans for companies/enterprises rather than individual and consumer loans. In Vietnam, bad debt has increased sharply since 2011 and still been serious until now. As we can see in Figure 1 and 2, NPL ratio has risen from 4.08% in Dec-2012 up to 4.67% in April- 2013, then decreased lightly to 4.46% in Jun-2013 and kept declining to 2. However, this does not represent an improvement in loan quality of banks but due to banks’ switching to other asset titles in the balance sheet to hide bad debts.
The Viet Nam Assets Management Company (VAMC) was established on July-2013 with its main objective is bad debts purchasing by issuing special bonds for payment. As of Jun-2016, VAMC purchased about 251.000 billions of bad debts from banks and only 15% of these bad debts were collected (VAMC, 2016). Hence, these purchased bad debts help to reduce NPL of banks but they were not collected in reality and still harm the whole economy. Furthermore, many bad debts have been restructured but still classified as normal debts instead of bad debt in almost Vietnamese banks (this problem is permitted by the State Bank of Viet Nam) and therefore these bad debts were hidden.
Figure 1: NPL rate of Viet Nam for the period from Dec-2012 to Jun-2013 2 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Source: State Bank of Viet Nam in http://tapchitaichinh.vn/ Figure 2: NPL of Viet Nam for the period from Jun-2014 to Dec-2015 Source: State Bank of Viet Nam Ogeisia et al. (2014) argue that lending in low income countries is notoriously risky because of information asymmetry problem which are high in developing countries. United Nations Conference on Trade and Development - UNCTAD (2005) explains that high level of information asymmetry arises from weak credit information infrastructure, ineffective public 3 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com records, lack of credit management skills and underdeveloped financial intermediation, which is worse by generally restrictive and complicated regulatory environment and a large informal cash-based economy. Majority of loans in Viet Nam are collateralized loans due to information asymmetry.
Although Vietnamese banks determine that loan approval is always based on the payment ability of borrowers, not collaterals, but in practice, collaterals is the most important condition that make a loan to be approved. Loans in Viet Nam are 100% secured loans, therefore the difference of NPL between banks depends on the various quality of banks’ screening procedures. Higher efficient banks focus on the screening quality and ask for collaterals only for increasing the borrowers’ incentive for loan repayment to avoid asset loss. In contrast, smaller banks who have higher cost, may loosen the borrowers screening quality and use collateral as the premier protection from loan loss.
Collateral plays the most important role in NPL control in small banks in Viet Nam. The information conflict between lender and borrower might be mitigated by collateral according to Berger et al. (2011) and therefore mitigate loan approval for the optimists. However, Manove and Padilla (1999) argue that collaterals can not help to distinguish the optimists and realist and therefore make the PD prediction base on collateral requirement is unclearly.
The reason is that the optimists always tend to accept the collaterals’ requirement conditions like the realists to get lower cost loans due to their confidence in the efficiency of their projects. Furthermore, different characteristics of collaterals may have different impact on PD of loans due to results found by by Berger et al (2011) as mentioned above. However, liquid collaterals in their work are only Deposit and Bank guarantee and non liquid ones are the other type of assets while in Viet Nam, the most popular collaterals are real estates and vehicles which are diversified in types and therefore in liquidities. Each type of them is ranked in one level of liquidity and desirability and this level is determined by banks.
According to these above problems, an investigation about the impact on PD of different collaterals which diversify in characteristics for the case of Viet Nam should be implemented. Research objectives and research questions The objective of this paper is to examine the impact of collaterals’ liquidity characteristics on loans’ probability of default (PD) at the commercial banks in Vietnam. 4 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com In order to achieve that research objective, this thesis aims to seek convincing answers for the following research questions: Do higher liquidity levels of collaterals decrease the PD of loans? If so, through which channels this effect is transmitted? 1. Research Methodologies and Data This paper applies the logit model to examine the responses of different liquidity levels of collaterals, loans amount and ranks of protection rates of loans on PD of personals loans.
All predictors are categorical variables and the response takes only one of two categories at the same time: default and non - default.