(Luận văn) the effect of credit growth on credit quality, evidences of commercial banks in dong nai province

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERAMUS UNIVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS t to ng hi ep VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS w n lo ad ju y th yi pl n ua al THE EFFECT OF CREDIT GROWTH ON CREDIT QUALITY: EVIDENCE FROM THE COMMERCIAL BANKS IN DONG NAI n va A thesis submitted in partial fulfilment of the requirements for the degree of ll fu MASTER OF ARTS IN DEVELOPMENT ECONOMICS oi m at nh z z By ht vb TRINH HOANG VIET k jm om n a Lu Dr VO HONG DUC l.c gm Academic Supervisor n va y te re HO CHI MINH CITY, December 2015 DECLARATION t to I hereby declare that the thesis “THE EFFECT ng CREDIT QUALITY: EVIDENCE FROM CREDIT GROWTH OF THE COMMERCIAL BANKS IN ON DONG NAI”, hi ep which is submitted to Vietnam – Netherlands Programme, is my original research work All of the contents which are not from my own work are cited carefully and w n clearly in this thesis lo ad I certified that the contents of this thesis have not been and are not being y th ju submitted for any other degrees yi pl This thesis was done under the supervision and guidance of Dr Vo Hong Duc, ua al Economic Regulation Authority, Western Australia and the Edith Cowan n University, Australia Any other contributions to this thesis are presented in the n va ACKNOWLEDGEMENT section fu ll Signature oi m at nh z z vb ht Trinh Hoang Viet jm Ho Chi Minh City, 1st November 2015 k gm In my capacity as the supervisor of this thesis, I certified that the statements om l.c above are true to the best of my knowledge n a Lu Signature n va y te re Dr Vo Hong Duc Date: i ACKNOWLEDGEMENT t to I would like to express my great appreciation to VNP Lecturer Team for their ng dedication in teaching, which brought to me useful knowledge and experiences in hi ep my academic career w I would like to express my deep gratitude to Dr Vo Hong Duc, my research n lo supervisors, for his patient guidance and useful critiques of this research work ad y th I would like to offer my special thanks to Mr Pham Quoc Bao and Mr Pham ju Thanh Huu for facilitating me to collect necessary data during my internship in The yi pl State Bank of Viet Nam, Dong Nai Branch al n ua I wish to acknowledge the contributions of all VNP students in Class 20, n va especially Mr Vo Van Hung and Mr Nguyen Son Kien, for sharing learning ll fu experiences and valuable academic materials oi m I would also like to extend my thanks to all VNP Staffs for their enthusiasm of at nh assisting my study over the last two years z Finally, I would not forget to send my deepest thank to my parents who z ht vb always encourage me to keep up with my study objectives k jm om l.c gm n a Lu n va y te re ii ABSTRACT t to This research is conducted to examine and quantify the effect of credit growth ng on credit quality for the commercial banks in Dong Nai In relation to this possible hi ep effect, theoretical framework of the so–called “three shifts” in the credit market is likely to explain that credit growth might have positive or negative effect on credit w n quality These three shifts are generally known as: (i) a supply shift (an expansion in lo ad bank loan supply by lowering credit standards), (ii) a demand shift (an increase in ju y th loan demand to optimize business activities) and (iii) productivity shift (a positive change in macroeconomic conditions) In addition, empirical evidence confirms that yi pl rapid credit growth of commercial banks could lead to a deterioration or al ua improvement of credit quality The macroeconomic context for banking industry n indicates that the decline in credit quality after a period of growth might be a va n reflection of (1) negative changes in the macroeconomic determinants which have a fu ll bad influence on the business activities of borrowers; and (2) information m oi externality which makes banks hardly gain efficiency in evaluating their customers nh at This study utilizes the data of 29 commercial banks operating in Dong Nai z z province for the period from 2009Q3 to 2014Q4 The econometric technique of vb ht Difference GMM for dynamic panel data model is adopted in order to examine the jm effect of credit growth on credit quality in the context of the commercial banks in k gm Dong Nai This study finds empirical evidence to confirm that credit growth causes om of credit growth in the long run is found in this study l.c the decrease in credit quality after three quarters to one year In addition, this effect a Lu These findings obtained from this study reflects that: (i) commercial banks in n Nai might have not been really favorable for business activities during the research y te re business customers and individuals; (ii) the conditions of local economy in Dong n va Dong Nai might have lowered their credit standards to increase their lending to period; (iii) and the information externality in the loan market might have distorted the accuracy of customers evaluation in relation to their financial capacity iii Keywords: credit growth, credit quality, commercial bank, difference GMM, dynamic model, non–performing loan t to ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re iv TABLE OF CONTENTS DECLARATION i t to ng ACKNOWLEDGEMENT ii hi ABSTRACT iii ep TABLE OF CONTENTS v w LIST OF TABLES vii n lo LIST OF FIGURES viii ad ju y th CHAPTER INTRODUCTION 1.1 PROBLEM STATEMENT yi pl 1.2 RESEARCH OBJECTIVE AND QUESTION al ua 1.3 RESEARCH SCOPE AND METHODOLOGY n 1.4 THESIS STRUCTURE n va ll fu CHAPTER LITERATURE REVIEW oi m 2.1 THE MACROECONOMIC CONTEXT FOR BANKING Main Characteristics of Banks 2.1.2 Shock and Vulnerability of Banking System 2.1.3 The Effect of Macroeconomic Determinants .6 2.1.4 Credit Growth and Vulnerability of Banking System at nh 2.1.1 z z ht vb k jm 2.2 CREDIT GROWTH AND CREDIT QUALITY THROUGH DIFFERENT SHIFTS gm 2.3 CONTROL FACTORS FOR CREDIT QUALITY 17 l.c 2.4 PREVIOUS EMPIRICAL STUDIES 20 om 2.5 THE CONCEPTUAL FRAMEWORK 26 a Lu CHAPTER METHODOLOGY AND DATA 27 n 3.2 DATA COLLECTION METHOD 29 Dynamic Panel Data Estimator 31 3.3.2 Econometric Problems 31 v y 3.3.1 te re 3.3 ECONOMETRIC METHODOLOGY 30 n va 3.1 MEASURING CREDIT QUALITY 27 t to 3.3.3 Estimating The Long–run Coefficients 33 3.3.4 Econometric Specification 35 3.3.5 Hypothesis testing .35 ng hi ep CHAPTER RESULT AND DISCUSSION 38 w CHAPTER CONCLUSIONS 46 n lo ad REFERENCES 49 ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re vi LIST OF TABLES t to ng Change in credit standard, credit growth and credit quality 16 TABLE 2.2 Summarization of the literature 25 TABLE 3.1 Necessary items and their account type 29 hi TABLE 2.1 ep TABLE 3.3 The calculation of variables 30 ad Hypotheses need testing 37 w The expected signs of variables used in the research 30 n TABLE 3.2 lo TABLE 3.4 y th yi Estimation result 41 pl TABLE 4.2 Descriptive statistics 39 ju TABLE 4.1 n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re vii LIST OF FIGURES t to FIGURE 2.1 The macroeconomic context for banking ng FIGURE 2.2 Supply shift 10 hi ep FIGURE 2.3 Demand shift 13 FIGURE 2.4 Productivity shift 15 w n FIGURE 2.5 Different shifts in the macroeconomic context for banking 16 lo ad FIGURE 2.6 The effect of credit growth on credit quality 26 y th ju FIGURE 4.1 Deposit growth rate and deposit interest rate 39 yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re viii CHAPTER INTRODUCTION t to ng 1.1 PROBLEM STATEMENT hi ep Commercial bank is one of the most important financial intermediaries in the w economy Their main functions are mobilizing and lending money to allocate n lo financial resources for households, firms and other economic entities The typical ad problem of banks is that when borrowers could not use well the money they had y th ju borrowed, a credit risk arose One of the main causes is that banks lower their credit yi standards to attract more borrowers Although it might be a good opportunity to pl ua al boost credit growth in the present time, banks will face a higher probability to deal with non–performing loans (NPLs) in the future However, if loans expansion is due n n va to an increase in the demand, this growth will not essentially lead to bad loans oi m circumstances ll fu Therefore, credit growth may be a reflection of credit quality under some nh When the economy is in the stage of recession, it is certain to affect negatively at z on the financial market especially the banking system The general picture is that z ht vb commercial banks attempt to boost credit growth for profit objective whereas jm households and firms who borrow money from banks have to face with difficulties k in business activities This leads to a consequence that credit growth may reduce gm credit quality The problem is whether the profit target of commercial banks by om l.c boosting credit growth would be efficient or it just increases the NPLs which bring no profits or even losses a Lu n The determination of the effect of credit growth on credit quality is getting lending activities For central bank, it will help to control the loans growth of y time of loosening or tightening credit standards and the decision to expand or limit te re policy makers For commercial banks, it may help them to consider the appropriate n va more and more important for not only commercial banks but also central bank and In addition, the “too–big –to–fail” hypothesis contributes to marginal effect of credit growth on credit quality The coefficient of credit growth 𝐂𝐑𝐄𝐃𝐈𝐓 with its t to interactive term 𝐂𝐑𝐄𝐃𝐈𝐓 × 𝐋𝐀𝐑𝐆𝐄𝐒𝐓, is interpreted as follows: ng hi ep 𝟒 𝟒 ∑ 𝛄𝐣 ∆𝐂𝐑𝐄𝐃𝐈𝐓𝐢𝐭−𝐣 + ∑ 𝛅𝐣 ∆(𝐂𝐑𝐄𝐃𝐈𝐓𝐢𝐭−𝐣 × 𝐋𝐀𝐑𝐆𝐄𝐒𝐓𝐢𝐭 ) w 𝐣=𝟏 𝐣=𝟏 n 𝟒 lo ad = ∑(𝛄𝐣 + 𝛅𝐣 𝐋𝐀𝐑𝐆𝐄𝐒𝐓𝐢𝐭 )∆𝐂𝐑𝐄𝐃𝐈𝐓𝐢𝐭−𝐣 , ሺ10ሻ ju y th 𝐣=𝟏 yi If 𝐋𝐀𝐑𝐆𝐄𝐒𝐓 = 1, the coefficient of 𝐂𝐑𝐄𝐃𝐈𝐓 would be (𝛄𝐣 + 𝛅𝐣 ) and the pl ua al variance is calculated as 𝐕𝐚𝐫(𝛄𝐣 + 𝛅𝐣 ) = 𝐕𝐚𝐫(𝛄𝐣 ) + 𝐕𝐚𝐫(𝛅𝐣 ) + 𝟐𝐂𝐨𝐯ሺ𝛄𝐣 , 𝛅𝐣 ሻ n The long–run coefficient of 𝐂𝐑𝐄𝐃𝐈𝐓 corresponding to 𝛄𝐣 and 𝛅𝐣 is calculated va n as formula (7), the variance is in formula (8) In the case of long–run coefficient of fu ll (𝛄𝐣 + 𝛅𝐣 ), the formula would be calculated as: oi m at 𝛄𝐋𝐑 + 𝛅𝐋𝐑 𝟒 nh 𝟒 𝟏 𝟏 =( × ∑ 𝛄𝐣 ) + ( × ∑ 𝛅𝐣 ) , ሺ11ሻ 𝟏−𝛂 𝟏−𝛂 z 𝐣=𝟏 z 𝐣=𝟏 ht vb k jm The corresponding variance of this long–run marginal effect (11) would be: 𝐕𝐚𝐫ሺ𝛄 +𝛅 𝐋𝐑 ሻ 𝐂𝐨𝐯(𝐂, ሺ𝟏 − 𝛂ሻ) 𝐕𝐚𝐫ሺ𝛂ሻ 𝐃𝟐 𝐂 [ ] , ሺ12ሻ = × − 𝟐 + ሺ 𝟏 − 𝛂ሻ 𝟐 ሺ 𝟏 − 𝛂ሻ 𝟐 𝐃𝟐 𝐂 ሺ 𝟏 − 𝛂ሻ om l.c gm 𝐋𝐑 n a Lu n va y te re 36 𝟒 𝟒 𝐃 = 𝐕𝐚𝐫 (∑ 𝛄𝐣 + ∑ 𝛅𝐣 ) t to 𝐣=𝟏 𝐣=𝟏 ng 𝟒 𝟒 𝟒 𝟒 hi = ∑ 𝐕𝐚𝐫 (𝛄𝐣 ) + ∑ 𝐕𝐚𝐫 (𝛅𝐣 ) + 𝟐 ∑ ∑ 𝐂𝐨𝐯(𝛄𝐣 , 𝛄𝐥 ) ep 𝐣=𝟏 𝐣=𝟏 𝟒 𝐣=𝟏 𝐥=𝟏,𝐥≠𝐣 𝟒 𝟒 𝟒 w n + 𝟐 ∑ ∑ 𝐂𝐨𝐯(𝛄𝐣 , 𝛅𝐥 ) + 𝟐 ∑ ∑ 𝐂𝐨𝐯(𝛅𝐣 , 𝛅𝐥 ) lo 𝐣=𝟏 𝐥=𝟏 ad 𝟒 𝐣=𝟏 𝐥=𝟏,𝐥≠𝐣 𝟒 y th 𝐂 = ∑ 𝛄𝐣 + ∑ 𝛅𝐣 ju 𝐣=𝟏 𝐣=𝟏 yi pl Hypotheses need testing n TABLE 3.4 ua al Table 3.4 presents four null hypotheses which need testing as follow: va Meaning H01 : γj = Credit growth does not have any effect on credit quality n Hypothesis ll fu oi nh H02 : γj + δj = m at lag j Credit growth does not have any effect on credit quality at z at lag j for the three largest banks z Credit growth does not have any long–run effect on ht vb H03 : γLR = Credit growth does not have any long–run effect on credit k H04 : γLR + δLR = jm credit quality om l.c gm quality for the three largest banks n a Lu n va y te re 37 CHAPTER RESULT AND DISCUSSION t to ng This chapter presents the estimation results and discusses the main findings hi ep According to the estimation result, credit growth has negative effects on credit quality at the lag level of and and the long–run coefficient of credit growth is w n also statistically significant This proves for the existence of supply shift and the lo ad information externality in the credit market, and the negative impact from the ju y th macroeconomic conditions yi Figure 4.1 is to compare the growth rate of deposit liabilities of Dong Nai pl ua al banking system (the growth rate data only capture commercial banks’ branches which were in Dong Nai from 2010Q1 to 2014 Q4) with the quarterly deposit n n va interest rate in Viet Nam As can be seen from the figure, the condition stated in the ll fu literature is hold when the deposit growth rate is higher than deposit interest rate It oi m implies the inexistence of potential shock or vulnerability of Dong Nai banking system Therefore, credit growth has not been a great concern for commercial banks nh at during this period However, this figure only brings some evidences to confirm that z z net resource might be transferred in the direction from depositors to banking vb system If credit growth does not perform well, it would become a large pressure for ht k jm commercial banks to boost their mobilizing activities in the future, which could gm disrupt the condition of deposit growth rate and interest rate and reverse the om l.c direction of net resource n a Lu n va y te re 38 FIGURE 4.1 Deposit growth rate and deposit interest rate 11 t to ng hi ep w n lo ad y th -1 ju yi pl Deposit growth rate Deposit interest rate ua al Source: The State Bank of Vietnam, Dong Nai branch n n va International Monetary Fund eLibrary Data fu ll Table 4.1 below presents a summary of descriptive statistics for the sample m z Mean Standard Deviation z Observation at Variable Descriptive statistics nh TABLE 4.1 oi used in this empirical study 0.0348 0.0394 CREDIT 551 0.0414 COST_EFF 551 ROA 0.1977 0.1570 –0.6192 0.5467 0.9050 0.1627 0.4036 1.4639 551 0.0089 0.0133 –0.0312 SIZE 551 0.0345 0.0443 0.0007 LEVERAGE 551 0.8120 0.1655 0.3893 LARGEST 551 0.1034 0.3048 0.0000 ∆NPL_SL 522 0.0010 0.0225 –0.1577 0.1530 ∆CREDIT 522 –0.0004 0.2148 –0.9063 0.9854 ht 0.0000 a Lu 551 vb NPL_SL Minimum Maximum k jm gm 0.0534 om l.c 0.2641 0.9938 1.0000 n y 19 te re Number of Quarters n 29 va Number of Banks 39 Table 4.2 presents the estimation result of one–step Difference GMM method with robust standard errors First, test for second order autocorrelation AR(2) shows t to that 𝛆𝐢𝐭−𝟏 does not correlate with 𝛆𝐢𝐭−𝟐 due to an existence of the high p–value ng hi obtained from the analysis Test for first order correlation AR(1) is as expected with ep small p–value (lower than 0.05) Therefore, the tests for instrument variables are w valid Second, both Sargan Test and Hansen Test provide very high p–value, which n lo proves that the null hypothesis of valid instrument variables might not be rejected ad These tests indicate that the problem of endogeneity would be solved and the y th coefficients in the model could be used for further analysis ju yi According to the estimation results, the coefficients of lagged independent pl ua al variable (∆𝐍𝐏𝐋_𝐒𝐋𝐢𝐭−𝟏 ) is positive and significant, so credit quality in the present n might associate with itself in the past It means higher (lower) credit quality might va lead to higher (lower) credit quality after one quarter of a particular year The n ll fu lagged variables of credit growth are also positive and significant at lag level of oi m and It means the decision of expanding lending activities of commercial banks in at nh Dong Nai has negative influence on credit quality after three quarters to one year As stated in the Circular No 02/2013/TT–NHNN, customer loans will be recorded z z as NPLs if they are overdue from 91 days and above It is about two–quarter shorter vb ht than the two significant lag levels of credit quality Therefore, new loans of jm commercial banks in Dong Nai might have very high chance of becoming NPLs k gm after two quarters from the overdue threshold In the shorter period of one and two om l.c quarters, the effect of credit growth on credit quality is not statistically significant n a Lu n va y te re 40 ad ju y th yi pl Baseline model Model (1) Model (2) Model (3) Model (4) Full model 0.4825** 0.5697*** 0.4030 0.4969** 0.5606*** 0.5119*** (0.1967) (0.2766) (0.2131) (0.1453) (0.1462) 0.0092 0.0071 0.0051 0.0096 0.0055 0.0113 (0.0098) (0.0120) (0.0112) (0.0097) (0.0107) (0.0085) 0.0061 0.0087 0.0141 0.0158* 0.0174* (0.0096) (0.0142) (0.0107) (0.0096) (0.0087) (0.0096) 0.0247*** 0.0149 0.0184* 0.0242*** 0.0261** 0.0248*** (0.0086) (0.0101) (0.0091) (0.0085) (0.0097) (0.0091) 0.0416*** 0.0268 0.0354*** 0.0401*** 0.0444*** 0.0368*** (0.0071) (0.0198) (0.0074) (0.0064) (0.0134) 0.0172 0.0363 0.0269 0.0235 0.0126 0.0652 (0.0279) (0.0404) (0.0385) (0.0306) (0.0362) (0.0551) 0.0941 0.1057 0.1011 0.1023 0.0953 0.1953* (0.0691) (0.0741) (0.0649) (0.0704) (0.0689) (0.1079) 0.0566 0.0587 0.0607 0.0571 0.0555 0.0629 (0.0535) (0.0514) (0.0675) (0.0656) (0.0459) (0.1965) 0.0193 0.0394 0.0251 0.0208 0.0154 –0.0254 (0.0483) (0.0692) (0.0737) (0.0602) n va ∆NPL_SLit−1 Estimation result n Dependent variable ua al TABLE 4.2 fu k gm (0.0098) om l.c an va n y te re ac th (0.0404) (0.2058) si g e cd 41 Lu ∆ሺCREDITit−4 × LARGESTit ሻ jm ∆ሺCREDITit−3 × LARGESTit ሻ ht ∆ሺCREDITit−2 × LARGESTit ሻ vb ∆ሺCREDITit−1 × LARGESTit ሻ z ∆CREDITit−4 z ∆CREDITit−3 0.0142 at ∆CREDITit−2 nh ∆CREDITit−1 oi Credit growth m ll (0.2117) jg hg ad ju y th yi pl n ∆COST_EFFit−1 ua al Cost efficiency n va at z ∆COST_EFFit−4 nh ∆COST_EFFit−3 oi m ll fu ∆COST_EFFit−2 –0.0086 0.0823 (0.0205) (0.0736) –0.0465* 0.0709 (0.0269) (0.0779) –0.0189 0.1105 (0.0426) (0.0879) –0.0538 0.1672 z k jm ∆ROAit−1 ht Profitability (0.1319) vb (0.1161) 1.0349 (0.2272) (0.7915) 0.3698 1.0998 l.c gm ∆ROAit−2 0.2330 (0.2211) (0.8471) om ∆ROAit−3 0.2590 0.3494 (1.0555) n ∆SIZE 0.2782 y te re Bank size 1.2169 va (0.5254) (0.9268) an ∆ROAit−4 Lu (0.3152) 1.1002 (3.1992) si g e cd 42 ac th (0.8120) 2.4969 jg hg ad ju y th yi pl n ∆LEVERAGEit−1 ua al Leverage n va at nh ∆LEVERAGEit−3 oi m ll fu ∆LEVERAGEit−2 z ∆LEVERAGEit−4 z vb 0.1733* 0.1274 (0.0906) (0.1623) 0.3617 0.5580 (0.3971) (0.5411) (0.3960) k (0.0190) (0.0370) 0.0404 0.0364 (0.0260) (0.0260) 0.0248 0.0279 (0.0250) (0.0257) 0.0257 –0.0038 (0.0484) (0.0659) 0.1133 0.1750* 0.2091** 0.1851** (0.0916) (0.0908) (0.0817) (0.0720) 0.3582 0.4049 0.4067 0.6104 (0.4687) (0.4402) 1.0702 0.039 0.005 0.027 0.286 0.280 0.577 0.580 0.641 0.998 26 35 om l.c gm ∆ሺCREDIT × LARGESTሻ jm ∆CREDIT –0.0554 ht Long–run coeficient –0.0375* Testing for autocorrelation and validity of instruments 0.017 0.155 AR(2) 0.279 0.381 0.338 Sargan Test 0.574 0.499 0.780 0.659 Hansen Test 0.537 0.338 0.763 0.502 0.798 22 26 26 23 va y te re Number of instruments an 0.041 n Lu AR(1) ac th Standard errors are presented in parentheses Symbol *, ** and *** represent for significant level at 10%, 5% and 1% si g e cd 43 jg hg As presented on Table 4.2, all the coefficients of credit quality variables interacting with dummy ∆(𝐂𝐑𝐄𝐃𝐈𝐓𝐢𝐭−𝐣 × 𝐋𝐀𝐑𝐆𝐄𝐒𝐓𝐢𝐭 ) are not statistically t to significant It means the effect of credit growth on credit quality of three largest ng hi commercial banks is not different from the others Moreover, almost bank ep characteristics which are used as control variables in this research are not w statistically significant in explaining the change of credit quality n lo ∆𝐋𝐄𝐕𝐄𝐑𝐀𝐆𝐄𝐢𝐭−𝟏 is significant at 10% but not as expected Besides, despite the ad insignificant coefficients (except for ∆𝐂𝐎𝐒𝐓_𝐄𝐅𝐅𝐢𝐭−𝟐), the signs of cost efficiency y th and profitability are all positive at all lag levels It partially reflects the potential ju yi existence of “Skimping” and “Pro–cyclical credit policy” hypothesis in Dong Nai pl ua al banking system n In the long–run, the coefficient of ∆𝐂𝐑𝐄𝐃𝐈𝐓 is positive and significant It va n indicates that credit growth of commercial banks in Dong Nai may gradually reduce fu ll credit quality The total effect of credit growth is much larger than individual effect m oi from lag levels Similar to the individual lags of credit growth interacting with at nh dummy, the long–run coefficient of ∆ሺ𝐂𝐑𝐄𝐃𝐈𝐓 × 𝐋𝐀𝐑𝐆𝐄𝐒𝐓ሻ is not significant, z which prove that the influence of credit growth on credit quality is the same among z ht vb largest banks and the others jm The estimation results have presented the negative relationship between credit k growth and credit quality of commercial banks in Dong Nai, which is represented in gm l.c both short–run and long–run timeframe This relationship reflects two main implications First, based on the literature, there may be a supply shift in the loan om market It appears that commercial banks in Dong Nai are willing to lower their a Lu credit standards in order to boost lending activities This action from the n activities of the economic entities, especially households and small and medium 44 y from the macroeconomic conditions which result in disadvantages for business te re have bad financial capacity Second, there would be the existence of adverse effects n va commercial banks results in the high chance of lending money to borrowers who enterprises They would hardly gain positive cash flows to finance their liabilities Thus, overdue loans increase Third, there would be the existence of information t to externality in the loan market Commercial banks in Dong Nai may mis–evaluate ng hi their new customers Firms, households and other borrowers may be able to ep approach many sources of loans, so they can use borrowed money from somewhere to pay the debts in somewhere else w n lo The effect of credit growth on credit quality is not adjusted by the ad y th characteristic of large bank size This proves for the inexistence of “too–big–to– ju fail” hypothesis in the case of commercial banks in Dong Nai Although some yi banks have much larger size than others, they seem to have partially similar credit pl ua al growth policy In the aspect of this hypothesis, it means that large banks not have n over–confidence psychology (which makes bank believes in the protection of The va State Bank of Vietnam) in lending activities In more details, banks whether large or n ll fu small size have the same change in credit quality corresponding with their change in oi m credit growth This is contrary to the expectation that larger banks often suffer from nh greater change in credit quality than the smaller banks Vietnam banks in general at and Dong Nai banks in particular play a very important role in the financial market z z If one of them collapses, it would influence other banks due to the problems of vb ht cross–deposit among banks and negative psychology of people, and the whole jm Vietnam banking system would be in trouble Therefore, it may not reasonable to k gm conclude that commercial banks not believe in the intervention from The State l.c Bank to prevent them from failure In the scope, methodology and available data of om this research, there is temporarily no evidence to confirm this hypothesis n a Lu n va y te re 45 CHAPTER CONCLUSIONS t to ng The relationship between credit growth and credit quality could be explained hi ep through three shifts in the loan market First, the supply shift represents for the fact that banks expand their lending activities by lowering their credit standards In these w n circumstances, banks will face a high probability of lending money to bad lo ad borrowers Second, the demand shift originates from the demand of the capital ju y th restructuring as well as taking advantage of the lower cost capital from banks than somewhere else in capital market Banks would tighten their credit standards for yi pl this shift, which reduces credit risks in the future Third, the productivity shift in al ua favorable conditions of the economy reflects the efficient business activities of n households, firms and other economic entities who had borrowed money from va n banks The ability of financing the debts would be improved In addition, the fu ll negative nexus between credit growth and credit quality is also explained by m oi adverse macroeconomic shocks on borrowers and the information problems, in at nh which banks misevaluate new customers and as a consequence, the banks not z take any care of negative effects of their loans on other banks’ information z vb In accordance with the empirical results obtained from this study on the ht k jm sample of 29 commercial banks in Dong Nai from 2009Q3 to 2014Q1, credit gm growth has negative effect on credit quality in both short run and long run This l.c partially proves for the existence of the supply shift in the loan market in the context om of Dong Nai Commercial banks in Dong Nai appear to lower their credit quality in a Lu this researched period to boost lending In addition, the local economy of Dong Nai is not a good environment for business activities Moreover, the credit externality n n va may exist in the loan market These findings may derive some policy implications y te re which can be presented as follows: 46 For the Commercial banks t to It is not the right time for boosting credit growth rapidly in Dong Nai The ng commercial banks have to be more cautious in appraising investment projects, hi ep evaluating collaterals and supervising their customers’ capital usage especially new customers in order to avoid bad borrowers Moreover, commercial banks should w focus greatly on projects on advantageous fields in Dong Nai such as agriculture, n lo production of exports, labor intensive and high technology industries In the ad y th relationship with customers, they should deploy and maintain solutions for their ju customers to overcome difficulties in business activities; and classify borrowers yi depending on their state of credit relationship to apply appropriate incentive pl ua al policies In addition, commercial banks need to control new NPLs, continue to n handle old NPLs and prepare sufficient provision for credit risk Finally, va commercial banks should keep track of the state of the local economy to implement n ll fu credit policies timely and efficiently m oi For The State Bank of Vietnam, Dong Nai branch (SBV–DN) nh at The State Bank of Vietnam, Dong Nai branch (SBV–DN) needs to supervise z z more closely on credit growth of commercial banks, especially commercial banks vb ht with high NPL ratio Most importantly, the SBV–DN should classify commercial k jm banks into groups based on their lending activities to target the appropriate rate of gm credit growth, avoiding high credit risk of weak commercial banks In addition, the l.c SBV–DN has to catch up with the conditions of local economy as well as the real om state of commercial banks’ activities in order to enhance the efficiency of a Lu administration and operation Finally, they should co–ordinate with the local n governments at various levels to improve local economy, create good business n va environment for commercial banks, households and enterprises y te re 47 For local government at various levels t to Local governments should ease the legal environment for commercial banks, ng households and enterprises First, they need to facilitate households and enterprise hi ep in the proceedings of business registration Second, they could co–ordinate with relevant departments to support for enterprises’ outputs and stabilizing the markets w Last but not least, they could direct Executive Office to speed up process of n lo recovering NPLs This would help commercial banks in injecting capital into the ad ju y th market continuously, which stimulates the local economy yi In addition to the main empirical findings, this research still has some pl limitations First, the research scope is only in Dong Nai province Hence, the result al n ua will not reflect the convincing outcomes for the whole banking system in Vietnam va Second, the period of available data is not sufficient to capture the lags of very long n time There are many former researches which indicated that the effect of credit fu ll growth on credit quality may be even three years Further studies may use data of m oi yearly financial statements and the scope for commercial banks in Vietnam and at nh other countries in the world z z ht vb k jm om l.c gm n a Lu n va y te re 48 REFERENCES t to Arellano, M., & Bond, S (1991) Some tests of 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