The role of credit and monetary transmission in Vietnam: a VAR approach

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 THE ROLE OF CREDIT AND MONETARY TRANSMISSION IN VIETNAM: A VAR APPROACH BY NGUYỄN LÊ THẢO NGUYÊN MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, May 2012 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 THE ROLE OF CREDIT AND MONETARY TRANSMISSION IN VIETNAM: A VAR APPROACH A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYỄN LÊ THẢO NGUYÊN Academic Supervisor: Dr NGUYỄN VĂN NGÃI HO CHI MINH CITY, May 2012 ACKNOWLEDGEMENT I have deeply grateful to many people who support and advise me during the writing this thesis The thesis will not be complete without their assistance and encouragement My first thanks to my supervisor- Dr Nguyen Van Ngai, who gave me valuable ideas, comments, suggestions, and motivation during the preparation of this thesis Thanks to his friendly attitude and enthusiasm has given me more self-confident to complete this study I sincerely thank Tutor- Mr Phung Thanh Binh who provided me materials, also economic techniques relevant to my thesis I am grateful to all lecturers and tutors of Vietnam-Netherlands Master Program in Development Economic, who have made invaluable contributions I wish my express my special thanks to my friends Nguyen Van Dung, Le Anh Khang, Vo Thi Ngoc Trinh They have spent a lot of time and effort in helping me during my writing Last but not least, I thankful to my lover, parents and brother who were always beside me and gave me spiritual support ABSTRACT Among different channels (namely: interest rate, asset price, credit, exchange rate channel) are affected by monetary policy, which one plays as a key channel in this mechanism In this study, I investigate the role of credit channel in monetary transmission mechanism in the case of Vietnam Two different specifications of loan markets are conducted: classical market (without domestic credit) and augmented market (with domestic credit) to look for the evidences of the role of credit Vector autoregression model which focuses on the reduced form will be employed as main econometric techniques in this thesis The empirical results support that credit channel plays important role in monetary transmission in Vietnam case The correlation between lending channel and monetary policy is somewhat weak The policy implication that credit sector should be carefully controlled when implements new monetary policy Key words: domestic credit, credit channel, monetary policy transmission, VAR model LIST OF TABLES Table 2.1: One decade and Vietnam’s credit Table 3.1: The data sources Table 4.1: Description of variables Table 4.2: Augment Dickey-Fuller test Table 4.3: Philips- Perron test Table 4.4: Optimal lap-Classical market Table 4.5: Optimal lap- Augmented market Table 4.6: VAR Regression Statistic- Classical market Table 4.7: VAR Regression Statistic- Augmented market Table 4.8: Variance Decompositions for vector autoregression for Classical and Augmented Market LIST OF FIGURES Figure 3.1: Analytical Framework Figure 4.1: The impulse response functions for classical market Figure 4.2: The impulse response functions for augmented market LIST OF ABBREVIATIONS IFS-IMF: International Financial Statistic- International Monetary Funds SBV: State Bank of Vietnam OMOs: Open Market Operation SOCBs: State Owned Commercial Bank JSBs: Join Stock Bank ADF: Augmented Dickey Fuller PP: Philips-Perron LR: sequential modified LR test statistic FPE: Final prediction error AIC: Akaike information criterion SC: Schawarz information criterion HQ: Hannan-Quinn information criterion U.S: United States TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 RELEVANCE AND BACKGROUND OF STUDY 1.2 PROBLEM STATEMENT 10 1.4.RESEARCH QUESTION 11 1.6 STRUCTURE OF THESIS 12 CHAPTER 2: LITERATURE REVIEW 14 2.1 CREDIT CHANNEL THEORY 14 2.2 MONETARY POLICY FRAMEWORK OF VIETNAM 16 2.2.1 LEGAL FRAMEWORK 16 2.2.2 MONETARY POLICY STRATEGY AND INSTRUMENTS 17 2.2.3 VIETNAM’S FINANCIAL MARKET OVERVIEW 19 2.3 EMPIRICAL LITERATURE 21 3.1 ANALYTICAL FRAMEWORK 27 3.2 MODEL SPECIFICATION 28 3.3 DATA SOURCES 30 3.4 STEPS OF ESTIMATION 32 CHAPTER 4: FINDING AND DISCUSSION 34 4.1 DESCRIPTIVE STATISTIC 34 4.2 UNIT ROOT TESTS 35 4.3 VAR REGRESSION STATISTICS FOR CLASSICAL AND AUGMENTED MARKET 37 4.4 IMPULSE RESPONES AND VARIANCE DECOMPOSITIONS 40 4.5 RESULTS COMPARISON 47 CHAPTER 5: CONCLUSION AND POLICY IMPLICATION 49 5.1 CONCLUSIONS 49 5.2 POLICY IMPLICATION 50 5.3 LIMITATION AND FURTHER STUDIES 53 5.3.1 LIMITATION 53 5.3.2 FURTHER STUDIES 53 REFERENCES 55 APPENDIX 58 CHAPTER 1: INTRODUCTION This chapter will present how important of this study is, its objectives and research questions In addition, a brief of methodology is also mentioned in this chapter Finally, the scope and structure of thesis are deal with in this part 1.1 RELEVANCE AND BACKGROUND OF STUDY The restructuring of state owned commercial banks (SOCBs) and the establishment of join stock banks (JSBs), had appeared since Vietnam financial reform in the first haft of 1990s Consequently, the finance system of Vietnam has deepened when monetization increased continuously (in 2004, the ratio M2 to GDP was above estimated 70% compare to 25% in mid-1990) Seventy-three percentage of total credit is provided by SOCBs in 2004 The credit market and other parts of financial system to be segmented proceeding JSBs and others small banks supplied credit primarily to private sector, whereas SOCBs almost loaned both sectors equivalently (Camen, 2006) When Vietnam took part in the World Trade Organization (WTO), lead to the surge of new foreign direct investment and portfolio inflows Globalization, it’s synonymous with Vietnam has posed significant challenges to their economy Unfavorable balance of payments is also the major concern Vietnam’s financial sector has been explosion since 2000 year only, noticeable in 2007-2008 periods Consequently, Vietnam’s credit market grew too hot, the number was estimated about 50 percentage in January 2008, that contributed a positive element to inflation rising, got 14 percentage at this time (Ishii, 2008) And at early months of year 2011, Vietnam’s inflation rate accelerated to 13.89 percent in March, peak out at highest in 25 months Moreover, the trade gap increased to $1.15 billion that month after look over $1.11 billion in February (S&P Reporting, 2011) 1.2 PROBLEM STATEMENT For facileness, most of economic models usually assume that the changes of economy which affect by financial conditions have just relatively bounded by set of several financial variables They could be risk-free interest rates in short term or government bond rates in long term (Hall, 2001) However, once the system of financial develops with high degree, especially in recent years, its impact on the economy becomes wider and deeper Hence, it’s quite hard to find the root of problem when the economy is developed, because of some variables may not be indicated For example, the world financial crisis in 2008 had a root from credit sector, typically, mortgage assets crisis in the U.S or the refugee capital of Vietnam security market in 2008 due to the easing monetary policy in previous years In the past, many economists such as Pintinkin, Gurley, Shaw, etc., emphasized the important role of financial intermediaries and credit markets Modigliani and Papademos (1977) also admitted that the traditional theory of monetary mechanism ignored the functions of financial intermediaries and bank credits Financial intermediaries were strong influence on credit supply than money supply (Gurley and Shaw, 1956) Evidently, credit channel contributes a significant factor and affects directly to decisions of policy makers Hence, understanding the position of credit channel in financial market is crucial to policy makers In detail, understanding the transmitted mechanism of monetary policy through credit channel is very important As a result, indentify the role of credit channel in monetary transmission is essential for enhancement current policies By that way, it contributes to the achievement of national economic objective 10 while it is blured in classical model Although lending rate shock has improved its role in augmented market, but still somewhat weak in comparison with others factors The output response is modestly smaller in the market with credit (8.4 percent compare to 9.2 percent at nine quarters) Another point of the result output variance decomposition, M2 shock accounts smaller in the market with credit (19.9 percent in comparison with 5.1 percent after nine quarters), and the different becomes larger at longer horizons Augmented market, which augments credit variable, makes lending rate drop its contribution from 20 percent to 14 percent to variance decomposition in output after five quarters Credit shocks account for 18.9 percent at thirteen quarters, a largest share in forecast error of output Once again, credit shock proves its important role in forecasting output error continuously According to the results, only output and price level keep relative role in forecast the error of credit, though, that result is somewhat fragile (15.2 and 14.8 percent at 13quarters horizon respectively) Similar with impulse response results, M2 shock also lacks its contribution in predicting credit error, only accounts 3.5 percent after thirteen quarters Credit shocks always account nearly haft in forecast error of itself during thirteen quarters Beside, with credit variable appearance, lending rate decomposition alters most of remain shocks Typically, 30 percent of the error in predicting lending rate is attributed to credit shocks, however, smaller with longer horizon 45 Table 4.8: Variance Decompositions for vector autoregression for Classical and Augmented Market Classical Market Dependent Variable Quarter s Cl_cpi decomposition at Cl_credit decomposition at Cl_lr 100 Cl_credi t 66.5 52.2 51.5 1.9 2.4 3.3 3.9 13 13 Cl_c pi 100 Cl_lr 68.8 53.0 52.4 Augmented Market Dependent Variable Cl_m Cl_out put Cl_refi n 6.8 6.8 6.9 8.5 8.0 8.2 3.3 6.7 7.4 12.6 25.4 25.1 Cl_cr edit Cl_cpi Cl_m Cl_ou tput Cl_r efin 6.6 10.7 11.4 6.9 7.1 7.1 3.9 9.5 9.2 14.1 18.1 17.5 96.1 0 0 14.8 14.9 14.8 55.9 44.9 43.2 9.7 12.4 12.4 3.2 2.9 3.5 13.3 15.2 15.2 3.1 9.6 10.9 Cl_lr decomposition at 13 12.3 43.1 37.3 37.7 87.7 40.5 35.9 32.9 5.4 10.5 10.9 4.8 5.5 6.9 6.3 10.8 11.5 6.6 37.5 32.2 34.3 30 12.1 9.9 9.3 63.4 27.5 26.6 22.9 6.2 15.0 14.7 4.6 4.8 7.7 12.2 11.5 11.1 Cl_m2 decomposition at 13 2.3 21.5 19.3 18.9 0.4 4.8 7.5 7.7 97.3 63.3 56.0 54.6 9.0 9.2 10.1 1.4 7.9 8.7 1.2 27 22.2 20.9 58.1 26.1 21.3 21.5 2.9 7.8 11.2 10.8 37.7 21.2 16.8 15.7 6.2 8.4 10.3 11.5 20.0 20.8 Cl_output decomposition at 0.9 11.6 1.2 86.2 0.2 1.3 12.6 3.2 87.8 13 6.6 18.1 19.2 20 16.2 14.8 20 19.9 20.8 47.1 36.3 35.2 6.3 9.3 9.9 8.9 19.9 18.4 18.1 19.0 18.9 14 12.7 11.9 6.2 5.1 6.0 45.9 34.3 33.9 6.8 9.0 10.9 11.4 12.7 0.4 75.4 8.5 0.4 19.6 0 71.5 13 54.8 44.3 43.2 13.9 12.3 12.2 11 14.2 14.6 2.8 5.9 6.8 17.5 23.3 23.2 47.4 37.9 36.9 0.9 1.2 2.8 21.6 21.3 19.7 6.5 10.7 10.9 3.9 6.6 8.7 19.6 22.4 20.8 Cl_refin decomposition at Sources: Calculated form IMF-IFS and GSO data 46 In brief, we can collect some remarkable concludes from empirical results In VAR regression statistic, neither the lagged value lending rate nor refinancing rate help predict money supply, hence, classical market might be lacked something Meanwhile, credit is highly significant in predict money supply in augmented market In impulse response and variance decomposition, the correlation between money supply and lending rate shock is sometimes abnormal in market without credit Whereas M2 reactions immediately and strongly for credit shock Credit shock plays important role in forecasting the error of money supply There have varied in magnitude, also order among macro variables with credit appearance in augmented market Credit and price level master a lot of output and M2 4.5 RESULTS COMPARISON Thesis’s results comparison will compare above estimation findings with other research relevant in Vietnam, also in other countries Hence, we can point out the similarity and difference among them to indentify the thesis’s contribution Our finding confirms the existing of credit channel and its role in Vietnam case since Bernanle and Gertler (1995) research The empirical results in this study consistent with majority previous study using VAR model as a main approach such as Kim (1999), Lown and Morgan (2002), Disyatat and Vongsinsirikul (2003), Abdul (2009); and structure vector autoregression model such as Kubo.A (2007), Catão and Pagan (2010) that credit channel plays important role in monetary transmission mechanism Once again, this study is in line with Podpiera (2007), Charoenseang J and Manakit P (2006) results by reconfirmed the role of credit channel in the case of Thailand or Chile in despite of different countries and econometric techniques With similarly topic for Vietnam research, the study agrees with Hung and Pfau (2008) and conclusion that 47 credit channel is more important than interest rate channel and to be the most significant channel in the case of Vietnam However, the study’s finding conflicts with several researches, such as Ramey (1993), Suzuki (2004) when their empirical provides evidence the insignificant role of credit in transmission of monetary policy In general, despite of different market conditions and Vietnam’s specific characteristic, the empirical finding still has same results to majority relevant studies 48 CHAPTER 5: CONCLUSION AND POLICY IMPLICATION This chapter will give conclusion and base on research findings, then we express policy implication also raise some recommendations Finally, limitation and further research of thesis are shown 5.1 CONCLUSIONS The thesis has identified the role of credit in monetary transmission mechanism in Vietnam case over 1996:Q1 to 2010:Q3 period Take advantage form IFS-IMF sources, most of data in this study that are extracted from here, excepting industrial output This study uses VAR model with reduced form as optimal economic techniques to answer key question Two markets are specified, including classical (without credit) and augmented market (with credit) that aim to explore the role of credit channel Stationary and unit-root test is the first step to test which data can be employed to run our model And base on minimum AIC criteria, we can choose the optimal lags for each case before VAR estimated Then, VAR Granger-causality test is used to examine causality between money supply and credit variable, also some relevant factors Impulse response is employed to see the reaction of each variable that shocks occurring Finally, variance decomposition is used to test how percentage of each variable is contributed to forecast error of monetary shock at given horizon The estimated results are following: First, there is no existing independent variables is Granger causality with money supply in classical market Money supply helps to predict most of dependent variable in market without credit, excepting the lending rate and vice versa Therefore, VAR regression statistic for classical market might be not sufficient to explain monetary transmission mechanism In augmented market, the domestic credit is highly significant to predict money supply And the worth findings that price level and lending rate are another ones help to predict money supply while they lost this function 49 in classical market But, the lagged value of money supply does not help to forecast credit, also output or lending rate Obviously, with augment credit variable in augmented market has contributed significance to accept the important role of credit channel in monetary policy transmission Second, in classical market, the output and refinancing rate response to monetary policy shock (tightening monetary policy in case) after one lag The output responses quite sensitive to money shock whereas the reaction of lending channel to money shock short affected and abnormal sometimes For market with credit, the reaction of output to credit shock is robust, happening after one lag, whereas the response of M2 is immediately, strongly and consistent with literature of Bernanke and Gertler The correlation between lending channel and credit channel is fairly weak Third, there is a discriminated between two markets in variance decomposition of M2 More than fifty percent of the error in the forecast of M2 is attributed by credit shocks at first quarter in augmented market Credit and price level shocks master a lot of variance decomposition of M2 and diminishing at larger horizons There has a big difference in magnitude, also the order of variance decomposition of M2 in market with credit Since those findings, the study agrees with Bernanke and Gertler view that credit channel played as important channel in monetary transmission mechanism in Vietnam case 5.2 POLICY IMPLICATION The study reveals some important implications for policy maker concerning to credit channel and monetary transmission mechanism As the estimation results of thesis proved the important role of credit channel in monetary policy transmission in 50 Vietnam; hence; in order to regulate the economy development through reasonable monetary policy at each period, some recommendations are given below: Firstly, credit channel plays important role in monetary transmission mechanism in the case of Vietnam Therefore, credit sector need to be carefully controlled when implements the new monetary policy Simply, it is a channel which be directly affected and strongly if government changes from loosen to tighten monetary policy and vice versa SBV plays crucial role to regulate credit flow to the economy by its instruments SBV as a central bank that manages and monitors the operation of commercial banks, need to make appropriate recommendations and practical policies to Government To carry out these tasks more effectively, should gives autonomy to SBV in decision making Secondly, money-quasi responses to credit shock immediately and strongly and output also falls dramatically to credit shock after one lag only Once tightening monetary policy is implemented; according to theory, this action will affect directly to credit channel through two sub channels: bank lending channel and balance sheet channel All of them lead to one resulting, that is output downward The main cause comes from the shortage in credit supply for manufacturing enterprises Therefore, it is essential to having support programs for these enterprises By that way, we can prevent too hot economic growth but not influence to production sector, especially an agriculture country like Vietnam In recent years, many subsidized programs have been implemented to this sector by the Vietnam’s government However, there are many insufficient and outstanding in implementation those programs Hence, the Government need control and supervise to ensure the policy effectively Thirdly, the relationship between lending channel and monetary policy does not follow as theoretical mechanism sometimes The causes have rooted from many reasons, under develop of Vietnam’s finance market is one of Although, has been given a selfcontrol in credit business, in which interest negotiation However, the commercial 51 banks still depend on the guidance of SBV in making lending decisions Hence, it is essential having another solution for lending rate rather than reality, a gradual marketization lending mechanism Fourthly, rely on variance decomposition result; credit and price level matter a lot of decomposition of money-quasi and diminishing at larger horizons Other words, credit growth and inflation play crucial role for error of money quasi in short-run Correspondingly, credit growth should be carefully control Essential for finance development projects instead of speculation operation to prevent bubble or bad debts Go further, monetary policy should be implemented cautiously and flexibly in order to enhance the effectiveness of money stock control In order to meet this duty, once again, the SBV need supervise, and forecast the changes in domestic as well as global financial market to impose appropriate policies timely Once, we understand the importance of credit channel in monetary transmission mechanism clearly We can eliminate the bad effects on it due to new policy implemented And if those measures are implemented successfully, they will be significant improvement the health of Vietnam’s financial market 52 5.3 LIMITATION AND FURTHER STUDIES 5.3.1 LIMITATION Although, this study has answered all the key questions about the role of credit in monetary transmission mechanism in Vietnam case, it also contains some limitations In particular, the availability of data resources is very limited for Vietnam country Due to this reason, the study can not access longer period of time Additionally, Vietnam’s GDP value only has existed since 2000 year, so that the thesis must use industrial output value as a proxy for GDP Again, standard variable; as proxy of the net percentage tightening6 had employed in Lown and Morgan’s research Then, domestic credit value is used instead of it Even VARs model are a powerful tools for indentify the role of credit in monetary transmission However, it has made lasting contributions to macro econometricians’s toolkit for describing data and generating reliable multivariable benchmark forecast (Stock and Watson, 2001) 5.3.2 FURTHER STUDIES This study has employed impulse response and variance decomposition of VAR model to examine the role of credit and monetary transmission for quarterly data 1996:Q1 to 2010:Q3 A further study could use monthly data for longer period to see the correlation, also reaction between them more exactly An addition, the further study should employ different model such as vector error correction (VECM) model to consider whether above conclusion is still effective in the case of Vietnam Besides that, the study could add several variables such as Federal Funds rate, exchange rate to exploit how the changes of estimated result with joined new variables The number of banks tightening less the number easing, divided by the number reporting (Lown and Morgan, 2002) 53 The credit plays important role in monetary transmission Hence, potential study may expand by consider the determinants of domestic credit in Vietnam case 54 REFERENCES Asteriou, D and Hall, S.G (2007) Applied Econometrics: A modern approach using eview and microfit, Revised Edition Palgrave Macmillan Abdul Aleem (2009) Transmission mechanism of monetary policy in India 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The economic record, vol 80, no 249: 145–156.(June) VietnamPlus News (2009) WB predicts growth of 5.5 percent Available from http://www.ncseif.gov.vn/sites/en/Pages/wbpredictsgrowthof5.5percent-nd13529.html Warner.E.J and Georges C (2001) The credit channel of monetary policy transmission: Evidence from stock returns Economic Inquiry Vol 39, Issue Available at SSRN: http://ssrn.com/abstract=253088 World Bank report,(2006) Overview the capital markets in Vietnam and directions for development Banking Finance and Investment Book-651, (May) 57 APPENDIX Original data illustration Figure 1a 2,400,000 2,000,000 1,600,000 1,200,000 800,000 400,000 1996 1998 2000 2002 M2 2004 OUTPUT 2006 2008 2010 CREDIT Figure 1b 200 160 120 80 40 1996 1998 2000 LR 2002 2004 REFIN 58 2006 CPI 2008 2010 Table 3: Descriptive statistic of level data Mean Median Maximum Minimum Std Dev Skewness Kurtosis CPI 99.60786 85.71913 166.5833 70.38970 28.70622 1.110776 2.900381 CREDIT 549177.7 265074.0 2350413 46248.30 617670.3 1.440890 4.044569 LR 12.11701 11.17500 21.00000 8.516667 3.094763 1.418351 4.485826 M2 592226.1 314276.3 2252240 47197.23 613318.5 1.213169 3.303865 OUTPUT 91988.86 78923.00 208347.0 27417.00 52686.84 0.512347 1.989271 REFIN 8.060734 6.500000 18.90000 4.800000 3.952356 1.469578 4.419529 Jarque-Bera Probability 12.15698 0.002292 23.09796 0.000010 25.20912 0.000003 14.69947 0.000643 5.092613 0.078371 26.19035 0.000002 Sum Sum Sq Dev 5876.864 47794.72 32401487 2.21E+13 714.9036 555.4984 34941342 2.18E+13 5427343 1.61E+11 475.5833 906.0249 Observations 59 59 59 59 59 59 Table 4: Descriptive statistic of changed data CL_CPI 1.509050 1.214760 8.968614 -1.535087 2.018160 1.432867 6.443011 CL_CREDIT 7.125907 6.837460 38.95502 -0.319156 5.354916 3.715985 22.74957 CL_LR -0.323911 0.000000 35.05047 -32.24432 9.643404 -0.259913 8.077671 CL_M2 6.983427 6.579830 35.56684 -0.048531 4.702351 3.912347 24.71221 CL_OUTPUT 3.654520 4.089613 12.42440 -8.978253 4.453939 -0.638997 3.804989 CL_REFIN -0.520797 0.000000 50.00000 -42.85714 13.69579 0.420237 7.485213 Jarque-Bera Probability 48.49465 0.000000 1076.092 0.000000 62.96132 0.000000 1287.227 0.000000 5.513088 0.063511 50.32354 0.000000 Sum Sum Sq Dev 87.52489 232.1594 413.3026 1634.482 -18.78682 5300.729 405.0388 1260.390 211.9621 1130.742 -30.20625 10691.76 Observations 58 58 58 58 58 58 Mean Median Maximum Minimum Std Dev Skewness Kurtosis 59