Impact of monetary policy on bank’s loan supply, bank’s balance sheet 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 IMPACT OF MONETARY POLICY ON THE SUPPLY OF BANK LOAN: BANK’S BALANCE SHEET APPROACH BY Ms NGUYEN NHU Y MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2013 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 IMPACT OF MONETARY POLICY ON THE SUPPLY OF BANK LOAN: BANK’S BALANCE SHEET APPROACH The thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By Ms NGUYEN NHU Y Academic Supervisor: DR NGUYEN HOANG BAO HO CHI MINH, DECEMBER 2013 Page ACKNOWLEDGEMENT There are a number of people without whom this thesis might not have written, and to whom I am greatly indebted Firstly, I would like to express the deepest appreciation to my family, without their encouragement and support, I would not have a chance to be finished the thesis Secondly, I would like to express my sincere thanks to my supervisor, Dr Nguyen Hoang Bao, for the patient guidance, encouragements, comments, and advices he has provided throughout the thesis process Thirdly, I would like to express my sincere thanks to Dr Truong Dang Thuy for the econometric guidance and advices Fourthly, I am very grateful to all lecturers of the Vietnam-Netherlands Programme for giving me knowledge and guidance to fulfill the thesis Besides, I would like to thank all the academic and technical support from the staffs of Vietnam – Netherlands Programme during the course Finally, I would like to thank my friends and people, who have any help and support for my thesis but are not above-mentioned Page ABSTRACT This study researches the impact of monetary policy onthe supply of bank loan in Vietnam during the period from 2008 to 2012 The impact is examined by using the Generalized Methods of Moments (GMM) approach The estimation results indicate that monetary policy change has negative impact on the supply of bank loan and the magnitude is different among banks Bank characteristics i.e asset size, liquidity, and capitalization depress the negative impact of monetary policy change on the supply of bank loan The purpose of this study is to hope policy maker take into consideration when using monetary policy to regulate the supply of bank loan in the context that different bank react and absorb the monetary transmission differently Key words: Monetary policy, supply of bank loan, bank characteristics, GMM, Vietnam Page LIST OF FIGURES Figure 2.1: The bank – lending channel mechanism 23 Figure 4.1: Analytical framework .50 Figure 5.1: The correlation among dependent variable and independent variables .55 Figure 5.2: The correlation among independent variables and cross-term variables 56 Figure A.1: Overview of the transmission mechanism (Égert & MacDonald, 2006) 92 Page LIST OF TABLES Table 3.1: The short-term three months interbank deposit offer rate from 2008 to 2012 34 Table 4.1: Variables definition and sources 36 Table 4.2: Expected signs of variables in equation (21) 44 Table 5.1: Summary statistics of the variables used in the regressions 54 Table 5.2: The empirical regression results of GMM estimation .59 Table A.1: The base rate of VND in the year 2008 .74 Table A.2: The base rate of VND in the year 2009 .75 Table A.3: The base rate of VND in the year 2010 .76 Table A.4: The required reserve rate of VND in the year 2008 77 Table A.5: The required reserve rate of VND in the year 2009 77 Table A.6: The required reserve rate of VND in the year 2010 78 Table A.7: The required reserve rate of VND in the year 2011 78 Table A.8: List of commercial banks 79 Table A.9: Correlation matrix 81 Table A.10: The empirical regression results of GMM estimation 85 Table A 11: Wooldridge test for autocorrelation in panel data 87 Table A 12 : White’s test for Heteroskedasticity in panel data 87 Table A 13 : Test the relevance of instrument varible 87 Table A.14: Summary of empirical literature reviews .88 Page TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objective 11 1.3 Research questions 12 1.4 Research methodology 12 1.5 Structure of thesis 13 CHAPTER 2: LITERATURE REVIEW 14 2.1 Theoretical literature .14 2.2 Empirical studies .24 CHAPTER 3: STYLIZED FACT ON VIETNAMESE MONETARY POLICY AND BANKING SYSTEM 28 3.1 Monetary policy system 28 3.1.1 Legal framework 28 3.1.2 Monetary policy strategy .29 3.1.3 Monetary policy instrument 30 3.2 Monetary policy and the supply of bank loan change in the period 2008 – 2012 31 CHAPTER 4: METHODOLOGY, MODEL SPECIFICATION AND DATA RESOURCES 36 4.1 Data and econometric model 36 4.1.1 Data and variables .36 4.1.2 Econometric model 40 4.2 Analytical framework 50 CHAPTER 5: FINDINGS .53 5.1 Descriptive and comparative data analysis .53 Page 5.1.1 General picture of data for variables of empirical model 53 5.1.2 General relationship among variables 55 5.1.3 Data analysis discussion 58 5.2 Econometric results 59 CHAPTER 6: CONCLUSION 66 6.1 Summarize of methodology .66 6.2 Summarize of major findings 66 6.3 Policy implications 68 6.4 Shortcomings of the study .69 6.5 Suggestions for further study 69 REFERENCES 70 APPENDIX 74 Page CHAPTER 1: INTRODUCTION This chapter begins the thesis research by introducing the research topic and states the research problems in terms of social and scientific point of view This chapter also includes research objective which is what the paper intends to study and states the research questions The next part is research methodology, which presents briefly the method will be used in the paper to solve the research objectives and obtains the answers for research questions The final part of this chapter presents the organization of the thesis 1.1 Problem statement Banking system plays a significant role in economic development process in Vietnam Banks are considered the capital transmission channel of the economy and its activity covers all economic and social activities Banks are financial intermediaries between savers and borrowers It provides capital for the economy and bridges the companies with market Therefore, it will be an effective tool for government to regulate the economy The government manages the macro-economy by implementing monetary policy, fiscal policy, foreign capital control policy, and trade policy Among the above policies, the study focuses on the monetary policy and its effect on banking system Banking system leads the market through credit operations and payments between commercial banks in the system following the government regulation Thereby, the banking system expands the volume of money supply in circulation by supplying credit to sectors in the economy and controls them effectively One of the most important functions of banking system is financial intermediary For the economy, this function has an important role in promoting the economic growth by satisfying capital needs for the continuity of production process and production expansion With this function, the bank makes inactive capital into active capital, stimulates the circulation of the Page capital,and promotes business growth.The supply of bank loan represents for the financial intermediary function of the bank The amount of the supply of bank loan indicates how much money relatively goes into the economy Theoretically, the loan supply of bank is influenced by several factors as capital input cost, monetary policies, economic situations, loan demand, etc Within the boundary of the study, the impact of monetary policy on loan supply will be solely discussed in detail Understanding the mechanism and factors, which determine the loan supply of a bank has important implications for strength and distributional effects of monetary policy Understanding how monetary policy influent the loan supply also strengthens the link between stabilization and regulatory policy from the government and the state bank of Vietnam as well as business decision of bankers B S Bernanke and Blinder (1989)suggested bank intermediation is seen to be especially crucial in a situation of asymmetric information and moral hazard since only bank specializes in monitoring their borrowers Moreover, bonds and bank loans are assumed not perfectly substitute so then many firms would turn into bank dependent Thus, the existence of bank lending channel becomes importance in monetary transmission mechanism In this case, monetary policy affects bank assets and bank liabilities It is not only shift the supply of deposit but also the supply of bank loan The importance thing isthat bank relies on deposit financing and adjustsits loan supply schedules following changes in bank reserves as monetary policy shock In this way, monetary policy shocks change the supply of bank loan.The existence of bank lending channel means that with monetary contraction, banks will cut back their loans supply and weak, undercapitalized bank will responds more than large and well-capitalized banks There are also several empirical studies on the field Kashyap and Stein (1995); Kashyap and Stein (1997) and Kashyap and Stein (2000)analyzed disaggregated data of banks and find that large banks are better able to neutralize monetary shocks than Page 10 Table A.6: The required reserve rate of VND in the year 2010 Required reserve (VND) Decision No Effective date 4%1 - 3%2 74/QĐ-NHNN dated 18/01/2010 01/02/2010 (1) for term under 12 months (2) for term over 12 months Source: State bank of Vietnam, 2013 Table A.7: The required reserve rate of VND in the year 2011 Required reserve (VND) Decision No Effective date 3%1 - 4%2 750/QĐ-NHNN dated 9/04/2011 01/05/2011 3%1 - 5%2 1209/QĐ-NHNN dated 1/06/2011 01/06/2011 3%1 - 6%2 1925/QD-NHNN dated 26/08/2011 (1) for term under 12 months 01/09/2011 (2) for term over 12 months Source: State bank of Vietnam,2013 Page 78 Table A.8: List of commercial banks No Local Name English Name ACB Asia Commercial Bank Agribank Vietnam Bank For Agriculture And Rural Development An Binh Bank An Binh Commercial Joint Stock Bank BIDV Bank For Investment And Development Of Vietnam Dai A Bank Great Asia Commercial Joint Stock Bank EAB Eastern Asia Commercial Joint Stock Bank Eximbank Viet Nam Export – Import Commercial Joint Stock Bank HD Bank Housing Development Commercial Joint Stock Bank Maritime Bank Maritime Commercial Joint Stock Bank 10 MB Bank Military Commercial Joint Stock Bank 11 MHB Housing Bank Of Mekong Delta 12 Nam A Bank Southeast Asia Commercial Joint Stock Bank 13 Sacombank SaiGonThuong Tin Commercial Joint-Stock Bank 14 SHB Saigon-Hanoi Commercial Joint Stock Bank 15 Southern Bank Southern Commercial Joint Stock Bank 16 Techcombank Viet Nam Technological And Commercial Joint Stock Bank 17 VIB Vietnam International Commercial Joint Stock Bank 18 Vietcombank Joint Stock Commercial Bank For Foreign Trade Of Vietnam 19 Vietinbank Vietnam Bank For Industry And Trade 20 VP Bank Vietnam Prosperity Commercial Joint-Stock Bank Page 79 Page 80 Table A.9: Correlation matrix 1.0000 𝑑𝐿𝑁𝑖,𝑡−1 0.4088 1.0000 0.2118 0.5938 1.0000 -0.5039 -0.4449 -0.4793 1.0000 -0.2490 -0.2028 -0.0382 0.1429 1.0000 𝐿𝐼𝑄𝑖𝑡−1 0.0733 0.1530 -0.0860 0.0423 -0.4979 1.0000 𝐾𝐴𝑖𝑡−1 0.0898 0.1167 -0.1837 0.1692 -0.5251 0.2838 1.0000 𝑑𝑇𝐷𝑖𝑡 0.7225 0.1383 -0.1340 -0.3142 -0.4462 0.1332 0.1383 1.0000 𝑑𝑇𝐷𝑖𝑡−1 0.3293 0.6773 0.4741 -0.0587 -0.2534 0.2024 -0.0748 0.1384 1.0000 𝑑𝐼𝐵𝑖𝑡 0.0167 -0.1228 -0.1593 -0.0384 -0.1900 0.2585 0.1375 0.0794 -0.0543 1.0000 𝑑𝐼𝐵𝑖𝑡−1 0.2073 0.2598 0.1657 -0.2972 -0.2282 0.0164 0.0862 0.2986 0.0870 -0.3386 0.2120 0.5838 0.9987 -0.4744 -0.0422 -0.0889 -0.1759 -0.1326 0.4697 -0.1566 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 -0.4965 -0.4390 -0.4791 0.9985 0.1483 0.0470 0.1620 -0.3143 -0.0585 -0.0374 𝑑𝑖𝑡 𝐿𝐼𝑄𝑖𝑡−1 -0.1989 -0.5672 -0.9725 0.4630 0.0230 0.0550 0.1849 0.1337 -0.4366 0.0822 𝑑𝑖𝑡−1 𝐿𝐼𝑄𝑖𝑡−1 0.4736 0.4146 0.4523 -0.9710 -0.1182 -0.0019 -0.1719 0.2976 0.0326 0.0631 𝑑𝑖𝑡 𝐾𝐴𝑖𝑡−1 -0.2035 -0.5627 -0.9917 0.4792 0.0582 0.0893 0.1922 0.1066 -0.4506 0.1661 𝑑𝐿𝑁𝑖𝑡 𝑑𝐿𝑁𝑖𝑡 (-1) 𝑑𝑖𝑡 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 𝑑𝑖𝑡 𝐴𝑖𝑡−1 𝑑𝐿𝑁𝑖𝑡 𝑑𝑖𝑡 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 Page 81 𝐿𝐼𝑄𝑖𝑡−1 𝐾𝐴𝑖𝑡−1 𝑑𝑇𝐷𝑖𝑡 𝑑𝑇𝐷𝑖𝑡−1 𝑑𝐼𝐵𝑖𝑡 𝑑𝑖𝑡−1 𝐾𝐴𝑖𝑡−1 0.4614 0.4013 0.4577 -0.9869 -0.1602 Page 82 -0.0461 -0.2046 0.3112 0.0428 0.0390 𝑑𝐿𝑁𝑖𝑡 𝑑𝐼𝐵𝑖𝑡−1 𝑑𝑖𝑡 𝐴𝑖𝑡−1 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 𝑑𝑖𝑡 𝐿𝐼𝑄𝑖𝑡−1 𝑑𝑖𝑡−1 𝐿𝐼𝑄𝑖𝑡−1 𝑑𝑖𝑡 𝐾𝐴𝑖𝑡−1 𝑑𝑖𝑡−1 𝐾𝐴𝑖𝑡−1 𝑑𝐿𝑁𝑖𝑡 (-1) 𝑑𝑖𝑡 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 𝐿𝐼𝑄𝑖𝑡−1 𝐾𝐴𝑖𝑡−1 𝑑𝑇𝐷𝑖𝑡 𝑑𝑇𝐷𝑖𝑡−1 𝑑𝐼𝐵𝑖𝑡 𝑑𝐼𝐵𝑖𝑡−1 𝑑𝑖𝑡 𝐴𝑖𝑡−1 1.0000 0.1709 1.0000 𝑑𝑖𝑡−1 𝐴𝑖𝑡−1 -0.3026 -0.4758 1.0000 𝑑𝑖𝑡 𝐿𝐼𝑄𝑖𝑡−1 -0.1203 -0.9764 0.4664 1.0000 𝑑𝑖𝑡−1 𝐿𝐼𝑄𝑖𝑡−1 0.2423 0.4511 -0.9774 -0.4683 1.0000 𝑑𝑖𝑡 𝐾𝐴𝑖𝑡−1 -0.2056 -0.9947 0.4816 0.9722 -0.4576 1.0000 0.3167 0.4554 -0.9895 -0.4470 0.9695 -0.4711 𝑑𝑖𝑡−1 𝐾𝐴𝑖𝑡−1 Page 83 1.0000 Note:All variable is in logarithm form and dis denoted for first-difference Page 84 Table A.10: The empirical regression results of GMM estimation Number of obs = 48 Wald chi2 (16) = 237.55 Instrument variables (GMM) regression Prob> chi2 = 0.0000 R-squared = 0.7863 GMM weight matrix: Robust ∆ln 𝐿𝑂𝐴𝑁𝑖𝑡 Root MSE = 0.0826 Coef Robust Std Err z P>|z| [95% Conf Interval] ∆𝑙𝑛 𝐿𝑂𝐴𝑁𝑖𝑡 (-1) -.296789 257776 -1.15 0.250 -.802021 -.802021 -1.56809 849664 -1.85 0.065 -3.2334 097212 ∆𝑙𝑛 𝑖𝑡−1 -2.38994 709293 -3.37 0.001 -3.78013 -.999752 ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1 139460 055863 2.50 0.013 029969 24895 ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1 145873 044488 3.28 0.001 058677 233069 ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1 019836 097066 0.20 0.838 -.170410 210084 ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1 156305 074218 2.11 0.035 010840 301770 ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐾𝐴𝑖𝑡−1 361629 156538 2.31 0.021 054818 668439 ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐾𝐴𝑖𝑡−1 093062 111074 0.84 0.402 -.124639 310763 055079 022138 2.49 0.013 011689 098469 ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1 Page 85 Table A.10: The empirical regression results of GMM estimation (continued) Coef Robust Std Err z P>|z| [95% Conf Interval] 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1 002972 030534 0.10 0.922 -.056874 062818 𝐿𝑛 𝐾𝐴𝑖𝑡−1 157447 074665 2.11 0.035 011106 303788 ∆𝑙𝑛 𝑇𝐸𝑅𝑀 𝐷𝐸𝑃𝑂𝑆𝐼𝑇𝑖𝑡 571054 110865 5.15 0.000 353761 788347 ∆𝑙𝑛 𝑇𝐸𝑅𝑀 𝐷𝐸𝑃𝑂𝑆𝐼𝑇𝑖𝑡−1 357324 153504 2.33 0.020 056462 658187 ∆𝑙𝑛 𝐼𝑁𝑇𝐸𝑅𝐵𝐴𝑁𝐾 𝐵𝑂𝑅𝑅𝑂𝑊𝑖𝑡 -.015010 011697 -1.28 0.199 -.037937 007917 -.002089 010458 -0.20 0.842 -.022586 018408 Cons -.570141 288161 -1.98 0.048 -1.13492 -.005356 ∆𝑙𝑛 𝐼𝑁𝑇𝐸𝑅𝐵𝐴𝑁𝐾 𝐵𝑂𝑅𝑅𝑂𝑊𝑖𝑡−1 Instrumented: ∆𝑙𝑛 𝐿𝑂𝐴𝑁𝑖𝑡 (-1) Instruments: ∆𝑙𝑛 𝑖𝑡 ; ∆𝑙𝑛 𝑖𝑡−1; ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1; ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1 ; ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1; ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1; ∆𝑙𝑛 𝑖𝑡 𝐿𝑛 𝐾𝐴𝑖𝑡−1; ∆𝑙𝑛 𝑖𝑡−1 𝐿𝑛 𝐾𝐴𝑖𝑡−1; 𝐿𝑛 𝐴𝑆𝑆𝐸𝑇𝑖𝑡−1 ; 𝐿𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌𝑖𝑡−1; 𝐿𝑛 𝐾𝐴𝑖𝑡−1; ∆𝑙𝑛 𝑇𝐸𝑅𝑀𝐷𝐸𝑃𝑂𝑆𝐼𝑇𝑖𝑡 ; ∆𝑙𝑛 𝑇𝐸𝑅𝑀𝐷𝐸𝑃𝑂𝑆𝐼𝑇𝑖𝑡−1; ∆𝑙𝑛 𝐼𝑁𝑇𝐸𝑅𝐵𝐴𝑁𝐾𝐵𝑂𝑅𝑅𝑂𝑊𝑖𝑡 ; ∆𝑙𝑛 𝐼𝑁𝑇𝐸𝑅𝐵𝐴𝑁𝐾𝐵𝑂𝑅𝑅𝑂𝑊𝑖𝑡−1; 𝑙𝑛 𝐿𝑂𝐴𝑁𝑖𝑡 (-2) Page 86 Table A 11: Wooldridge test for autocorrelation in panel data Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 11) = 0.920 Prob > F = 0.3580 Table A 12 : White’s test for Heteroskedasticity in panel data White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(47) Prob > chi2 = = 48.00 0.4321 Cameron & Trivedi's decomposition of IM-test Source chi2 df p Heteroskedasticity Skewness Kurtosis 48.00 11.07 1.69 47 16 0.4321 0.8049 0.1940 Total 60.76 64 0.5917 Table A 13 : Test the relevance of instrumentvarible Test of endogeneity (orthogonality conditions) Ho: variables are exogenous GMM C statistic chi2(1) = 671123 Page 87 (p = 0.4127) Table A.14: Summary of empiricalliteraturereviews Researching countries and Research Author periods methodology Findings Kashyap USA, disaggregate The six-variable Tightening monetary and Stein quarterly data on prediction equation in policy declines deposit for (1995) bank balance sheet B Bernanke (1990) all size categories from 1976Q1 to Classifying banks by An increase in the Federal 1992Q2 asset size and using reserve funds rate has a the Federal reserve negative and statistically funds rate as the significant effect on the monetary policy growth rate of total loans instrument Small banks are more sensitive to change in monetary policy Kashyap USA, disaggregate The Two-Step The impact of tightening and Stein quarterly data on regression approach monetary policy on a (2000) bank balance sheet bank’s lending activity is from 1976Q1 to stronger for less liquid 1993Q2 banks Kishan and USA, disaggregate The OLS regression Opiela quarterly data on approach Segregating undercapitalized banks are (2000) bank balance sheet banks by asset size the most responsive to from 1980Q1 to and capital leverage monetary policy 1995Q4 ratio Page 88 Loans of small and Altunbaş et Euro, disaggregate al (2002) yearly data on bank prediction equation in matter what size they are balance sheet from B Bernanke (1990) tend to react more to 1991 to 1999 Classifying banks by policy change The six-variable Undercapitalized banks no asset size and capital Westerlund Sweden, Autoregressive Small, undercapitalized (2003) disaggregate distributed lag bank are sensitive and monthly data on (ARDL) approach strongly react to monetary bank balance sheet policy change from 1998:M1 to 2003:M6 Alfaro et al Chile, disaggregate Autoregressive (2003) yearly data on bank distributed lag capitalized banks have to balance sheet compress their loan (ARDL) approach Small, illiquid, and less during the period supply during the period 1990 to 2002 of monetary policy shock Gambacorta Italy, disaggregate The GMM approach Well-capitalized banks and quarterly data on can better shield their Mistrulli bank balance sheet lending from monetary (2004) during the policy shocks Small and period1992Q3 to illiquid banks tend to react 2001Q3 more toward monetary shock Page 89 Bichsel and Switzerland, The Two-Step Better-capitalized banks Perrez disaggregate Regression Approach are relatively immune to (2005) quarterly data on changes in the monetary bank balance sheet policy stance from the period 1996Q1 to 2003Q1 Golodniuk Ukraine, The GMM approach Undercapitalized bank (2006) disaggregate yearly Segregating banks by face serious problem to data on bank theirs asset size, maintain the loan supply balance sheet capitalization, and level in tightening during the period liquidity monetary policy period of 1998 to 2003 Gómez- Colombia and The six-variable For both case of Gonzalez Argentina prediction equation in Argentina and Columbia: and Grosz Disaggregate B Bernanke (1990) Better-capitalized and (2007) monthly data on liquid banks reduce the bank balance sheet effect of tightening during the period monetary policy on the of 2003M8 to supply of bank loan 2005M11 for Argentina and 1995M1 to 2005M9 for Colombia Page 90 Brissimis France, Germany, The six-variable Only japan and Greece and Delis Greece, Japan, UK prediction equation in present the existence of (2009) and USA B Bernanke (1990) bank lending channel Disaggregate There is weak bank yearly data on bank lending channel in France balance sheet Germany, US and UK during the period not have ban k lending of 1996 to 2003 channel Ezema Nigeria The GMM approach (2009) Disaggregate policy affects more on quarterly data on small and illiquid banks bank balance sheet during the period of 1999Q1 to 2008Q4 Page 91 The tightening monetary Figure A.1: Overview of the transmission mechanism(Égert & MacDonald, 2006) FOREIGN EXCHANGE CHANNEL Bank capital channel LT market & banking (deposit and loan) norminal interest rate Structure of banking sector Short term nominal interest rate Balance sheet channel Bank lending channel Capacity to borrow ASSET PRICE CHANNEL Portfolio adjustment: desired liquidity level Interest rate pass-through CREDIT CHANNEL Equity and property prices INTEREST RATE CHANNEL Long-term real interest rate Wealth effect Liquidity effect MONETARY POLICY Page 92 N V O I E U F S T L T P A M U T E T I Income effect N O Substitution effect T N Cost of capital Expectation channel I ... effect of monetary policy to the supply of bank loan is that the situation of banking sector could also affect monetary policy decision The empirical model indicates the impact of monetary policy. .. capitalization depress the negative impact of monetary policy change on the supply of bank loan The purpose of this study is to hope policy maker take into consideration when using monetary policy. .. summarizing and describing section also contain comments on the impact of changesin monetary policy on the banking system in the context of concerned variable 3.1 Monetary policy system 3.1.1 Legal