(LUẬN văn THẠC sĩ) the determinants of net interest margins in asean banks in the period 2008 – 2012

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM – THE NETHERLANDS PROJECT FOR M.A ON DEVELOPMENT ECONOMICS THE DETERMINANTS OF BANK INTEREST MARGINS IN ASEAN BANKS IN THE PERIOD 2008 – 2012 BY VAN THI THANH NHAN MASTER OF ARTS IN ECONOMICS OF DEVELOPMENT HO CHI MINH CITY – DECEMBER 2014 TIEU LUAN MOI download : skknchat@gmail.com UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIET NAM THE NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE DETERMINANTS OF NET INTEREST MARGIN IN ASEAN BANKS IN THE PERIOD 2008 - 2012 By VAN THI THANH NHAN MASTER OF ARTS IN DEVELOPMENT ECONOMICS Ho Chi Minh City, December 2014 -1- TIEU LUAN MOI download : skknchat@gmail.com UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIET NAM THE NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE DETERMINANTS OF NET INTEREST MARGIN IN ASEAN BANKS IN THE PERIOD 2008 - 2012 A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By VAN THI THANH NHAN Academic supervisor Dr NGUYEN TRONG HOAI Ho Chi Minh City, December 2014 -2- TIEU LUAN MOI download : skknchat@gmail.com CERTIFICATION I hereby assure that the thesis “The determinants of net interest margin in Asean banks in the period 2008 – 20012” was made by me under supervisor of Dr Nguyen Trong Hoai I also certify that data and results of this thesis are honest and have not published by anyone In addition, the substance of the thesis has not been submitted for any other degrees VAN THI THANH NHAN -3- TIEU LUAN MOI download : skknchat@gmail.com ACKNOWLEDGEMENT In the process of researching is not always convenient and smooth as expected Sometimes, when I faced with difficulties and challenges I wanted to give up without support, help and encouragement of whose are always by my side Hence, before I introduce the content of this paper I want to send to my loved ones deepest gratitude To my parents and my big family who are always beside and have instructed me on my ways whenever I am failure or successful To my beloved husband who always encourage, motivate me not only in the process of completing this study but also in the life Thank you, love you so much To my beloved daughter, thanks my angel who has given me the impetus from love and responsibility so that I can awake at night and work hard Thanks for helping me forget all the fatigue and back down when I look at you Thank to Dr Nguyen Trong Hoai who has always supported me in this process Thanks for your reminder and encouragement so that I could complete this paper Especially, thank for giving me can feel the love and confidential teacher To the Doctors, tutors in VNP program have imparted knowledge with all of passion, enthusiasm Thanks to the other employees, students in the program support me when I study in VNP program To the friends, colleagues has supported and facilitated during the completion of this research VAN THI THANH NHAN -4- TIEU LUAN MOI download : skknchat@gmail.com TABLE OF CONTENTS Certification Acknowledgement List of figures List of tables Abbreviations 10 Abstract 11 CHAPTER 1: INTRODUCTION 1.1 Problem statements 12 1.2 Research objectives 17 1.3 Research questions 18 1.4 Research scope 18 1.5 Research structure 18 CHAPTER 2: LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK 2.1 Literature review for interest margins 19 2.1.1 Definition of net interest margin 19 2.1.2 Determinants of NIM 21 2.1.2.1 Related literature 21 2.1.2.2The macroeconomic factors 23 2.1.2.3The bank specific factors 24 2.1.2.4 The banking market factor 27 -5- TIEU LUAN MOI download : skknchat@gmail.com 2.2 The suggested research approach 32 2.3 The concept framework 34 CHAPTER 3: RESEARCH METHODOLOGY AND DATA COLLECTION 3.1 Identification of variables 36 3.1.1 The dependent variable 36 3.1.2 The independent variables and hypothesis testing 36 3.1.2.1 The macroeconomic factors 36 3.1.2.2 The banking market factor 38 3.1.2.3 The banking specific factors 38 3.2 Data collection and expected results 43 3.3 The research methodology 45 3.3.1 The model 45 3.3.2 The estimation method 45 3.3.2.1 Fixed Effect Model 45 3.3.2.2 Random Effect model 47 3.3.2.3 Selecting the appropriate model 48 3.4 The outline of estimation method 48 CHAPTER 4: DATA ANALYSIS AND DISCUSSION Descriptive statistical analysis 50 4.1.1 The data description 50 4.1.2 The summary statistic 51 4.1.3 Testing for correlation relationship 54 -6- TIEU LUAN MOI download : skknchat@gmail.com 4.1.4 Checking for multicollinearity 54 4.1.5 The relationship between independent variables and Net interest margins 55 Econometric estimation and testing models: 61 4.2.1 Whether FEM or REM is more consistent 62 4.2.2 Fixed Effects Model 63 4.3 Empirical findings 65 4.3.1 Hypothesises rejected 65 4.3.2 Hypothesises accepted 65 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 5.1 Conclusion 68 5.2 Policy Recommendation 69 5.3 Limitation and further research 71 REFERENCES 72 APPENDIX A 77 APPENDIX B 79 -7- TIEU LUAN MOI download : skknchat@gmail.com LIST OF FIGURES FIGURE 1: GDP growth rate in main regions and countries, 2005 – 2009 14 FIGURE 2: The growth rate of worldwide industrial exports, 2005 – 2009 .15 FIGURE 3: GDP growth rate from 2008 to 2009 in Asean countries 16 FIGURE 4: Inflation rate from 2008 to 2012 in Asean countries 16 FIGURE 5: Trend of Net Interest Margins in Asean banks from 2008 – 2012 17 FIGURE 6: The relationship between GDP and NIM 56 FIGURE 7: The relationship between INF and NIM 56 FIGURE 8: The relationship between HHI and NIM .57 FIGURE 9: The relationship between SIZE and NIM 57 FIGURE 10: The relationship between LIQ and NIM 58 FIGURE 11: The relationship between CRD and NIM 58 FIGURE 12: The relationship between CAP and NIM 59 FIGURE 13: The relationship between OPE and NIM 59 FIGURE 14: The relationship between IIP and NIM .60 FIGURE 15: The relationship between MGE and NIM 60 -8- TIEU LUAN MOI download : skknchat@gmail.com LIST OF TABLES Table 1: Feature and source of variables 43 Table 2: Data description 50 Table 3: Deterministic statistic of main variables 51 Table 4: Correlation coefficient of variables .54 Table 5: Testing for multicollinearity 55 Table 6: Comparison of regression result of FEM and REM .61 Table 7: Testing for selecting appropriate model .62 Table 8: Results of Fixed Effect Estimator 63 Table A: The summary of main literatures review 28 -9- TIEU LUAN MOI download : skknchat@gmail.com SUMMARY CHAPTER As is showed, this chapter tried to answer the questions and objectives of study This part show the summary of statistical analysis for all variables and description of dependent variable NIM and independent variables GDP, INF, HHI, SIZE, CRD, CAP, LIQ, IIP, OPE, MGE as well as the relationship between dependent variable and independent variables in Asean countries over the period surveyed 2008 – 2012 The results determined that FEM was appropriate model by using Hausman test In addition, the hypothesis also tested in which hypothesizes 1, 2, 3, 4, 5, and were rejected and hypothesis 7, and 10 were accepted It is demonstrated that capital adequacy implicit interest payment and managerial efficiency were significant effects on net interest margins - 67 - TIEU LUAN MOI download : skknchat@gmail.com CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 5.1 CONCLUSION The banking system plays an important role in the economy of each country, banks are seen as financial intermediates However, as well as other business firms in the economy, the main objective is profit Efficient operation of the bank is shown in NIM Therefore, the objective of the study was to determine the factors affecting the NIM and measure the impact of these factors in the banking system in the ASEAN economic crisis the world 2008 - 2012 Since then, researchers want to be the basis for the bank management policies provide management, operating and monitoring the effectiveness This research has analyzed panel data during the period 2008 – 2012 across nine countries in Asean region to determine the determinant of bank interest margins FEM and REM model were applied to analyse data set and Hausman test was employed to choose the appropriate model The results showed that Fixed Effect Model was used for this research There were ten (10) hypothesizes tested to statisfy objectives of study, of which seven (7) hypothesis were rejected including hypothesis of GDP growth rate, inflation rate, banking market, size of bank, liquidity risk, credit risk, operating cost and hypothesis were accepted those were capital adequacy, implicit interest payment and managerial efficiency As expected by theoretical model, capital adequacy has positive significant impact on NIM This explained that increasing equity will make the cost of funds rise, higher capital adequacy indicates that a bank is well capitalized with regard to its perceived risk, thereby confirming long-term bank solvency; therefore banks need higher banks margins to cover this cost This finding is consistent with findings of Saunders and Schumacher (2000) ad Brock and Suarez (2000) One of the most significant variables in the explanation of the interest margins is the level of implicit interest payment This study - 68 - TIEU LUAN MOI download : skknchat@gmail.com found that implicit interest payment are highly significant and have strong influence on NIM, this result supported the free services of banks are not really free because it is compensated by higher interest margins This indicated that banks offer free banking services instead of remunerating deposits explicitly by paying an interest rate, which in turn leads higher interest margins This reflects the fact that an increase in the importance of explicit collection of banking commission results in a smaller volume of implicit interest payment, which led to a decline of NIM At the same time, the results of this research also show that there is a negative significantly relationship between managerial efficiency and NIM As prediction by model, the higher quality of management the lower net interest margins because if bank manage efficiently, the cost will be low; therefore cost which NIM bearing is low This result supported the findings of Angbazo (1997) and Mausos and de Guevara (2004) 5.2 POLICY RECOMMENDATIONS Based on the findings of study, the author would like to suggest some recommendations for managers of banks for controlling and adjusting net interest margins with strategies consistent with the objectives The capital structure: The positive effect of capital adequacy on met margins is basis of recommendation about capital structure In theory, the total equity in the property, the greater the cost of capital due to the higher average cost of equity is higher than the cost of debt However, during the period of economic instability, the cost of debt accounted for a large proportion of the banks not pay dividends to shareholders Meanwhile, if banks want to increase profits by increasing interest rates will increase the NIM However, it will be difficult because of the competition between banks and rising interest rates reduce demand for social capital On the other hand, the equity determines the extent of bank activities and factors determining capital adequacy of the bank's operations So, - 69 - TIEU LUAN MOI download : skknchat@gmail.com depending on the bank's strategy, managers need to consider capital structure to property owners to adjust the distance NIM to ensure profitable and efficient operation of the bank The implicit interest payment: As mentioned above, the finding showed that implicit interest payment is the factor having the most significant positively effect on bank margins This implies that an increase in implicit interest payment enables the net margins to rise, suggesting that the cost on implicit payments, remarkably, is transferred to the NIM Therefore, free services of banks are not really free Hence, managers of bank need to consider carefully offering fee of services, when bank increase fee of services for deposit instead of paying interest rate, the implicit interest payment decrease and this make NIM go down and vice versa The efficiency of banking management: The research’s results have demonstrated inverse relationship between effective management to the NIM Banks need to improve its management’s quality by tighten supervisor as well as transparency regulations In addition, implementation and monitoring of good governance can also be used to prevent unhealthy practices in the banking sector Bank’s management is expected to be able to create the conditions for an efficient banking system through good corporate governance and lowering operational costs, this will certainly contribute positively to the decline in intermediation costs to be borne by the public Similarly, if banks want to ensure profitable performance of the bank, regardless of quality management The quality of bank management depends on the cost-effective operation Therefore, to increase NIM, the bank management should reduce the operating costs at the lowest possible level 5.3 LIMITATIONS AND FURTHER RESEARCH: - 70 - TIEU LUAN MOI download : skknchat@gmail.com 5.3.1 LIMITATIONS Besides the achieved results as above, this study also contain limitations need to overcome in further research To begin with, due to limitations of data collection should study can only crawl countries in total 10 countries in Asean At the same time, the data of the bank in a country that does not have a full range of factors that research should be selected only the author of the banks have sufficient data on time as well as the variables being studied Therefore, the number of observations in the study does not reflect the entire banking system in ASEAN countries Secondly, the research has launched a new model includes factors specific to the banking and macroeconomic factors but not considering other factors such as the compulsory reserve ratio, risk aversion, regulation, legal, etc Besides, an increasingly complex banking activity, it is possible the size of non - traditional activity though specific variables can be used as a determinant of NIM, along with the development of businesses banks, the non - traditional activity is one indicator od the bank to print fee based income and a potential income through interest In addition, this study employed the Random Effected and Fixed Effect estimator to analyze but there may occur bias Finally, this study just determines the factors affecting on NIM but not provide the solution to adjust these factors in accordance with strategic of each bank 5.3.2 FURTHER RESEARCH As a result, fro From the above limitations, the authors would like to make some suggestions for future research, such as expanding the scope of research and study time At the same time, adding factors such as the compulsory reserve ratio, opportunity cost, braching regulation, legal regulation, etc.in model for analyzing as well as offering solutions that can be adjusted according to the objective of the bank in the different period - 71 - TIEU LUAN MOI download : skknchat@gmail.com REFERENCES Acharya, V V., & Richardson, M (2009) Causes of the financial crisis Critical Review, 21(2-3), 195-210 Aisen, A., & Franken, M (2010) Bank credit during the 2008 financial crisis: A cross-country comparison IMF Working Papers, 1-25 Aliaga-Dıaz, R., & Olivero, M P (2005) The Cyclical Behavior of Net Interest Margins: Evidence from the United States Banking Sector Manuscript, North Carolina State University Allen, L (1988) The determinants of bank interest margins: A note Journal of Financial and Quantitative Analysis, 23(2), 231-235 Angbazo, L (1997) Commercial bank net interest margins, default risk, interestrate risk, and off-balance sheet banking 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margins in Central and Eastern Europe: A comparison with the West Economic Systems, 32(2), 197-216 12 Demirgỹỗ-Kunt, A., & Huizinga, H (1999) Determinants of commercial bank interest margins and profitability: Some international evidence The World Bank Economic Review, 13(2), 379-408 13 Dietrich, A., Wanzenried, G., & Cole, R (2010) Why are net-interest margins across countries so different? 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Economic systems, 35(4), 481-495 22 García-Herrero, A., Gavilá, S., & Santabárbara, D (2009) What explains the low profitability of Chinese banks? Journal of Banking & Finance, 33(11), 2080-2092 23 Grigor′ ev, L., & Salikhov, M (2009) Financial Crisis 2008 Problems of Economic Transition, 51(10), 35-62 - 73 - TIEU LUAN MOI download : skknchat@gmail.com 24 Hasan, I., & Marton, K (2003) Development and efficiency of the banking sector in a transitional economy: Hungarian experience Journal of Banking & Finance, 27(12), 2249-2271 25 Hawtrey, K., & Liang, H (2008) Bank interest margins in OECD countries The North American Journal of Economics and Finance, 19(3), 249-260 26 Ho, T S., & Saunders, A (1981) The determinants of bank interest margins: theory and empirical evidence Journal of Financial and Quantitative Analysis, 16(4), 581-600 27 Ivashina, V., & Scharfstein, D (2010) Bank lending during the financial crisis of 2008 Journal of Financial economics, 97(3), 319-338 28 Kannan, R., Narain, A., & Ghosh, S (2001) Determinants of net interest margin under regulatory requirements: an econometric study Economic and Political Weekly, 337-344 29 Kashyap, A K., & Stein, J C (1997) The role of banks in monetary policy: A survey with implications for the European monetary union Economic PerspectivesFederal Reserve Bank of Chicago, 21, 2-18 30 Kasman, A., Tunc, G., Vardar, G., & Okan, B (2010) Consolidation and commercial bank net interest margins: Evidence from the old and new European Union members and candidate countries Economic Modelling, 27(3), 648-655 31 Keeton, W (2003) The role of community banks in the US economy.Economic Review, (Q II), 15-43 32 Lin, J R., Chung, H., Hsieh, M H., & Wu, S (2012) The determinants of interest margins and their effect on bank diversification: Evidence from Asian banks Journal of Financial Stability, 8(2), 96-106 33 Maudos, J and de Guevara J.F (2004): Factors Explaining the Interest Margin in the Banking Sectors of the European Union, Journal of Banking and Finance 28, 2259-2281 - 74 - TIEU LUAN MOI download : skknchat@gmail.com 34 McShane, R W., & Sharpe, I G (1985) A time 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Schwaiger, M S., & Liebeg, D (2008) Determinants of bank interest margins in Central and Eastern Europe OeNB Financial Stability Report, 208 41 Schwaiger, M S., & Liebeg, D (2008) Determinants of bank interest margins in Central and Eastern Europe OeNB Financial Stability Report, 208 42 Sidabalok, L R (2012) The Determinants of Banks' Net Interest Margin in Indonesia: A Dynamic Approach Universitas Indonesia, Graduate School of Management Research Paper, (13-02) 43 Tan, M T B P (2012) Determinants of Credit Growth and Interest Margins in the Philippines and Asia (EPub) (No 12-123) International Monetary Fund 44 Tarus, D K., Chekol, Y B., & Mutwol, M (2012) Determinants of Net Interest Margins of Commercial Banks in Kenya: A Panel Study Procedia Economics and Finance, 2, 199-208 - 75 - TIEU LUAN MOI download : skknchat@gmail.com 45 Williams, B (2007) Factors determining net interest margins in Australia: domestic and foreign banks Financial Markets, Institutions & Instruments, 16(3), 145-165 46 Wong, K P (1997) On the determinants of bank interest margins under credit and interest rate risks Journal of Banking & Finance, 21(2), 251-271 47 Zhou, K., & Wong, M C (2008) The determinants of net interest margins of commercial banks in mainland China Emerging Markets Finance and Trade, 44(5), 41-53 - 76 - TIEU LUAN MOI download : skknchat@gmail.com APPENDIX A Table A -11 : The data description: Contains data obs: 1,010 vars: 14 size: 52,520 (99.9% of memory free) variable name nim gdp inf hhi size liq crd cap ope iip mge cc id t storage display type format float float float float float float float float float float float byte int byte value label %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g %8.0g variaable label NIM GDP INF HHI SIZE LIQ CRD CAP OPE IIP MGE CC Sorted by: Note: dataset has changed since last saved Table A -2: 2: Description Statistics of variables Variable Obs Mean nim gdp inf hhi size 1010 1010 1010 1010 1010 liq crd cap ope iip mge cc id t Std Dev Min Max 744337 911736 749471 14.587 165555 19.72427 -14.05 2.94025 -2.329849 4.756319 -.8538899 9.417242 7.299929 8442338 4.032128 484.23 14.78079 24.99718 96.33308 8.460281 1010 1010 1010 1010 1010 544.17781 54.2423 188.72454 075863 234438 268.4126 0714965 21.2459 -.9556481 18.04645 -6.01182 4.581811 1033992 3.205682 -25.83798 6550.495 96.5864 99.2036 31.19787 23.81817 1010 1010 1010 1010 588.81804 262376 101.5 30.55281 2.657426 58.34055 1.414914 3.93 1 467.53 202 TIEU LUAN MOI download : skknchat@gmail.com Table A- 3: The correlation relationship between variables (obs=1010) nim gdp inf hhi size liq crd cap ope iip mge nim gdp inf hhi size liq crd 1.0000 0.0026 -0.0196 -0.0219 -0.1029 0.0096 -0.0253 0.0451 0.2462 0.4054 0.0105 1.0000 0.2641 0.0603 -0.0594 -0.0161 0.0043 -0.0829 -0.0384 0.0750 -0.0061 1.0000 -0.1521 0.0756 -0.0452 0.0498 -0.1462 -0.0878 0.0338 -0.1202 1.0000 -0.1905 0.0191 -0.1758 0.0375 -0.0476 0.0239 0.0537 1.0000 -0.1416 0.1187 -0.4800 -0.3130 -0.1474 -0.2923 1.0000 -0.1704 0.3632 0.0229 -0.0170 0.0043 1.0000 -0.2887 -0.0798 0.2262 -0.1352 cap ope iip mge 1.0000 0.3871 1.0000 -0.2203 0.0133 1.0000 0.1155 0.2825 0.2980 1.0000 Table A – 4: Checking for multicollinearity Variable VIF 1/VIF cap size iip ope mge crd liq inf hhi gdp 1.94 1.57 1.33 1.31 1.31 1.22 1.20 1.14 1.12 1.10 0.516100 0.635652 0.751706 0.763369 0.765275 0.821818 0.835513 0.876240 0.891109 0.907251 Mean VIF 1.32 78 TIEU LUAN MOI download : skknchat@gmail.com APPENDIX B Table B – 1: The Random Effect Estimation Results Random-effects GLS regression Group variable: id Number of obs Number of groups = = 1010 202 R-sq: Obs per group: = avg = max = 5.0 within = 0.3696 between = 0.2321 overall = 0.2752 Random effects u_i ~ Gaussian corr(u_i, X) = (assumed) theta = 40015856 Wald chi2(10) Prob > chi2 = = 17.69 0.0604 (Std Err adjusted for 202 clusters in id) Robust st Std Err Er nim Coef z gdp inf hhi size liq crd cap ope iip mge _cons 0248353 -.0777133 -.0007359 1.231906 -.1746049 -15.69101 14.61398 93.60504 417.9434 -.1798791 7.022192 083654 549 060869 697 000771 719 1.84395 951 289122 223 14.4999 992 12.028 284 61.5534 348 269.955 556 110756 566 7.32987 871 sigma_u sigma_e rho 8.1172107 13.607357 2624549 (fracti tion of variance due to u_i) 0.30 -1.28 -0.95 0.67 -0.60 -1.08 1.21 1.52 1.55 -1.62 0.96 P>|z| 0.767 0.202 0.340 0.504 0.546 0.279 0.224 0.128 0.122 0.104 0.338 [95% Conf Interval] -.1391254 -.1970156 -.0022487 -2.382172 -.7412743 -44.11034 -8.961262 -27.03756 -111.1598 -.3969581 -7.344091 188796 0415891 000777 4.845985 3920644 12.72832 38.18921 214.2476 947.0467 0371999 21.38848 Table B – 2: The Fixed Effect Estimation Results Fixed-effects (within) regression Group variable: id Number of obs Number of groups = = 1010 202 R-sq: Obs per group: = avg = max = 5.0 within = 0.3988 between = 0.0918 overall = 0.1841 corr(u_i, Xb) F(10,201) Prob > F = -0.5880 = = 0.51 0.8787 (Std Err adjusted for 202 clusters in id) Robust t Std Er rr nim Coef t gdp inf hhi size liq crd cap ope iip mge _cons 0781859 0236975 2243791 -2.659778 -.0017152 -.062357 2475961 -.2927425 5.918933 -.209689 23.40936 09353 36 051821 13 327277 76 3.11764 44 002396 66 065729 97 177856 66 588707 71 3.74782 24 129290 01 22.452 29 sigma_u sigma_e rho 16.19838 13.607357 58627836 (fracti ion of variance due to u_i) 0.84 0.46 0.69 -0.85 -0.72 -0.95 1.39 -0.50 1.58 -1.62 1.04 P>|t| 0.404 0.648 0.494 0.395 0.475 0.344 0.165 0.620 0.116 0.106 0.298 [95% Conf Interval] -.1062519 -.0784857 -.4209587 -8.807263 -.0064409 -.1919653 -.103108 -1.453577 -1.471163 -.4646278 -20.86408 2626236 1258806 869717 3.487706 0030105 0672512 5983003 8680917 13.30903 0452498 67.68281 79 TIEU LUAN MOI download : skknchat@gmail.com Table B – 3: The Hausman Test hausman FE RE, sigmamore Coefficients s (b) ( (B) FE RE size liq crd cap ope iip mge inf gdp hhi -2.659777 -.1715223 -6.235703 24.75962 -29.27423 591.8933 -.209689 0236974 0781859 0022438 1.2 231906 -.17 746049 -15 .69101 14 .61398 93 .60504 417 7.9434 -.17 798791 -.07 777133 02 248353 -.00 007359 (b-B) Difference sqrt(diag(V_b-V_B)) S.E -3.891683 0030827 9.455306 10.14564 -122.8793 173.9499 -.0298099 1014107 0533506 0029796 3.342072 0904691 5.030316 8.263108 22.4644 18.00039 0152851 0659535 0450712 003754 b = nsistent under Ho and Ha; obtained from xtreg B = inconsistent under r Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coef fficients not systematic chi2(10) = (b-B)' '[(V_b-V_B)^(-1)](b-B) = 109.99 Prob>chi2 = 0.0000 80 TIEU LUAN MOI download : skknchat@gmail.com 81 TIEU LUAN MOI download : skknchat@gmail.com ... study investigates the determinants of bank interest margins in Association of Southeast Asian Nations (Asean) banks over the period 2008 – 2012 by using of a panel data set In this research, the. .. measured by the ratio of the net interest income to average total earning assets of banks Net interest income is the difference between interest income and interest costs earned on interest expense... THE DETERMINANTS OF NET INTEREST MARGIN IN ASEAN BANKS IN THE PERIOD 2008 - 2012 A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS