The impact of interest rate and its volatility on banking sector development empirical evidence from southeast asia 2022

MINISTRY OF EDUCATION TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY  TRẦN NGỌC THANH THỦY THE IMPACT OF INTEREST RATE AND ITS VOLATILITY ON BANKING SECTOR DEVELOPMENT EMP.

MINISTRY OF EDUCATION & TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY - - TRẦN NGỌC THANH THỦY THE IMPACT OF INTEREST RATE AND ITS VOLATILITY ON BANKING SECTOR DEVELOPMENT: EMPIRICAL EVIDENCE FROM SOUTHEAST ASIA GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 HO CHI MINH CITY, 2022 MINISTRY OF EDUCATION & TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY - - TRẦN NGỌC THANH THỦY THE IMPACT OF INTEREST RATE AND ITS VOLATILITY ON BANKING SECTOR DEVELOPMENT: EMPIRICAL EVIDENCE FROM SOUTHEAST ASIA GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 SUPERVISOR NGUYỄN DUY LINH, Ph.D HO CHI MINH CITY, 2022 COMMENTS OF THE SUPERVISOR Ho Chi Minh city, …/… /2022 Supervisor Ph.D Nguyễn Duy Linh i ABSTRACT For all economies, especially in the countries of Southeast Asia, the banking system plays a very important role in the movement and supply of capital in the economy For macroeconomic activities, the interest rate is one of the crucial tools to control and regulate the market to stabilize and promote economic growth Because of these reasons, this thesis examines the relationship between interest rate, interest rate volatility, and banking sector development of countries in Southeast Asia including Indonesia, Malaysia, Myanmar, Singapore, and Vietnam from 1996 to 2020 The thesis utilizes the main method of quantitative research as the basis for the topic The author manipulates a variety of regression methods including Pooled OLS, FEM, REM and FGLS Experimental results from running the model and the tests will be used as a basis for accepting or rejecting the research hypotheses, ensuring the appropriateness of the model Empirical results show that all indicators of the banking industry receive a positive impact from interest rates, at the same time, this connection also becomes weaker when interest rates are lower because of the convex relationship between interest rates and the development of the banking industry In addition, the empirical results supply evidence that interest rate volatility has a negative impact on several banking sector development indicators, implying that the banking sector of the sample is susceptible to interest rate risk Moreover, all indicators of the banking industry are negatively affected by GDP Finally, for the banking system and policymakers, these findings have important implications for strengthening the banking sector and promoting economic growth in these countries ii COMMITMENT I thus certify that my thesis "The impact of interest rate and its volatility on banking sector development: Empirical evidence from Southeast Asia" is my own research work, conducted under the supervision of Dr Nguyen Duy Linh after a rigorous working procedure The research findings are trustworthy since they are free of already published or created other content, with the exception of fully cited sources in the thesis I assume full responsibility for my commitment Ho Chi Minh City, ……………… 2022 Author Trần Ngọc Thanh Thủy iii ACKNOWLEDGEMENTS To conclude my thesis, I would like to express my sincere gratitude to the lecturers at the Banking University of Ho Chi Minh City, specifically, the teachers of the Faculty of Finance and Banking who have provided me with valuable knowledge over the last four years These experiences, I believe, will be extremely beneficial in helping me develop as a person in the future I would also like to express my gratitude to Dr Nguyen Duy Linh, who went above and beyond to assist me and create the finest possible conditions for me to complete my graduation thesis Moreover, I want to convey my gratitude to my family and friends for their encouragement and support as I worked on this thesis Because of the constraints of knowledge, flaws are unavoidable during the thesis writing process I look forward to receiving comments and suggestions in order to make the topic more complete, and at the same time create a better foundation for future research Thank you sincerely! Ho Chi Minh City, ……………… 2022 Author Trần Ngọc Thanh Thủy iv TABLE OF CONTENTS ABSTRACT i COMMITMENT ii ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LIST OF ABBREVIATIONS viii LIST OF TABLES AND FIGURES ix CHAPTER INTRODUCTION 1.1 REASONS FOR CHOOSING THE TOPIC .1 1.2 RESEARCH OBJECTIVES AND QUESTIONS .3 1.2.1 Overall research objective .3 1.2.2 Specific research objectives .3 1.2.3 Research questions 1.3 RESEARCH SCOPE AND SUBJECT 1.3.1 Research subject 1.3.2 Research scope 1.4 RESEARCH METHODOLOGY .5 1.5 NEW CONTRIBUTIONS OF THE STUDY 1.5.1 Research gap 1.5.2 New contributions 1.6 FRAMEWORK OF THE RESEARCH PROCESS 1.7 STRUCTURE OF THE RESEARCH v CHAPTER THEORETICAL BASIS AND OVERVIEW OF RELATED STUDIES 10 2.1 THEORETICAL BASIS OF INTEREST RATE, INTEREST RATE VOLATILITY, AND BANKING SECTOR DEVELOPMENT 10 2.1.1 Concept of interest rate 10 2.1.2 Concept of interest rate volatility 12 2.1.3 The relationship between interest rate and different aspects of the banking industry 13 2.1.4 The relationship between interest rate volatility and banking sector development (BSD) 15 2.2 THEORETICAL BACKGROUND 15 2.2.1 Classical Theory of Interest 15 2.2.2 Liquidity Preference Theory of Interest 16 2.2.3 Loanable funds theory 18 2.3 THE RELEVANT EMPIRICAL STUDIES 19 2.3.1 Vietnamese researches 20 2.3.2 English researches 20 CONCLUSION OF CHAPTER 25 CHAPTER RESEARCH METHODOLOGY 26 3.1 DATA SOURCE 26 3.2 DESCRIPTION OF VARIABLE .27 3.2.1 Dependent variable 28 3.2.2 Explanatory variable .30 3.2.3 Control variable .33 3.3 RESEARCH MODEL AND ECONOMETRIC METHODOLOGY 34 vi 3.4 RESEARCH PROCESS 36 3.5 RESEARCH METHODS 37 CONCLUSION OF CHAPTER 39 CHAPTER EMPIRICAL RESULTS AND DISCUSSION 40 4.1 PANEL UNIT-ROOT TESTS 40 4.2 DESCRIPTIVE STATISTICS 43 4.3 CORRELATION COEFFICIENT MATRIX 46 4.4 MULTICOLLINEARITY TEST 47 4.5 REGRESSION RESULTS 48 4.5.1 Regression results with FEM method 48 4.5.2 Regression results with REM method 49 4.5.3 Regression results with pooled OLS estimator .51 4.5.4 Regression results with FGLS estimator 54 CONCLUSION OF CHAPTER 58 CHAPTER CONCLUSIONS AND RECOMMENDATIONS 59 5.1 CONCLUSIONS 59 5.2 RECOMMENDATIONS 61 5.2.1 For the banking sector in the sample countries 61 5.2.2 For interest rate policymakers .62 5.3 LIMITATIONS AND FUTURE RESEARCH DIRECTIONS OF THE STUDY 63 5.3.1 Limitations of the study 63 5.3.2 Future research directions 64 CONCLUSION OF CHAPTER 65 vii REFERENCES 66 APPENDIX 74 Appendix 1: Creating “Index” by using the principal component analysis (PCA) method 74 Appendix 2: Panel Unit-root Tests .75 Appendix 3: Descriptive statistic 78 Appendix 4: Regression of the model following Pooled OLS, FEM, REM 79 Appendix 5: Model selection test Pooled OLS, FEM, REM 81 Appendix 6: FGLS method 84 70 38 King, R.G., & Levine, R., (1993) Finance and growth: schumpeter might be right The Quarterly Journal of Economics, 108 (3), 717–737 39 Koech, W.J., Maina, D.K.E., (2020) Effect of interest rate volatility drivers on loan repayment among commercial banks in Eldoret town, Kenya International Journal of Finance and Accounting, (1), 1–13 40 Levin, A., Lin, C.F., Chu, C.S.J., (2002) Unit-root tests in panel data: asymptotic and finite-sample properties Journal of Econometrics, 108, 1–24 41 Levine, R., (1997) Financial development and economic growth: views and agenda Journal of Economic Literature, 35 (2), 688–726 Available online http://www.jstor.org/stable/ 2729790 42 Levine, R., (2005a) Finance and growth: theory and evidence In: Aghion, P., Durlauf, S (Eds.), Handbook of Economic Growth, pp 865–934 43 Levine, R., (2005b) Chapter 12 finance and growth: theory and evidence In: Handbook of Economic Growth, 1, pp 865–934 https://doi.org/10.1016/S1574-0684 (05)01012-9 (A) 44 Levine, R., Loayza, N., Beck, T., (2000) Financial intermediation and growth: causality and causes The Journal of Monetary Economics, 46 (1), 31–77 https://doi.org/10.1016/S0304-3932 (00)00017-9 45 Levine, R., Zeroes, S., (1998) Stock markets, banks and economic growth The American Economic Review, 88 (3), 537–558 Available online http://www.jstor.org/stable/116848 46 Lynch, D., (1993) Alternative measures of financial development Center of Studies of Money, Banking and Finance (CMBF) Paper No University of Macquarie 47 Mankiw, N.G., (1986) The allocation of credit and financial collapse The Quarterly Journal of Economics, 101 (3), 455–470 https://doi.org/10.2307/1885692 Available online 48 Masih, M., Al-Elg, A., Madani, H., (2009) Causality between financial development and economic growth: an application of vector error correction 71 and variance decomposition methods to Saudi Arabia Applied Economics, 41 (13), 1691–1699 49 McKinnon, R.P.I., (1973) Money and Capital in Economic Ddevelopment The Brookings Institution Press., Washington DC 50 Mitchell, K., (1989) Interest Rate Risk at Commercial Banks: An Empirical Investigation Financial Review, 24 (3), 431–455 https://doi.org/10.1111/j.1540-6288.1989.tb00351.x 51 Mushtaq, S., & Siddiqui, D.A., (2017) Effect of interest rate on bank deposits: evidence from Islamic and non-Islamic economies Future Business Journal, (1), 1–8 https://doi.org/ 10.1016/j.fbj.2017.01.002 52 Naveed, M.Y., (2015) Impact of monetary policy shocks in a dual banking system in Pakistan: a vector auto regressive approach (VAR) European Academic Research, (11), 14684–14700 53 Papadamou, S., Siriopoulos, C., (2014) Interest rate risk and the creation of the Monetary Policy Committee: Evidence from banks’ and life insurance companies’ stocks in the UK J Econ Bus 71, 45–67 https://doi.org/10.1016/j.jeconbus.2013.09.001 54 P´erez Montes, C., Ferrer P´erez, A., (2018) The impact of the interest rate level on bank profitability and balance sheet structure Revista de estabilidad financiera 35 (noviembre November 2018), 123–152 Nº 55 Pradhan, R.P., Arvin, B.M., Norman, N.R., Nishigaki, Y., (2014a) Does banking sector development affect economic growth and inflation? A panel cointegration and causality approach Applied Financial Economics, 24 (7), 465–480 https://doi.org/10.1080/09603107.2014.881968 56 Pradhan, R.P., Arvin, M.B., Hall, J.H., Bahrain, S., (2014b) Causal nexus between economic growth, banking sector development, stock market development, and other macroeconomic variables: The case of ASEAN countries Review of Financial Economics, 23 (4), 155–173 doi: 10.1016/j.rfe.2014.07.002 72 57 Robinson, J., (1952) The rate of interest and other essays Chapter the Generalization of the General Theory MacMillan, London 58 Saldías, M., (2017) (WP/17/184) “The Nonlinear Interaction Between Monetary Policy and Financial Stress.” Working Paper International Monetary Fund 59 Saunders, A., & Yourougou, P., (1990) Are banks special? The separation of banking from Commerce and interest rate risk Journal of Economics and Business, 42 (2), 171–182 https://doi.org/ 10.1016/0148-6195(90)90033-9 60 Schaffer, M.E., & Stillman, S., (2010) xtoverid: Stata module to calculate tests of overidentifying restrictions after xtreg, xtivreg, xtivreg2 and xthtaylor Retrieved August 6, 2014 61 Shaw, E.S., (1973) Financial Deepening in Economic Development Oxford University Press, New York 62 Simpson, J.L., & Evans, J.P., (2003) Banking Stock Returns and Their Relationship to Interest Rates and Exchange Rates: Australian Evidence Working Paper, No 5-2003 (Accessed Sep 2) Available online: https://doi.org/10.2139/ssrn.443302 SSRN Journal 63 Sun, L., Wu, S., Zhu, Z., Stephenson, A., (2017) Noninterest Income and Performance of Commercial Banking in China Scientific Programming, 2017, https://doi.org/10.1155/ 2017/4803840 article ID 4803840 64 Tripathi, V., & Ghosh, R., (2012) Interest rate sensitivity of banking stock returns in India Interest rate sensitivity of banking stock returns in India, (4), 18–28 65 Trujillo-Ponce, A., (2013) What determines the profitability of banks? Evidence from Spain Accounting and Finance, 53(2) https://doi.org/10.1111/j.1467-629X.2011.00466.x 66 Tuna, G., & Almahadin, H A., (2021) Does interest rate and its volatility affect banking sector development? Empirical evidence from emerging 73 market economies Research in International Business and Finance, 58 https://doi.org/10.1016/j.ribaf.2021.101436 67 Wang, X., (2020) Frequency dynamics of volatility spillovers among crude oil and international stock markets: the role of the interest rate Energy Economics, 91, 104900 68 White, H., (1980) A heteroskedastic-consistent covariance matrix and a direct test for heteroskedasticity Econometrica 48, 817–838 69 Wiley, J E., & Robertson, D H., (1940) Essays in Monetary Theory Journal of the Royal Statistical Society, 103(3) https://doi.org/10.2307/2980467 70 World Bank, (2021) Global Financial Development Available online: http://data.worldbank.org/data-catalog/world-development-indicators (Accessed March 3, 2021) 71 Wright, R E (2012) Money and Banking Saylor Foundation 72 Yourougou, P., (1990) Interest-rate risk and the pricing of depository financial intermediary common stock Journal of Banking & Finance, 14 (4), 803–820 https://doi.org/10.1016/ 0378-4266(90)90077-F 73 Zhang, J., & Deng, X., (2020) Interest rate liberalization and bank liquidity creation: evidence from China China Finance Review International, 10 (4) 74 Zhou, C., (1996) Stock Market Fluctuations and the Term Structure In: (Accessed Jan 03 1996) Available online: https://ssrn.com/abstract=7277 (3) FEDS, pp 1–30 74 APPENDIX Appendix 1: Creating “Index” by using the principal component analysis (PCA) method pca PC LL BM BD Principal components/correlation Number of obs Number of comp Trace Rho Rotation: (unrotated = principal) = = = = 125 4 1.0000 Component Eigenvalue Difference Proportion Cumulative Comp1 Comp2 Comp3 Comp4 3.53274 413859 0497806 00361615 3.11889 364078 0461645 0.8832 0.1035 0.0124 0.0009 0.8832 0.9867 0.9991 1.0000 Principal components (eigenvectors) Variable Comp1 Comp2 Comp3 Comp4 Unexplained PC LL BM BD 0.5180 0.5199 0.5227 0.4338 -0.2087 -0.2837 -0.2578 0.8997 -0.8266 0.4540 0.3295 0.0459 0.0702 0.6657 -0.7428 0.0134 0 0 predict Index, score (3 components skipped) Scoring coefficients sum of squares(column-loading) = Variable Comp1 Comp2 Comp3 Comp4 PC LL BM BD 0.5180 0.5199 0.5227 0.4338 -0.2087 -0.2837 -0.2578 0.8997 -0.8266 0.4540 0.3295 0.0459 0.0702 0.6657 -0.7428 0.0134 75 Appendix 2: Panel Unit-root Tests LLC test xtunitroot llc RATE, demean lags(1) Levin-Lin-Chu unit-root test for RATE Ho: Panels contain unit roots Ha: Panels are stationary Number of panels = Number of periods = AR parameter: Common Panel means: Included Time trend: Not included Asymptotics: N/T -> 25 Cross-sectional means removed ADF regressions: lag LR variance: Bartlett kernel, 9.00 lags average (chosen by LLC) Statistic Unadjusted t Adjusted t* -6.1325 -3.3384 p-value 0.0004 xtunitroot llc RATE, demean lags(2) Levin-Lin-Chu unit-root test for RATE Ho: Panels contain unit roots Ha: Panels are stationary Number of panels = Number of periods = AR parameter: Common Panel means: Included Time trend: Not included Asymptotics: N/T -> 25 Cross-sectional means removed ADF regressions: lags LR variance: Bartlett kernel, 9.00 lags average (chosen by LLC) Statistic Unadjusted t Adjusted t* -6.1074 -2.6887 p-value 0.0036 The same applies to variables include VR, LL, dLL, PC, dPC, BM, dBM, BD, dBD, Index, dIndex, lnGDP, dlnGDP with lags and 76 IPS test xtunitroot ips RATE, demean lags(0) Im-Pesaran-Shin unit-root test for RATE Ho: All panels contain unit roots Ha: Some panels are stationary Number of panels = Number of periods = 25 AR parameter: Panel-specific Panel means: Included Time trend: Not included Asymptotics: T,N -> Infinity sequentially Cross-sectional means removed ADF regressions: lags Statistic W-t-bar -5.8688 p-value 0.0000 xtunitroot ips VR, demean lags(0) Im-Pesaran-Shin unit-root test for VR Ho: All panels contain unit roots Ha: Some panels are stationary Number of panels = Number of periods = 24 AR parameter: Panel-specific Panel means: Included Time trend: Not included Asymptotics: T,N -> Infinity sequentially Cross-sectional means removed ADF regressions: lags Statistic W-t-bar -4.4230 p-value 0.0000 The same applies to variables include LL, dLL, PC, dPC, BM, dBM, BD, dBD, Index, dIndex, lnGDP, dlnGDP with lags 77 The commands of the two tests are as follows: 78 Appendix 3: Descriptive statistic xtsum dIndex RATE VR dLL dPC dBD dBM dlnGDP Variable Mean Std Dev Min Max Observations dIndex overall between within 080104 2749187 0939826 2616385 -.5986401 -.0243065 -.6592819 1.089743 2231809 1.056638 N = n = T = 120 24 RATE overall between within 0406291 0561855 0073861 0557926 -.2460017 0305395 -.2510324 1915933 0473207 1876665 N = n = T = 125 25 VR overall between within 0215427 0269296 0078919 0259799 0001516 0132981 -.0109459 1821335 0326401 171036 N = n = T = 120 24 dLL overall between within 0232801 0720118 0270465 0677907 -.161167 -.005722 -.1946901 2902852 0662251 2843245 N = n = T = 120 24 dPC overall between within 0131524 0709852 0246208 0674527 -.3272917 -.0092807 -.3048586 2044958 0537514 1866519 N = n = T = 120 24 dBD overall between within 0125064 0575535 0114385 0566291 -.1519578 -.0036161 -.167065 2915706 0276135 2764634 N = n = T = 120 24 dBM overall between within 0223133 0728394 0272328 0686097 -.1611733 -.0033281 -.19448 2902885 0662585 2833611 N = n = T = 120 24 dlnGDP overall between within 036441 4259708 0413637 4243475 -4.250205 -.025047 -4.188717 4345287 0896277 4960167 N = n = T = 120 24 79 Appendix 4: Regression of the model following Pooled OLS, FEM, REM Fixed-effects model xtreg dIndex RATE RATE_SQ VR GDP, fe robust Fixed-effects (within) regression Group variable: id Number of obs Number of groups R-sq: Obs per group: within = 0.4365 between = 0.0620 overall = 0.2771 corr(u_i, Xb) = = 120 = avg = max = 24 24.0 24 = = 4.58 0.0847 F(4,4) Prob > F = -0.3608 (Std Err adjusted for clusters in id) Robust Std Err dIndex Coef t RATE RATE_SQ VR GDP _cons 1.758842 1.475018 -1.416862 -4.009906 2034928 6554052 2.937287 1.612583 1.339586 0799112 sigma_u sigma_e rho 15128883 20336643 35625927 (fraction of variance due to u_i) 2.68 0.50 -0.88 -2.99 2.55 P>|t| 0.055 0.642 0.429 0.040 0.064 [95% Conf Interval] -.0608543 -6.680197 -5.89411 -7.729193 -.0183761 The same applies to dependent variables include dLL, dPC, dBM, dBD The commands of FEM are as follows: 3.578539 9.630233 3.060386 -.2906185 4253618 80 Random-effects model xtreg dIndex RATE RATE_SQ VR GDP, re robust Random-effects GLS regression Group variable: id Number of obs Number of groups R-sq: Obs per group: within = 0.4099 between = 0.0815 overall = 0.2991 corr(u_i, X) = = 120 = avg = max = 24 24.0 24 = = 15.43 0.0039 Wald chi2(4) Prob > chi2 = (assumed) (Std Err adjusted for clusters in id) Robust Std Err dIndex Coef z RATE RATE_SQ VR GDP _cons 1.585382 5.197433 -2.114076 -2.476373 142704 762945 3.21657 1.460427 1.228428 0750669 sigma_u sigma_e rho 20336643 (fraction of variance due to u_i) 2.08 1.62 -1.45 -2.02 1.90 P>|z| 0.038 0.106 0.148 0.044 0.057 [95% Conf Interval] 0900373 -1.106929 -4.976461 -4.884048 -.0044244 The same applies to dependent variables include dLL, dPC, dBM, dBD The commands of REM are as follows: 3.080727 11.5018 7483091 -.0686986 2898324 81 Pooled OLS model regress dIndex RATE RATE_SQ VR GDP Source SS df MS Model Residual 2.6902276 6.30382576 115 6725569 054815876 Total 8.99405336 119 07558028 dIndex Coef RATE RATE_SQ VR GDP _cons 1.585382 5.197433 -2.114076 -2.476373 142704 Std Err .3980388 3.608082 9793845 538937 0433098 t 3.98 1.44 -2.16 -4.59 3.29 Number of obs F(4, 115) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.000 0.152 0.033 0.000 0.001 Appendix 5: Model selection test Pooled OLS, FEM, REM Multicollinearity test vif Variable VIF 1/VIF VR RATE_SQ RATE GDP 1.51 1.47 1.10 1.08 0.662208 0.679476 0.907893 0.926064 Mean VIF 1.29 120 12.27 0.0000 0.2991 0.2747 23413 [95% Conf Interval] 7969439 -1.949483 -4.054048 -3.543904 0569157 The same applies to dependent variables include dLL, dPC, dBM, dBD The commands of Pooled OLS are as follows: = = = = = = 2.37382 12.34435 -.1741036 -1.408843 2284923 82 Correlation coefficient matrix pwcorr dIndex dLL dPC dBM dBD RATE RATE_SQ VR GDP, star(99) dIndex dIndex dLL dPC dBM dBD RATE RATE_SQ VR GDP dPC dBM dBD RATE 1.0000 -0.1884* GDP 1.0000 Breusch and Pagan Lagrangian multiplier test for REM xttest0 Breusch and Pagan Lagrangian multiplier test for random effects dIndex[id,t] = Xb + u[id] + e[id,t] Estimated results: Var dIndex e u Test: RATE_SQ 1.0000 0.9705* 1.0000 0.7813* 0.6404* 1.0000 0.9707* 0.9825* 0.6439* 1.0000 0.8784* 0.8668* 0.4969* 0.8624* 1.0000 0.3629* 0.3517* 0.2314* 0.3695* 0.3660* 1.0000 0.1319* 0.1620* -0.0560* 0.1531* 0.2482* 0.0325* 1.0000 -0.1474* -0.0615* -0.3553* -0.0775* -0.0184* -0.2494* 0.5195* -0.3546* -0.3657* -0.1096* -0.3701* -0.4732* 0.0568* -0.2525* VR VR GDP dLL sd = sqrt(Var) 0755803 0413579 2749187 2033664 Var(u) = chibar2(01) = Prob > chibar2 = 0.00 1.0000 The same applies to dependent variables include dLL, dPC, dBM, dBD 83 Heteroskedasticity test estat imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(13) Prob > chi2 = = 31.33 0.0030 Cameron & Trivedi's decomposition of IM-test Source chi2 df p Heteroskedasticity Skewness Kurtosis 31.33 10.48 2.45 13 0.0030 0.0330 0.1172 Total 44.27 18 0.0005 Autocorrelation (Wooldridge test) xtserial dIndex RATE RATE_SQ VR GDP Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 4) = 0.449 Prob > F = 0.5394 The same applies to dependent variables include dLL, dPC, dBM, dBD 84 Appendix 6: FGLS method xtgls dIndex RATE RATE_SQ VR GDP, panels(hetero) Cross-sectional time-series FGLS regression Coefficients: Panels: Correlation: generalized least squares heteroskedastic no autocorrelation Estimated covariances = Estimated autocorrelations = Estimated coefficients = dIndex Coef RATE RATE_SQ VR GDP _cons 1.235622 4.425357 -1.546188 -1.563154 0940907 5 Number of obs Number of groups Time periods Wald chi2(4) Prob > chi2 Std Err .2805764 2.596135 7432659 4185193 0368892 z 4.40 1.70 -2.08 -3.73 2.55 P>|z| 0.000 0.088 0.038 0.000 0.011 = = = = = 120 24 46.13 0.0000 [95% Conf Interval] 6857025 -.6629737 -3.002962 -2.383436 0217893 1.785542 9.513687 -.0894133 -.742871 1663922 The same applies to dependent variables include dLL, dPC, dBM, dBD The commands of FGLS are as follows: ... graduate thesis on the topic ? ?The impact of interest rate and its volatility on banking sector development: Empirical evidence from Southeast Asia? ?? 1.2 RESEARCH OBJECTIVES AND QUESTIONS 1.2.1 Overall... Scope of content: The primary goal of this thesis is to investigate the impact of interest rates and its volatility on the development of the banking sector in five Southeast Asian countries Clarifying,... fluctuations and the development of the banking sector in the economies of five Southeast Asian countries from 1996 to the end of 2020 From previous studies, the author continues to build on the knowledge