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TABLE OF CONTENT SUPERVISOR’S REMARK ABSTRACT ACKNOWLEDGEMENT LIST OF ABBREVIATIONS LIST OF TABLES AND FIGURES Chapter 1: INTRODUCTION .................................................................................1 1.1. The necessity of the research............................................................................1 1.2. The overview of the research............................................................................1 1.3. The purpose of the research..............................................................................3 1.4. The object and scope of the research................................................................3 1.5. The methods of the research .............................................................................4 1.6. The novelty and contribution of the research ...................................................4 1.7. The structure of the research.............................................................................5 Chapter 2: LITERATURE REVIEW .....................................................................6 2.1. Credit risk and loan loss provisions of commercial banks ...............................6 2.1.1. Credit risk ...................................................................................................6 2.1.2. Loan loss provision ....................................................................................8 2.2. Fundamental literature on determinants of loan loss provisions ....................15 2.2.1. Bankspecific factors................................................................................15 2.2.2. Macroeconomic factors ............................................................................24 Chapter 3: METHODOLOGY ..............................................................................27 3.1. Data and sample..............................................................................................27 3.2. Hypothesis development.................................................................................28 3.3. Variables ........................................................................................................ 28 3.3.1. Dependent variable.................................................................................. 29 3.3.2. Independent variables.............................................................................. 29 3.4. Econometric model ........................................................................................ 35 Chapter 4: DATA ANALYSIS AND RESULTS................................................. 38 4.1. Introduction of Vietnamese commercial banks ............................................. 38 4.3. Regression results .......................................................................................... 44 4.3.1. Descriptive statistics and correlation matrix ........................................... 44 4.3.2. Empirical results...................................................................................... 49 Chapter 5: THE OUTLOOK, ORIENTED DEVELOPMENT AND RECOMMENDATIONS FOR IMPROVEMENT OF LOAN LOSS PROVISIONS OF VIETNAMESE COMMERCIAL BANKS ......................... 59 5.1. The outlook of Vietnamese commercial banks ............................................. 59 5.2. Orientation for loan loss provisions of Vietnamese commercial banks ........ 60 5.3. Recommendations for improvement of loan loss provisions of Vietnamese commercial banks ................................................................................................. 62 5.3.1. Recommendations for commercial banks ............................................... 62 5.3.2. Recommendations for the government.................................................... 70 CONCLUSION....................................................................................................... 78 REFERENCES ....................................................................................................... 79 ANNEX 1 ANNEX 2
FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS GRADUATION THESIS Major: International Business Economics DETERMINANTS OF LOAN LOSS PROVISIONS OF VIETNAMESE COMMERCIAL BANKS Author: Pham Thi Thanh Yen Student ID: 1201016673 Class: K51CLC1 Course: K51 Academic Supervisor: MA Nguyen Thu Hang Thesis ID: 69 Ho Chi Minh City, May 2016 Mã KLTN: 69 TRƯỜNG ĐẠI HỌC NGOẠI THƯƠNG CƠ SỞ II TẠI TP HỒ CHÍ MINH NHẬN XÉT KHĨA LUẬN TỐT NGHIỆP Họ tên sinh viên: Phạm Thị Thanh Yến Tên đề tài: DETERMINANTS OF MSSV: 1201016673 LOAN LOSS PROVISIONS OF VIETNAMESE COMMERCIAL BANKS Điểm tinh thần, thái độ, chuyên cần (tối đa điểm; cho điểm lẻ đến 0,1): Ý kiến nhận xét (khoanh tròn lựa chọn phù hợp): Sinh viên nghiêm túc thực KLTN theo hướng dẫn GVHD GVHD chịu trách nhiệm tên đề tài, mục đích, đối tượng, phạm vi & phương pháp nghiên cứu tên chương, đề mục chi tiết (3 chữ số) Sinh viên thực theo hướng dẫn GVHD chưa đầy đủ GVHD chịu trách nhiệm tên đề tài, mục đích, đối tượng, phạm vi, phương pháp nghiên cứu tên chương, đề mục (2 chữ số) Sinh viên không thực đầy đủ hướng dẫn GVHD GVHD không chịu trách nhiệm đề tài Sinh viên không thực hướng dẫn GVHD GVHD không đồng ý cho sinh viên nộp KLTN Tp Hồ Chí Minh, ngày … tháng … năm 2016 Giảng viên hướng dẫn (Ký ghi rõ họ tên) ABSTRACT The thesis explores the determinants of loan loss provisions of Vietnamese commercial banks including income smoothing, signaling, capital management, procyclical behaviors and other bank-specific factors It does this by looking at a sample of 39 Vietnamese commercial banks over the period 2007 to 2014 By examining the impacts of earlier mentioned factors, this thesis contributes to the literature on how Vietnamese commercial banks use loan loss provisions and why they are set up at a certain level The findings demonstrate that loan loss provisions of commercial banks in Vietnam are in significant relationship with income smoothing, signaling, pro-cyclicality and some other bank-specific factors comprising nonperforming loans, loan growth and one-year ahead provisions Meanwhile, for the conjectures that Vietnamese commercial banks engage in capital management through the manipulation of loan loss provisions and provisions have any significant association with bank size, there is no sufficient evidence to support these suggestions ACKNOWLEDGEMENT The author wants to give best regards and sincere thanks to the author’s supervisor Ms Nguyen Thu Hang for her helpful advices and useful guide throughout the time completing this thesis The author also wants to express great gratitude to all the teachers at Foreign Trade University – Ho Chi Minh City campus for providing and teaching the author with specialized and useful knowledge which stands as a strong basis for this thesis content Despite special drives, certain shortcomings are inevitable throughout this thesis due to strict format regulations together with the lack of practical and specialized experience of the author The author sincerely respects sympathy and concessions in assessment of this thesis Ho Chi Minh City, May 2016 Pham Thi Thanh Yen TABLE OF CONTENT SUPERVISOR’S REMARK ABSTRACT ACKNOWLEDGEMENT LIST OF ABBREVIATIONS LIST OF TABLES AND FIGURES Chapter 1: INTRODUCTION 1.1 The necessity of the research 1.2 The overview of the research 1.3 The purpose of the research 1.4 The object and scope of the research 1.5 The methods of the research .4 1.6 The novelty and contribution of the research 1.7 The structure of the research Chapter 2: LITERATURE REVIEW .6 2.1 Credit risk and loan loss provisions of commercial banks .6 2.1.1 Credit risk 2.1.2 Loan loss provision 2.2 Fundamental literature on determinants of loan loss provisions 15 2.2.1 Bank-specific factors 15 2.2.2 Macroeconomic factors 24 Chapter 3: METHODOLOGY 27 3.1 Data and sample 27 3.2 Hypothesis development 28 3.3 Variables 28 3.3.1 Dependent variable 29 3.3.2 Independent variables 29 3.4 Econometric model 35 Chapter 4: DATA ANALYSIS AND RESULTS 38 4.1 Introduction of Vietnamese commercial banks 38 4.3 Regression results 44 4.3.1 Descriptive statistics and correlation matrix 44 4.3.2 Empirical results 49 Chapter 5: THE OUTLOOK, ORIENTED DEVELOPMENT AND RECOMMENDATIONS FOR IMPROVEMENT OF LOAN LOSS PROVISIONS OF VIETNAMESE COMMERCIAL BANKS 59 5.1 The outlook of Vietnamese commercial banks 59 5.2 Orientation for loan loss provisions of Vietnamese commercial banks 60 5.3 Recommendations for improvement of loan loss provisions of Vietnamese commercial banks 62 5.3.1 Recommendations for commercial banks 62 5.3.2 Recommendations for the government 70 CONCLUSION 78 REFERENCES 79 ANNEX ANNEX 81 20 Blundell, R and S Bond, 1998, Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics 87, 11-143 21 Bouvatier, V and Lepetit, L., 2008, Banks pro-cyclical behavior: does provisioning matter?, Journal of International Financial Markets, Institutions and Money, volume 18, 513-26 22 Bouvatier, V and Lepetit, L., 2012, Effects of Provisioning Rules on Bank Lending: A Theoretical Model, Journal of International Financial Markets, Volume 8, 25-31 23 Bryce, C., Dadoukis, A., Hall, M., Linh, N., and Simper, R., 2015, An analysis of loan loss provisioning behavior in Vietnamese banking, Finance Research Letters Volume 14, 69-75 24 Bushman, R and Williams, C., 2012, Accounting Discretion, Loan Loss Provisioning, and Discipline of Banks’ Risk-Taking, Journal of Accounting and Economics 54, 1-18 25 Cavallo, M and Majnoni, G., 2002, Do banks provision for bad loans in good times? Empirical evidence and policy implications, World Bank Policy Research Working Paper, No 2619 26 Caouette, J B., Altman, E I., Narayanan, P., and Nimmo, R., 2008, Managing Credit Risk: The Great Challenge for Global Financial Markets 2nd Edition, Wiley Finance 27 Chang, R D., Sen, W H., and Fang, C J., 2008, Discretionary Loan Loss Provisions And Earnings Management For The Banking Industry, International Business and Economics Research Journal, Volume 7, Number 3, 9-20 28 Collins, J H., Shackelford, D A., and Wahlen J M., 1995, Bank differences in the coordination of regulatory capital, earnings, and taxes, Journal of Accounting Research 33, 263-291 82 29 Curcio, D., and Hasan, I (2013), Earnings and capital management and signaling: the case of loan loss provisions by European banks, The European Journal of Finance, 1-25 30 Craigwell, R C and Elliott, W A., 2011, Loan loss provisioning in the commercial banking system of Barbados: practices and determinants, Munich Personal RePEc Archive Paper No 33426 31 Dong, X., Liu, J., and Hu, B., 2012, Research on the relationship of commercial bank's loan loss provision and earnings management and capital management, Journal of Service Science and Management, 171-179 32 Eng, L L and Nabar, S., 2007, Loan loss provisions by banks in Hong Kong, Malaysia and Singapore, Journal of International Financial Management and Accounting, 1-21 33 Fernando, W D I and Ekanayake, E M N N., 2015, Do Commercial Banks Use Loan Loss Provisions to Smooth Their Income? Empirical Evidence from Sri Lankan Commercial Banks, Journal of Finance and Bank Management June 2015, Volume 3, No 1, 167-179 34 Floro, D., 2010, Loan Loss Provisioning and the Business Cycle: Does Capital Matter? 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Empirical evidence and policy implications, World Bank Policy Research Working Paper No 2619 52 Minsky, H P., 1982, Can it happen again? Essays on instability and finance, M.E Sharpe, New York 53 Moyer, S E., 1990, Capital adequacy ratio regulations and accounting choices in commercial banks, Journal of Accounting and Economics 13, 123-154 54 Mulford, C W and Comiskey, E E., 2002, The Financial Numbers Game: Detecting Creative Accounting Practices 55 Norden, L and Stoian, A., 2013, Bank earnings management through loan loss provisions: A double-edged sword?, De Nederlandsche Bank, Working Paper No 404 56 Packer, F and Zhu, H., 2012, Loan loss provisioning practices of Asian banks, Bank for international settlements, Working Paper No 375 57 Pain, D., 2003, The provisioning experience of the major UK banks: a small panel, Bank of England, Working Paper No 177 58 Perez, D., Salas, V and Saurina, J., 2006, Earnings and Capital Management in Alternative Loan Loss Provisions Regulatory Regimes, Working Paper 0614, Bank of Spain 85 59 Phuong, N T L., 2015, Solutions for the improvement of loan classification, loan loss reserves in Vietnam Maritime Commercial Joint Stock Bank, Banking Institution 60 Pinho, S P and Martins, N C., 2009, Determinants of Portuguese Bank’s Provisioning Policies: Discretionary Behavior of Generic and Specific Allowances, Journal of Money, Investment and Banking ISSN 1450-288X Issue 10 61 Roodman, D., 2009, How to xtabond2: An introduction to difference and system GMM in Stata, Stata Journal, 9(1), 86-136 62 Santiago, F L and Alicia, G H., 2010, Dynamic Provisioning: Some Lessons from Existing Experiences, Asian Development Bank Institute Working Paper Series, No 218 63 Saurina, J., 2008, Dynamic Provisioning: The Experience of Spain, The World Bank, Note No 64 Schweser Notes, 2013, CFA Level 1, book 5: Fixed income, derivatives, and alternative investments, Kaplan 65 Schweser Notes, 2013, CFA Level 2, book 5: Derivatives and portfolio management, Kaplan 66 Son, N H., Tu, T T T and Yen, T T H., 2014, Bank Restructuring–International Perspectives and Vietnam Practices, Accounting and Finance Research, Volume 3, No 2, 36-50 67 State Bank of Vietnam, 2013, Circular No 02/2013/TT-NHNN 68 Suhartono, 2012, Macroeconomic and bank-specific determinants of loan loss provisioning in Indonesia, Journal of Economics, Business, and Accountancy, 15(3), 359-372 69 Taktak, N B., Shabou, R and Dumontier, P., 2010, Income Smoothing Practices: Evidence from Banks Operating in OECD Countries, International Journal of Economics and Finance, Volume 2, No 4, 140-150 86 70 Valverde, S C and Fernandez, F R., 2014, Do banks game on dynamic provisioning?, Federal Reserve Bank of San Francisco 2015 Summit Meeting, Session 10, 71 Wahlen, J M., 1994, The nature of information in commercial bank loan loss disclosures, The Accounting Review 69 (July), 455-478 72 Walter, J., 1991, Loan loss reserves, Federal Reserve Bank of Richmond’s Economic Review 77, 20-30 73 Wetmore, J and Brick, J., 1994, Loan-Loss Provisions of Commercial Banks and Adequate Disclosure: A Note, Journal of Economics and Business, 46, 299-305 II Websites asianbankingandfinance.net, Vietnamese banks' capitalization to remain depressed by high loan-loss provisions, referenced 27/04/2016, available at: http://asianbankingandfinance.net/retail-banking/news/vietnamese-bankscapitalisation-remain-depressed-high-loan-loss-provisions cafef.vn, NHNN "siêu cổ đông" hệ thống ngân hàng thương mại Việt Nam, referenced 20/03/2016, available at: http://cafef.vn/tai-chinh-ngan-hang/nhnn-la-sieu-co-dong-cua-he-thong-ngan-hangthuong-mai-viet-nam-20151026162427627.chn cafef.vn, Trật tự bảng xếp hạng vốn 36 ngân hàng nay, referenced 20/03/2016, available at: http://cafef.vn/tai-chinh-ngan-hang/trat-tu-moi-trong-bang-xep-hang-von-cua-36ngan-hang-hien-nay-20150913104230311.chn English.vietnamnet.vn, Vietnamese banks enhanced transparency in 2015: Moody's, referenced 27/04/2016, available at: http://english.vietnamnet.vn/fms/business/153069/vietnamese-banks-enhancedtransparency-in-2015 moody-s.html kinhtetaichinh.blogspot.com, Bad debt, referenced 25/02/2016, available at: 87 http://kinhtetaichinh.blogspot.com/2012/07/bad-debt.html?m=1 langkinhkinhte.com, Tổng quan tình hình nợ xấu Việt Nam đến tháng 6/2015, referenced 31/03/2016, available at: http://langkinhkinhte.com/tai-chinh-ngan-hang/item/442-tong-quan-tinh-hinh-noxau-viet-nam-den-thang-6-2015 tinnhanhchungkhoan.vn, Tái cấu trúc ngân hàng qua bước đầu, referenced 31/03/2016, available at: http://tinnhanhchungkhoan.vn/tien-te/tai-cau-truc-ngan-hang-moi-chi-qua-duocbuoc-dau-118770.html vietbao.vn, Tái cấu đưa nợ xấu từ 17% xuống 3% nào?, referenced 31/03/2016, available at: http://vietbao.vn/Kinh-te/Tai-co-cau-da-dua-no-xau-tu-17-xuong-3-nhu-thenao/2147603234/90/ bvsc.com.vn, Áp lực trích lập dự phịng rủi ro 2016, referenced 27/04/2016, available at: http://www.bvsc.com.vn/News/2016129/414258/ap-luc-trich-lap-du-phong-rui-ro2016.aspx 10 div.gov.vn, Hóa giải toán nợ xấu, referenced 01/05/2016, available at: http://www.div.gov.vn/Default.aspx?tabid=122&CategoryID=1&News=2766 11 economicshelp.org, Policies To Reduce Inflation, referenced 30/04/2016, available at: https://www.economicshelp.org/blog/42/inflation/economic-policies-to-reduceinflation/ 88 ANNEX LIST OF 39 RESEARCHED COMMERCIAL BANKS Number Abbreviation ABBANK ACB AGRIBANK BAOVIETBANK BIDV DAIABANK DONGABANK EXIMBANK 10 11 12 FICOMBANK GPBANK HABUBANK HDBANK 13 14 15 KIENLONGBANK LIENVIETBANK MARITIMEBANK 16 17 18 19 20 MB MDB MHB NAMABANK NCB 21 22 23 OCB OCEANBANK PGBANK 24 SACOMBANK 25 26 27 28 29 30 SAIGONBANK SCB SEABANK SHBANK SOUTHERNBANK TECHCOMBANK 31 TIENPHONGBANK Names An Binh Commercial Joint Stock Bank Asia Commercial Joint Stock Bank Vietnam Bank for Agriculture and Rural Development Bao Viet Commercial Bank Joint Stock Commercial Bank for Investment and Development of Vietnam Dai A Commercial Bank Joint Stock Bank Dong A Commercial Joint Stock Bank Vietnam Export Import Commercial Joint Stock Bank First Joint Stock Commercial Bank Global Petro Commercial Joint Stock Bank Hanoi Building Commercial Joint Stock Bank Ho Chi Minh City Development Commercial Joint Stock Bank Kien Long Commercial Joint Stock Bank Lien Viet Post Commercial Joint Stock Bank Vietnam Maritime Commercial Joint Stock Bank Military Commercial Joint Stock Bank Mekong Development Joint Stock Bank Mekong Housing Bank Nam A Commercial Joint Stock Bank National Citizen Commercial Joint Stock Bank Orient Commercial Joint Stock Bank Ocean Commercial Joint Stock Bank Petrolimex Group Commercial Joint Stock Bank Saigon Thuong Tin Commercial Joint Stock Bank Saigon Bank for Industry and Trade Saigon Commercial Joint Stock Bank Southeast Asia Commercial Joint Stock Bank Saigon Hanoi Commercial Joint Stock Bank Southern Commercial Joint Stock Bank Vietnam Technology and Commercial Joint Stock Bank Tien Phong Commercial Joint Stock Bank 89 32 33 34 35 36 37 38 39 TINNGHIABANK Vietnam Tin Nghia Commercial Joint Stock Bank VIB Vietnam International Commercial Joint Stock Bank VIETABANK Vietnam Asia Commercial Joint Stock Bank VIETCAPITALBANK Vietnam Capital Commercial Joint Stock Bank VIETCOMBANK Joint Stock Commercial Bank for Foreign Trade of Vietnam VIETINBANK Vietnam Joint Stock Commercial Bank for Industry and Trade VPBANK Vietnam Prosperity Commercial Joint Stock Bank WESTERNBANK Western Commercial Joint Stock Bank 90 ANNEX REGRESSION RESULTS PERFORMED ON STATA 12 OLS regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, CAP, SIGN, SZ, NPL, LG, GDPG, INF, and GFC reg llp lag ebtp cap sign sz npl lg gdpg inf gfc, cluster(bank1) Linear regression Number of obs = F( 10, 38) = Prob > F = R-squared = Root MSE = 139 32.00 0.0000 0.4805 30008 (Std Err adjusted for 39 clusters in bank1) llp Coef lag ebtp cap sign sz npl lg gdpg inf gfc _cons 5455994 11.14538 -.6494483 0797729 -.0497409 0358452 -.4604966 -.1024376 -.0049664 -.1147888 6743215 Robust Std Err .0749118 3.399951 3828031 0242202 0316194 0274929 2910572 1400845 0040625 1106104 1.013306 t 7.28 3.28 -1.70 3.29 -1.57 1.30 -1.58 -0.73 -1.22 -1.04 0.67 P>|t| 0.000 0.002 0.098 0.002 0.124 0.200 0.122 0.469 0.229 0.306 0.510 [95% Conf Interval] 3939484 4.262539 -1.424393 0307416 -.113751 -.0198113 -1.049711 -.3860238 -.0131906 -.3387078 -1.377008 6972505 18.02822 1254962 1288041 0142692 0915016 128718 1811486 0032577 1091303 2.725651 FEM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, CAP, SIGN, SZ, NPL, LG, GDPG, INF, and GFC xtreg llp lag ebtp cap sign sz npl lg gdpg inf gfc, fe Fixed-effects (within) regression Group variable: bank1 Number of obs Number of groups = = 139 39 R-sq: Obs per group: = avg = max = 3.6 within = 0.1960 between = 0.2792 overall = 0.2449 corr(u_i, Xb) F(10,90) Prob > F = -0.0675 llp Coef lag ebtp cap sign sz npl lg gdpg inf gfc _cons 3569806 8.872994 271607 0619317 -.1228956 0055832 -.4498483 -.1642296 -.0049456 -.241281 2.665088 1526684 6.542454 8660329 041197 1311269 0264686 3968448 1048323 0065756 1492309 2.643627 sigma_u sigma_e rho 24591113 31801987 37418901 (fraction of variance due to u_i) F test that all u_i=0: Std Err F(38, 90) = t 2.34 1.36 0.31 1.50 -0.94 0.21 -1.13 -1.57 -0.75 -1.62 1.01 0.63 P>|t| = = 0.022 0.178 0.755 0.136 0.351 0.833 0.260 0.121 0.454 0.109 0.316 2.19 0.0250 [95% Conf Interval] 0536782 -4.124732 -1.448918 -.0199134 -.3834021 -.0470012 -1.23825 -.3724974 -.018009 -.5377543 -2.586939 660283 21.87072 1.992132 1437767 1376108 0581676 3385532 0440381 0081179 0551923 7.917116 Prob > F = 0.9434 91 GMM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, CAP, SIGN, SZ, NPL, LG, GDPG, INF, and GFC xtabond2 llp lag ebtp cap sign sz npl lg gdpg inf gfc, gmm(llp, lag(2 2)) iv(ebtp cap sign sz npl lg gdpg inf gfc) twostep robust small or > thogonal Favoring speed over space To switch, type or click on mata: mata set matafavor space, perm Warning: Two-step estimated covariance matrix of moments is singular Using a generalized inverse to calculate optimal weighting matrix for two-step estimation Difference-in-Sargan/Hansen statistics may be negative Dynamic panel-data estimation, two-step system GMM Group variable: bank1 Time variable : years Number of instruments = 22 F(10, 38) = 21.61 Prob > F = 0.000 llp Coef lag ebtp cap sign sz npl lg gdpg inf gfc _cons 5073007 12.50481 -.5964141 0832292 -.0484661 0398282 -.4563499 -.1618398 -.006729 -.1468056 9633174 Number of obs Number of groups Obs per group: avg max Corrected Std Err .2013605 4.818119 4229742 0327657 04675 0213822 2314785 0899704 0034296 0985559 934337 t 2.52 2.60 -1.41 2.54 -1.04 1.86 -1.97 -1.80 -1.96 -1.49 1.03 P>|t| 0.016 0.013 0.167 0.015 0.306 0.070 0.056 0.080 0.057 0.145 0.309 = = = = = 139 39 3.56 [95% Conf Interval] 0996677 2.751042 -1.452681 0168986 -.1431065 -.0034577 -.9249536 -.3439754 -.0136718 -.3463217 -.9281489 9149337 22.25859 2598523 1495598 0461743 0831142 0122538 0202958 0002138 0527104 2.854784 Instruments for orthogonal deviations equation Standard FOD.(ebtp cap sign sz npl lg gdpg inf gfc) GMM-type (missing=0, separate instruments for each period unless collapsed) L2.llp Instruments for levels equation Standard ebtp cap sign sz npl lg gdpg inf gfc _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL.llp Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(11) = 37.73 but not weakened by many instruments.) overid restrictions: chi2(11) = 10.33 weakened by many instruments.) 0.13 0.23 Pr > z = Pr > z = 0.893 0.816 Prob > chi2 = 0.000 Prob > chi2 = 0.501 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 8.82 Prob > Difference (null H = exogenous): chi2(6) = 1.51 Prob > iv(ebtp cap sign sz npl lg gdpg inf gfc) Hansen test excluding group: chi2(2) = 1.48 Prob > Difference (null H = exogenous): chi2(9) = 8.85 Prob > chi2 = chi2 = 0.116 0.959 chi2 = chi2 = 0.477 0.451 92 GMM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, CAP, SIGN, NPL, LG, GDPG, INF, and GFC xtabond2 llp lag ebtp cap sign npl lg gdpg inf gfc, gmm(llp, lag(2 2)) iv(ebtp cap sign npl lg gdpg inf gfc) twostep robust small ortho > gonal Favoring speed over space To switch, type or click on mata: mata set matafavor space, perm Warning: Two-step estimated covariance matrix of moments is singular Using a generalized inverse to calculate optimal weighting matrix for two-step estimation Difference-in-Sargan/Hansen statistics may be negative Dynamic panel-data estimation, two-step system GMM Group variable: bank1 Time variable : years Number of instruments = 21 F(9, 38) = 19.56 Prob > F = 0.000 llp Coef lag ebtp cap sign npl lg gdpg inf gfc _cons 5240889 11.94881 -.2847657 0665148 0387378 -.418792 -.1519237 -.0052455 -.1135779 1949217 Number of obs Number of groups Obs per group: avg max Corrected Std Err .2081229 4.697251 3985239 0215926 0224686 2312348 0839589 0033219 0948969 6840951 t 2.52 2.54 -0.71 3.08 1.72 -1.81 -1.81 -1.58 -1.20 0.28 P>|t| 0.016 0.015 0.479 0.004 0.093 0.078 0.078 0.123 0.239 0.777 = = = = = 139 39 3.56 [95% Conf Interval] 1027661 2.439724 -1.091535 0228028 -.0067475 -.8869024 -.3218896 -.0119704 -.3056867 -1.189956 9454117 21.4579 5220037 1102267 0842231 0493185 0180422 0014793 0785309 1.5798 Instruments for orthogonal deviations equation Standard FOD.(ebtp cap sign npl lg gdpg inf gfc) GMM-type (missing=0, separate instruments for each period unless collapsed) L2.llp Instruments for levels equation Standard ebtp cap sign npl lg gdpg inf gfc _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL.llp Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(11) = 37.51 but not weakened by many instruments.) overid restrictions: chi2(11) = 9.87 weakened by many instruments.) 0.05 0.21 Pr > z = Pr > z = 0.960 0.834 Prob > chi2 = 0.000 Prob > chi2 = 0.542 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 8.79 Prob > Difference (null H = exogenous): chi2(6) = 1.08 Prob > iv(ebtp cap sign npl lg gdpg inf gfc) Hansen test excluding group: chi2(3) = 5.16 Prob > Difference (null H = exogenous): chi2(8) = 4.71 Prob > chi2 = chi2 = 0.118 0.982 chi2 = chi2 = 0.161 0.788 93 GMM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, SIGN, SZ, NPL, LG, GDPG, INF, and GFC xtabond2 llp lag ebtp sign sz npl lg gdpg inf gfc, gmm(llp, lag(2 2)) iv(ebtp sign sz npl lg gdpg inf gfc) twostep robust small orthogo > nal Favoring speed over space To switch, type or click on mata: mata set matafavor space, perm Warning: Two-step estimated covariance matrix of moments is singular Using a generalized inverse to calculate optimal weighting matrix for two-step estimation Difference-in-Sargan/Hansen statistics may be negative Dynamic panel-data estimation, two-step system GMM Group variable: bank1 Time variable : years Number of instruments = 21 F(9, 38) = 24.00 Prob > F = 0.000 llp Coef lag ebtp sign sz npl lg gdpg inf gfc _cons 5283578 9.396396 0870762 -.0269463 0377996 -.4666915 -.1574802 -.0057645 -.1278706 4819032 Number of obs Number of groups Obs per group: avg max Corrected Std Err .2407093 4.469599 0304467 0442822 0226368 3043791 09547 0039441 0989598 9408518 t 2.20 2.10 2.86 -0.61 1.67 -1.53 -1.65 -1.46 -1.29 0.51 P>|t| 0.034 0.042 0.007 0.546 0.103 0.133 0.107 0.152 0.204 0.611 = = = = = 139 39 3.56 [95% Conf Interval] 0410673 348167 0254401 -.1165909 -.0080262 -1.082875 -.3507491 -.0137488 -.3282042 -1.422752 1.015648 18.44463 1487123 0626983 0836254 1494917 0357887 0022198 0724629 2.386558 Instruments for orthogonal deviations equation Standard FOD.(ebtp sign sz npl lg gdpg inf gfc) GMM-type (missing=0, separate instruments for each period unless collapsed) L2.llp Instruments for levels equation Standard ebtp sign sz npl lg gdpg inf gfc _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL.llp Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(11) = 39.17 but not weakened by many instruments.) overid restrictions: chi2(11) = 10.47 weakened by many instruments.) 0.14 0.31 Pr > z = Pr > z = 0.891 0.757 Prob > chi2 = 0.000 Prob > chi2 = 0.489 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 8.91 Prob > Difference (null H = exogenous): chi2(6) = 1.56 Prob > iv(ebtp sign sz npl lg gdpg inf gfc) Hansen test excluding group: chi2(3) = 5.51 Prob > Difference (null H = exogenous): chi2(8) = 4.96 Prob > chi2 = chi2 = 0.113 0.955 chi2 = chi2 = 0.138 0.762 94 GMM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, CAP, SZ, NPL, LG, GDPG, INF, and GFC xtabond2 llp lag ebtp cap sz npl lg gdpg inf gfc, gmm(llp, lag(2 2)) iv(ebtp cap sz npl lg gdpg inf gfc) twostep robust small orthogona > l Favoring speed over space To switch, type or click on mata: mata set matafavor space, perm Warning: Two-step estimated covariance matrix of moments is singular Using a generalized inverse to calculate optimal weighting matrix for two-step estimation Difference-in-Sargan/Hansen statistics may be negative Dynamic panel-data estimation, two-step system GMM Group variable: bank1 Time variable : years Number of instruments = 21 F(9, 38) = 14.88 Prob > F = 0.000 llp Coef lag ebtp cap sz npl lg gdpg inf gfc _cons 3273694 15.0381 -.3764842 0376344 0315208 -.3396399 -.0855005 -.0040481 -.0505194 -.0712912 Number of obs Number of groups Obs per group: avg max Corrected Std Err .1176862 3.402709 3103305 0365578 0247768 3415021 067311 0047876 0794717 8689709 t 2.78 4.42 -1.21 1.03 1.27 -0.99 -1.27 -0.85 -0.64 -0.08 P>|t| 0.008 0.000 0.233 0.310 0.211 0.326 0.212 0.403 0.529 0.935 = = = = = 223 39 5.72 [95% Conf Interval] 0891261 8.149672 -1.004715 -.0363731 -.0186372 -1.030975 -.2217645 -.0137401 -.2114015 -1.830431 5656127 21.92652 251747 1116419 0816787 3516951 0507635 0056439 1103626 1.687848 Instruments for orthogonal deviations equation Standard FOD.(ebtp cap sz npl lg gdpg inf gfc) GMM-type (missing=0, separate instruments for each period unless collapsed) L2.llp Instruments for levels equation Standard ebtp cap sz npl lg gdpg inf gfc _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL.llp Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(11) = 38.24 but not weakened by many instruments.) overid restrictions: chi2(11) = 21.28 weakened by many instruments.) -2.40 -0.42 Pr > z = Pr > z = 0.016 0.671 Prob > chi2 = 0.000 Prob > chi2 = 0.031 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 10.54 Prob > Difference (null H = exogenous): chi2(6) = 10.74 Prob > iv(ebtp cap sz npl lg gdpg inf gfc) Hansen test excluding group: chi2(3) = 2.58 Prob > Difference (null H = exogenous): chi2(8) = 18.69 Prob > chi2 = chi2 = 0.061 0.097 chi2 = chi2 = 0.460 0.017 95 GMM regression of loan loss provisions (LLP) with independent variables: LAG, EBTP, NPL, LG, GDPG, INF, and GFC xtabond2 llp lag ebtp npl lg gdpg inf gfc, gmm(llp, lag(2 2)) iv(ebtp npl lg gdpg inf gfc) twostep robust small orthogonal Favoring speed over space To switch, type or click on mata: mata set matafavor space, perm Warning: Two-step estimated covariance matrix of moments is singular Using a generalized inverse to calculate optimal weighting matrix for two-step estimation Difference-in-Sargan/Hansen statistics may be negative Dynamic panel-data estimation, two-step system GMM Group variable: bank1 Time variable : years Number of instruments = 19 F(7, 38) = 11.35 Prob > F = 0.000 llp Coef lag ebtp npl lg gdpg inf gfc _cons 392213 12.69707 0193809 -.3827745 -.0896174 -.0049928 -.0891967 6423601 Number of obs Number of groups Obs per group: avg max Corrected Std Err .1152596 2.898599 0197135 2798526 0647788 0043627 0706794 364396 t 3.40 4.38 0.98 -1.37 -1.38 -1.14 -1.26 1.76 P>|t| 0.002 0.000 0.332 0.179 0.175 0.260 0.215 0.086 = = = = = 223 39 5.72 [95% Conf Interval] 1588822 6.829161 -.0205271 -.9493065 -.2207551 -.0138246 -.2322796 -.095321 6255438 18.56497 0592888 1837576 0415204 003839 0538862 1.380041 Instruments for orthogonal deviations equation Standard FOD.(ebtp npl lg gdpg inf gfc) GMM-type (missing=0, separate instruments for each period unless collapsed) L2.llp Instruments for levels equation Standard ebtp npl lg gdpg inf gfc _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL.llp Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(11) = 42.22 but not weakened by many instruments.) overid restrictions: chi2(11) = 20.11 weakened by many instruments.) -2.47 -0.16 Pr > z = Pr > z = 0.013 0.873 Prob > chi2 = 0.000 Prob > chi2 = 0.044 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 10.91 Prob > Difference (null H = exogenous): chi2(6) = 9.20 Prob > iv(ebtp npl lg gdpg inf gfc) Hansen test excluding group: chi2(5) = 4.70 Prob > Difference (null H = exogenous): chi2(6) = 15.42 Prob > chi2 = chi2 = 0.053 0.163 chi2 = chi2 = 0.454 0.017