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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 MACROECONOMIC, FINANCIAL AND INSTI[.]
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 MACROECONOMIC, FINANCIAL AND INSTITUTIONAL DETERMINANTS OF BANKING CRISIS: THE MONEY MARKET PRESSURE INDEX APPROACH A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By CHAU THE VINH Academic Supervisor: Assoc Prof NGUYEN TRONG HOAI HO CHI MINH CITY, December2014 CERTIFICATION “I certify that the substance of this thesis has not already been submitted for any degree and has not been currently submitted for any other degree I certify that to the best of my knowledge and help received in preparing this thesis and all used sources have acknowledged in this dissertation” CHAU THE VINH Date: 31st December 2014 i ACKNOWLEDGEMENT Upon completing this thesis, I have received a great deal of encouragement and support from many people First of all, I would like to express my deepest gratitude towards Assoc Prof Nguyen Trong Hoai, my esteemed academic supervisor, for his patient guidance, encouragement and valuable critiques for my research work Also, I would like to thank Dr Truong Dang Thuy for his guidance and advice in econometric techniques, Dr Pham Khanh Nam for his encouragement and valuable advice in the starting phase of my thesis research design My gratefulness is also extended to all of my lecturers and staffs of the VietnamNetherlands Program for their assistance during my first days in this programme Besides, I would love to thank my parents and my families for their ceaseless encouragement and support during my study period Moreover, my special thanks to my C.E.O – Mr Nguyen Huu Tram, who understands and gives me approval for my long personal leave to finalize my thesis on time Without them, I would not have opportunities and incentives to have my thesis finished Finally, I would like to thank all my friends and other people who have had any help and support for my thesis but are not above-mentioned ii ABSTRACT The thesis estimates a logit regression model by fixed effect with a combination of some macroeconomic and financial indicators from the work of Hagen and Ho (2007) and Worldwide Governance Indicators (WGI) from the updated database of Kaufmann (2013) as explanatory variables for binary dependent variable banking crises generated from the approach of money market pressure index (Hagen and Ho, 2007) The monthly panel dataset, which is available in full range and easy of approach from International Financial Statistics CD-ROM (2011), of 18 countries from Latin America and Asian over the scope of 2001 – 2010is applied Some specific lag lengths of indicators are also applied according to the suggestion of “flexibility in forecast horizon” of Drehmann et al (2011) The crisis phenomenon of banking system seems to be well-described in light of the present of depreciation, former year crisis, high real interest rate in prior of 36 months, growth of credit to GDP in prior 12 months Moreover, impact of inflation seems to support the school of thought that it is negative effect to crisis Simultaneously, growth rate of bank deposits to GDP is likely useful to prevent banking systems from profitability risks exposure that leads to banking crisis probability However, unfortunately, the indicators of growth of monetary base and growth of M2 to reserves give incorrect expected sign and negligible effect on banking crisis Furthermore, the included institutional variables from WGI give insignificant statistic meaning Hence, another set of institutional indicators such as that from International Country Risk Guide (ICRG) should be considered in future analysis to test for the relationship between Government health and banking crisis probability Despite, on one hand, there should be a more adequate research to be examined in the future, this thesis attempts to contribute so-called new updates information on the would-be banking crisis determinants Nevertheless, on the other hand, there is likely no proper explanation on the tranquil periods of banking system Hence, it is iii suggested that thereshould be some assessment ofsuch time of banking system, which over a long time has beenneglected (Kauko, 2014) Key words: banking crisis, tranquiltime, determinants, institutional indicators, fixed effect logitregression iv TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objective 1.3 Research question 1.4 Structure of the thesis CHAPTER 2: LITERATURE REVIEW 2.1 Defining banking crisis 2.2 Trends of banking crises researchtogether with crises mechanism 2.2.1 The first trend 2.2.2 The second trend 10 2.2.3 The third trend 14 2.3 Money Market Pressure (MMP) Index (Hagen and Ho, 2007) 19 2.4 Chapter summary 21 CHAPTER 3: METHODOLOGY, MODEL SPECIFICATION AND DATA 28 3.1 Model selection 28 3.2 Model specification 31 3.2.1 Macroeconomic indicators 33 3.2.2 Financial indicators 34 3.2.3 Institutional indicators 36 3.2.4 Use of lagged terms 37 3.3 Estimation strategies and relevant model diagnostics 40 3.3.1 Calculation of MMP for banking crisis assessment 40 3.3.2 Model estimation steps and diagnostics 41 3.4 Data scope and sources 43 3.5 Conceptual framework 46 3.6 Research Process 47 CHAPTER 4: RESUTLS AND FINDINGS 48 4.1 Descriptive statistics of explanatory indicators 48 4.2 Statistical tests for model 51 4.2.1 Model specification test 51 4.1.2 Goodness of fit test 51 4.1.3 Test for multicollinearity 51 v 4.3 Coefficients interpretation 53 4.3.1 Macroeconomic indicators 53 4.3.2 Financial indicators 55 4.3.3 Institutional indicators 57 CHAPTER 5: CONCLUSION, POLICY RECOMMENDATION AND LIMITATION 58 5.1 Conclusion 58 5.2 Policy recommendation 58 5.3 Limitation of the research 60 REFERENCES 61 APPENDICES 65 Table 2.1 Summary of literature reviewed 22 Figure 2.1 Mechanisms of banking crisis 27 Table 3.1 Data for MMP index calculation 44 Table 3.2 Data and sources of explanatory variables 45 Table 4.1 Banking crisis dates retrieved from MMP index 65 Table 4.2 Summary statistics of variables used in the regression 49 Table 4.3a The correlation on the sample observations 50 Table 4.3b The correlation on the sample observations 50 Table 4.4Linktest for specification error of logit model 66 Table 4.5 Goodness of fit test of model 67 Tabel 4.6 Full model multicollinearity test result 67 Table 4.7 Dropping significantly high correlated variables GE, RL: 68 Table 4.8 Dropping high correlated variables GE, RL and CC 68 Table 4.9 Using interactive term of GE and RL 69 Table 4.10 Full model 69 Table 4.11 Restricted model without GE, RL, CC 70 Table 4.12 Fixed effect model with lags 70 Table 4.13 Random effect model with lags 71 Table 4.14 Simple logit model with lags 72 Table 4.15Comparison of lagged terms of indicators in simple logit, FEM and REM 73 vi ABBREVIATION MMP: Money Market Pressure WGI: World Governance Indicator WB: World Bank IMF: International Monetary Fund IFS: International Financial Statistics ICRG: International Country Risks Guide FEM: Fixed Effect Model REM: Random Effect Model BC: Banking Crisis vii CHAPTER 1: INTRODUCTION 1.1 Problem statement Banking crisis in nowadays economies is not a new issue or even an old one that has been given awareness to, discussed and researched from many angles and perspectives by applying many approaches from simple to complicate There have been three trends of banking system crisis researches from its first trend of qualitative description by Friedman and Schwartz (1963) about US crisis over its past decades to the second trend in which econometric analysis with panel data were employed according to relatively enough banking crises observations and to the third trend since the 2007 “global financial turmoil” The trends of banking crisis research contribute most of important indicators related to macroeconomics and banking sectors such as reserves, current account, real exchange rate (Kaminsky et al, 1998) Despite the fact that the logistic regression approach focused more on quantitative economics model, it has seemed to be an important tool for anticipating the crisis signals and timing as well as significant indicators However, there was also some noise that could affect the effectiveness of this model Hence, it led to the rise of further studies in terms of developing new method and other new critical variables As suggested, there have been many criteria to help researchers with banking crisis identification Amongst, money market pressure index from the work of Hagen and Ho (2007), who expanded the literature of Eichengreen, Rose, and Wyplosz (1995, 1996a, 1996b) for currency crisis, stands out to be convenient for understanding and data collecting but still provide good judgment value for banking crisis symptom Such index observed the periods that banking systems experience its liquidity problem by considering simultaneously the phenomenon of both high central bank reserves demand and fluctuations of short-term real interest rate Originally, the index provides the criterion to indicate whether there is a crisis or not under the scope analyzed Banks relevant data, to some extent, seems to be difficult to obtain precisely due to i their sensitiveness Given those difficulties, the research will make use of macroeconomic indicators as suggested in a survey that emphasized “the analysis of macroeconomic variables is of some help for banking supervisors in order to fully assess banks’ health” (Quagliariello, 2008) In accordance with both suggestion from Quagliariello (2008) and Hagen and Ho (2007), some available macroeconomic and financial variables such as inflation, growth of monetary base, depreciation, real interest rate, growth of private credit over GDP, growth of deposits over GDP and growth of M2 over reserves are examined In recent years, there has been the use of institutional signals (Kaufmann et al, 2008) to predict for the probability of vulnerability and crisis occurrence besides quantitative economic indicators to enhance the limitation of the model by Kaminsky et al (1998) Moreover, being motivated by the work of Breuer et al (2006) on institutional variables and currency crisis, this research will take this idea together with the combination with six updated world governance indicators (Kaufmann, 2013) namely voice and accountability, government effectiveness, political stability, rule of law, regulatory quality, control of corruption to assess the role of “health” of Government in the relationship with crisis time of the banking systems Last but not least, the 12-month lagged term of banking crisis included into the regression model (Falcetti and Tudela, 2006) also give significant assessment Nevertheless, it seems that most of relevant researches tend to try to explain the reasons for a banking crisis occurrence but not that why banking crisis does not take place in some situation over some period in some country The attempt to understand or even forecast the crisis is important on one hand But, on the other hand, future researches should be carried out with the tranquil time of the banking system, i.e the “non-crisis” situation, still has its important role which seems to be belittled or even no need to be explained (Kauko, 2014) Although there have been researches and studies on banking crisis, it seems that there are likely few works considering simultaneously the health of Government, macroeconomic and financial background in a same model Thus, the contribution ... contribute so-called new updates information on the would-be banking crisis determinants Nevertheless, on the other hand, there is likely no proper explanation on the tranquil periods of banking system... control of corruption to assess the role of “health” of Government in the relationship with crisis time of the banking systems Last but not least, the 12-month lagged term of banking crisis included... introduction of three trends of banking crisis analyses The third part of this section gives detailed explanation and discussion on money market pressure index used by Hagen and Ho (2007 )and the last