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VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS EARLY WARNING SYSTEM FOR SOVEREIGN DEBT CRISIS IN DEVELOPING COUNTRIES FOR PERIOD 1981-2010 Supervisor: Prof Dr Nguyen TrongHoai Student: Vu ThiLan Phuong Class: MDE 20 Ho Chi Minh City, October 2016 ABSTRACT This study constructed an Early warning system to explain and predict sovereign debt crisis in 31 developing countries whose data is available through the period 1981-2010 at one year precedence by employing three-stage strategy with multinomial logit regression While three-stage strategy allowed selecting the best predictors among wide range of explanatory variables, multinomial logit regression solved “post-crisis” bias and thus, improved prediction quality The main findings are: (i) Solvency, measured by Public debt over GDP ratio, is positively correlated with sovereign debt crisis; (ii) Liquidity measures are highly associated with sovereign debt crisis When short-term debt to total external debt ratio grows up or reserves to total external debt ratio decrease, the likelihood of both entering into debt crisis and remaining in debt crisis rises; (iii) The macroeconomic fundamentals significantly affect sovereign debt crisis: while GDP per capita growth rate is negatively associated with both entering into and remaining in crisis , inflation only affect positively post-crisis period; (iv) The international liquidity, represented by the three-month the U.S Treasury bill rate, is highly associated with the first year of crisis and the following years of crisis rather than the initial year of crisis and (v) both external trade link and political institution measurements not impact on sovereign debt crisis As a result, the study specified a multinomial logit Early warning model predicting sovereign debt crisis at one year precedence with six determinants namely Public debt over GDP ratio, Short-term debt to total external debt ratio, Reserves to total external debt ratio, GDP per capita growth rate, Inflation rate and Three-month the U.S Treasury bill rate In addition, several policy implications are recommended for the countries to avert sovereign debt crisis ACKNOWLEDGEMENT First and foremost, I would like to take this opportunity to express my sincere gratitude to Prof Dr Nguyen Trong Hoai, my supervisor, for his strong support and useful advice from the very first days of my research work He was patient and sympathetic towards my delay His inspiration as well as prompt and intellectual guidance has encouraged me to finish the thesis Finally, I would like to express my deepest grateful to my family, my colleagues and my friends for their continuous encouragement and support during the time I were busy with the study Thanks to their understanding and help, my thesis was finally completed TABLE OF CONTENTS CHAPTER I: INTRODUCTION 1.1 RESEARCH STATEMENT 1.2 RESEARCH OBJECTIVES 1.3 RESEARCH QUESTIONS 1.4 RESEARCH STRUCTURE CHAPTER II: LITERATURE REVIEW 2.1 SOVEREIGN DEBT CRISIS AND EARLY WARNING SYSTEM 2.1.1 Sovereign debt crisis 2.1.2 Early warning system (EWS) 2.2 THEORETICAL LITERATURE ON DEBT DEFAULT 2.2.1 Model of debt overhang 2.2.2 Model of debt repudiation 2.3 EMPIRICAL LITERATURE ON SOVEREIGN DEBT CRISIS 11 2.3.1 Sovereign debt crisis and liquidity measures 11 2.3.2 Sovereign debt crisis and solvency measures 12 2.3.3 Sovereign debt crisis and macroeconomics fundamentals 13 2.3.4 Sovereign debt crisis and external trade link 13 2.3.5 Sovereign debt crisis and political institutions 14 2.3.6 Sovereign debt crisis and global liquidity 15 2.4 CHAPTER REMARKS .16 CHAPTER III: RESEARCH METHODOLOGY 18 3.1 MODEL SPECIFICATION 18 3.2 VARIABLES AND MEASUREMENTS 20 3.2.1 Sovereign debt crisis 20 3.2.2 Explanatory variables 22 3.2.2.1 Country characteristics 22 3.2.2.2 Exogenous factor 25 3.2.3 Analytical framework for the study 25 3.3 DATA SOURCES 27 3.4 ESTIMATION METHOD 27 CHAPTER IV: RESEARCH RESULTS 30 4.1 PRELIMINARY STATISTICS 30 4.2 REGRESSION RESULTS FOR EWS .33 4.2.1 Individual regression 33 4.2.2 Backward stepwise regression 35 4.2.3 Multinomial logit regression and final specification 35 4.2.4 Result discussion 39 4.2 CHAPTER REMARKS 44 CHAPTER V: CONCLUSION 46 5.1 CONCLUSION 46 5.2 POLICY IMPLICATIONS 48 5.3 RESEARCH LIMITATION 49 5.4 FURTHER RESEARCH RECOMMENDATION 50 REFERENCE 51 APPENDICES 54 LIST OF ABBREVIATIONS CPIA Country Policy and Institutional Assessment EWS Early Warning System FDI Foreign Direct Investment GDP Gross Domestic Product IMF International Monetary Fund M2 Broad Money Supply NEER Nominal effective exchange rate REER Real effective exchange rate U.S United States WB World Bank WDI World Bank Development Indicators WEO World Economic Outlook Database WGI Worldwide Governance Indicators LIST OF TABLES Table 3.1: Regime definition in Multinomial logit model 19 Table 3.2: Countries and sovereign debt crisis episodes during 1980-2010 21 Table 3.3: Analytical framework 26 Table 4.1: Summary on crisis occurrence during 1981-2010 30 Table 4.2: Average of explanatory variables 31 Table 4.3: 17 Variables passing first step 34 Table 4.4: Eight variables passing second step .35 Table 4.5: Correlation matrix of benchmark model 36 Table 4.6: Multinomial logit regression result 37 Table 4.7: Relative risk ratio of benchmark model .38 Table 4.8: Average marginal effect of explanatory variables .39 Table A1: Summary statistics of 27 explanatory variables 54 Table A2: Binominal logit variable-by-variable regression result 55 Table A3: Backward Stepwise regression result 56 Table A4: Benchmark model regression result – Full sample 57 Table A5: Benchmark model regression result – Restricted sample .58 CHAPTER I: INTRODUCTION 1.1 RESEARCH STATEMENT The world has witnessed a numerous debt crises arising in recent years, for instance the 1997-1998 crisis in Asia region, the outright default of Argentina in 2001, the external crisis of Honduras prolongs from 1981 to 2010, and more recently, the crisis Eurozone such as Greece, Spain, Ireland and Portugal since the year of 2009 The crises had disruptive influence on the performance of the in-trouble countries and even, the regional or global economy The frequent occurrence of debt crises and crisis’s serious consequences challenges the governments, especially developing countries where appear to be much more vulnerable compared to advanced economies It, in turn, has stimulated a controversy among various researchers on identification of leading indicators of debt crises, Kaminsky and Reinhart (1999), Manasse et al (2003) and Kraay and Nehru (2006) for example Those empirical studies attempt to construct an effective empirical model which helps to identify factors driving to debt servicing difficulties as well as predict the eve of debt crisis, the socalled Early warning systems However, due to unavailability of data on sovereign debt, only little work on establishment of Early warning system for debt crisis has been done compared to a wide range of researches on currency crisis and banking crisis In addition, in almost previous empirical studies on establishment of Early warning system for debt crisis, binomial probit/ logit regression is highly preferred for example Manasse et al (2003), Kraay and Nehru (2006) and Fuertes et al (2007) However, the result of binary logit/ probit regression result may be impacted by “post-crisis bias” This term, originally proposed by Bussiere and Fratzscher (2006), describes the bias caused by disregarding the difference in economics factors’ behaviors between “tranquil” state, the run-up to the crisis, and “recovery” state – the adjustment period after crisis Thus, discovery of more effective method tackling this kind of bias is open for researchers Taken together above concerns, this study is carried out to answer the question which factors accounting for debt crisis in developing countries by applying more effective method – multinomial logit model – compared to empirical studies Specifically, this study constructs an Early Warning System for explaining sovereign debt crisis in 31 developing countries through the period 1981-2010 The results of the study will make a valuable contribution to the empirical literature on debt crisis determination, especially for Page | developing countries group By using multinomial logistic model which was proposed by the work of Bussiere and Fratzscher (2006) on predicting the onset of currency crisis in 20 open emerging markets during 1993-2001, the issue of post-crisis bias has been resolve As a result, the study could work better at determining predictors for sovereign debt crisis in the developing countries More important, this study recommends several policies/ measures for the countries to prevent the occurrence/ prolongation of sovereign debt crisis based on the result analysis 1.2 RESEARCH OBJECTIVES Sovereign debt crises have severe impact on the economies’ performance at country level and even at regional and global level The crises in Asia in 1997-1998 and European since 2009 are typical examples For that reason, identification of sovereign debt crisis and implementation measures to avert the undesirable crisis is important and necessary mission for developing countries’ governments Based on the facts, this study is designed with two principal objectives Firstly, to determine an early warning system explaining for sovereign debt crisis in 31 developing countries whose data is available during the period from 1981 to 2010 at one year precedence Secondly, to be made some recommendations for policy makers preventing the countries from debt service difficulties 1.3 RESEARCH QUESTIONS To reach the two targets mentioned above, there are two research questions needs answering In the first place, what factors drive to occurrence/ existence of sovereign debt crisis in 31 developing countries during the period 1981-2010? Secondly, by which measures/ policies, the developing countries are able to obviate sovereign debt crisis? 1.4 RESEARCH STRUCTURE The thesis is structured with five major chapters as follows Chapter I introduces the research statement, research objectives and research questions Page | Chapter II reviews theoretical literature and empirical literature about heterogeneity of sovereign debt crisis definitions among studies and the nexus between sovereign debt crisis and potential explanatory variables which is useful for design of early warning model in this study Chapter II provides the research methodology consist of model specification, response variables and explanatory variables and measurements together with research hypotheses, data sources and estimation method employed in the study Chapter IV presents preliminary statistic of all variables and empirical regression results The result discussion in line with research’s questions is also provided in this chapter Finally, Chapter V summarizes the main findings of the study as well as policy implications Besides, this chapter presents major concerns on the research limitation and proposal for further research Page | The relative risk ratios of this variable indicate that given other things unchanged, if threemonth The U.S Treasury bill rate goes up by one unit, probability of entering into crisis over tranquil state and likelihood of remaining in crisis after the initial year to tranquil state by approximately 20.94 percent and 6.24 percent respectively From table 4.8, it could be said that an increase in three-month The U.S Treasury bill rate by one percentage point lead to an increase of about 0.50 percentage points in likelihood of crisis and an increase of 0.66 percentage points in post-crisis probability on average 4.2 CHAPTER REMARKS This section summarizes the major process and findings of the study Firstly, the study constructs a rather comprehensive definition of debt crisis event based on the definition of Reinhart and Rogoff (2003, 2010) and Manasse et al (2003, 2009) Comprehensive definition is a prerequisite for an effective Early Warning System for debt crisis since it does not miss any case of debt crisis in different notions and thus, makes the developing countries are more careful when managing sovereign debt to avoid the occurrence of debt servicing difficulties Secondly, the study employs General-to-specific approach with three-stage strategy which allows selecting the best indicators signaling sovereign debt crisis among 27 explanatory variables and avoiding omission issue In addition, the study applies multinomial logit regression with three outcomes for sovereign debt status namely crisis, post-crisis and tranquil states contributes to the improvement of prediction quality compared to bimomial logit, according to Bussiere and Fratzscher (2006) Thirdly, the study investigates the 31 developing countries for the period showed and reports the below findings Significant factors driving to sovereign debt crisis in the 31 developing countries during the period 1981-2010 are identified They are solvency measure (Public debt over GDP ratio), liquidity measures (Short-term debt to total external debt ratio and Reserves to total external debt ratio), macroeconomic factors (GDP per capita growth rate and Inflation rate) and global liquidity (Three-month the U.S Treasury Page | 44 bill rate) The six indicators (in Italic) construct a multinomial logit EWS model predicting sovereign debt crisis at one year precedence Measures of external trade link and political institution are evidenced not account for sovereign debt crisis in the 31 developing countries for the period investigated Page | 45 CHAPTER V: CONCLUSION 5.1 CONCLUSION The major purpose of this study is to identify an Early warning system explaining for the sovereign debt crisis at one year precedence in the 31 developing countries during the period 1981-2010 For the reason that there is no consensus on debt crisis definition among studies, this paper adopts the definition as well as the database provided by Reinhart and Rogoff (2003, 2010) and Manasse et al (2003, 2009) to construct an aggregate definition Specifically, a country is defined as being in crisis if there is the occurrence of at least one of three following conditions (i) the country fails to meet a principal or interest payment on the due date (or within the specified grace period) toward external and/or domestic creditors Not only outright default, repudiation, rescheduling and restructuring are counted as well; (ii) the country is classified as being in debt crisis by Standard and Poor’s; and (iii) the country receives a large non-concessional IMF loan in excess of 100 percent of quota By applying General-to-specific approach with three-step strategy, the paper constructs a multinomial logit model to explain and predict the likelihood of entering into crisis (for the first year of crisis) and probability of remaining in crisis (for the crisis years following the first year of crisis) at one year precedence While the General-to-specific approach with three-stage strategy allow to start with a wide range of indictors (27 explanatory variables) and through reduction and selection procedures, reduce gradually irrelevant variables to form a restricted model, the multinomial logit model is effective method to tackle postcrisis bias The main findings of the study are as follows (i) The solvency measures are positively correlated with sovereign debt crisis Specifically, Public debt over GDP ratio is positively associated with the probability of remaining in or exiting from debt crisis However, this ratio does not have significant impact on the likelihood of entering into debt crisis Page | 46 (i) The liquidity measures are positively associated with sovereign debt crisis Specifically, the short-term debt to total external debt ratio grows up, the likelihood of both entering into debt crisis and remaining in/ exiting from debt crisis rises Conversely, a decrease in reserves to total external debt ratio leads to the more frequent occurrence of debt crisis and longer crisis episode (iii) The macroeconomic fundamentals significantly affect sovereign debt crisis Specifically, when GDP per capita growth rate declines, the probability of entering into debt crisis as well as probability of remaining in crisis after the first year of crisis is both higher By contrast, inflation rate is positively correlated with post-crisis state – the crisis years after the initial year of crisis, however, inflation is not a significant explanatory variable for entering into crisis (iv) The external trade link is not associated with sovereign debt crisis Although using a number of measurements namely Imports to GDP ratio, Exports over GDP ratio, current account balance over GDP ratio, Terms of Trade and Trade openness, however, the countries’ trade linkage with the outside is not account for sovereign debt crisis (v) The political institution is not correlated with sovereign debt crisis In this paper, political institution is proxied by dummy variable for legislature/ executive election year No evidence for the relationship between sovereign debt crisis and political institution is provided (vi) The international liquidity is highly associated with sovereign debt crisis In the paper, international liquidity is represented by the three-month the U.S Treasury bill rate The indicator found to have a positive relationship with debt crisis occurrence and post-crisis state as well As a result, the study specified a multinomial logit EWS model predicting sovereign debt crisis at one year precedence with six determinants namely Public debt over GDP ratio, Short-term debt to total external debt ratio, Reserves to total external debt ratio, GDP per capita growth rate, Inflation rate and Three-month the U.S Treasury bill rate Page | 47 5.2 POLICY IMPLICATIONS From the above mentioned principal findings, several recommendations to avert undesirable sovereign debt crisis are made for policy makers The research findings highlight the importance of solvency measures and liquidity measures in determination of sovereign debt crisis In particular, Public debt over GDP ratio and Short-term debt to total external debt ratio is positively associated with debt crisis while influence sign of Reserves to total external debt ratio is negative Thus, each country should implement proper debt policy for sustainable debt status or increase country’s reserves of power currency: the U.S dollar for instance Firstly, a reasonable public debt level should be maintained through setting a public debt ceiling and keeping it not breaching the threshold A World Bank project group, from annual data of 101 developing and developed countries during 1980-2008, established a threshold of 77 percent for public debt over GDP ratio (Caner et al (2010)) For the developing countries examined in this study, the threshold should be set at level lower than 77 percent Secondly, similar to public debt, the developing countries had better to maintain external debt stock at a reasonable level in order to reduce vulnerability to the external, especially in case depreciation of borrowing country’s currency Thirdly, decreasing the stock of short term debt might help to increase liquidity and so, reduce probability of sovereign debt crisis When almost countries’ major projects are long term, they require long payback period Consequently, if the projects are financed by short term loans, the country probably may face difficulties in servicing such short-repaymentscheduled loans One of the good measures is that the developing countries could borrow from the internal or the external by issuing long-term government bond in local or international market Besides implementing a sustainable debt policy, the developing countries should have effective policies to increase foreign exchange reserves Export promotion could be a solution, especially for the countries have advantages in exports such as Brazil – top coffee exporter or Ecuador, Panama, the Philippines - top banana exporting countries The Page | 48 countries may also improve reserves by policy of attracting foreign investors Capital inflows not only are beneficial to reserves, but help to accelerate economic growth and create jobs in long run as well For macroeconomics conditions, the high GDP per capita growth and low inflation help to reduce probability of sovereign debt crisis Nevertheless, high level of GDP per capita growth obviously should be considered as a country’s target rather than measure to prevent debt crisis Thus, the effective measure for the developing countries is controlling inflation through tight monetary policy and tight fiscal policy Low level of inflation means that the countries receive higher real income for debt repayment Moreover, low inflation is an incentive for production and investment and in turn, beneficial to economic growth Regarding to international liquidity aspect, three-month the U.S Treasury bill rate was found to be positively correlated with sovereign debt crisis However, it is exogenous factor to the developing countries More important, no developing country has power to adjust the U.S Treasury bill rate in reality Thus, the resolution for the developing counties is closely monitoring the fluctuation of the U.S Treasury bill rate or the interest policy of the U.S Federal Reserves and timely preparing proper reaction plans in case the U.S interest rate rises 5.3 RESEARCH LIMITATION The first limitation of the study can be considered as the constraint in variables selection which is caused by the data unavailability The aim of purpose is constructing effective EWS model to explain for sovereign debt crisis in the 31 developing countries through period 1981-2009 and so, the more indicators available, the better predictors could be identified However, for some factors, the selection of measurement is limited For example, political institution in this paper represented by dummy for legislature/ executive election only and these variables found to be not associated with debt crisis event Actually, there are several high quality indicators measuring political stability, government quality or institutional status such as the WGI index (Worldwide Governance Indicators index) and CPIA index (Country Policy and Institutional Assessment index) Nevertheless, the dataset is unavailable for the 31 developing countries in the period investigated WGI database is only available 1996 onwards and not available for all countries CPIA database even is only Page | 49 available for several countries since 2005 Thus, here is a tradeoff between sample size and number of explanatory variables Secondly, the study does not consider the potential causal linkage between sovereign debt crisis and explanatory variables To illustrate, economic growth probably impacts on the occurrence of debt crisis, however, the debt crisis can affect economic growth as well 5.4 FURTHER RESEARCH RECOMMENDATION Firstly, as discussed in Chapter II, the definition of sovereign debt crisis is very heterogeneous among studies Thus, constructing comprehensive definition on debt crisis is still open for future studies Compared to previous empirical studies such as Ciarlone et al (2005), Detragiache and Spilimbergo (2001) and Manasse et al (2003),the study investigates the determinants of sovereign debt crisis in more recent period – from 1981 to 2010 – for a specific countries groups (31 developing countries) However, there is a gap with current time as consequence of data unavailability Thus, in order to improve the meaning and applicability of EWS model for sovereign debt crisis in reality, further researches with more recent time are highly recommended Further empirical studies with higher quality indicators (such as WDI index, CPIA index for political institution factor) if data is available are also suggested Finally, further researches on sovereign debt crisis determination which considers the potential causal relationship between sovereign debt crisis and several economic fundamentals should be conducted Page | 50 REFERENCE Aylward, M L., & Thorne, M R (1998) An Econometric Analysis of Countries' Repayment Performance to the International Monetary Fund International Monetary Fund Balkan, E M (1992).Political instability, country risk and probability of default Applied Economics, 24(9), 999-1008 Bussiere, M., &Fratzscher, M (2006).Towards a new early warning system of financial crises Journal of International Money and Finance, 25(6), 953-973 Caggiano, G., Calice, P., &Leonida, L (2014) Early warning systems and systemic banking crises in low income countries: A multinomial logit approach Journal of Banking & Finance, 47, 258-269 Caner, M., Grennes, T J., &Köhler-Geib, F F N (2010) Finding the tipping point-when sovereign debt turns bad Chalk, M N A., & Hemming, M R (2000) Assessing fiscal sustainability in theory and practice (No 0-81).International Monetary Fund Ciarlone, A.,&Trebeschi, G (2005) Designing an early warning system for debt crises Emerging Markets Review, 6(4), 376-395 Darvas, Z (2012) Real effective exchange rates for 178 countries: a new database De Paoli, B., &Hoggarth, G (2006) Costs of sovereign default Bank of England Quarterly Bulletin, Fall Detragiache, E., &Spilimbergo, A (2001) Crises and liquidity: evidence and interpretation Eaton, J., &Gersovitz, M (1981) Debt with potential repudiation: Theoretical and empirical analysis The Review of Economic Studies, 48(2), 289-309 Eaton, J., Gersovitz, M., &Stiglitz, J E (1986) The pure theory of country risk European Economic Review, 30(3), 481-513 Edwards, S (1983) LDC's foreign borrowing and default risk: An empirical investigation Fuertes, A M., &Kalotychou, E (2007).Optimal design of early warning systems for sovereign debt crises.International Journal of Forecasting 23(2007) 85–100 Goldstein, M., Kaminsky, G L., & Reinhart, C M (2000) Assessing financial vulnerability: an early warning system for emerging markets Peterson Institute Page | 51 Haque, N U., Kumar, M S., Mark, N., & Mathieson, D J (1996) The economic content of indicators of developing country creditworthiness Staff Papers, 43(4), 688-724 http://www.federalreserve.gov/releases/H15/data.htm Kraay, A., & Nehru, V (2006) When is external debt sustainable? The World Bank Economic Review, 20(3), 341-365 Krugman, P (1988) Financing vs forgiving a debt overhang Journal of development Economics, 29(3), 253-268 Manasse, P., &Roubini, N (2009).“Rules of thumb” for sovereign debt crises Journal of International Economics, 78(2), 192-205 McFadden, D., Eckaus, R., Feder, G., Hajivassiliou, V., & O’Connell, S (1985) Is there life after debt? An econometric analysis of the creditworthiness of developing countries International debt and the developing countries, 179-209 Myers, S C (1977) Determinants of corporate borrowing Journal of financial economics, 5(2), 147-175 Ostry, J D., Ghosh, A R., Kim, J I., & Qureshi, M S (2010) Fiscal space.International Monetary Fund, Research Department Pescatori, A., &Sy, A N (2007) Are debt crises adequately defined? IMF Staff Papers, 54(2), 306-337 Petrie, M., & Hemming, M R (2000) A Framework for Assessing Fiscal Vulnerability (No 0-52).International Monetary Fund Reinhart, C M., Rogoff, K S., &Savastano, M A (2003) Debt intolerance(No w9908).National Bureau of Economic Research Reinhart, C M., &Rogoff, K S (2008) This time is different: A panoramic view of eight centuries of financial crises (No w13882) National Bureau of Economic Research Reinhart, C M., &Rogoff, K S (2009) This time is different: eight centuries of financial folly Princeton university press Roubini, N (2001) Debt sustainability: How to assess whether a country is insolvent Stern School of Business, New York University, mimeo Sachs, J D (1983) Theoretical issues in international borrowing NBER Working Paper Series, 1189 Page | 52 Schimmelpfennig, M A., Roubini, N., &Manasse, P (2003) Predicting sovereign debt crises (No 3-221).International Monetary Fund Sutton, M B., &Catão, M L (2002) Sovereign defaults: the role of volatility(No 2-149) International Monetary Fund Sy, A N (2004) Rating the rating agencies: Anticipating currency crises or debt crises? Journal of Banking & Finance, 28(11), 2845-2867 Sy, M A N., &Pescatori, A (2004) Debt crises and the development of international capital markets (No 4-44).International Monetary Fund Page | 53 APPENDICES APPENDIX Table A1: Summary statistics of 27 explanatory variables Variable Solvency measures Public debt/GDP (%) Total external debt/GDP (%) External debt stocks/Exports (%) Total debt service/Exports (%) Liquidity measures Short-term debt/total external debt (%) Short-term debt/reserves (%) Debt service on external public debt/GDP (%) Debt service on total external debt/GDP) (%) Reserves/total external debt (%) M2/reserves ratio Macroeconomics fundamentals Inflation, GDP deflator (annual %) GDP per capita growth (annual %) Total reserves minus gold growth rate (%) FDI net inflows/GDP (%) Gross domestic savings/GDP (%) Government expenditure/GDP (%) Gross national expenditure/GDP (%) NEER growth (%) REER growth (%) External trade link Exports/GDP (%) Imports/GDP (%) Sum of exports and imports/GDP (%) Current account balance/GDP (%) Terms of Trade (index) Political institutions Dummy for legislature election Dummy for executive election Global liquidity 3-month The U.S Treasury bill rate (%) Name in model Obs Mean Std Dev Min Max publicdebt extdebt edstock_exp dser_exp 930 930 930 930 72.09366 66.58043 251.3019 24.85075 83.03348 102.9002 306.7977 16.68982 3.216656 2.644807 0 1209.303 2687.685 3575.291 200.5074 STdebt_ed STDebt_re dseronpd dseroned re_ed m2_re 930 930 930 930 930 930 14.73316 265.6726 4.370817 6.452851 43.27381 6.760853 9.449128 1391.264 2.952132 4.10078 152.6734 12.93494 0 0.09145 0.198438 0.103003 0.596251 54.7986 26089.99 36.317 68.62582 2370.947 148.3119 inflation gdppercapgr Resevegrowth fdiinflows savings govexpend naexpend neergrowth reergrowth 930 930 926 930 930 930 930 930 930 92.69792 1.741207 30.51635 2.044036 20.59057 12.83469 101.806 -9.66513 1.184431 719.9626 -26.3 4.408252 -15.4583 299.2364 -87.69845 2.27131 -12.2084 10.45523 -15.0904 4.423412 8.858334 67.91981 20.84219 -99.9606 30.70835 -94.8896 13611.63 30.34224 8940.967 17.13427 57.06182 43.47921 140.2893 53.60972 794.8866 exports imports openness ca tot 930 930 930 930 930 30.26017 18.64372 32.05083 17.97743 62.311 35.543 -2.41007 6.761217 109.0319 35.084 3.338307 6.320343 -34.136 43.87755 121.3118 100.5974 220.4074 26.521 312.3077 legelec exelec 930 930 0.234409 0.423857 0.16129 0.367996 0 1 tbyield 930 5.456667 3.162682 0.15 14.04 Page | 54 APPENDIX Table A2: Binominal logit variable-by-variable regression result Variable group Solvency measures Variable publicdebt extdebt edstock_exp dser_exp Coef Std Err P>|z| 0.0320249 0.0458281 0.0122623 0.0380438 0.0039785 0.0049938 0.0012352 0.0074878 0.000 0.000 0.000 0.000 STdebt_ed STDebt_re dseronpd dseroned re_ed m2_re 0.0239762 0.0037132 0.1756777 0.0903895 -0.1151542 0.039751 0.0104561 0.0007045 0.0399213 0.0290732 0.0125627 0.0187285 0.022 0.000 0.000 0.002 0.000 0.034 inflation gdppercapgr Resevegrowth fdiinflows savings govexpend naexpend neergrowth reergrowth 0.0330442 -0.1339181 0.00304 -0.4740526 -0.0151476 -0.0017701 -0.0404489 -0.0434095 -0.0029018 0.0052336 0.0226538 0.0014609 0.0630647 0.0142573 0.0279146 0.0150249 0.0061351 0.0030657 0.000 0.000 0.037 0.000 0.288 0.949 0.007 0.000 0.344 exports imports openness ca tot -0.0462134 -0.0739074 -0.0346262 -0.0513365 0.0001055 0.0114681 0.0131588 0.0067774 0.016823 0.0025572 0.000 0.000 0.000 0.002 0.967 lagged legelec exelec 4.421904 -0.132733 -0.1137607 0.2683638 0.1990866 0.2238067 0.000 0.505 0.611 tbyield 0.276154 0.0318538 0.000 Liquidity measures Macroeconomics fundamentals External trade link Political institutions Global liquidity Page | 55 APPENDIX Table A3: Backward Stepwise regression result Logistic regression Number of obs LR chi2(10) Prob > chi2 Pseudo R2 Log likelihood = -423.11111 crisis Coef publicdebt tbyield gdppercapgr inflation STdebt_ed STDebt_re ca dseroned re_ed m2_re _cons 0155476 0999505 -.0704199 0069066 0293689 0029002 056697 -.07748 -.0525878 -.1098577 -.4259945 Std Err .002889 0300962 0225324 002397 0131723 0008113 0181645 0281833 0079999 0276058 4810539 z 5.38 3.32 -3.13 2.88 2.23 3.57 3.12 -2.75 -6.57 -3.98 -0.89 P>|z| 0.000 0.001 0.002 0.004 0.026 0.000 0.002 0.006 0.000 0.000 0.376 = = = = 930 408.75 0.0000 0.3257 [95% Conf Interval] 0098854 0409631 -.1145826 0022086 0035516 0013101 0210952 -.1327183 -.0682672 -.1639641 -1.368843 0212099 158938 -.0262572 0116046 0551863 0044903 0922987 -.0222416 -.0369083 -.0557513 5168539 Page | 56 APPENDIX Table A4: Benchmark model regression result – Full sample Multinomial logistic regression Number of obs LR chi2(12) Prob > chi2 Pseudo R2 Log likelihood = -531.22014 debtstatus Coef Std Err z P>|z| = = = = 930 419.89 0.0000 0.2833 [95% Conf Interval] (base outcome) publicdebt STdebt_ed re_ed gdppercapgr inflation tbyield _cons -.0010118 0693293 -.0440536 -.1079147 0044896 1901283 -4.034717 0072533 0197929 0164266 0405767 0054515 0584533 9318033 -0.14 3.50 -2.68 -2.66 0.82 3.25 -4.33 0.889 0.000 0.007 0.008 0.410 0.001 0.000 -.0152281 0305359 -.0762491 -.1874436 -.0061951 075562 -5.861018 0132044 1081226 -.0118581 -.0283857 0151744 3046947 -2.208417 publicdebt STdebt_ed re_ed gdppercapgr inflation tbyield _cons 0176407 045724 -.0442706 -.0645511 0104436 0605291 -1.818311 0027007 0111272 0071301 0223177 0031178 0297455 4119597 6.53 4.11 -6.21 -2.89 3.35 2.03 -4.41 0.000 0.000 0.000 0.004 0.001 0.042 0.000 0123474 0239152 -.0582452 -.108293 0043328 0022289 -2.625738 0229339 0675329 -.0302959 -.0208093 0165544 1188292 -1.010885 Page | 57 APPENDIX Table A5: Benchmark model regression result – Restricted sample Multinomial logistic regression Number of obs LR chi2(12) Prob > chi2 Pseudo R2 Log likelihood = -513.44821 debtstatus Coef Std Err z P>|z| = = = = 810 317.24 0.0000 0.2360 [95% Conf Interval] (base outcome) publicdebt STdebt_ed re_ed gdppercapgr inflation tbyield _cons -.0031357 0612523 -.0334495 -.1036483 0034592 2082637 -3.946925 0075269 0200165 017149 0405904 0054311 059265 9666812 -0.42 3.06 -1.95 -2.55 0.64 3.51 -4.08 0.677 0.002 0.051 0.011 0.524 0.000 0.000 -.0178881 0220207 -.067061 -.183204 -.0071856 0921064 -5.841585 0116167 1004839 000162 -.0240927 014104 3244211 -2.052265 publicdebt STdebt_ed re_ed gdppercapgr inflation tbyield _cons 0161567 0399411 -.0358107 -.0619015 0094381 080504 -1.792841 0027114 011129 0073302 0225057 0030217 0307894 4235491 5.96 3.59 -4.89 -2.75 3.12 2.61 -4.23 0.000 0.000 0.000 0.006 0.002 0.009 0.000 0108424 0181286 -.0501776 -.1060119 0035156 0201578 -2.622982 021471 0617535 -.0214437 -.0177912 0153606 1408501 -.9627003 Page | 58 ... existence of sovereign debt crisis in 31 developing countries during the period 1981- 2010? Secondly, by which measures/ policies, the developing countries are able to obviate sovereign debt crisis? ... debt crisis definition, early warning system method and the backbone of model explaining debt crisis which was learnt from the relevant literature 2.1 SOVEREIGN DEBT CRISIS AND EARLY WARNING SYSTEM. .. is applied in building the EWS model for explaining debt crisis in 31 developing countries over the period 1981- 2010 Applying multivariate logistic regression to predict crisis is initially recommended