Luận văn thạc sĩ UEH developing an early warning system to predict currency crises in emerging

UNIVERSITY OF ECONOMICS

HO CHI MINH CITY

VIETNAM

INSTITUTE OF SOCIAL STUDIES

THE HAGUE

THE NETHERLANDS

VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN

DEVELOPMENT ECONOMICS

DEVELOPING AN EARLY WARNING SYSTEM

TO PREDICT CURRENCY CRISES

IN EMERGING MARKETS

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

HOANG THUY HONG NHUNG

Academic Supervisor

Assoc. Prof. NGUYEN VAN NGAI

Ho Chi Minh City, December 2014

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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”.

HOANG THUY HONG NHUNG

Date: 27

th December 2014

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ACKNOWLEDGEMENTS

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 deep gratitude to Assoc. Prof. Nguyen Van

Ngai, my academic supervisor, for his patient guidance, enthusiasm and

encouragement..

I would also like to thank Dr. Truong Dang Thuy for his professional advices, and

Mr. Truong Hong Tuan and Mr. Luong Duy Quang, former students, for their

valuable comments.

My gratefulness is also extended to all of my lecturers and staff of the Vietnam￾Netherlands Program, particularly, Assoc. Prof. Nguyen Trong Hoai and Dr. Pham

Khanh Nam for their assistance during the first days when I started this program.

I wish to thank my family for their encouragement and support during my study as

well. Without them, I would not have a chance to finish the thesis.

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.

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ABSTRACT

This thesis develops a new early warning system (EWS) model to predict the

currency crises in emerging markets by using the logit regression. According to the

results, the macroeconomic variables and the institution variables are valuable

indicators which play important roles in EWS model for predicting the currency

crises. It shows that the real exchange rate, export growth, import growth, current

account surplus/GDP, short-term debt/reserves have correct sign and are statistically

significant at 5% level. It also shows that the law and order, external conflict have

correct sign and are statistically significant at 1%. In addition, this thesis also

applies credit-scoring method to get the optimal cut-off threshold in order to have a

more accurate probability of predicting currency crises. Since then, the policy￾makers can consider taking the effective pre-emptive actions to prevent the currency

crises occurring in the future.

Key words: currency crisis, early warning system, emerging market, logit model

TABLE OF CONTENTS

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CHAPTER 1: INTRODUCTION ........................................................................... 1

1.1. Problem statement.....................................................................................................1

1.2. Research objectives...................................................................................................4

1.3. Research questions....................................................................................................4

1.4. The scope of the thesis ..............................................................................................4

1.5. The structure of the thesis .........................................................................................5

CHAPTER 2: LITERATURE REVIEWS.................................................................. 6

2.1. Definition of currency crisis......................................................................................6

2.2. Theoretical literatures of currency crises ..................................................................7

2.2.1. First generation models of currency crises ....................................................7

2.2.2. Second generation currency crisis theoretical model.....................................9

2.2.3. Third generation currency crisis theoretical model .....................................10

2.2.4. “Fourth generation” currency crisis theoretical model...............................12

2.3. Empirical studies of currency crises........................................................................14

2.3.1. Indicators of currency crisis.........................................................................14

2.3.2. Existing methods approach in EWS model of currency crisis......................16

2.3.3. Summary of recent empirical findings..........................................................19

2.4. Conceptual framework ............................................................................................26

CHAPTER 3: RESEARCH METHODOLOGY AND DATA................................... 28

3.1. The EWS model specification.................................................................................28

3.1.1. Dating the currency crisis and define the dependent variable......................28

3.1.2. Explanation variables choice and hypothesis testing ...................................29

3.1.3. Methodology research ..................................................................................36

3.2. How to choose the optimal cut-off threshold ..........................................................39

3.3. Data collection.........................................................................................................42

3.4. Estimation strategy and statistical tests of the model..............................................43

CHAPTER 4: RESEARCH RESULTS ................................................................... 45

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4.1. The descriptive statistic of the sample ....................................................................45

4.2. Empirical results......................................................................................................50

4.2.1. Effected by macroeconomics factors ............................................................51

4.2.2. Effected by institution factors.......................................................................53

4.3. Choosing the optimal cut-off threshold...................................................................55

4.4. Predicting the currency crisis..................................................................................58

4.4.1. Asian Crisis 1997-1998 ................................................................................59

4.4.2. Turkey crisis in 1994 and 2001.....................................................................59

4.5. Robustness test ........................................................................................................62

4.5.1. Out-of-sample test of Latin America case.....................................................62

4.5.2. Choosing optimal cut-off threshold of EWS model in Latin American.........64

4.6. Compare results with other empirical studies.........................................................65

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS .............................. 68

5.1. Main findings ..........................................................................................................68

5.2. Policy implications..................................................................................................69

5.3. Research limitations................................................................................................71

5.4. Suggestions for future researches............................................................................72

REFERENCES ........................................................................................................ 73

APPENDIX A: LITERATURE WORKSHEET AND DATA SOURCES....................... 77

APPENDIX B: RESULTS OF CHOOSING CUT-OFF THRESHOLDS AND

PREDICTING VALUE OF EWS MODEL IN ASIA..................................................... 90

APPENDIX C: RESULTS OF ROBUSTNESS TEST ................................................... 93

APPENDIX D: DISCRIPTIVE STATISTIC................................................................. 96

APPENDIX E: COMPARISON OF TWO MODELS: MACROECONOMIC

VARIABLES ONLY AND INCLUDING INSTITUTIONS VARIABLES................... 108

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LIST OF FIGURES

Figure 2.1: The flowchart of developing an EWS model to predict currency crises...........19

Figure 2.2: Conceptual framework .....................................................................................27

Figure 3.1: Logit and probit cumulative distributions........................................................37

Figure 3.2: The optimal cut-off identification .....................................................................42

Figure 3.3: Research processing .........................................................................................44

Figure 4.1: Optimal cut-off threshold of 12-months EWS model in Asian countries..........57

Figure B.1: The fitted and predicted value of EWS model in Asian countries....................90

Figure C.1: Optimal cut-off threshold of 12-months EWS model in Latin America ...........93

Figure C.2: The fitted and predicted value of EWS model in Latin America countries......94

Figure D.1: Reserve loss .....................................................................................................96

Figure D.2: Export growth .................................................................................................96

Figure D.3: Import growth ..................................................................................................98

Figure D.4: Short-term debt/Reserves.................................................................................99

Figure D.5: GDP growth...................................................................................................100

Figure D.6: Current account/GDP....................................................................................101

Figure D.7: Real exchange rate growth ............................................................................102

Figure D.8: Government stability......................................................................................103

Figure D.9: Corruption .....................................................................................................104

Figure D.10: Law and order..............................................................................................105

Figure D.11: External conflict...........................................................................................106

Figure D.12: Internal conflict ...........................................................................................107

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LIST OF TABLES

Table 3.1: Summary expected sign of explanation variables ..............................................36

Table 4.1: The summary of sample used in the regressions................................................47

Table 4.2: The multicollinearity between independent variables........................................48

Table 4.3: The correlation between independent variables ................................................49

Table 4.4: The empirical results of logit regression of 12-month EWS model....................51

Table 4.5: Specification error test .......................................................................................51

Table 4.6: Probability of predictability of 12-months EWS model (cut-off =13.27%) .......57

Table 4.7: EWS model performance with different cut-off point.........................................58

Table 4.8: Robustness test of Asian countries in 1994, 1997, 2001, 2007 ..........................60

Table 4.9: Performance of EWS model in Asian countries when cut-off = 13.27% ...........62

Table 4.10: The results of EWS model in Latin American countries...................................63

Table 4.11: Results of explanation variables compare with other empirical studies..........67

Table A.1: The summary references of explanatory variables of the model .......................77

Table A.2: Summary data, sources and period time of explanation variables....................79

Table A.3: The literature worksheets of empirical studies..................................................80

Table B.1: Identify optimal cut-off in Asian countries by Credit-scoring approach...........90

Table C.1: Probability of predictability of 12-months EWS model (cut-off =12.02%).......93

Table C.2: Performance of EWS model in Latin American countries, cut-off = 12.02% ...93

Table E.1: Comparing 12-month EWS predicting of 02 models in Asia: 1992 - 2011 .....109

Table E.2: Nested model test .............................................................................................110

Table E.3: Specification test of macroeconomic model.....................................................110

Table E.4: Specification test of full model.........................................................................110

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CHAPTER 1: INTRODUCTION

1.1. Problem statement

There were a lot of financial crises which occurred during the 1990s: the crises of

European in 1992-1993, Mexico in 1994-1995, the crises of Asia in 1997-1998,

Brazil in 1999, Turkey in 2001, Argentina in 2002 and the economic crises over the

world in 2008-2009. These financial crises have strong influences on economy,

politics and society. They caused the economic uncertainty which suffered from

high inflation, slow growth, high unemployment and poverty. It made the GDP

growth rate is negative, the abrupt changes in nominal exchange rate with over 50%

devaluation. In Argentina, it lost 20% of GDP growth and the real wages decrease

match with it percentage. The policy-makers were all under the pressure of

implementing new policies in order to recover the affected economy. Moreover, the

cost of crises was very high, which led to an increase in the number of empirical

studies with the aim of constructing the monitoring tools to predict the crisis

occurrence. These studies were often called early warning system (EWS).

There are three common types of financial crises: currency crisis, banking crisis and

debt crisis. However, The EWS model in this thesis only focuses on the currency

crises like most of EWS models in previous empirical studies.

EWS models for currency crises were first built by Krugman (1979) and enhanced

by Flood and Garber (1984). They proved that reserve loss is an important indicator

to predict crises. Obstfeld (1994, 1996) has proposed a different model for

predicting currency crises. He stated that the currency crises occurred due to the

expectation of speculators. However, the model failed to take time matter into

account therefore it could not predict the time when crises occurred. After Asian

crisis in 1997, it has created the foundation to develop a new model for currency

crises. Kaminsky and Reinhart (1999) built the models of the EWS for twin crises

that combine banking crises and currency crises. They also stated that, banking

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crisis often occurred prior to currency crisis, when the currency crisis occurred, this

deepened the banking crisis; as the result the economy is in twin crises. In the

general, these studies used the macroeconomic and financial indicators to predict

the currency crises such as foreign reserves, export and import, real interest rate,

real exchange rate, M2/reserves, M2 multiplier, current account deficit (or surplus)

to GDP ratio, short-term debt/reserve (Kaminsky et al.,1998, Frankel and Rose,

1996, Berg and Pattilo, 1999). In the recent years, some economists concerned

about institutional factors such as bureaucratic quality, government stability,

government effectiveness, voice and accountability, rules of law, democracy,

election, control of corruption and so on (Block, 2003, Shimpalee and Breuer, 2006,

Leblang and Satyanath, 2008) that were used to predict the probability of imminent

crises.

Besides selecting the potential indicators, several methods have been suggested.

The most popular and suitable one is logit models that were applied by Frankel and

Rose (1996), Berg and Pattillo (1999). And the second is the signal approaches that

were proposed by Kaminsky et al. (1998) and applied by Edison (2003),

Bruggemann and Linne (2000), Subbaraman, Jones and Shiraishi (2003)). Some

alternative approaches are cross-country regression models which proposed by

Sachs et al. (1996), Ordinary least square (OLS) method such as Tornell (1999),

Brussiere and Mulder (1999), Markov-switching method applied by Martinez-Peria

(1999), Abiad (2003), and Artificial Neural networks (ANN) method applied by

Nag and Mitra (1999).

Nevertheless, most of the EWS models only focus on identifying the indicators,

which are statistically and economically significant, that should be included in the

models to predict the currency crises, the problem raised is that the ability to predict

of those EWS models were unexamined. In order to solve the problem, the optimal

cut-off threshold is chosen to evaluate the EWS model and minimizing the crisis

risk. If the chosen cut-off point is low, it will give more signals of crises, therefore

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more crises will be detected, however, resulting in false alarms (having the signals

but no crises happen – type 2 error) increase. Conversely, if the chosen cut-off point

is high, the fewer correct crises will be detected; thus, the missing signals (the crises

occur but no preceding alarm – type 1 error) will decrease. Kaminsky et al. (1998)

developed the method named the noise-signal-ratio (NSR) to choose the optimal

threshold that minimized the ratio of false signals to good signals. Berg and Pattilo

(1999) used the Quadratic probability score (QPS) and the Log probability score

(LPS) to prove that their EWS models have better forecasting ability than the

Kaminsky et al. (1998). Bussiere and Fratcher (2002) based on the Damirguc-Kunt

and Detragiache (1999) idea to build the loss function for policy-maker to predict

the currency crises. They said that the choice of optimal cut-off thresholds and the

predictive periods were based on the risk-aversion degree. In the recent years,

Candelon et al. (2012) who were the first ones to summarize many methods to

choose the absolute optimal cut-off points that highly contributes to evaluate the

EWS forecast performance. They concluded that Credit Scoring approach and

Accuracy measure are better than given cut-off point method or the noise-to-signal

ratio of Kaminsky et al. (1998).

Following the trend of this development and enhancement of EWS models, this

thesis will use seven macroeconomic variables that suggested by many previous

studies such as Kaminsky et al (1998), Berg and Pattillo (1999), Bussiere and

Fratzscher (2002) combine with five institutional indicators used by Shimpalee and

Breuer (2006); simultaneously, use the logit approach to develop EWS models in

terms of predicting the probability of currency crisis occurrence in emerging

markets. In order to evaluate the predictability of EWS models, this thesis will

apply the Credit-scoring approach according to Candelon et al. (2012). This is also

one of earlier paper studies applied Credit-scoring approach to evaluate the EWS

models performance to predict the currency crises.

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