CAN THAILAND FINANCIAL CRISIS BE EXPLAINED BY FUNDAMENTAL ECONOMIC WEAKNESSES?

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1 CAN THAILAND FINANCIAL CRISIS BE EXPLAINED BY FUNDAMENTAL ECONOMIC WEAKNESSES? by Chanisa Vadthanakul Doctor of Business Administration Program, School of Business, University of the Thai Chamber of Commerce, Bangkok, 10400, Thailand ABSTRACT This paper examines whether Thailand financial crisis can be explained by fundamental economic weaknesses. The study focuses on the macroeconomic variables. These include liberalization dummy variable, capital inflows as a percentage of Gross Domestic Product, trade balance as a percentage of GDP, real exchange rates, the difference between U.S real interest rates and local real interest rates, broad of money as a percentage of foreign exchange reserve, bank lending as a percentage of GDP and foreign debt as a percentage of GDP. The results of this study show that Thailand financial crisis resulted from the concurrent fundamental economic weaknesses. KEYWORDS Financial Crisis, Economic, Capital Inflows, GDP INTRODUCTION The Thailand financial crisis has revived the long-held beliefs that the collapses were caused by fundamental economic weaknesses and policy inconsistencies, which can lead to very different policy responses. In this study, Thailand financial turmoil will be examined. The herding behaviour of investors could be behind the stock market volatility. First and foremost, whether the Thailand financial crisis can be explained by fundamental economic weaknesses is examined. Noticeable effects of fundamental economic variables on volatility suggests that Thailand financial crisis was caused by fundamental economic weaknesses. This study shows that it is possible identify the relationship between fundamental economic weaknesses and Thailand financial crisis. Understanding of the source and propagation of the crisis are important as policy makers seek reforms to contain the contagion, kick-start recovery and prevent future similar crises. Framework In this study, (1) the financial crisis is examined as the stock market volatility of Thailand. (2) The estimation is separated into three periods: An overall period (Jan.1, 1989 Dec.31, 2008), a pre-crisis period (Jan.1, 1989 Jun.30, 1997) and a post-crisis period (Jul.1, 1997 Dec.31, 2008). This break is reasonable. According to Radelet and Sachs (1998b) by June 1997, Asian currencies were clearly in crisis. This paper is organized into five parts. First, the introduction consists of the statement of the problem and its significance, objectives, framework, benefits and its implications and organization of the study. The literature is reviewed in the second part contains many empirical studies which state the important determinants of contagion and the fundamental economic imbalances which generate the crises. In third part, the methodology, data description and sources of data are discussed. The fourth part, analyzes the relationship between the fundamental economic weaknesses and the results. Finally, the last chapter provides the conclusions.

2 LITERATURE REVIEW There is extensive literature on the causes of the crisis and the role of fundamental economic weaknesses. Kaminsky and Reinhart (1996) analyzed the links between banking and currency crises, and examined the empirical regularities and the sources and scope of problems in the trigger of currency banking crises. They found that banking crises generally begin before currency collapses, and currency crises were deepened by banking crises, which are themselves preceded by financial liberalization. They also found evidence suggesting that currency collapse further undermines an already ailing banking sector, which in turn worsens the currency crisis. Finally, in both crises they found many corresponding weakness of economic fundamentals, which suggest that they are unlikely to be self-fulfilling crises. Sachs, Tornell, and Velasco (1996) examined Mexico s unexpected financial crisis in 1994, and presented a model to determine a country s vulnerability to financial crisis, based on large exchange rate appreciation, weak banking system, and low foreign exchange reserves. Countries that experienced lending booms are likely to suffer currency crises. Financial liberalization without prudent supervision can lead to sharp lending boom by both banks and non-bank financial institutions, resulting in a financial crisis. All M2 is the central bank s liabilities resulting from implicit or explicit government guarantees. Kerdpon (1997) examined macroeconomic variables as leading indicators for the and 1997 financial crises in Thailand by multivariate logit model. She found seven variables that can signal financial crises in Thailand. These are the SET index, international reserves, commercial bank deposits, real exchange rate, the ratio of M2 and international reserves, current account, and the ratio of lending interest rate to deposit rate. However, behaviour and trend of leading indicators are different for the two crises. Radelet and Sachs (1998a) examined financial crises in Mexico ( ), Argentina (1995), and five East Asian economies (1997). Each of these crises displayed elements of self-fulfilling crises; creditor withdrawals resulted panic and deep contractions that were avoidable. East Asian economies were hit by multiple international macroeconomic shocks between 1994 and 1996, including a dramatic surge by competitor economies and the abrupt reversal of the Yen's long-term trend of appreciation against the US Dollar, which combined with weaknesses in the East Asian financial systems to cause the crisis. Each of the five economies had started liberalizing and reforming their financial systems, which left them with growing shortterm foreign debt, rapidly expanding bank credit, and inadequate regulation of financial institutions, making them vulnerable to rapid capital flow reversal. While the East Asian economies continued to grow rapidly in the 1990s, there were also growing imbalances and weaknesses in the East Asian economies, both at microeconomic and macroeconomic scales. Also factors preceding the crisis were capital inflows, exchange rate pegging against real exchange rate appreciation, slow export growth, domestic lending boom and a rise in short-term foreign borrowing. In essence, there were three broad explanations for the East Asian crisis; shifts in international markets such as the rise of China as a major economy and the sharp real appreciation of the U.S dollar against the European currencies and the Yen, growing weaknesses and mismanagement in the Asian economies, and instabilities in the international capital markets. In their subsequent study, Radelet and Sachs (1998b) discussed the role of financial panic in the Asian crisis. They hypothesized that as the crisis originated from the large short-term foreign capital inflows to the financial systems of regional countries caused by their financial vulnerability, financial panic is caused by this financial vulnerability. They explored this possibility by examining the initial imbalances and weaknesses, the build-up to the crisis and the events that led to the financial panic. They found that macroeconomic imbalances, weak financial institutions, widespread corruption, and inadequate regulation contributed to the vulnerability of the Asian economies, and used the probit analysis to test their hypothesis. They found that that the weak macro- and micro-economic fundamentals of the Asian economies were not severe enough to warrant a financial crisis of the magnitude that took place in the latter half of According to this study, certain policy choices and events along the way exacerbated the panic and unnecessarily deepened the crisis. Corsetti, Pesenti and Roubini (1998c) examined the role of fundamental weaknesses in the East Asian economies as a contagion effect. They found that the relationship between currency volatility and financial fragility index led to the crisis. From this, they constructed a crisis index; the average of the percentage rate of exchange rate depreciation relative to US dollar and the percentage rate of change in foreign reserves. They also created a financial fragility index, combining non-performing loans index and lending boom indicators, the index of current account imbalance and the index of foreign reserves adequacy. They used regression analysis to examine the relationship between the crisis index and the financial fragility index, current account index and foreign reserve adequacy index, and found that structural imbalances precipitated the crisis. Yoshitomi and Ohno (1999) stated that the combination of capital account crisis and internal credit contraction can explain the Asian crisis during Like many similar studies, they characterized the capital account crisis as an international capital inflow, mostly short-term foreign currency denominated loans, that greatly outsize the current account deficit. This double mismatched both currency and maturity in the balance sheets of domestic financial

3 institutions, which were responsible for the subsequent twin financial crises: currency freeze and international liquidity crisis on the one hand, and credit contraction resulting from domestic banking crisis on the other. Mei (1999) examined political uncertainty in emerging markets during financial crises as factors impacting currency and market volatility. Election cycles were used as political dummy variables in a combination of probit and switching regression analysis. He found heightened market volatility during election periods, and that the financial crisis was affected by political risk independent of economic condition and contagion. Bustelo, Gaicia, and Olivie (1999) studied how financial globalization increased the emerging market' vulnerability to crises. They analysed the macroeconomic situation in Indonesia, Malaysia, the Philippines, South Korea and Thailand. The East Asian countries saw increased vulnerability from two causes: increased uncertainty due to capital markets failures, and large capital inflows due to excessively aggressive financial liberalization of emerging markets. This combined with intermediate fundamentals to change private expectations, leading to financial crisis. Thanapornpun (2000) stated that Thailand's bubble economy was due mostly to foreign factors and the bubble effect was in the real estate market before finding its way to the stock market. Influx of Japanese tourists into the Thai market fuelled the real estate boom of High economic growth rate also increased domestic demand for the same services. These two factors spurred speculation in the real estate market. Land and stock prices were overvalued, thus resulting in a bubble economy. Dekle and Kletzer (2001) focused on the relationship between foreign capital inflows, economic growth and subsequent banking crises under a fixed exchange rate. Their model concentrated on the interactions between domestic financial institutions, regulation and subsidization of domestic financial transactions by government, and foreign capital inflows leading up to a financial crisis. The model predicted a financial crisis as the fixed exchange rate regime collapse. Demirgüç-Kunt, A., and Detragiache E. (1998) evaluated the relationship between banking crises and financial liberalization with a multivariate logit model, with financial liberalization and banking crisis dummy variables for developed and developing countries. The logit regression estimated the probability of a banking crisis as a function of the financial liberalization dummy variable and a number of control variables. They found that the financial liberalization dummy variable is strongly positively correlated with the probability of a banking crisis, and therefore banking crises are more likely to take place in liberalized financial systems. Methodology METHODOLOGY AND DATA DESCRIPTION To investigate whether the Thailand financial crisis can be explained by fundamental economic weaknesses, Generalized Least Squares (GLS) are generated to identify the relationship between these variables. If fundamental economic variables have significant effects on volatility, then it is inferred that the Thailand financial crisis was caused by fundamental economic weaknesses. This is the hypothesis of this study. The GLS analysis is in two steps. First, it transforms the population regression function to one with the desired disturbance term and then applies Ordinary Least Square (OLS) to the transformed variables. The estimator assigns unequal weight or importance to each observation. It is able to satisfy the BLUE properties best, linear, unbiased, and efficient estimators, so the hypothesis is estimated by using the GLS procedure. The standard errors and t-statistics are computed using a heteroskedasticity consistent covariance matrix as suggested by White (1980). H t = fn(lib i,t, CPG i,t, TG i,t,rer i,t,drin i,t, M2R i,t, LBG i,t, FLG i,t, ) Transformed to: H t = + 1t LIB i,t + 2t CPG i,t + 3t TG i,t + 4t RER i,t + 5t DRIN i,t + 6t M2R i,t + 7t LBG i,t + 8t FLG i,t + it To test the hypothesis of whether the Thailand financial crisis can be explained by fundamental economic weaknesses, the hypothesis is: H 0 : I 0 H 1 : I 0 If the null hypothesis (H 0 ) is rejected, the coefficients ( i ), at least one, are not equal to zero with significance. This shows that the fundamental economic weaknesses do affect stock market volatility, and also implies that the Thailand financial crisis was caused by fundamental economic weaknesses. This study classifies fundamental economic weaknesses as independent variables; macroeconomic event and moral hazard event.

4 Data Descriptions The data used in this paper cover the period between January 1989 and December 2008 on monthly basis. The independent variables used to explain fundamental economic weaknesses came from a GLS estimation consisting of capital inflows as a percentage of Gross Domestic Product (GDP), trade balance as a percentage of GDP, real exchange rate, the difference between US real interest rates and Thai real interest rates, broad of money as a percentage of foreign exchange reserve, bank lending as a percentage of GDP and foreign debt as a percentage of GDP. All data are obtained from the Bank of Thailand. The financial crisis is examined as the stock market volatility in Thailand. The estimation is done over three periods: the overall period between January 1, 1989 and December 31, 2008, the pre-crisis period from January 1, 1989 to June 30, 1997, and finally the post-crisis period from July 1, 1997 to December 31, The partition is based on the fact that Asian currencies were clearly in crisis by June 1997 (Radelet and Sachs, 1998b). High frequency data are used to maximize the potential of the crisis analysis. Macroeconomic data is typically not available at higher frequencies, but financial market data on the other hand is available at much higher frequencies. Therefore the low-frequency macroeconomic data is mixed with the high-frequency financial data by interpolating the low-frequency data into the high-frequency data. (Christoffersen and Errunza, 2001) H t,i = the stock market volatility of the country at the point in time. A financial crisis is defined as a significant increase in stock market volatility. LIB i,t = liberalization dummy variable. Financial liberalization attract large capital inflows into emerging markets, resulting in financial vulnerabilities. Therefore, the next test is a test for whether stock market volatility can be explained by financial liberalization. Dependent variable LIB serves as the financial liberalization dummy variable; its value is one for periods of financial liberalization, and zero otherwise. Financial liberalization dates are obtained from Bekaert and Harvey (1999). CPG i,t = capital inflows as a percentage of GDP. The weaknesses of Thailand's financial systems were made even more severeby foreign capital inflows, which were large, volatile, unsustainable, and poorly utilized. GDP calculation is on an annualized quarter basis, while the capital flows and GDP are obtained from the Bank of Thailand. TG i,t = trade balance as a percentage of GDP. Current account deficits has a disruptive influence on the financial markets, as in troubled economies it pressured the confidence of foreign investors and encouraged international speculators to attack the local currencies. Current accounts consist of trade balance, which is almost always in deficit, and service balance, which is usually in surplus. Overall current account is almost always in deficit, so the slowdown of export growth led to the current account deficit. The trade balance, the difference between export and import, to GDP ratio is used to assess the current account imbalance which led to the crisis. DRIN i,t = difference between US and Thai real interest rate. The high domestic interest rates in most of the troubled economies also attracted large capital inflows. In contrast, low interest rates in the US raised investments out into emerging markets. The differential is calculated from short-term interest rate adjusted for inflation rate. The data is transformed from annual to monthly basis. Short-term interest rates for US are from IFS, while inflation rate is calculated from the change in the Consumer Price Index (CPI). RER i,t = real exchange rate. This variable is likely to influence volatility. The weekly exchange rates are calculated from the price index in U.S. dollars and the price index in Thai currency. The rate of change of the exchange rate is first calculated, then it is multiplied by the exchange rate of that period. The real exchange rates are obtained by applying the Consumer Price Index (CPI). Rate of change in exchange rate t = Exchange rate t where = Exchange rate t-1 * Rate of change in exchange rate t LC PI t $ Pi t = Weekly local price index at period t = Weekly US dollar price index at period t CPI Discrete RER t = ER t *

5 Continuous RER t = LN(ER t ) + LN(CPI us T ) - LN(CPI LC t ) where, RER t = Real exchange rate at period t ER t = Exchange rate at period t US CPI t = U.S. Consumer Price Index at period t LC CPI t = Local Consumer Price Index at period t M2R i,t = broad of money (M2) as a percentage of foreign exchange reserves. This is a measure of foreign exchange reserves, and is the ratio of money assets to foreign reserves. In an exchange rate crisis or panic, any liquid money assets can be converted into foreign exchange. An increase in this ratio indicates a decrease in capability of a country to defend its currency or an increase in the currency s vulnerability to a speculative attack. The ratio of a broad of money measure of liquid monetary assets to foreign reserves could be used as a measurement of liquidity, according to Calvo (1995) and Sachs, Tornell, and Velasco (1996). LBG i,t = private sector lending as a percentage of GDP. This ratio is a measure of the lending boom as described by Sachs, Tornell and Velasco (1996) and Bustelo, Garcia and Olivie (1999). This is a measure of financial fragility, and is obtained from the claims on the private sector on the deposit money bank. FLG i,t = foreign debt as a percentage of GDP. Weak financial systems will see a rapid rise in this measure, due to East Asia s successful track record and financial liberalization attract foreign credits and capital. EMPIRICAL RESULTS Regression results were estimated by the GLS procedure to identify a relationship between fundamental economic weaknesses and stock market volatility. The standard errors and t-statistics are computed using a heteroskedasticity consistent covariance matrix as suggested by White (1980). The regression also includes multicollinearity and autocorrelation corrections. One way to resolve this problem is to adjust the variables by replacing the variables with residuals of the high pair-wise correlation regression. The overall significance of the relationship between explanatory variables and dependent variables is investigated by the adjusted R-squared and the probability of F-statistic. The t-statistic and probability of t-statistic are used to verify the statistical significance of each coefficient. The probability of t-statistic in each coefficient is used to examine whether the economic fundamentals can explain stock market volatility. The regression result is reported as follows: TABLE 1 THE RELATION BETWEEN STOCK MARKET VOLATILITY AND FUNDAMENTAL ECONOMIC WEAKNESSES To estimate the relation between stock market volatilty and fundamental economic weaknesses, this study employed GLS. Stock market volatility in the country (H t ) as a dependent variable. It has been developed by an asymmetric GARCH. The data used as the independent variables consist of liberalization dummy variable (LIB), capital inflows as a percentage of GDP (CPG), trade balance as a percentage of GDP (TG), real exchange rates (RER), the difference between U.S. real interest rates and local real interest rates (DRIN). Also included are broad of money as a percentage of foreign exchange reserve (M2R), bank lending as a percentage of GDP (LBG) and foreign debt as a percentage of GDP (FLG). The study breaks an estimation into three period an overall period (Jan 1, Dec 31, 2008), pre-crisis period (Jan 1, Jun 30, 1997) and post-crisis period (Jul 1, Dec 31, 2008). H t = + 1t LIB i,t + 2t CPG i,t + 3t TG i,t + 4t RER i,t + 5t DRIN i,t + 6t M2R i,t + 7t LBG i,t + 8t FLG i,t + it Variable Overall Sample Period Pre-crisis Subsample Period Post-crisis Subsample Period Coeff. t-stat Prob. Coeff. t-stat Prob. Coeff. t-stat Prob. C LIB NA NA NA CPG adj *** ** ** TG ** * * RER *** * DRIN M2R LBG adj

6 FLG ** AR Adjusted R squared Prob (F-stat) Durbin Watson stat Remark: (*) Coefficient is significance at 90 percent confidence. (**) Coefficient is significance at 95 percent confidence. (***) Coefficient is significance at 99 percent confidence. Table 1 shows the statistical result of Thailand s stock market. Testing the overall significance, the probability of F-statistic in each period is equal to The null hypothesis is therefore rejected. The adjusted R-squared of the overall period, pre-crisis period and post-crisis are , and respectively. In the overall period, Thailand s stock market volatility can be significantly explained by capital inflows as a percentage of GDP (CPG), real exchange rates (RER) with 99% confidence and trade balance as a percentage of GDP (TG) with 95% confidence. CPG has a negative effect on volatility, while TG and RER have a positive effect. Capital inflows as a percentage of GDP (CPG) and trade balance as a percentage of GDP (TG) in the pre-crisis period significantly affect volatility with 95% and 90% confidence respectively, and volatility can also be explained by foreign debt as a percentage of GDP (FLG) with 95% confidence. CPG has a negative effect on volatility, while TG and FLG have a positive effect. In the post-crisis period, volatility can be significantly explained by capital inflows as a percentage of GDP (CPG) with 95% confidence, trade balance as a percentage of GDP (TG) and real exchange rates (RER) with 90% confidence, while CPG has a negative effect on volatility, and TG and RER have a positive effect on the volatility. CPG, TG, and FLG have a significant effect on volatility during the normal period, while CPG, TG, and RER have a significant effect on volatility on the crisis period. The results indicate that macroeconomic imbalances do have bearing on the financial crisis in Thailand. The increase in capital inflows led to a significant reduction in volatility in normal periods, while the decrease in capital inflows led to a significant increase in volatility in the crisis periods. This is probably as a result of the large capital inflows during the pre-crisis period, and contributed to financial vulnerability. They also financed insufficiently productive longer-term investments. After the Thai Baht collapsed, investors panicked and lost their confidence in Thailand s economy and stock market, withdrawing their investments en masse from the region and causing Thailand s stock index to plunge considerably then fluctuate violently due the subsequent decrease in capital inflows. The positive effect of TG to stock market volatility shows that increasing trade balances as a percentage of GDP result in significant increase in volatility. In the pre-crisis period, however, Thailand was in trade balance deficits, a consequence of loss in competitiveness due to its real exchange rate appreciation and new competitors. After the crisis, the trade balance of Thailand increased as the Thai Baht saw depreciation. The result shows that increase in trade balance during the crisis period led to significant increase in volatility. It is possible that an increase in trade balance during the crisis period is a result of currency depreciation, and probably contributed to the high stock market fluctuation during the crisis. RER also had a positive effect on volatility during the crisis. Increases in real exchange rate (depreciating Baht) forced a significant increase in volatility, and led to increased value of outstanding US Dollar debt obligations, as domestic firms built up vast un-hedged foreign debt in US Dollars. As the Thai Baht devalued, the local currency value of these debts increased. There was indeed depreciation in the real exchange rate during the crisis period. The ensuing sovereign insolvency was bad news as a result. Thailand s stock market plummeted rapidly and fluctuated wildly. Thailand s stock market volatility can therefore be explained by macroeconomic imbalances. The decrease in capital inflows, increase in trade balances and depreciation in the real exchange rate can cause a significant increase in volatility. Policy makers, should therefore take heed of the size of capital inflows and the trade balance, for if there is downward trend in capital inflows, volatility will increase and a financial crisis may be triggered. Also, if trade balances trends towards the rise, volatility may also increase.

7 CONCLUSION In this study, the relationship between fundamental economic weaknesses and stock market volatility is examined by using Generalized Least Squared (GLS). The results clearly shows that Thailand's financial crisis resulted from fundamental economic weaknesses, and also indicate that several factors of Thailand's financial crisis, namely CPG, TG and RER, had significant effects on Thailand s stock market volatility. It can be concluded that macroeconomic imbalances have significant effects on Thailand. REFERENCES Abeysinghe, T Thai Meltdown and Transmission of Recession within ASEAN4 and NIE4. IMF working paper : Available from Bekaert, G. and Harvey, C.R Foreign Speculators and Emerging Equity Markets. Journal of Finance 55 : Bekaert, G., Harvey, C.R., and Lundblad, C Emerging Equity Markets and Economic Development. NBER working paper : Available from Bollerslev, T., and Wooldridge, J. M Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances. Econometric Reviews 11 : Burnside, C., Eichenbaum, M. and Rebelo, S Hedging and Financial Fragility in Fixed Exchange Rate Regimes. NBER working paper : Available from Bustelo, P., Garcia, C., and Olivie, I Global and Domestic Factors of Financial Crises in Emerging Economies: Lessons From the East Asian Episoded ( ). ICEI Working Paper 16 : Available from Calvo, G. A Capital Flows and Capital Market Crises: The Simple Economics of Sudden Stops. Journal of Applied Economics 1: Corsetti, G Interpreting the Asian Financial Crisis: Open Issues in Theory and Policy. Asian Development Review 16 : Corsetti, G., Pesenti P., and Roubini N. 1998a. What Caused the Asian Currency and Financial Crisis? Part I: a Macroeconomic Overview. NBER working paper : Available from Corsetti, G., Pesenti P., and Roubini N. 1998b. What Caused the Asian Currency and Financial Crisis? Part II: theory and policy responses. NBER working paper : Available from Corsetti, G., Pesenti P., and Roubini N. 1998c. Fundamental Determinants of the Asian Crisis: a Preliminary empirical assessment. NBER working paper : Available from Corsetti, G., Pesenti P., and Roubini N. 1998d. Paper Tigers? A Model of the Asian Crisis. NBER working paper : Available from Dekle, R., and Kletzer, K. M Domestic Bank Regulation and Financial Crises: Theory and Empirical Evidence from East Asia. NBER working paper : Available from Demirgüç-Kunt, A., and Detragiache E., 1998, Financial Liberalization and Financial Fragility. IMF working paper : Available from De Gregorio, J., and Valdes, R. O Crisis Transmission : Evidence from the Debt, Tequila, and Asian Flu Crises. NBER working paper : Available from Dooley, M. P A model of crises in emerging markets. Economic Journal 110 : Eichengreen, B. J., Rose A. K., and Wyplosz, C. A Contagious Currency Crises. NBER working paper : Available from

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