1. Contagious Currency Crises - Dissertation Paper- Student: Dumitru Delia Supervisor: Prof. Moisã Altãr The Academy of Economic Studies Doctoral School of Banking and Finance Bucharest, July 2003

2. Objectives: The Currency Crisis from Russia, august 1998: testing for the existence of a contagion effect; Determine whether the macroeconomic similarities between countries represented a channel of contagion; Determine the domestic economic fundamentals that influenced the pressure on the exchange market.

3. Definitions: A currency crisis is usually defined as a situation in which an attack on the currency leads to a sharp depreciation of the exchange rate. Testing for contagion means searching whether the probability of a crisis in a country at a point in time increases the probability of crises in other countries after controlling for the effect of political and economic fundamentals.

4. Litherature Review Krugman’s Model (1979) - crises were caused by weak economic fundamentals; Obstfeld’s Model (1986) - self- fulfilling crises; Early Warning System Models: -Kaminsky, Lizondo and Reinhart, 1998; -Eichengreen, Rose and Wyplosz, 1996; Gerlach and Smets (1995)- trade links; Goldfajn and Valdes (1995) – illiquidity; Eichengreen, Rose and Wyplosz (1996)- trade and similarity links; Sachs, Tornell and Velasco (1996)- contagion due to similar economic features. Three generations of models referring to currency crises: Contagious Currency Crises

5. The Data: Countries: Russia, Ukraine, Latvia, Lithuania, Estonia, Poland, Hungary, the Czech Republic, the Slovak Republic, Romania and Bulgaria; Quarterly Data: Q1:1993- Q1:2003; Date Sources: International Financial Statistics, IMF-World Bank-OECD-BIS joint table.

6. When did speculative attacks take place? Index of exchange market pressure : where: e i,t - the price of a USD in country’s i currency at time t; Δi i,t - the variation of short term interest rate; Δr i,t - the variation of international reserves; α, β, γ - weights.

7. When did speculative attacks take place? Extreme values of EMP: 1, if EMP i,t ≥1.5σ EMP +μ EMP Crisis i,t = 0, otherwise. Results: QuarterRUSUKRSLOPOLLITLATHUNESTCZHBULROM 1998:310000000000 1998:400000000000 1999:100110001100 1999:200000000001

8. The Model  Equation:  Fundamentals: - domestic credit; - current account; - CPI growth; - employment; - GDP growth; - unemployment; - money; - government deficit; - ratio of short term debt to reserves; - deviation of the real exchange rate from the trend.

9. The Model Determine the macroeconomic similarities whose existence might be a potential channel for contagion. Being “similar” means having similar macroeconomic conditions; Similarity weights: Variables: domestic credit, money, CPI, output growth and current account.

10. The Czech Republic EMP index Russia EMP- significant positive coefficient; Current account similarity: significance (1%); domestic credit and money-no sign. Domestic influences: - domestic credit(+); - ratio of short term debt to reserves(+); - percentage of current account in GDP(-); - economic growth(-). variableCoefficientT-statisticProb. D(pctcrt(-1))-1.135928-5.9469430.0000 D(domcred(-2))0.0008234.9432560.0000 DGDP(-2)-0.050498-1.5822900.1252 Emp1rus(-2)0.0819062.7147490.0114 R-squared0.628581 Adjusted R-squared0.559800 S.E. of regression 0.042134 Schwarz criterion -3.060881 Akaike info criterion -3.332973

11. Bulgaria EMP Index The probability that Russia EMP might be significant is around 50%; Domestic fundamentals found significant: - CPI inflation(+); - current account(-); - ratio of short term debt to reserves(+); - deviation of real exchange rate from trend(+). variableCoefficientT-statisticProb. CPIL0.51508412.099390.0000 ctcrt-0.000188-2.3838440.0232 Devreer(-1)0.58211013.535600.0000 dtsrez0.1031501.6251610.1139 R-squared 0.836911 Adjusted R-squared 0.816524 S.E. of regression 0.192737 Schwarz criterion -0.112205 Akaike info criterion -0.329896

12. Estonia EMP Index Russia EMP - significant positive coefficient(1%); GDP similarity: best results; Significant influence: - domestic credit(+); - percentage of current account in GDP(-); - CPI inflation(+). variableCoefficientT-statisticProb. CPIL0.0080673.4316870.0019 pctcrt-0.325318-4.0797430.0004 Emp1rus(-2)0.1202803.9974950.0004 D(domcred(-1),2)5.51E-061.5629030.1297 R-squared 0.443104 Adjusted R-squared 0.339975 S.E. of regression 0.040774 Schwarz criterion -3.126489 Akaike info criterion -3.398581 Breusch-Godfrey Serial Correlation LM Test: F-statistic 0.64710 Prob 0.532106 Obs*R-squared 0.377274Prob 0.828087

13. Latvia No evidence of contagion(35%); Significant influences: - Election(+); - Current account(+); - CPI inflation(+). Similarity weights: variableCoefficientT-statisticProb. CPIL0.0047052.8048090.0092 ctcrt0.0001276.2047860.0000 elections0.0198992.3067850.0290 R-squared 0.576670 Adjusted R-squared 0.513954 S.E. of regression 0.017422 Schwarz criterion -4.890526 Akaike info criterion -5.119547 Durbin – Watson stat 2.082432

14. Lithuania EMP Index No evidence of contagion; High current account similarity; Significant influence: - domestic credit(+); - money(+); - deviation of real exchange rate from trend(+). variableCoefficientT-statisticProb. D(domcred)1.29E-052.7110430.0112 D(money)2.65E-051.9731540.0581 devreer0.0046731.7659320.0879 R-squared 0.618261 Adjusted R-squared 0.578770 S.E. of regression 0.020152 Schwarz criterion -4.676371 Akaike info criterion -4.857766 Durbin – Watson stat 2.071606

15. Poland EMP Index variableCoefficientT-statisticProb. Defbug(-1)-2.18E-06-2.7282120.0130 D(domcred)2.08E-0.62.4785910.0222 devreer0.5578484.5993560.0002 Emp1rus(-2)0.0447443.0776660.0059 R-squared0.742046 Adjusted R-squared0.677558 S.E. of regression0.028311 Schwarz criterion -3.801626 F-statistic 11.50665 Prob(F-statistic)0.000025 Akaike info criterion-4.091956 EMP Russia – significant; GDP similarity - best results; Significant influences: - government deficit(-); - domestic credit(+); - deviation of real exchange rate from trend(+).

16. The Slovak Republic EMP Index VariableCoefficientT-statisticProb. DGDP(-1)-0.078978-4.7328860.0001 D(money(-1))9.62E-065.8882470.0000 dtsrez0.0965404.0525450.0004 D(domcred(-1),2)3.21E-074.6365950.0001 devreer0.0414084.9855420.0000 Emp1rus(-2)0.0276161.5429390.1345 R-squared0.777728 Adjusted R-squared0.728334 S.E. of regression0.023180 Schwarz criterion -4.195540 Akaike info criterion-4.091956 EMP Russia – positive coefficient; High current account similarity; Influences: - GDP growth(-) - money(+) - deviation of real exchange rate from trend(+) - domestic credit(+) - ratio of short term debt to reserves(+)

17. Ukraine EMP Indexes VariableCoefficientT-statisticProb. D(ctcrt)-9.12E-05-2. 8801430.0114 Emp2rus0.4885198.3946800.0000 R-squared0. 854556 Adjusted R-squared0.806074 S.E. of regression0.077818 Schwarz criterion -1.735484 Akaike info criterion-2.033919 Durbin-Watson 1.783723 EMP Russia significant; All similarity coefficients are high; Significant influences: - money(+); - current account(-).

18. Hungary VariableCoefficientT-statisticProb. D(dCPI)0.5170712.4161130.0225 D(money,2)9.37E-054.7138450.0001 employment-2.60E-05-8.2024280.0000 D(domcred,2)7.31E-056.2016010.0000 devreer0.0067945.4486210.0000 D(ctcrt)1.99E-051.9659770.0593 R-squared0.829776 Adjusted R-squared0.793300 S.E. of regression0.026885 Schwarz criterion -3.906587 Akaike info criterion-4.217656 No evidence of contagion; Significant influence: - CPI inflation(+); - deviation of real exchange rate from trend(+); - domestic credit(+); - employment(-); - money(+); - current account(-). EMP Index

19. Romania EMP Index EMP Russia – positive significant coefficient; Domestic fundamentals: - CPI inflation(+) - deviation of real exchange rate from trend(+) - ratio of short term debt to reserves(+) - Government deficit(+)

20. Romania VariableCoefficient Std. Error t-Statistic Prob. D(CPI,2)0.000835 0.000405 2.062037 0.0518 C 1.029751 0.248285 4.147457 0.0005 D(DEF) -1.09E-05 3.83E-06 -2.840305 0.0098 DGDP -1.097253 0.249253 -4.402171 0.0002 D(DTSREZ)0.778237 0.181645 4.284391 0.0003 D(DEVREER,2)0.000529 0.000105 5.034097 0.0001 EMP1RUS(-3)0.248825 0.052644 4.726602 0.0001 R-squared 0.907751 Mean dependent var-0.032190 Adjusted R-squared0.877002 S.D. dependent var 0.158816 S.E. of regression 0.055698 Akaike info criterion-2.708777 Sum squared resid0.065149 Schwarz criterion-2.331592 Log likelihood 47.27727 F-statistic 29.52075 Durbin-Watson stat1.843044 Prob(F-statistic) 0.000000 Breusch-Godfrey Serial Correlation LM Test: F-statistic 0.166708 Probability0.917425 Obs*R-squared 0.000000 Probability1.000000

21. Romania Bilateral trade weights: twice the percentage of exports and once the percentage of imports with Russia; The Wald test in this case: F-statistic 80.62561 Probability 0.000000 Chi-square 80.62561 Probability0.000000

22. Conclusions A speculative attack in Russia seems to have increased significantly the odds of an attack in 6 of the countries included in the sample - it does not represent a definitive proof of contagion; The hypothesis that attacks spread to other countries where economic policies and conditions are similar is not always confirmed – similarities are difficult to capture in a weighting scheme. The fundamental causes of speculative attacks differ across countries- it is very difficult to find a set of fundamentals underlying all crises.

23. References Abiad, A (2003), “Early Warning Systems: a Survey and a Regime – Switching Approach”, IMF Working Paper No.32/2003 ((Washington: International Monetary Fund). Berger, W. and H. Wagner (2002), “Spreading Currecncy Crises: The Role of Economic Interdependence”, IMF Working Paper No.02/144 (Washington: International Monetary Fund). Bussiere, M and M.Fratzcher (2002), “Towards a New Early Warning System of Financial Crises”, ECB Working Paper No. 145/2002 (European Central Bank). Bussiere, M. and C. Mulder (1999), “External Vulnerability in Emerging market economies: How High Liquidity can offset Weak Fundamentals and the Effects of Contagion”, IMF Working Paper No.99/88 (Washington: International Monetary Fund). Eichengreen, B., A.K.Rose and C.Wyplosz (1996), “Contagious Currency Crises”, NBER Working Paper No.5681 (Cambridge: National Bureau of Economic Research). Frankel, J. and A.K.Rose (1996), “Currency Crashes in Emerging Markets: Empirical Indicators”, NBER Working Paper No.5437/96 (Cambridge: National Bureau of Economic Research). Fratzcher, M. (2002), “On Currency Crises and Contagion”, ECB Working Paper No. 139/2002 (European Central Bank). Ghosh, S. and A. Ghosh (2002), “Structural Vulnerabilities and Currency Crises”, IMF Working Paper No.02/9 (Washington: International Monetary Fund). Kaminsky, G., S. Lizondo and C.Reinhart (1998), “Leading Indicators of Currency Crises”, Staff Papers, International Monetary Fund, Vol.45. Kaminsky, G. and C.Reinhart (1996), “The Twin Crises: The Causes of Banking and Balance of Payments Problems”, International Finance Discussion Paper, (Washington: Board of Governors of the Federal System). Kaminsky, G (1999), “Currency and banking Crises: The Early Warnings of Distress”, IMF Working Paper No.99/178 (Washington: International Monetary Fund). Mathieson, D, J. A.Chan-Lau and J.Y.Yoo, 2002, “Extreme Contagion in Equity Markets”, IMF Working Paper No.02/98 (Washington: International Monetary Fund).