Download - Contagious Currency Crises
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
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.
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.
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
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 .
When did speculative attacks take place?
• Index of exchange market pressure :
where: ei,t - the price of a USD in country’s i currency at time t; Δii,t - the variation of short term interest rate; Δri,t - the variation of international reserves; α, β, γ - weights.
titititi rieEMP ,,,, %%
When did speculative attacks take place?
• Extreme values of EMP: 1, if EMPi,t≥1.5σEMP+μEMP
Crisisi,t= 0, otherwise. • Results:
Quarter RUS UKR SLO POL LIT LAT HUN EST CZH BUL ROM
1998:3 1 0 0 0 0 0 0 0 0 0 0
1998:4 0 0 0 0 0 0 0 0 0 0 0
1999:1 0 0 1 1 0 0 0 1 1 0 0
1999:2 0 0 0 0 0 0 0 0 0 0 1
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.
tititjti LIEMPEMP ,,,, )(
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.
]/)[(]/)[(1 ,,, iitiiitjji xxw
The Czech Republic
-.2
-.1
.0
.1
.2
.3
93 94 95 96 97 98 99 00 01 02
EMP1CEH
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(-).variable Coefficient T-statistic Prob.
D(pctcrt(-1)) -1.135928 -5.946943 0.0000
D(domcred(-2)) 0.000823 4.943256 0.0000
DGDP(-2) -0.050498 -1.582290 0.1252
Emp1rus(-2) 0.081906 2.714749 0.0114
• R-squared 0.628581 • Adjusted R-squared 0.559800
• S.E. of regression
0.042134 • Schwarz criterion -3.060881
• Akaike info criterion -3.332973
Bulgaria
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
93 94 95 96 97 98 99 00 01 02
EMP1BULG
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(+).
variable Coefficient T-statistic Prob.
CPIL 0.515084 12.09939 0.0000
ctcrt -0.000188 -2.383844 0.0232
Devreer(-1) 0.582110 13.53560 0.0000
dtsrez 0.103150 1.625161 0.1139
• R-squared 0.836911 • Adjusted R-squared
0.816524 • S.E. of regression
0.192737 • Schwarz criterion -0.112205
• Akaike info criterion -0.329896
Estonia
-.16
-.12
-.08
-.04
.00
.04
.08
.12
93 94 95 96 97 98 99 00 01 02
EMP1EST
EMP Index•Russia EMP - significant positive coefficient(1%);
•GDP similarity: best results;
•Significant influence: - domestic credit(+); - percentage of current account in GDP(-); - CPI inflation(+).
variable Coefficient T-statistic Prob.
CPIL 0.008067 3.431687 0.0019
pctcrt -0.325318 -4.079743 0.0004
Emp1rus(-2) 0.120280 3.997495 0.0004
D(domcred(-1),2) 5.51E-06 1.562903 0.1297
• 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 0.532106Obs*R-squared 0.377274 Prob 0.828087
Latvia
-.06
-.04
-.02
.00
.02
.04
.06
93 94 95 96 97 98 99 00 01 02
EMP1LET
•No evidence of contagion(35%);
•Significant influences:- Election(+);- Current account(+);- CPI inflation(+).
0.0
0.2
0.4
0.6
0.8
1.0
93 94 95 96 97 98 99 00 01 02
SIMCPISIMCTCRTSIMDOMCRED
SIMGDPSIMMONEY
Similarity weights:
variable Coefficient T-statistic Prob.
CPIL 0.004705 2.804809 0.0092
ctcrt 0.000127 6.204786 0.0000
elections 0.019899 2.306785 0.0290
• 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
Lithuania
-.12
-.10
-.08
-.06
-.04
-.02
.00
.02
93 94 95 96 97 98 99 00 01 02
EMP2LIT
EMP Index•No evidence of contagion;
•High current account similarity;
•Significant influence: - domestic credit(+); - money(+); - deviation of real exchange rate from trend(+).
variable Coefficient T-statistic Prob.
D(domcred) 1.29E-05 2.711043 0.0112
D(money) 2.65E-05 1.973154 0.0581
devreer 0.004673 1.765932 0.0879• 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
Poland
-.10
-.05
.00
.05
.10
.15
93 94 95 96 97 98 99 00 01 02
EMP1POL
EMP Index
variable Coefficient T-statistic Prob.
Defbug(-1) -2.18E-06 -2.728212 0.0130
D(domcred) 2.08E-0.6 2.478591 0.0222
devreer 0.557848 4.599356 0.0002
Emp1rus(-2) 0.044744 3.077666 0.0059
• R-squared 0.742046 • Adjusted R-squared 0.677558 • S.E. of regression 0.028311 • 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(+).
The Slovak Republic
-.08
-.04
.00
.04
.08
.12
.16
93 94 95 96 97 98 99 00 01 02
EMP1SLO
EMP Index
Variable Coefficient T-statistic Prob.
DGDP(-1) -0.078978 -4.732886 0.0001
D(money(-1)) 9.62E-06 5.888247 0.0000
dtsrez 0.096540 4.052545 0.0004
D(domcred(-1),2) 3.21E-07 4.636595 0.0001
devreer 0.041408 4.985542 0.0000
Emp1rus(-2) 0.027616 1.542939 0.1345
• R-squared 0.777728 • Adjusted R-squared 0.728334
• S.E. of regression 0.023180
• 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(+)
Ukraine
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
93 94 95 96 97 98 99 00 01 02
EMP1UCR EMP2UCR
EMP Indexes
Variable Coefficient T-statistic Prob.
D(ctcrt) -9.12E-05 -2. 880143 0.0114
Emp2rus 0.488519 8.394680 0.0000
• R-squared 0. 854556 • Adjusted R-squared 0.806074
• S.E. of regression 0.077818
• 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(-).
Hungary
-.16
-.12
-.08
-.04
.00
.04
.08
.12
.16
93 94 95 96 97 98 99 00 01 02
EMP2UNGVariable Coefficient T-statistic Prob.
D(dCPI) 0.517071 2.416113 0.0225
D(money,2) 9.37E-05 4.713845 0.0001
employment -2.60E-05 -8.202428 0.0000
D(domcred,2) 7.31E-05 6.201601 0.0000
devreer 0.006794 5.448621 0.0000
D(ctcrt) 1.99E-05 1.965977 0.0593
• R-squared 0.829776 • Adjusted R-squared 0.793300
• S.E. of regression 0.026885
• 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
Romania
-.6
-.5
-.4
-.3
-.2
-.1
.0
.1
.2
.3
93 94 95 96 97 98 99 00 01 02
EMP1ROM
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(+)
Romania• Variable Coefficient 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-squared 0.877002 S.D. dependent var 0.158816• S.E. of regression 0.055698 Akaike info criterion -
2.708777• Sum squared resid 0.065149 Schwarz criterion -2.331592• Log likelihood 47.27727 F-statistic
29.52075• Durbin-Watson stat 1.843044 Prob(F-statistic) 0.000000Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.166708 Probability 0.917425Obs*R-squared 0.000000 Probability 1.000000
Romania
00,020,040,060,080,10,120,14
93 94 95 96 97 98 99 2000
Year
Bilateral weights Romania-Russia
Import weights Export weights
•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 Probability 0.000000
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.
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).