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

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