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Contagious Currency Crises

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Title: Contagious Currency Crises


1
Contagious Currency Crises
The Academy of Economic Studies Doctoral School
of Banking and Finance
  • - Dissertation Paper-

Student Dumitru Delia Supervisor Prof.
Moisã Altãr
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
Three generations of models referring to currency
crises
Contagious Currency Crises
  • Krugmans Model (1979) - crises were caused by
    weak economic fundamentals
  • Obstfelds 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.

5
The Data
  • Countries Russia, Ukraine, Latvia, Lithuania,
    Estonia, Poland, Hungary, the Czech Republic, the
    Slovak Republic, Romania and Bulgaria
  • Quarterly Data Q11993- Q12003
  • 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 ei,t - the price of a USD in
    countrys i currency at time t
  • ?ii,t - the variation of
    short term interest rate
  • ?ri,t - the variation of
    international reserves
  • a, ß, ? - weights.

7
When did speculative attacks take place?
  • Extreme values of EMP
  • 1, if EMPi,t1.5sEMPµEMP
  • Crisisi,t
  • 0, otherwise.
  • Results

Quarter RUS UKR SLO POL LIT LAT HUN EST CZH BUL ROM
19983 1 0 0 0 0 0 0 0 0 0 0
19984 0 0 0 0 0 0 0 0 0 0 0
19991 0 0 1 1 0 0 0 1 1 0 0
19992 0 0 0 0 0 0 0 0 0 0 1
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(-).

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

11
Bulgaria
  • 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().

EMP Index
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

12
Estonia
  • Russia EMP - significant positive
    coefficient(1)
  • GDP similarity best results
  • Significant influence
  • - domestic credit()
  • - percentage of current account in GDP(-)
  • - CPI inflation().

EMP Index
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
0.532106 ObsR-squared 0.377274 Prob
0.828087
13
Latvia
Similarity weights
  • No evidence of contagion(35)
  • Significant influences
  • Election()
  • Current account()
  • - CPI inflation().

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

14
Lithuania
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

15
Poland
EMP Index
  • EMP Russia significant
  • GDP similarity - best results
  • Significant influences
  • - government deficit(-)
  • - domestic credit()
  • - deviation of real exchange rate from
    trend().

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

16
The Slovak Republic
  • 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()

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

17
Ukraine
  • EMP Russia significant
  • All similarity coefficients are high
  • Significant influences
  • - money()
  • - current account(-).

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

18
Hungary
  • No evidence of contagion
  • Significant influence
  • - CPI inflation()
  • - deviation of real exchange rate from
    trend()
  • - domestic credit()
  • - employment(-)
  • - money()
  • - current account(-).

EMP Index
Variable 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

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
  • 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)
    0.000000

Breusch-Godfrey Serial Correlation LM
Test F-statistic 0.166708
Probability 0.917425 ObsR-squared 0.000000
Probability 1.000000
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
Probability 0.000000
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).
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