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

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Contagious currency crises

The Academy of Economic Studies

Doctoral School of Banking and Finance

Contagious Currency Crises

- Dissertation Paper-

Student: Dumitru Delia

Supervisor: Prof. Moisã Altãr

Bucharest, July 2003


Objectives
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
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.

Litherature Review

Three generations of models referring to currency crises:

Contagious Currency Crises


The data
The Data: economic fundamentals;

  • 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
When did speculative attacks take place? economic fundamentals;

  • 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.


When did speculative attacks take place1
When did speculative attacks take place? economic fundamentals;

  • Extreme values of EMP:

    1, if EMPi,t≥1.5σEMP+μEMP

    Crisisi,t=

    0, otherwise.

  • Results:


The model
The Model economic fundamentals;

  • 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.


The model1
The Model economic fundamentals;

  • 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.


The czech republic
The Czech Republic economic fundamentals;

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(-).

  • 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
Bulgaria economic fundamentals;

  • 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

  • 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
Estonia economic fundamentals;

  • Russia EMP - significant positive coefficient(1%);

  • GDP similarity: best results;

  • Significant influence:

  • - domestic credit(+);

  • - percentage of current account in GDP(-);

  • - CPI inflation(+).

EMP Index

  • 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-statistic0.64710Prob0.532106

Obs*R-squared0.377274 Prob0.828087


Latvia
Latvia economic fundamentals;

Similarity weights:

  • No evidence of contagion(35%);

  • Significant influences:

  • Election(+);

  • Current account(+);

  • - CPI inflation(+).

  • 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
Lithuania economic fundamentals;

EMP Index

  • No evidence of contagion;

  • High current account similarity;

  • Significant influence:

  • - domestic credit(+);

  • - money(+);

  • - deviation of real exchange rate from trend(+).

  • 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
Poland economic fundamentals;

EMP Index

  • EMP Russia – significant;

  • GDP similarity - best results;

  • Significant influences:

  • - government deficit(-);

  • - domestic credit(+);

  • - deviation of real exchange rate from trend(+).

  • R-squared 0.742046

  • Adjusted R-squared 0.677558

  • S.E. of regression 0.028311

  • Schwarz criterion-3.801626

  • F-statistic11.50665

  • Prob(F-statistic) 0.000025

  • Akaike info criterion-4.091956


The slovak republic
The Slovak Republic economic fundamentals;

  • 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

  • R-squared 0.777728

  • Adjusted R-squared 0.728334

  • S.E. of regression 0.023180

  • Schwarz criterion-4.195540

  • Akaike info criterion-4.091956


Ukraine
Ukraine economic fundamentals;

  • EMP Russia significant;

  • All similarity coefficients are high;

  • Significant influences:

  • - money(+);

  • - current account(-).

EMP Indexes

  • 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


Hungary
Hungary economic fundamentals;

  • No evidence of contagion;

  • Significant influence:

  • -CPI inflation(+);

  • - deviation of real exchange rate from trend(+);

  • - domestic credit(+);

  • - employment(-);

  • - money(+);

  • - current account(-).

EMP Index

  • R-squared 0.829776

  • Adjusted R-squared 0.793300

  • S.E. of regression 0.026885

  • Schwarz criterion-3.906587

  • Akaike info criterion-4.217656


Romania
Romania economic fundamentals;

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(+)


Romania1
Romania economic fundamentals;

  • Variable CoefficientStd. Errort-StatisticProb.

  • D(CPI,2) 0.000835 0.0004052.0620370.0518

  • C 1.029751 0.2482854.1474570.0005

  • D(DEF)-1.09E-05 3.83E-06-2.8403050.0098

  • DGDP-1.097253 0.249253-4.4021710.0002

  • D(DTSREZ) 0.778237 0.1816454.2843910.0003

  • D(DEVREER,2) 0.000529 0.0001055.0340970.0001

  • EMP1RUS(-3) 0.248825 0.0526444.7266020.0001

  • 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

Obs*R-squared0.000000 Probability 1.000000


Romania2
Romania economic fundamentals;

  • Bilateral trade weights: twice the percentage of exports and once the percentage of imports with Russia;

  • The Wald test in this case:

F-statistic 80.62561Probability0.000000

Chi-square80.62561Probability 0.000000


Conclusions
Conclusions economic fundamentals;

  • 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
References economic fundamentals;

  • 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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