Barro, Robert J., 2001, “Economic Growth in East Asia Before and After the Financial Crisis,” NBER Working Paper No. W8330 (Cambridge, Massachusetts: National Bureau of Economic Research).
Berg, Andrew, 1999, “The Asia Crisis: Causes, Policy Responses and Outcomes,” IMF Working Paper 99/138 (Washington: International Monetary Fund).
Cerra, Valerie, and Sweta C. Saxena, 2002, “Contagion, Monsoons and Domestic Turmoil in Indonesia’s Currency Crisis,” Review of International Economics, Volume 10, Issue 1, pp. 36–44.
Cerra, Valerie, and Sweta C. Saxena, 2000, “Alternative Methods of Estimating Potential Output and the Output Gap: An Application to Sweden,” IMF Working Paper 00/59 (Washington: International Monetary Fund).
Corsetti, G, P. Pesenti, and N. Roubini, 1998, “What Caused the Asian Currency and Financial Crisis?”, NBER Working Paper No. 6833 (Cambridge, Massachusetts: National Bureau of Economic Research).
Diebold, Francis, Joon-Haeng Lee, and Gretchen Weinbach, 1994, “Regime Switching with Time-Varying Transition Probabilities,” in Non-Stationary Time Series Analysis and Cointegration, ed. by C. Hargreaves (Oxford, England: Oxford University Press).
Filardo, Andrew J., 1994, “Business Cycle Phases and Their Transitional Dynamics,” Journal of Business and Economic Statistics, Vol. 12 (July), pp. 299–308.
Friedman, Milton, 1969, Monetary Studies of the National Bureau, the National Bureau Enters its 45th Year, 44th Annual Report, 7-25, NBER, New York; Reprinted in Friedman, M., The Optimum Quantity of Money and Other Essays, Aldine, Chicago.
Friedman, Milton, 1993, “The ‘Plucking Model’ of Business Fluctuations Revisited,” Economic Inquiry, Vol. 31 (April), pp. 171–77.
Garcia, René, 1998, “Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models,” International Economic Review, Vol. 39 (August), pp. 763–88.
Hamilton, James D., 1989, “A New Approach to the Economic Analysis of Nonstationary Times Series and the Business Cycle,” Econometrica, Vol. 57 (March), pp. 357–84.
Hansen, Bruce E., 1992, “The Likelihood Ratio Test Under Non-standard Conditions: Testing the Markov Switching Model of GNP,” Journal of Applied Econometrics, Vol. 7, pp. S61–S82.
Kim, Chang-Jin, and Christian J. Murray, 2002, “Permanent and Transitory Components of Recessions,” Empirical Economics Vol. 27, No. 2, pp. 163–83.
Kim, Chang-Jin, and Charles R. Nelson, 1999, State Space Models with Regime Switching: Classical and Gibbs Sampling Approaches with Applications (Cambridge, Massachusetts: MIT Press).
Kim, Chang-Jin, and Jeremy Piger, 2002, “Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations,” Journal of Monetary Economics, Vol. 49 (September), pp. 1189–1211.
Kochhar, Kalpana, Prakash Lougani, and Mark Stone, 1998, “The East Asian Crisis: Macroeconomic Developments and Policy Lessons,” IMF Working Paper 98/128 (Washington: International Monetary Fund).
Park, Yung Chul, and Jong Wha Lee, 2002, “Recovery and Sustainability in East Asia,” in Korean Crisis and Recovery, ed. by David T. Coe and Se-Jik Kim (Washington: International Monetary Fund).
Radelet, Steven, and Jeffrey Sachs, 1998, “The Onset of the East Asian Financial Crisis,” NBER Working Paper No. 6680 (Cambridge, Massachusetts: National Bureau of Economic Research).
Stock, James H., and M. W. Watson, 1989, “New Indexes of Coincident and Leading Indicators,” in NBER Macroeconomics Annual 1989 Vol. 4, ed. by O. J. Blanchard and S. Fischer (Cambridge, Massachusetts: MIT Press) pp. 351–93.
Stock, James H., and M. W. Watson, 1991, “A Probability Model of the Coincident Economic Indicators,” in Leading Economic Indicators: New Approaches and Forecasting Records, ed. by K. Lahiri and G. H. Moore (New York, NY: Cambridge University Press) pp. 63–85.
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Stock, James H., and M. W. Watson, 1993, “A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experiences,” in Business Cycles, Indicators, and Forecasting, ed. by J. H. Stock and M. W. Watson (Chicago, Illinois: University of Chicago Press) pp. 95–156.
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Economist, European I Department, IMF; and Assistant Professor, Graduate School of Public and International Affairs, University of Pittsburgh, respectively. This paper was presented at the Asian Crisis III conference in Tokyo, Japan in July 2001. The authors gratefully acknowledge Chang-Jin Kim, Chris Murray, and Jeremy Piger for providing original Gauss programs upon which the program used in this paper was based. They would also like to thank Bas Bakker, Craig Beaumont, Peter Berezin, Tarhan Feyzioglu, Munehisa Kasuya, Kalpana Kochhar, and Papa N’Diaye for helpful suggestions.
The assumption of unitary variance is made for identification, but the assumption is not particularly restrictive, as the variances of the permanent and temporary components of output, investment, and consumption depend on the magnitude of the factor loadings.
Quarterly data for Thailand was available for only three years, so it was dropped from consideration.
Several sets of initial values were employed to ensure the robustness of the results.
Testing for the number of states in Markov switching models is complicated by a number of problems, particularly, nuisance parameters under the null hypothesis and a singular Hessian. If there nuisance parameters exist only under the alternative hypothesis but not under the null hypothesis, the likelihood ratio, LM, and Wald tests cannot be applied. In this particular model, some of the AR parameters and transition probabilities are unidentified under the null hypothesis that all of the gammas are zero, or that all of the lambdas are zero. Hansen (1992) and Garcia (1998), among others, have considered the problem of nuisance parameters under the null, but the distribution of the test statistic for the state space model employed in this paper is unknown when nuisance parameters exist only under the alternative hypothesis. Nevertheless, there is scope for inference in the model: the hypothesis that any particular factor loading equals zero does not involve any unidentified parameters and standard distribution theory is valid. Moreover, while the estimations assume the existence of two state variables, there is no reason to presuppose the estimated permanent loss would be economically significant.
Testing whether the transition probabilities, p and q, are zero or one, is complicated by the fact that if the parameter lies on the boundary, standard inference is invalid. As the expected duration of a state becomes either long-lasting or of very short-duration, the associated transition probability would lie close to a boundary value.
These effects are the extent of contemporaneous output loss over 1997–99. To the extent that the sum of the AR coefficients on the permanent components are positive (negative), the output losses would continue to mount (would diminish) beyond the crisis period. The AR components (ϕ1 and ϕ2 in Table 4) sum to a positive number for all countries except Malaysia and the Philippines.
The common temporary component increases for Indonesia, but λ3 is negative, thus the effect on consumption would be negative.