Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator Nilai Tukar Riil Menggunakan Model SWARCH (2,3)

Sugiyanto Sugiyanto, Etik Zukhronah, Dewi Retnosari

Abstract

The financial crisis that hit Asia in mid-1997 began with the financial crisis in Thailand which then spread to Indonesia. The impact of the financial crisis in Indonesia is so severe that a crisis detection system is needed. The financial crisis detection system can be done by simple monitoring of macroeconomic indicators such as real exchange rate. Excessive real exchange rate is predicted to have a great chance of crisis.
The result shows that the real exchange rate from January 1990 to June 2013 has heteroscedasticity effect and there are structural changes so it can be modeled using SWARCH model (2,3) with ARMA (1.0) as conditional average model and ARCH (3) as model conditional variance. The inferred probabilities value of the SWARCH (2,3) model in February 1998 of 1 and July 1998 of 0.9968 over 0.5 indicates that the period is in a high volatile condition indicating a crisis. The SWARCH model (2.3) based on the real exchange rate indicator was able to capture the high volatile conditions in February 1998 and July 1998 as the impact of the 1997 Asian financial crisis.
Keywords : Deteksi, krisis keuangan, nilai tukar riil, SWARCH

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References

Abimanyu, A. dan M. H. Imansyah, Sistem Pendeteksian Dini Krisis Keuangan di Indonesia, Fakultas Ekonomi UGM, Yogyakarta, 2008.

Bollerslev, T., Generalized Autoregressive Conditional Heteroscedasticity, Journal of Econometrics 31 (1986), 307 – 327.

Canarella, G. and S. K. Pollard, A Switching ARCH (SWARCH) Model of Stock Market Volatility: Some Evidence from Latin America, International of Review Economics 54 (2007), 445-462.

Cerra, V. and S. C. Saxena, Contagion, Monsoons, and Domestic Turmoil in Indonesia: A Case Study in the Asian Currency Crisis, IMF Working Paper, 2000.

Chang, K., K. Y. Cho, and M. Hong, Stock Volatility, Foreign Exchange Rate Volatility and the Global Financial Crisis, Journal of Economic Research 15 (2010), 249-272.

Cryer, J. D., Time Series Analysis, PWS Publisherrs Duxbury Press, Boston, 1986.

Edison, H. J., Do indicators of financial crises work? An evaluation of an early warning system, International Journal of Finance and Economics 8 (2000), no.1, 11-53.

Engle, R. F., Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Journal of Econometrica 50 (1982), no.4, 987 – 1006.

Ford, J. L., B. Santoso dan N. J. Horsewood, Asian Currency Crisis: Do Fundamentals Still Matter? A Markov-switching Approach to Causes and Timming, Working Papers, Working papers, 2007.

Gujarati, D. N., Basic Econometrics, 4 ed., The McGraw-Hill Companies, 2004.

Gray, S.F, Modeling the Conditional Distribution of Interest rates as a Regime-Switching Process, Econometrics 42 (2006), 27-62.

Hamilton, J. D., A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57 (1989), no. 2, 357-384.

Hamilton, J. D. and R. Susmel, Autoregressive Conditional Heteroscedas-ticity and Changes in Regime, Journal of Econometrics 64 (1994), 307-333.

Kaminsky, G., S. Lizondo, and C. M. Reinhart, Leading Indicators of Currency Crises, International Monetary Fund Staff Papers 45 (1998), no. 1, 1-48.

Tim Kajian Pola Krisis Ekonomi, Laporan Tim Kajian Pola Krisis Ekonomi, Kementrian Keuangan, Indonesia, 2012.

Tsay, R. S., Analysis of Financial Time Series, John Wiley and Sons, Canada, 2002.

DOI: https://doi.org/10.13057/ijas.v1i1.24082

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