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Designing an Early Warning System for Currency Crisis in Iran's Economy: An Application of Bayesian Averaging and Markov Regime-Switching with Endogenous Transition Probability | ||
| اقتصاد باثبات | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 09 آبان 1405 اصل مقاله (939.86 K) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22111/sedj.2026.54511.1677 | ||
| نویسندگان | ||
| Alireza Ghobashi* 1؛ Teymour Mohammadi2؛ Reza Taleblo3 | ||
| 1Ph.D. in economics, Corresponding Author, Allameh Tabatabaei university, Tehran, Iran. | ||
| 2Professor, Department of Economics, Faculty of Economics, Allameh Tabataba’i University, Tehran, Iran. | ||
| 3Associate Professor, Department of Economics, Faculty of Economics, Allameh Tabataba’i University, Tehran, Iran | ||
| چکیده | ||
| The recurrence of periods of severe economic stress and sharp exchange-rate depreciations in Iran over the 2001–2021 period highlights the need for an analytical tool capable of identifying exchange-rate vulnerabilities at an early stage. The primary objective of this study is to develop an early warning system for forecasting currency crises and estimating the probability of transitions between periods of stability and crisis. The main contribution of the paper lies in integrating two complementary econometric approaches. First, Bayesian Model Averaging (BMA) is employed to address model uncertainty and identify key determinants from a broad set of macroeconomic variables and a Google Trends–based uncertainty index. Second, these variables are incorporated into a Markov-switching framework with endogenous transition probabilities to capture the nonlinear behavior of the foreign exchange market.The Bayesian results indicate that the exchange-rate gap, liquidity growth, external-sector conditions, the budget deficit, and the uncertainty index have the highest posterior probabilities in explaining the Exchange Market Pressure (EMP) index. The findings from the Markov-switching model further confirm the nonlinear dynamics of the foreign exchange market and show that the probability of transitioning from a tranquil regime to a crisis regime is significantly affected by these variables. In-sample and out-of-sample evaluations confirm the model’s high accuracy in reproducing EMP dynamics and generating timely warning signals ahead of the currency crises of 2012 and 2018. From a policy perspective, continuous monitoring of these key variables, together with structural reforms in monetary and fiscal policy and effective management of expectations, can significantly reduce the likelihood of the economy entering a currency-crisis regime | ||
| کلیدواژه‌ها | ||
| Currency crisis؛ Early Warning System (EWS) Bayesian Averaging؛ Markov Switching؛ Uncertainty Index | ||
| مراجع | ||
|
Abiad, A. (2003). Early warning systems: A survey and a regime-switching approach. IMF Working Paper 03/32. International Monetary Fund.
Abrishami, H., Kamijani, A., Nouri, M., & Memarian, M. H. (2020). Early warning system of currency crises using Bayesian model averaging and Markov switching approaches. Journal of Monetary Economics Studies, 18(2), 45–72. (in persian)
Afonso, A., & Silva, J. (2020). Leading indicators for financial crises: Evidence from European countries. Economic Modelling, 93, 120–134. https://doi.org/10.1016/j.econmod.2020.07.006
Aghion, P., Bacchetta, P., & Banerjee, A. (2000). A simple model of monetary policy and currency crises. European Economic Review, 44(4–6), 728–738.
Alessi, L., & Detken, C. (2018). Identifying excessive credit growth and leverage. Journal of Financial Stability, 35, 215–245.
Babecký, J., Havránek, T., & Matějů, J. (2014). Early warning indicators of economic crises: Lessons from the 2008–2009 global financial crisis. Czech Journal of Economics and Finance, 64(4), 302–321.
Babecký, J., Havránek, T., & Matějů, J. (2021). Economic crises and crisis indicators revisited. Economic Modelling, 95, 94–113.
Babecký, J., Havránek, T., Matějů, J., Rusnák, M., Šmídková, K., & Vašíček, B. (2012). Leading indicators of crisis incidence: Evidence from developed countries. Journal of International Money and Finance, 31(5), 1293–1311.
Bayani, M., & Mohammadi, T. (2019). Investigating the causes and indicators of currency crises in Iran using early warning models. Iranian Economic Research Quarterly, 23(2), 55–78. (in Persian)
Belke, A., Domnick, C., & Gros, D. (2019). Business cycle synchronization in the EMU: Core vs. periphery. Journal of Economic Integration, 34(1), 1–33.
Berg, A., & Pattillo, C. (1999). Predicting currency crises: The indicators approach and an alternative. Journal of International Money and Finance, 18(4), 561–586.
Bontempi, M. E., Golinelli, R., & Squadrani, M. (2016). Forecasting crises in emerging markets: Evidence from macro-financial indicators. Empirical Economics, 51(4), 1475–1498.
Boudia, N., Sy, A., & Sghaier, I. M. (2019). Early warning systems for currency crises using dynamic panel threshold models. Applied Economics Letters, 26(9), 750–755.
Brewer, T. (2006). International political economy of foreign exchange crises. Global Economy Journal, 6(4), 1–28.
Caggiano, G., Castelnuovo, E., Colombo, V., & Nodari, G. (2014). Estimating fiscal multipliers: News from a non-linear world. Economic Journal, 125(584), 746–776.
Choi, H., & Varian, H. (2012). Predicting the present with Google Trends. Economic Record, 88(s1), 2–9.
Corsetti, G., Pesenti, P., & Roubini, N. (1998). Paper tigers? A model of the Asian crisis. European Economic Review, 43(7), 1211–1236.
Dzielinski, M. (2012). News sensitivity and the cross-section of stock returns. Journal of Finance and Quantitative Analysis, 47(6), 1249–1270.
Edison, H. J. (2003). Do indicators of financial crises work? An evaluation of an early warning system. International Journal of Finance & Economics, 8(1), 11–53.
Edwards, S. (1984). The order of liberalization of the external sector in developing countries. Princeton Essays in International Finance, 156, 1–43.
Farzanegan, M. R. (2020). Oil booms and government expenditures in the Iranian economy. Energy Policy, 139, 111342. https://doi.org/10.1016/j.enpol.2020.111342
Feldkircher, M. (2014). The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk. Journal of International Money and Finance, 43, 19–49.
Filardo, A. (1994). Business-cycle phases and their transitional dynamics. Journal of Business & Economic Statistics, 12(3), 299–308.
Flood, R. P., & Garber, P. (1984). Collapsing exchange-rate regimes: Some linear examples. Journal of International Economics, 17(1–2), 1–13.
Frankel, J. A., & Rose, A. K. (1996). Currency crashes in emerging markets: An empirical treatment. Journal of International Economics, 41(3–4), 351–366.
Ghobashi A, Mohammadi T, Taleblou R, Seyednourani S M. Ranking of Factors Affecting Currency Crises and Their Implications for the Iranian Economy.. J. Mon. Ec. 2024; 19 (1) : 5 URL: http://jme.mbri.ac.ir/article-1-681-en.html (in persian)
Ghosh, A., & Ghosh, S. (2002). Structural vulnerabilities and currency crises. Emerging Markets Review, 3(3), 217–238.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357–384.
Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford University Press.
Jordà, Ò., Schularick, M., & Taylor, A. M. (2017). Macrofinancial history and the new business cycle facts. NBER Macroeconomics Annual, 31(1), 213–263.
Kaminsky, G. L., & Reinhart, C. M. (1999). The twin crises: The causes of banking and balance-of-payments problems. American Economic Review, 89(3), 473–500.
Kaminsky, G. L., Lizondo, S., & Reinhart, C. M. (1998). Leading indicators of currency crises. IMF Staff Papers, 45(1), 1–48.
Khosrosereski, M., & Dashtbani, M. (2024). Applying the Markov-switching model to identify exchange‑rate regimes in Iran. Economic Policy Research Journal, 12(1), 33–59. (in Persian)
Korhonen, I., & Mehrotra, A. (2010). Real exchange rate, output and oil: Case of four large energy producers. Journal of Economics and Business, 62(5), 391–404.
Krugman, P. (1979). A model of balance-of-payments crises. Journal of Money, Credit and Banking, 11(3), 311–325.
Lanoie, P., & Lemarbre, C. (1996). Three approaches to predict the timing of environmental policy change. Environmental and Resource Economics, 7, 111–127.
Leamer, E. E. (1978). Specification searches: Ad hoc inference with nonexperimental data. John Wiley & Sons.
Nasrollahi, M., Mohammadzadeh, A., & Esfandiari, R. (2017). An empirical analysis of the performance of an early warning system for the Iranian foreign exchange market. Iranian Economic Studies, 21(3), 119–144. (in Persian)
Obstfeld, M. (1994). The logic of currency crises. Cahiers Economiques et Monetaires, 43, 189–213.
Obstfeld, M. (1996). Models of currency crises with self-fulfilling features. European Economic Review, 40(3–5), 1037–1047.
Pesaran, M. H., & Mohaddes, K. (2020). The global VAR (GVAR) approach to modelling and forecasting macroeconomic interdependencies. Cambridge Working Papers in Economics, 2031.
Pires, J. M., Pereira, A., & Coelho, M. (2013). Designing and evaluating early warning systems: The Portuguese banking case. Economic Modelling, 33, 614–626.
Quandt, R. E. (1972). A new approach to estimating switching regressions. Journal of the American Statistical Association, 67(338), 306–310.
Radelet, S., & Sachs, J. D. (1998). The East Asian financial crisis: Diagnosis, remedies, prospects. Brookings Papers on Economic Activity, 29(1), 1–90.
Raftery, A. E., Gneiting, T., Balabdaoui, F., & Polakowski, M. (1999). Using Bayesian model averaging to calibrate forecast ensembles. Monthly Weather Review, 127(9), 2277–2287.
Raftery, A. E., Madigan, D., & Hoeting, J. A. (1997). Bayesian model averaging for linear regression models. Journal of the American Statistical Association, 92(437), 179–191.
Reinhart, C. M., & Rogoff, K. S. (2009). This time is different: Eight centuries of financial folly. Princeton University Press.
Sala-i-Martin, X., Doppelhofer, G., & Miller, R. I. (2004). Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. American Economic Review, 94(4), 813–835.
Salmani, H., Hosseini, S., & Gholami, A. (2019). Evaluating leading indicators of currency crises in Iran. Economic Research, 19(1), 89–112. (in Persian)
Sen, A., & Schmidt, P. (2011). On the use of BMA in model selection. Econometric Reviews, 30(5), 445–463.
Sevim, C., Oztekin, A., Bali, O., Gumus, S., & Guresen, E. (2014). Developing an early warning system to predict currency crises. Expert Systems with Applications, 41(4), 1856–1868.
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