Volume 19, Issue 1 (3-2024)
J. Mon. Ec. 2024, 19(1): 93-117 |
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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
URL: http://jme.mbri.ac.ir/article-1-681-en.html
1- Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran
2- Professor of Economics, Faculty of Economics, Allameh Tabatabai University,Iran
2- Professor of Economics, Faculty of Economics, Allameh Tabatabai University,Iran
Abstract: (1517 Views)
This research aims to rank the most persistent factors influencing currency crises in Iran. It analyzes key variables using Bayesian averaging methods applied to seasonal data from 2001 to 2021. Unlike classical approaches, Bayesian analysis accounts for uncertainty and prior knowledge in model and parameter selection, offering a more accurate evaluation of the significance and effects of each variable on currency crises. By integrating uncertainty into the modeling process, Bayesian techniques improve the precision in identifying the most influential factors. The results reveal that nine key variables significantly impact exchange rate fluctuations. Among these, the export-to-output ratio, the deviation of the exchange rate from its equilibrium level, inflation, and the uncertainty index play crucial roles in determining exchange rate movements. Moreover, imbalanced liquidity growth and rising inflation intensify pressure on the exchange rate, thereby increasing the risk of currency crises. Excessive liquidity expansion combined with inflationary pressures can lead to financial instability.
This study not only identifies the main determinants of currency crises but also emphasizes the importance of economic policy reforms. According to the Bayesian model findings, variables that consistently exert influence regardless of other factors are termed "non-breakable." Prioritizing these non-breakable factors in policymaking is essential for maintaining financial stability. By focusing on these critical variables, economic authorities can develop more effective strategies to prevent currency crises and mitigate their adverse economic consequences.
This study not only identifies the main determinants of currency crises but also emphasizes the importance of economic policy reforms. According to the Bayesian model findings, variables that consistently exert influence regardless of other factors are termed "non-breakable." Prioritizing these non-breakable factors in policymaking is essential for maintaining financial stability. By focusing on these critical variables, economic authorities can develop more effective strategies to prevent currency crises and mitigate their adverse economic consequences.
Article number: 5
Type of Study: Original Research - Empirical |
Subject:
Macroeconomics
Received: 4 Mar 2025 | Accepted: 1 Jun 2025 | Published: 29 Jun 2025
Received: 4 Mar 2025 | Accepted: 1 Jun 2025 | Published: 29 Jun 2025
References
1. Adiningsih, S., Setiawati, D. N., & Solihah. (2002). Macroeconomic Vulnerability in Indonesia (EADN Research Paper No. 2–3). East Asian Development Network
2. Aghion, P., Bacchetta, P., and Banerjee, A. (2000). A Simple Model of Monetary Policy and Currency Crises. European Economic Review, 44, 728-738.
3. Ari, A., & Cergibozan, R. (2018). Currency Crises in Turkey: An Empirical Assessment. Research in International Business and Finance.
4. Babecký, J., Havránek, T., Matějů, J., Rusnák, M., Šmídková, K., & Vašíček, B. (2014). Banking, debt, and currency crises in developed countries: Stylized facts and early warning indicators. Journal of Financial Stability, 15, 1–17
5. Bali, O., Sevim, C., Oztekin A., Gumus, S., & Guresen, E. (2014). Developing an Early Warning System to Predict Currency Crises. European Journal of Operational Research, 237, 1095–1104.
6. Barro, R. J. (1990). Government spending in a simple model of endogenous growth. Journal of Political Economy, 98(5, Part 2), S103–S125.
7. Bastanzad, H, Davoodi, P. (2022). Analyzing Exchange Rate Crises in Iran's Economy Using Early Warning Models. Journal of Business Research, 26(103), 29-67. [In Persian]
8. Bayani, A., & Mohammadi, T. (2019). Factors affecting financial crises in Iran’s economy: A Bayesian averaging approach. Quantitative Economics (Economic Reviews), 16(2), 145–180. Retrieved from https://sid.ir/paper/383432/fa [In Persian]
9. Berg, A., Borensztein, E., & Pattillo, C. (2005). Assessing early warning systems: How have they worked in practice? IMF Working Paper No. 52, International Monetary Fund, Washington, D.C.
10. Berg, A., and Pattillo, C. (1999). Are Currency Crises Predictable? A Test. IMF Staff Papers, June, 127-138.
11. Bernanke, B. S., & Gertler, M. (1989). Agency costs, net worth, and business fluctuations. American Economic Review, 79(1), 14–31.
12. Bilson, J. F. O. (1979). Recent developments in monetary models of exchange rate determination. IMF Staff Papers, 26(2), 201–223.
13. Bodea, C., Houle, C., & Kim, H. (2019). Do financial crises increase income inequality? Review of International Political Economy, 26(2), 271–296.
14. Boonman, T. M. (2019). Dating Currency Crises in Emerging Market Economies. The North American Journal of Economics and Finance, 49, 273-286.
15. Brewer, N. (2006). Uses and abuses of eyewitness identification confidence. Legal and Criminological Psychology, 11(1), 3–23.
16. Brüggemann, A., & Linne, T. (2012). Are the Central & Eastern European transition countries still vulnerable to a financial crisis? Results from the signals approach. IWH Discussion Papers, No. 157, Halle Institute for Economic Research.
17. Calvo, G.A., and Reinhart, C.M. (2000). Fear of Floating. NBER Working Paper No. 7993, National Bureau of Economic Research, Cambridge, MA.
18. Castillo, F. A. (2006). Predicting a currency crisis: Alternative approaches and applications to the Philippines (Master's thesis). Singapore Management University, Institutional Knowledge at Singapore Management University.
19. Catania, L. , & Billio, M. (2021). Bayesian Model Averaging in Economic Forecasting. Journal of Economic Forecasting. 24(3), 5-27.
20. Chang, R., & Velasco, A. (1998). Financial Crises in Emerging Markets. The Quarterly Journal of Economics, 116, 489-517.
21. Chiodo, A.J., and Owyang, M.T. (2002). A Case Study of a Currency Crisis: The Russian Default of 1998. Review, Federal Reserve Bank of St. Louis, November, 7-18.
22. Ciccarelli, M., & Rebucci, A. (2006). Bayesian VARs: A survey of the recent literature with an application to the European Monetary System. Journal of Economic Surveys, 20(2), 231–255
23. Comelli, F. (2014). Comparing parametric and non-parametric early warning systems for currency crises in emerging market economies. Review of International Economics, 22(4), 700–721.
24. Corden, W. M., and Neary, J. P. (1982). Booming sector and de-industrialisation in a small open economy. Economic Journal, 92(368), 825–848.
25. Corsetti, G., Pesenti, P., & Roubini, N. (1998). What Caused the Asian Currency & Financial Crisis? Part I: A Macroeconomic Overview. NBER Working Paper No. 6833.
26. Demirguc-Kunt, A., & Detragiache, E. (1997). The Determinants of Banking Crises in Developing & Developed Countries. IMF Working Paper No. 126, International Monetary Fund, Washington, D.C.
27. Draper, D. (1995). Assessment and propagation of model uncertainty. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 45–70
28. Edison, H.J. (2003). Do Indicators of Financial Crises Work? An Evaluation of an Early Warning System. International Journal of Finance and Economics, 8, 11-53.
29. Edwards, S. (1984). Liberalization policies, macroeconomic adjustment, and growth in Latin America. In S. Edwards & S. Fischer (Eds.), Capital flows, economic growth, and stabilization (pp. 11-51). University of Chicago Press.
30. Eichengreen, B., Rose, A. K., & Wyplosz, C. (1995). Exchange market mayhem: The antecedents and aftermath of speculative attacks. Economic Policy, 21, 249–312
31. Feldkircher, M., Horváth, R., & Rusnák, M. (2014). Exchange market pressures during the financial crisis: A Bayesian model averaging evidence. Journal of International Money and Finance, 39, 21-41.
32. Ferdous, L.T., Kamal, M.M., Ahsan, A., Hoang, N.H.T., & Samaduzzaman, M. (2022). An Early Warning System for Currency Crises in Emerging Countries. Journal of Risk and Financial Management.
33. Feridun, M. (2008). Currency Crises in Emerging Markets: The Case of Post-Liberalization Turkey. Development Economics, 46(4), 386-427.
34. Flood, R.P., and Garber, P.M. (1984). Collapsing Exchange Rate Regimes: Some Linear Examples. Journal of International Economics, 17, 1-13.
35. Frankel, J., & Rose, A. (1996). Currency Crashes in Emerging Markets: Empirical Indicators. NBER Working Paper Series No. 5437.
36. Ghosh, S., & Ghosh, A. (2002). Structural Vulnerabilities and Currency Crises. IMF Working Paper No. WP/09/02, Washington, D.C.
37. Gibbs, G. (1988). Learning by Doing: A Guide to Teaching and Learning Methods. Oxford Polytechnic: Further Education Unit.
38. Haji Shahvordi, D., Zamordian, G., Falah Shams Lialastani, M., and Hanifi, F. (2019). Designing a System for Early Warning of Systemic Banking Crises in Iran’s Financial Market (Using Markov Chains). Financial Economics (Financial Economics and Development), 13(47), 153-175. [In Persian]
39. Hardy, D., and Pazarbasioglu, C. (1999). Determinants & Leading Indicators of Banking Crises: Further Evidence. IMF Staff Paper Vol. 46, No. 3.
40. Hoshi, T., and Kashyap, A. K. (2004). Japan's financial crisis and economic stagnation. Journal of Economic Perspectives, 18(1), 3–26
41. Husted, L., Rogers, J., & Sun, B. (2018). Uncertainty, Currency Excess Returns, and Risk Reversals. Journal of International Money and Finance, 88, 228-241.
42. Jdaitawi, Q. (2014). Developing an Early Warning System For Currency Crises: the case of Jordan. Modern Applied Science, 8(1), 39 50.
43. Jeffreys، H. (1961). Theory of probability (3rd ed.). Oxford University Press.
44. Kamin, S. B., & Babson, O. D. (1999). The contributions of domestic and external factors to Latin American devaluation crises: An early warning systems approach. International Finance Discussion Paper No. 645. Board of Governors of the Federal Reserve System.
45. Kaminsky, G. L. (1999). Currency and banking crises: The early warnings of distress (IMF Working Paper No. 99/178). International Monetary Fund.
46. Kaminsky, G., & Reinhart, C. M. (1999). The twin crises: The causes of banking and balance of payment problems. American Economic Review, 89(3), 473–500
47. Kaminsky, G.L., Lizondo, S., & Reinhart, C.M. (1998). The Leading Indicators of Currency Crises. IMF Staff Papers, 45(1), 1-48.
48. Khosrosereshki, M., & Dashtbany, Y. (2024). Early warning model and currency crisis in the Iranian economy: A probit approach. Quarterly Journal of Economic Research, 24(4), 161–189. Retrieved from http://ecor.modares.ac.ir/article-18-72603-fa.html. [In Persian]
49. Kibritçioğlu, A., Güray, N., & Özatay, F. (2001). Leading indicators of currency crises in emerging markets: Evidence from Turkey. Journal of International Money and Finance, 20(2), 185–206
50. Koop, G., & Potter, S. M. (2003). Bayesian analysis of endogenous switching models. Journal of Econometrics, 114(2), 553–573.
51. Krol, R. (2014). Economic Policy Uncertainty and Exchange Rate Volatility. International Finance, 17(2), 241–256.
52. Krolzig, H.M. (2003). Markov-Switching Vector Autoregressions: Modelling, Statistical Inference, and Application to Business Cycle Analysis. Springer.
53. Krugman, P. (1979). A Model of Balance of Payment Crises. Journal of Money, Credit and Banking, 11(3), 311-325.
54. Krugman, P. R. (1999). Balance sheets, the transfer problem, and financial crises. . In P. Isard, A. Razin, & A. K. Rose (Eds.), International finance and financial crises: Essays in honor of Robert P. Flood, Jr. (Vol. 6, pp. 459–472). Springer
55. Lanoie, P., & Lemarbre, S. (1996). Three Approaches to Predict the Timing & Quantity of LDC Debt Rescheduling. Applied Economics, 28(2), 241-246.
56. Leamer، E. E. (1978). Specification searches: Ad hoc inference with nonexperimental data. John Wiley & Sons.
57. Mishkin, F. S. (1996). Understanding financial crises: A developing country perspective. NBER Working Paper No. 5600. National Bureau of Economic Research.
58. Moral Benito, E. (2012). Determinants of economic growth: A Bayesian panel data approach. The Review of Economics and Statistics, 94(2), 566–579.
59. Nasrollahi, M., Yavari, K., Najarzadeh, R., and Mehrgan, N. (2017). Designing an Early Warning System for Exchange Rate Crises in Iran: A Logistic Regression Approach. Economic Research, 52(1), 187-214. [In Persian]
60. Nasrollahi, M., Yavari, K., Najarzadeh, R., and Mehrgan, N. (2020). Designing an Early Warning System for Exchange Rate Crises in Iran: A Markov Regime Change Approach. Economic Policy, 12(24), 107-138. [In Persian]
61. Obstfeld, M. (1994). The logic of currency crises. NBER Working Paper No. 4640. National Bureau of Economic Research.
62. Peng, X., & Bajona, C. (2008). China's vulnerability to currency crisis: A KLR signals approach. Journal of Comparative Economics, 36(3), 461–483
63. Poirier, D. (1995). Intermediate Statistics and Econometrics: A Comparative Approach. Cambridge: The MIT Press.
64. Radelet, S., & Sachs, J. (1998). The Onset of the East Asian Financial Crisis. NBER Working Paper No. 6680. Retrieved from: https://www.nber.org/papers/w6680.pdf.
65. Rogoff, K. S. (2003). Globalization and global disinflation. Economic Review, 88(4), 45–78. Federal Reserve Bank of Kansas City.
66. Sachs, J. D., & Warner, A. M. (1995). Natural resource abundance and economic growth. NBER Working Paper No. 5398. National Bureau of Economic Research
67. Salmani, B., Asgharpoor, H., & Kalami, M. (2019). Designing an early warning model for currency crises in Iran: Logistic and Markov switching vector autoregression approaches. Retrieved from https://civilica.com/doc/1187999 [In Persian]
68. Saqib, O.F. (2002). An Investigation into the 1999 Collapse of the Brazilian Real. German Institute for Economic Research Discussion Papers, 2222, No. 324, 1-22.
69. Sevim, C., Oztekin, A., Bali, O., Gumus, S., & Guresen, E. (2014). Developing an Early Warning System to Predict Currency Crises. European Journal of Operational Research, 237, 1095-1104.
70. Stiglitz Commission. (2010). The Stiglitz Report: Reforming the International Monetary and Financial Systems in the Wake of the Global Crisis. New York: The New Press.
71. Tinakorn, P. (2002). Indicators and Analysis of Vulnerability to Currency Crisis. Retrieved from https://www.utzverlag.de/assets/pdf/44098dbl.pdf
72. United Nations Conference on Trade and Development (UNCTAD). (2010). The least developed countries report 2010 (Vol. 17, No. 2, pp. 241–256). New York, NY: United Nations.
73. Warjiyo, P. (2015). Indonesia: Global Spillover and Policy Response. Paper presented at the Asia Economic Policy Conference (AEPC), Federal Reserve Bank of San Francisco (FRBSF), November.
74. Wasserman, L. (2000). Bayesian model selection and model averaging. Journal of Mathematical Psychology, 44(1), 92–107.
75. Yap, J. T. (2002). Monitoring economic vulnerability and performance: Applications to the Philippines. Discussion Paper No. 2002-13. Philippine Institute for Development Studies.
76. Zellner, A. (1986). On assessing prior distributions and Bayesian regression analysis with g-prior distributions. In P. K. Goel & A. Zellner (Eds.), Bayesian inference and decision techniques: Essays in honor of Bruno de Finetti (pp. 233–243). Amsterdam: North-Holland.
77. Zhu, M. N., & Yan, S. (2015). Dynamic spillovers of economic policy uncertainty and RMB exchange rate. Journal of International Trade and Economic Development, 10, 111–119.[(In Chinese]
78. Zhuang, J., & Dowling, M. (2002). Causes of the 1997 Asian Financial Crisis: What Can an Early Warning System Model Tell Us? ERD Policy Brief No. 7, Manila: Asian Development Bank.
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