Effects of Exchange Rate Volatility on Seaborne Import Volume In Iran
محورهای موضوعی : International Journal of Finance, Accounting and Economics Studiesmahdokht habibi 1 , abbas memarnezhad 2 , zahra afshari 3
1 - Department of Management and Economic, Science and Research branch, Islamic Azad University, Tehran, Iran.
2 - Department of Management and Economic, Science and Research branch, Islamic Azad University, Tehran, Iran.
3 - Professor of Economics, Department of Economics, The Faculty of SocialSciences and Economics, Alzahra University, Tehran, Iran.
کلید واژه: Seaborne Import Volume , Exchange Rate Volatility , EGARCH, ARDL.,
چکیده مقاله :
The exchange rate is a key variable in the economy. Given the recent currency fluctuations, which profound consequences on a country's trade, especially in the maritime sector the present study examined effects of exchange Rate volatility on maritime trade (import) in Iran, which used quartly data from 1380- 1403. The study used the EGARCH model to analyze the USD/RIAL exchange rate volatility and combined with an autoregressive distributed lag (ARDL) analysis indicate that exchange rate volatility has a statistically significant negative influence on Iran’s seaborne import volume. The results of estimating the long-term equilibrium equation through cointegration relationships indicated that a 1% increase in real income led to a 0.014 % increase in import volume, and increases in the real effective exchange led to a 0.018% decrease in import volume. On the other hand, an increase of 1% in world commodity prices, which secured statistical significance, led to a increase of 0.12% in import volume. Moreover, the results of a vector error correction model (VECM) analysis found that the exchange rate volatility exhibited short-term unidirectional causality on import volume and real income.
The exchange rate is a key variable in the economy. Given the recent currency fluctuations, which profound consequences on a country's trade, especially in the maritime sector the present study examined effects of exchange Rate volatility on maritime trade (import) in Iran, which used quartly data from 1380- 1403. The study used the EGARCH model to analyze the USD/RIAL exchange rate volatility and combined with an autoregressive distributed lag (ARDL) analysis indicate that exchange rate volatility has a statistically significant negative influence on Iran’s seaborne import volume. The results of estimating the long-term equilibrium equation through cointegration relationships indicated that a 1% increase in real income led to a 0.014 % increase in import volume, and increases in the real effective exchange led to a 0.018% decrease in import volume. On the other hand, an increase of 1% in world commodity prices, which secured statistical significance, led to a increase of 0.12% in import volume. Moreover, the results of a vector error correction model (VECM) analysis found that the exchange rate volatility exhibited short-term unidirectional causality on import volume and real income.
Aftab, M., Syed, K. B. S., & Katper, N. A. (2017). “Exchange-rate volatility and Malaysian-Thai bilateral industry trade flows”. Journal of Economic Studies, 44(1), 99-114.
ARIZE, A.C., OSANG, T. and SLOTTJE, D.J. (2000), “Exchange-rate volatility and foreign trade: evidence from thirteen LDC’s,” Journal of Business & Economic Statistics , Vol. 18.
Bahmani-Oskooee, M., & Baek, J. (2020). On the asymmetric effects of exchange-rate volatility on trade flows: Evidence from Korea-U.S. commodity trade., Aust Econ Pap. 2020; 1–36. DOI: 10.1111/1467-8454.12221
Bahmani-Oskooee, M., & Aftab, M. (2017). On the asymmetric effects of exchange rate volatility on trade flows: New evidence from US-Malaysia trade at the industry level. Economic Modelling, 63, 86-103.
Bahmani-Oskooee, M., & Harvey, H. (2019). A nonlinear approach to the U.S.-Australia commodity trade and the J-curve: Evidence from 123 Industries. Australian Economic Papers, 58, 318–363.
Bahmani-Oskooee, M., & Hegerty, S. W. (2009). The effects of exchange-rate volatility on commodity trade between the U.S. and Mexico. Southern Economic Journal, 75, 1019–1044.
BOLLERSLEV, T. (1986), “Generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, Vol. 31, No. 3, pp. 307327.
Bahmani-Oskooee, M., & Gelan, A. (2018). Exchange-rate volatility and international trade performance:Evidence from 12 African countries. Economic Analysis and Policy, 58, 14-21.
Bahmani‐Oskooee, M., & Wang, Y. (2007). United States‐China trade at the commodity level and the yuan‐dollar exchange rate. Contemporary Economic Policy, 25(3), 341-361.
Choudhry, T. (2005). Exchange rate volatility and the United States exports: evidence from Canada and Japan. Journal of the Japanese and International economies, 19(1), 51-71.
CHI, J. (2014), “Income and exchange rate sensitivities of cross-border freight flows: Evidence from U.S.-Canada exports and imports by truck, rail, air, and pipeline,” Journal of Transportation Research Forum, Vol. 53, No.2, pp. 59-71.
CHI, J. and CHENG, S.K. (2016), “Do exchange rate volatility and income affect Australia's maritime export flows to ASIA?”, Transport Policy, Vol. 47, pp.13-21.
Chi, Junwook. (2020),”Asymmetric Exchange Rate Effects on Cross-Border Freight Flows between the United States and Canada”. Journal of the Transportation Research Board: 348–61.
Choudhry, T. (2005). Exchange rate volatility and the United States exports: evidence from Canada and Japan. Journal of the Japanese and International economies, 19(1), 51-71.
Ekanayake, E. M., and Amila Dissanayake. 2022. Effects of Real Exchange Rate Volatility on Trade: Empirical Analysis of the United States Exports to BRICS.Journal of Risk and Financial Management 15: 73.
Elliot, G., Rothenburg, T.J. and Stock, J.H. (1996), “Efficient test for an autoregressive unit root,” Econometrica, Vol. 64, pp. 813–836.
ENGLE, R.F. and GRANGER, C.W. (1987), “Co-integration and error correction: representation, estimation, and testing,” Econometrica, Vol. 55, pp.251–276.
Hurley D. T., Papanikolaou N., “Autoregressive Distributed Lag (ARDL) analysis of U.S.-China commodity trade dynamics”, The Quarterly Review of Economics and Finance, 81, 454-467
Jugović, A., Komadina, N., & Perić Hadžić, A. (2015). Factors influencing the formation of freight rates on maritime shipping markets. Pomorstvo, 29(1), 23-29.
KASMAN, A. and KASMAN, S. (2005), “Exchange rate uncertainty in Turkey and its impact on export volume,” METU Studies in Development, Vol.32, pp. 41–58.
Kim, C. B. (2016). Impact of exchange rate movements, global economic activity, and the BDI volatility on loaded port cargo throughput in South Korea. The Asian Journal of Shipping and Logistics, 32(4), 243-248.
Kim, Chang Beom. 2017. Does Exchange Rate Volatility Affect Korea’s Seaborne Import Volume? The Asian Journal of Shipping and Logistics 33: 43–50
Lotfalipour, M. Bazargan, B. Investigating the effects of changes in the real effective exchange rate, exports and imports on Iran's trade balance. Iranian Journal of Economic and Research Spring 1395 Pages 94-73
McKenzie, M. D. (1999). The impact of exchange rate volatility on international trade flows. Journal of economic Surveys, 13(1), 71-106.
NG, S. and PERRON, P. (2001), “Lag length selection and the construction of unit root tests with good size and power,” Econometrica, Vol.69, pp. 1519-1554
NYUNT, Lwin Khaing, (2019). The Impact of exchange rate volatility on international trade evidence from Asean member states. KDI School of Public Policy and Management.
Okene AJ, Ibenta SN, Nwanna IO. , 2023 “Efects of exchange rate volatility on international trade performance in Nigria (GARCH/ARDL Bounds Test Approach).African Banking and Finance Review Journal.
Pesaran, M. Hashem, Yongcheol Shin, and Richard J. Smith. 2001. Bounds testing approaches to the analysis of level relationships.
Pesaran, H.M., & Pesaran, B (1997). Working with Microfit 4.0: An introduction to econometrics. London, UK: Oxford University Press. Journal of Applied Econometrics 16: 289–326.
Smallwood, Aaron D. 2019. Analyzing exchange rate uncertainty and bilateral export growth in China: A multivariate GARCH- ased approach. Economic Modelling 82: 332–44.
Souri, Ali (2012) Econometrics, with the use of Eviews software, Tehran; Farhang shenasi Publications.
Yosri Nasr Ahmed1, & Huang Delin, (2019). Current Situation of Egyptian Cotton:Econometrics Study Using ARDL Model. Journal of Agricultural Science; Vol. 11, No. 10; 2019
REVIEW OF MARITIME TRANSPORT (2022), (2023)
UNCTAD (2023). Review of Maritime Transport. UN, New York Review of Maritime Transport.
UNCTAD (2022). Review of Maritime Transport. UN, New York Review of Maritime Transport.
World Bank. (2023). World Bank National Accounts Data. The World Bank, Washington, D.C.
www.pmo.ir
www.investing.com
IMF (2023) (2024). International Monetary Fund. IMF Data Portal.
