Analyzing and Identifying the Effects of Fluctuations of Exchange Rate, Oil and Gold Prices on Trade Balance in Iran: Approach of Fuzzy Regression and Generalized TOPSIS

Document Type : Original Article


1 PhD Candidate in Economics, Faculty of Economics and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Associate Professor of Economics, Faculty of Economics and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran

3 Assistant Professor of Mathematics, Faculty of Mathematical and Computer Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran



Exchange rates, oil and gold prices are important economic variables that stimulate global economic developments. In this study, the relationships between the variables of oil, gold prices and exchange rate and their impacts on the trade balance in Iran using the new hybrid approach of fuzzy regressions and multi-criteria decision-making framework is investigated. For this, five novel fuzzy regression models are considered and ranked by Generalized TOPSIS method using the annual data during the period of 1979-2021 and among the models, the fuzzy weighted model has been selected as the best model to describe the optimal relationship between variables. According to the results, among the variables of oil, gold and foreign exchange rate, the exchange rate variable has the most impact on the trade balance. Other results show that the use of fuzzy regression models approaches with various logics in the design of the error function produces more accurate estimates of the coefficients. The range of minimum and maximum effect of exchange rate on trade balance was extracted as (1.474 and -1.382). These fuzzy cumulative regressions show that the priority of influencing the trade balance is the exchange rate, oil price and then gold price. Hence to improve the trade balance, policies should be focused on the exchange rate, then the price of oil, and finally the price of gold.


Main Subjects

- Abolhassanbeigi, H. & Mahdavi, A. (2019). The Effect of Exchange Rate on Iranian Trade Balance Under Uncertainty. Iranian Applied Economic Studies, 8(32), 1-5 (In Persian).
- Ahmadian, A., Fouladi, K., & Araabi, B. N. (2020). Model-based Persian Calligraphy Synthesis via Learning to Transfer Templates to Personal styles. International Journal on Document Analysis and Recognition (IJDAR), 23(3), 183-203 (In Persian).
- Ali, D. A., Johari, F. & Alias, M.H. (2014). The Effect of Exchange Rate Movements on Trade Balance: A Chronological Theoretical Review. Economics Research International, 24(4), 1-8.
- Arefi, M. (2020). Quantile Fuzzy Regression Based on Fuzzy Outputs and Fuzzy Parameters. Soft Computing, 24(1), 311-320 (In Persian).
- Arize, A. C., Malindretos, J. & Igwe, E. U. (2018). Do Exchange Rate Changes Improve the Trade Balance: An Asymmetric Nonlinear Cointegration Approach. International Review of Economics & Finance, 49, 313-326.
- 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., & Hegerty, S.W. (2010). The J-and S-Curves: A Survey of the Recent Literature. Journal of Economic Studies, 37(6), 580-596.
- Bahmani-Oskooee, M., & Ratha, A. (2004). The J-Curve: A Literature Review. Applied Economics, 36(13), 1377-1398.
- Bams, D., Blanchard, G., Honarvar, I. & Lehnert, T. (2017). Does Oil and Gold Price Uncertainty Matter for the Stock Market? Journal of Empirical Finance, 44, 270-285.
- Banerjee, B., Shi, H., Radovan, J., Sheng, Y. and Li, X. (2017). The Impact of the Exchange Rate and Trade Composition on China’s Trade Balance Vis-À-Vis Selected Partner Countries. Comparative Economic Studies, 59(3), 311-344.
- Basher, S.A., Haug, A.A. and Sadorsky, P. (2016). The Impact of Oil Shocks on Exchange Rates:  Markov-Switching Approach. Energy Economics, 54, 11-23.
- Chachi, J., Taheri, S. M. & D’ Urso, P. (2022). Fuzzy Regression Analysis Based on M-estimates. Expert Systems with Applications, 187, 115891.
- Chachi, J. (2019). A Weighted least Squares Fuzzy Regression for Crisp Input-fuzzy Output Data. IEEE Transactions on Fuzzy Systems, 27, 739-748.
- Chkili, W. (2022). The Links between Gold, Oil Prices and Islamic Stock Markets in a Regime Switching Environment. Eurasian Economic Review, 12(1), 169-186.
- Chukhrova, N., & Johannssen, A. (2019). Fuzzy Regression Analysis: Systematic Review and Bibliography. Applied Soft Computing84, 105708.
- Dadgar, Y. Fahimifar, F. & Nazari, R. (2020). Analyzing the Synchronization of Exchange Rate Cycles with Oil Price, Gold Price, and Stock Value in Iran: A Markov-Switching Model with Component Structure. Economics and Modeling, 11(3), 151-193 (In Persian).
- Dong, F. (2017). Testing the Marshall-Lerner Condition between the US and Other G7 Member Countries. The North American Journal of Economics and Finance, 40, 30-40.
- Duasa, J. (2007). Determinants of Malaysian Trade Balance: An ARDL Bound Testing Approach. Global Economic Review, 36(1), 89-102.
- Effiong, U. E., Udonwa, U. E. & Udofia, M. A. (2022). Trade Balance, Exchange Rate Movements and Economic Growth in NIGERIA: A Disaggregated Approach. Scientific notes of Lviv University of Business and Law, 32, 107-127.
- Elyaspour, B., Ahmadi Shadmehri, M., Lotfalipour, M. & Falahi, M. (2018). The Effect of Exchange Rate Uncertainty on Iran's Non-Oil Trade Balance: Stochastic Volatility Model Approach. Financial Monetary Economy, 25(15), 49-80 (In Persian).
- Fattahi, Sh. & Kian Poor, S. (2020). The Dependence of Returns in Stock Exchange Returns and Gold Markets with Spread of Covid-19 Virus in Iran: The Copula Functions Approach. Economics and Modelling, 11(2), 181-221 (In Persian).
- Ferraro, M. B., Coppi, R., Rodríguez, G. G. & Colubi, A. (2010). A linear Regression Model for Imprecise Response. International Journal of Approximate Reasoning, 51(7), 759-770.
- Filis, G., Degiannakis, S. & Floros, CH. (2011). Dynamic Correlation between Stock Market and Oil Prices: The Case of Oil Importing and Oil Exporting Countries. International Review of Financial Analysis, 20(3), 152-164.
- Kazemifard. A. (2020). An Extension of TOPSIS Model Based on Monotonic Utility of Criteria. JAMM, 10(1), 196-214 (In Persian)
- Kazemifard. A. & Sadeghian, R. (2020) Multiple Attribute Decision Making. Danesh Parvar Pub. (In Persian).
- Kazemifard, A., & Chachi, J. (2022). MADM Approach to Analyze the Performance of Fuzzy Regression Models. Journal of Ambient Intelligence and Humanized Computing, 13(8), 4019-4031.
- Khammar, A.H., Arefi, M., & Akbari, M.G. (2020). A Robust Least Squares Fuzzy Regression Model Based on Kernel Function. Iranian Journal of Fuzzy Systems, 17(4), 105-119 (In Persian).
- Le, T. H. & Chang, Y. (2015). Effects of Oil Price Shocks on the Stock Market Performance: Do Nature of Shocks and Economies Matter? Energy Economics, 51, 261-274.
- Lin, S., Shi, K. & Ye, H. (2018). Exchange Rate Volatility and Trade: The Role of Credit Constraints. Review of Economic Dynamics, 30, 203-222.
- Marshall, A. (1923). Money, Credit and Commerce. London, Macmillan. 198-204.
- Melvin, M. (2012). Microeconomics. Cengage Learning, International Money and Finance.
- Melvin, M. & Norrbin, S.C. (2013). The Balance of Payments. International Money and Finance (Eighth Edition).
- Saadat, R., Erfani, A. & Jodki, H. (2016). The Effect of Exchange Rate Fluctuations on Iran's Exports to Venezuela. Economic Research, 51(3), 595-609 (In Persian).
- Salvatore, D. (2013). International Economics. John Wiley & Sons.
- Sari, R. H., Amoudeh, S. & Soyatas, U. (2010). Dynamics of Oil Price, precious Metal Price and Exchange Rate. Energy Economics, 32,351–362.
- Singhal, S., Choudhary, S. & Biswal, P.C. (2019). Return and Volatility Linkages among International Crude Oil price, Gold price, Exchange Rate and Stock Markets: Evidence from Mexico. Resources Policy, 60, 255-261.
- Sorkheh, K., Kazemifard, A. & Rajabpoor, S. (2018). A Comparative Study of Fuzzy Linear Regression and Multiple Linear Regression in Agricultural Studies: A Case Study of Lentil Yield Management. Turkish Journal of Agriculture and Forestry42(6), 402-411.
- Tanaka, H., Hayashi. I. & Watada J. (1989). Possibilistic Linear Regression Analysis for Fuzzy Data. Eur J Oper Res, 40, 389–396.
- Tiwari, A. K., & Sahadudheen, I. (2015). Understanding the Nexus between Oil and Gold. Resources Policy46, 85-91.
- Wang, C. H., Lin, C. H. A. & Yang, C. H. (2012). Short-Run and Long-Run Effects of Exchange Rate Change on Trade Balance: Evidence from China and Its Trading Partners. Japan and the World Economy, 24(4), 266-273.
- Xu, R. & Li, C. (2001). Multidimensional Least-squares Fitting with a Fuzzy Model. Fuzzy Sets and Systems, 119, 215-223.
- Zeng, W., Feng, Q. & Lia, J. (2017). Fuzzy Least absolute Linear Regression. Appl Soft Compute, 52, 1009–1019.