The Impact of Iran Oil Sanctions on the Exchange Rates: An Analysis Using Google Search Index

Authors

1 Department of Economics, University of Isfahan, Isfahan, Iran

2 Department of Economics, University of Shiraz, Shiraz, Iran

3 Department of Economics and Energy Management, Petroleum University of Technology, Tehran, Iran

Abstract

Iran has faced oil and banking sanctions since 2012. Following the sanctions and instability of the exchange rates, the Rial has sharply lost its value. Rising economic unrest has widened the gap between the official exchange rate and the parallel market rate. However, the depreciation of Iran’s Rial does not show a uniform trend, and the decline path has been complicated. We know sanctions against Iran have created new expectations, concerns, and attention. Google Trends has provided an analytic tool for measuring and monitoring people’s expectations based on their Internet search data. This study attempted to analyze and model the exchange rate trends in Iran using sanctions-related expectations extracted from Google Trends. The Google search index (GSI) of the sanctions demonstrated the agent’s expectations. Monthly data and the autoregressive distributed lag (ARDL) method were used for estimation. The results indicated a significant and positive impact of GSI on the unofficial exchange rate (UER) and just a positive impact on the real unofficial exchange rate (RUER). We can conclude that the effects of sanctions appear partly through changes in people’s expectations that can be extracted using GSI. Moreover, the difference in inflation showed a significant positive impact on the market exchange rate in Iran. Thus, an improvement in the expectations through reducing international tensions and a perspective shift can strengthen the Rial exchange rate. Moreover, the policymaker can control the volatility and depreciation of the exchange rates in Iran by restricting M2 growth through an appropriate long-run monetary policy.

Keywords


Aghaei, M., & Rezagholizadeh, M. (2018). Impact of Economic and Commercial Sanctions on Iran's Trade Relations and their Major Trading Partners. Strategic Studies of Public Policy, 8(28), 49-68.
Afkhami, M., Cormack, L., & Ghoddusi, H. (2017). Google Search Keywords that Best Predict Energy Price Volatility. Energy Economics67, 17-27.
Baghestani, H., & Toledo, H. (2019). Oil Prices and Real Exchange Rates in the NAFTA Region. The North American Journal of Economics and Finance, 48, 253-264.
Bonyani, A., & Alimohammadlou, M. (2018). Identifying and Prioritizing Foreign Companies Interested in Participating in Post-Sanctions Iranian Energy Sector. Energy Strategy Reviews21, 180-190.
Babajani Baboli, M., Esfandabadi, J., Majid, S. A., & Zayandeh Roody, M. (2018). The Impact of Shocks in Oil Price and Exchange Rate on Inflation in Iran: The Application of the VAR Approach. Environmental Energy and Economic Research2(1), 51-61.
Baharumshah, A. Z., Sirag, A., & Soon, S. V. (2017). Asymmetric Exchange Rate Pass-through in an Emerging Market Economy: The Case of Mexico. Research in International Business and Finance41, 247-259.
Banerjee, A. J., Dolado, J., & Mester, R. (1992). On Some Simple Tests for Cointegration: The Cost of Simplicity. Bank of Spain, Working Paper, 9302, Retrieved from https://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/93/Fich/dt9302e.pdf
Behrad-Amin, M., Zamanian, G., & Esfandiari, M. (2017). The Effect of Oil Shocks on Foreign Trade under Inflation and Exchange Rate Targeting Policies (In the form of a Dynamic Stochastic General Equilibrium Model for Iran). International Journal of Economics and Financial Issues7(3), 342-351.
Bolgorian, M., & Mayeli, A. (2019). Banks' Characteristics, State Ownership and Vulnerability to Sanctions: Evidence from Iran. Borsa Istanbul Review, Retrieved from https://doi.org/10.1016/j.bir.2019.02.003
Bijl, L., Kringhaug, G., Molnár, P., & Sandvik, E. (2016). Google Searches and Stock Returns. International Review of Financial Analysis45, 150-156.
Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., & Weber, I. (2012). Web Search Queries Can Predict Stock Market Volumes. PloS one7(7), Retrieved from https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0040014
Campos, I., Cortazar, G., & Reyes, T. (2017). Modeling and Predicting Oil VIX: Internet Search Volume versus Traditional Variables. Energy Economics, 66, 194-204.
Choi, H., & Varian, H. (2012). Predicting the Present with Google Trends. Economic Record88, 2-9.
Da, Z., Engelberg, J., & Gao, P. (2015). The Sum of All FEARS Investor Sentiment and Asset Prices. The Review of Financial Studies, 28(1), 1-32.
---------- (2011). In Search of Attention. The Journal of Finance, 66(5), 1461-1499.
Dreger, C., Kholodilin, K. A., Ulbricht, D., & Fidrmuc, J. (2016). Between the Hammer and the Anvil: The Impact of Economic Sanctions and Oil Prices on Russia’s Ruble. Journal of Comparative Economics, 44(2), 295-308.
Dudlák, T. (2018). After the Sanctions: Policy Challenges in Transition to a New Political Economy of the Iranian Oil and Gas Sectors. Energy Policy121, 464-475.
Ezati, M., & Salmani, Y. (2014). Investigating Direct and Indirect Impacts of Sanctions on Iran Economic Growth by Emphasis on Foreign Sector of the Economy. Afagh Amneiat Journal, 7(25), 149-175.
Engle, R. F., & Granger, C. W. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica: Journal of the Econometric Society, Retrieved from http://links.jstor.org/sici?sici=00129682%28198703%2955%3A2%3C251%3ACAECRE%3E2.0.CO%3B2-T
Faraji Dizaji, S. (2014). The Effects of Oil Shocks on Government Expenditures and Government Revenues Nexus (with an Application to Iran's Sanctions). Economic Modelling40, 299-313.
Faraji Dizaji, S., & Van Bergeijk, P. A. (2013). Potential Early Phase Success and Ultimate Failure of Economic Sanctions: A VAR Approach with an Application to Iran. Journal of Peace Research50(6), 721-736.
Farzanegan, M. R., & Raeisian Parvari, M. (2014). Iranian-Oil-Free Zone and International Oil Prices. Energy Economics45, 364-372.
Gurvich, E., & Prilepskiy, I. (2016). The Impact of Financial Sanctions on the Russian Economy. Russian Journal of Economics, 1(4), 359-385.
Gharehgozli, O. (2017). An Estimation of the Economic Cost of Recent Sanctions on Iran Using the Synthetic Control Method. Economics Letters157, 141-144.
Guzman, G. (2011). Internet Search Behavior as an Economic Forecasting Tool: The Case of Inflation Expectations. Journal of Economic and Social Measurement36(3), 119-167.
Gujarati, D. N. (2005). Basic Econometrics (5th). New York: McGraw-Hill.
Ji, Q., & Guo, J. F. (2015). Oil Price Volatility and Oil-related Events: An Internet Concern Study Perspective. Applied Energy, 137, 256-264.
Korhonen, I., & Juurikkala, T. (2009). Equilibrium Exchange Rates in Oil-exporting Countries. Journal of Economics and Finance33(1), 71-79.
Kim, N., Lučivjanská, K., Molnár, P., & Villa, R. (2019). Google Searches and Stock Market Activity: Evidence from Norway. Finance Research Letters, 28, 208-220.
Li, X., Ma, J., Wang, S., & Zhang, X. (2015). How Does Google Search Affect Trader Positions and Crude Oil Prices? Economic Modelling49, 162-171.
Mao, H., Counts, S., & Bollen, J. (2011). Predicting Financial Markets: Comparing Survey. Retrieved from News, Twitter and Search Engine Data.
Mirdala, R. (2014). Exchange Rate Pass-through to Consumer Prices in the European Transition Economies. Procedia Economics and Finance12, 428-436.
Mellon, J. (2014). Internet Search Data and Issue Salience: The Properties of Google Trends as a Measure of Issue Salience. Journal of Elections, Public Opinion & Parties24(1), 45-72.
---------- (2013). Where and When Can We Use Google Trends to Measure Issue Salience? PS: Political Science & Politics46(2), 280-290.
Moeeni, Sh. (2019). Modeling the Petroleum Export Behavior of Iran after Oil Sanction in the Framework of Analysis of the Strategic Relations of the Oil Market. Journal of Sustainable Growth and Development (The Economic Research), 19(3), 163-185.
Moeeni, Sh., & Tayebi, K. (2019). Is It Necessary to Restrict Forex Financial Trading? A Modified Model. Journal of Money and Economy, 13(1), 63-80.
Moeeni, Sh. & Sharifi, A. (2020).An Analysis of the Intra-OPEC Bargaining Game with Emphasis on New Outlook and Sanctions (2011-2019) Using Google Trends. International Economics Studies, 50(1), 53-60.
Neuenkirch, M., & Neumeier, F. (2016). The Impact of US Sanctions on Poverty. Journal of Development Economics121, 110-119.
Nuti, S. V., Wayda, B., Ranasinghe, I., Wang, S., Dreyer, R. P., Chen, S. I., & Murugiah, K. (2014). The Use of Google Trends in Health Care Research: a Systematic Review. PloS one9(10), 1-49.
Pesaran, M. H., Shin, Y., & Smith, R. J. (1996). Testing for the 'Existence of a Long-run Relationship' (9622). The University of Cambridge, Retrieved from https://ideas.repec.org/p/cam/camdae/9622.html
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics16(3), 289-326.
Rao, T., & Srivastava, S. (2013). Modeling Movements in Oil, Gold, Forex, and Market Indices using Search Volume Index and Twitter Sentiments (336-345). Proceedings of the 5th Annual ACM Web Science Conference, Retrieved from doi.1145/2464464.2464521
Sadat Akhavi, S. M., & Hoseini, S. Sh. (2017). Evaluating the Impacts of Economic Sanctions on Inflation of the Iranian Economy. Journal of Applied Economics, 7(21), 33-50.
Samadi, S., & Moeeni, Sh. (2012). The Analysis of Metropolitan Housing Price and UGB in Iran: Application of Panel Data Technique in Selected Metropolises (Tehran, Isfahan, Shiraz). Urban-Regional Studies and Research, 14, 21-24.
Sameti, M., Moeeni, Sh., Mardiha, S., & Khanizadeamiri, M. (2012). Estimation of the Recreational Value of Najvan Park of Isfahan Using a Contingent Valuation Method. Iranian Journal of Applied Ecology, 1(1), 64-79.
Smith, G. P. (2012). Google Internet Search Activity and Volatility Prediction in the Market for Foreign Currency. Finance Research Letters9(2), 103-110.
Tang, B. (2015). Real Exchange Rate and Economic Growth in China: A Cointegrated VAR Approach. China Economic Review34, 293-310.
Tashkini, A. (2005). Applied Econometrics by "Microfit". Tehran: Dibagaran Art & Cultural Institute.
Torbat, A. E. (2005). Impacts of the US Trade and Financial Sanctions on Iran. World Economy28(3), 407-434.
Tuzova, Y., & Qayum, F. (2016). Global Oil Glut and Sanctions: The Impact on Putin’s Russia. Energy Policy90, 140-151.
Tayebi, S., & Sadeghi, A. (2017). The Impacts of International Sanctions and Other Factors Affecting Exchange Rate in Iran.  Tahghighat- e Eghtesadi, 52(3), 641-661 (In Persian).
Takhtamanova, Y. F. (2010). Understanding Changes in Exchange Rate Pass-through. Journal of Macroeconomics32(4), 1118-1130.
Von Hagen, J. V., & Zhou, J. (2005). The Choice of Exchange Rate Regime: an Empirical Analysis for Transition Economies. Economics of Transition13(4), 679-703.
Yu, L., Zhao, Y., Tang, L., & Yang, Z. (2019). Online Big Data-driven Oil Consumption Forecasting with Google Trends. International Journal of Forecasting35(1), 213-223.