Exchange Rate Pass-Through to the Consumer Price Index in Iran

Subject Areas : Computational economics

Seyedeh Darajati ¹ , شهریار نصابیان ^{2 *} , Reza Moghaddasi ³ , Marjan Damankeshideh ⁴

1 -
2 - دانشیار گروه علوم اقتصادی دانشگاه آزاد اسلامی ، واحد تهران مرکزی
3 - مدیر گروه اقتصاد کشاورزی دانشگاه علوم تحقیقات تهرات
4 - Assistant Professor, Department of Economics and Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Received: 2025-06-08 Accepted : 2025-09-03 Published : 2025-10-01

Keywords: Exchange rate passage, structural failure, vector auto regression ,

Abstract :

 

Extended Abstract

Purpose

The exchange rate plays a crucial role in open economies by affecting the price of imported and exported goods and services. An increase in exchange rates, due to economic policies or other reasons, can significantly raise the prices of imports and domestic goods, impacting both wholesale and retail prices..

Exchange-Rate Pass-Through (ERPT) is the percentage change in the domestic price of imported goods due to a one percent change in the currency exchange rate between exporting and importing countries   .ERPT is said to be complete if each percent change in the exchange rate results in a one percent change in the domestic price of imported goods and is called partial otherwise.

 Methodology

The data collection method in this research was of library studies. The relevant data in the period 1993-2023 were thus extracted from the website of the Central Bank of Iran and the Statistical Centre of Iran. In this study, first, the ERPT to the CPI was investigated, using the recursive VAR. Moreover, The study analyzed structural failures across decades using multivariate tests, investigating the sources of failure and the impact of oil prices on ERPT changes in total CPI through IRFs of disaggregated CPI and real exchange rates.

To shed light on the effects of exchange rates on consumer prices in Iran in this study, the recursive VAR with degree q according to the research by Hyeongwoo et all. (2021) and the following model was used:

 

in which, C denotes a lower-triangular (Choleski factorization) matrix, and U_t is a vector of mutually orthonormal structural shocks, that is, . S_t Represents the real exchange rate, Y_t is the real gross domestic product (GDP), and P_t shows the CPI. All the variables were also log transformed and differed.

This study focused on the IRFs of the CPI in the next period (j), relative to the structural shock that occurred at time t.

The variables used here included real GDP logarithm, exchange rate logarithm (viz. free market), the Organization of the Petroleum Exporting Countries (OPEC) crude oil price logarithm (ROP), total CPI logarithm, and separate CPI sub-indices such as food, apparel, transportation, medical care, energy, all items except energy, all items except food, and all items except food and energy.

Finding

To prevent false regressions in the present study, the significance of the variables was first investigated, using the Dickey-Fuller, and Phillips-Perron, and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. The results show that all the research variables are at the 95% confidence level as the value of the reported significant level of these variables is less than 0.05. The null hypothesis that there is a unit root is also rejected and all the variables are stable based on the first-order difference. In addition, the results indicate that the Lagrange multiplier (LM) test statistic does not reject the hypothesis significance of the variables tested by KPSS, and all are in the first-order difference.

The next step was to determine the optimal number of intervals. In this study, the Bayesian, Akaik, and Hannan-Quinn information criteria were exploited to determine the optimal interval length. In the three-variable VAR, the Akaik information criterion and the final prediction error of the optimal interval length were p=3, the Schwartz information criterion considered the optimal interval length as p=3, the Hannan-Quinn information criterion also assumed the optimal interval length by p=3. In the four-variable VAR, the Akaik information criterion and the final prediction error set the optimal interval length as p=2. Based on the results, interval 3 is used for optimal interval in three-variable equations and interval 2 is optimal for four-variable ones.

After determining the optimal interval, the ERPT to the CPI was investigated using VAR (1). In this process, much attention was paid to identifying the structural changes in the x_t data generation over time. 

To demonstrate the statistical significance of the estimated IRF, the CPI responses of two sub-sample periods (namely, 1993-2009 and 2010-2023) are presented. the total CPI responses to exchange rate shocks are significant and negative only in the post-2010 sample period (i.e., 2010-2023). Nevertheless, firstly positive reactions and then negative ones can be observed in the period before 2010 (vi. 1993-2009). The qualitative difference in the reactions reveals that the exchange rate to the CPI in Iran changes over time.

After confirming the statistical evidence of the structural failure of the ERPT to the CPI, the search for the source of failure began. The highest absolute value of the ERPT was thus related to the CPI of food and energy and the lowest absolute value was associated with the CPI of apparel and medical care.

Conclusion

In this study, the ERPT to the CPI and the effect of oil price fluctuations on it were evaluated using three- and four-variable VAR analysis, IRFs, and multivariate structural failure tests. The occurrence of structural failure was investigated over different decades and the results showed that the ERPT to the CPI could change viz. rise or fall over time. In addition, the highest absolute value of ERPT was related to the food and energy CPI. Examining the four-variable VAR, the study results revealed that oil price fluctuations were the main factors affecting the changes in the ERPT to total CPI in Iran.

Based on the empirical findings, economic policymakers are recommended to avoid severe currency shocks in their plans to stabilize prices by adopting appropriate policies. In addition, considering the impact of oil revenue instability on the ERPT, Iran's government is suggested to properly manage economic instability, whose main source is oil revenue instability, based on the objectives of the National Development Fund.

 

 

References:

-Asgharpour, H. and Mahdilo, A. (2014). The Impact of Inflationary Environment on Exchange Rate Pass- Through on Import Prices in Iran: Markov–Switching Approach. Quarterly Journal of Economic Research and Policy 22(70), 75-102. Retrieved from http://qjerp.ir/article-1-758-en.html/
(In Persian)
-Bandt, O. D. and Razafindrabe, T. (2014). Exchange rate pass-through to import prices in the Euro-area: A multi-currency investigation. International Economics, 138, 63–77.
Retrieved from https://doi.org/10.1016/j.inteco.2014.01.001/
- Beckmann, J., Belke, A. and Verheyen, F. (2013). Exchange rate pass-through into German import prices – A disaggregated perspective. Applied Economics,46(34),4164-4177.
Retrieved from https://doi.org/10.1080/00036846.2014.946184/
-Bigerna, S. (2024). Connectedness analysis of oil price shocks, inflation, and exchange rate for the MENA region countries. Resources Policy, 84,104344. Retrieved from https://doi.org/10.1016/j.resourpol.2023.104344
- Campa, J. M. and L. S. Goldberg (2005). Exchange rate pass-through into import prices, The Review of Economics and Statistics, 87(4), 679-690. . Retrieved from https://doi.org/10.1162/003465305775098189/
-Christiano, L., M. Eichenbaum, and C. L. Evans. (1999). Monetary policy shocks: What have we learned and to what end?. Handbook of Macroeconomics, 1, 65-148. Retrieved from https://doi.org/10.1016/S1574- 0048(99)01005-8/
-Çitçi, S.H. and Kaya, H. (2024). Exchange rate uncertainty and the connectedness of inflation. Borsa Istanbul Review, 23(3), 723-735. Retrieved from https://doi.org/10.1016/j.bir.2023.01.009/
-Ezzati Shurgoli, A. Khodavisi, H. (2020). Estimation of the degree of exchange rate passage to domestic prices in the Iranian economy: An application of variable parameter models. Quarterly Journal of Economic Research, 21(1),29-62.Retrieved from
https://doi.org/20.1001.1.17356768.1400.21.1.2.0/ (In Persian)
-Frankel, J., D. Parsley, and S.-J. Wei. (2012). Slow pass-through around the world: A new import for developing countries. Open Economies Review, 23(2), 213-25. Retrieved from https://doi.org/10.1007/s11079-011-9210-8/
-Gagnon, J. E., and J. Ihrig. (2004). Monetary policy and exchange rate pass-through. International Journal of Finance & Economics, 9(4), 315-338.
Retrieved from https://doi.org/10.1002/ijfe.253/
-Goldfajn, I. and Werlang, S. R. D. C. (2000). The pass-through from deprecia tion to inflation: a panel study. Werlang, Sergio R., the Pass Through from Depreciation to Infla tion: A Panel Study. Banco Central de Brasil Working Paper, (5). Retrieved from http://dx.doi.org/10.2139/ssrn.224277/
-Heydari, H. and Bashiri, S. (2024). Estimating the transfer effects of exchange rates on the prices of industrial sub-sectors in Iran using a Bayesian approach. Journal of Monetary Policy, 17( 33), 57-84. Retrieved from
https://doi.org /10.22034/EPJ.2024.21571.2593/ (In Persian)
-Schroder, M. and Hufner, F.P. (2002). Exchange rate pass-through to consumer prices: A European perspective. ZEW discussion paper, 02-20.
Retrieved from https://doi.org 10.34989/sdp-2015-9
-Hyeongwoo K., Ying L. and Henry, T. )2021(. Exchange Rate Pass-Through to Consumer Prices: The Increasing Role of Energy Prices. Open Economies Review, 32(2), 395-415. Retrieved from
https://doi.org 10.1007/s11079-020-09601-7/
-Laflèche, T. (1996). The Impact of Exchange Rate Movements on Consumer Prices. Bank of Canada Review, 21–32.
-Mashhadizadeh, F., Khosrow. P., Akbari Moghadam. B. and Zare, H. (2019) Monetary Policy and Exchange Rate Transmission in Iran. Quarterly Journal of Applied Economic Studies of Iran. 8(30), 25-55.
Retrieved from https://doi.org/10.22084/AES.2019.17891.2780/(In Persian)
-Mesbahi, M., Asgharpour, H., Haghighat, J., Kazeruni, S. and Fallahi, F. (2017). The degree of exchange rate pass-through to import prices in the Iranian economy with emphasis on oil revenue fluctuations (nonlinear approach). Quarterly Journal of Economic Modeling,11(37),77-100. (In Persian)
-Pish bahar, I., Ghahramanzadeh, M. and Aref Eshghi, T. (2013). Exchange Pass-Through in to Food Inflation in Iran, Agricultural Economics, 7(3),1-21. (In Persian)
-Qu, Z., and P. Perron (2007). Estimating and testing structural changes in multivariate regressions. Econometrica, 75(2), 459-502. Retrieved from
https://doi.org/10.1111/j.1468- 0262.2006.00754.x/
-Romer, D. (1993). Openness and inflation: theory and evidence. The quarterly journal of economics, 108(4), 869 903. Retrieved from
https://doi.org/10.2307/2118453/
-Takhtamanova, Y. F. (2010). Understanding changes in exchange rate pass-through. Journal of Macroeconomics, 32(4), 1118.1130. Retrieved from https://doi.org/10.1016/j.jmacro.2010.04.004/
-Taylor, J. B. (2000). Low inflation, pass-through, and the pricing power of firms. Euro-pean Economic Review, 44(7), 1389-1408. Retrieved from https://doi.org/10.1016/S0014-2921(00)00037-4/