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تحلیل پویای واکنش رشد اقتصادی ایران به شوک های تحریمی و اقتصادی؛ کاربرد مدل الگوهای خود رگرسیون برداری تعمیم یافته با پارامتر متغیر زمان
[Dynamic Analysis of Iran's Economic Growth Response to Sanctions and Economic Shocks: Application of the Generalized Vector Autoregression Model with Time-Varying Parameters]

Author

Listed:
  • Rahimi Kahkashi, Sanaz
  • Asharieen, Nasim
  • Adeli, OmidAli
  • Roudari, Soheil

Abstract

In the years following the Islamic Revolution, Iran's economy has been affected by international sanctions with varying degrees of intensity. In recent years, the scope and severity of these sanctions have increased, leaving profound impacts on economic indicators, including gross domestic product (GDP) growth. This study aims to dynamically analyze Iran’s economic growth response to sanctions and economic shocks over the period 1981–2021, using a Factor-Augmented Vector Autoregression (FAVAR) model combined with a Time-Varying Parameter (TVP) framework. This model enables a dynamic examination of the temporal effects of economic and sanction-related shocks. The explanatory variables in the model include liquidity volume, tax revenues, government current expenditures, exchange rate, income inequality, human capital, oil revenues, and sanctions. A dummy variable has been incorporated to represent sanctions during selected key sanction periods (1981–1988, 1996–1997, 2006–2013, and 2018–2021). The estimated model results indicate that Iran’s economic growth exhibits nonlinear responses to various shocks. Sanctions, exchange rate increases, rising income inequality, and declining human capital have had negative effects on economic growth, whereas positive reactions to government current expenditures have contributed to economic expansion. Regarding tax revenues, the findings suggest that increasing tax revenues can play a crucial role in reducing dependence on oil income. However, without structural reforms, raising taxes may increase production costs and reduce investment, thereby hindering economic growth. Therefore, instead of merely increasing taxes, emphasizing tax transparency, reducing tax evasion, and optimizing tax exemptions is essential. Regarding oil revenues, the study finds that their impact on economic growth varies depending on how they are managed. On the one hand, investing these resources in infrastructure, research and development, and financing imports of intermediate and capital goods can boost economic growth. On the other hand, excessive reliance on oil revenues, especially under sanction conditions, increases economic vulnerability and negatively affects growth stability. Sanctions have had a significant negative impact on Iran’s gross domestic product (GDP), particularly through their effects on trade, investment, and production capacity. The findings of this study underscore the importance of proper oil resource management, reducing Iran's dependence on external economic factors, implementing effective tax policies, and strengthening productive sectors. Accordingly, policies that enhance economic resilience against sanctions, develop domestic production capacity, and mitigate the adverse effects of oil revenue fluctuations will play a key role in achieving sustainable economic growth.

Suggested Citation

  • Rahimi Kahkashi, Sanaz & Asharieen, Nasim & Adeli, OmidAli & Roudari, Soheil, 2025. "تحلیل پویای واکنش رشد اقتصادی ایران به شوک های تحریمی و اقتصادی؛ کاربرد مدل الگوهای خود رگرسیون برداری تعمیم یافته با پارامتر متغیر زمان [Dynamic Analysis of Iran's Economic Growth Response to Sanctions and Economic Shocks: Application of the Gene," MPRA Paper 127342, University Library of Munich, Germany, revised 22 Sep 2025.
  • Handle: RePEc:pra:mprapa:127342
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    References listed on IDEAS

    as
    1. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    3. Roudari, Soheil & Ahmadian- Yazdi, Farzaneh & Arabi, Seyed Hadi & Hammoudeh, Shawkat, 2022. "Sanctions and Iranian Stock Market: Does the Institutional Quality Matter?," MPRA Paper 126831, University Library of Munich, Germany, revised 15 Mar 2023.
    4. Roudari, Soheil & Sadeghi, Abdorasoul & Gholami, Samad & Mensi, Walid & Al-Yahyaee, Khamis Hamed, 2023. "Dynamic spillovers among natural gas, liquid natural gas, trade policy uncertainty, and stock market," Resources Policy, Elsevier, vol. 83(C).
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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