تحلیل رفتار بازیکنان در تحریم امریکا علیه ایران: رویکرد مبتنی بر عامل

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری اقتصاد، دانشکده علوم اجتماعی و اقتصاد، دانشگاه الزهرا (س)

2 استاد دانشکده علوم اجتماعی و اقتصاد، دانشگاه الزهرا (س)

3 دانشیار دانشکده علوم اجتماعی و اقتصاد، دانشگاه الزهرا (س)

چکیده

تحریم های اعمال شده بر ایران ازسوی کشورهای خارجی و برخی نهادهای بین المللی، یکی از مهمترین چالش های اقتصادی کشور در سالهای اخیر بوده است. تحریم مجموعه ابزاری شامل اقدامات برنامه ریزی شده یک یا چند ِ دولت برای محدود کردن ِ مناسبات اقتصادی و اعمال فشار بر کشور هدف با مقاصد مختلف اقتصادی و سیاسی است. همراهی سایر بازیگران مهم اقتصادی و سیاسی با کشور تحریم کننده نقش مؤثری در موفقیت این کشور برای دستیابی به اهداف خواهد داشت. این همراهی بر پیچیدگی های روابط بازیکنان در فضای بین المللی تحریم ها میافزاید.
این مطالعه ضمن ارائه یک رویکرد چند رشته ای شامل نظریه بازی ها، سیستم های مبتنی بر عامل، هوش مصنوعی و طراحی سازوکار در تحلیل موضوعات پیچیده ای نظیر بازی تحریم ایران توسط ایالات متحده و متحدان آن و همچنین ارائه نتایج حاصل از شبیه سازی رفتار بازیکنان، می کوشد به معرفی روش نوینی در حوزه مدل سازی پدیده های اقتصادی سیاسی بپردازد. به این منظور بازیکنان، ویژگی ِ های مؤثر آنها در بازی تحریم و ِ طیف راهبرد بازی تعیین و شبیه سازی رفتار بازیکنان در چارچوب ذکر شده انجام شده است. نتایج شبیه سازی رفتار بازیکنان بر طیف پیشنهادی که شامل دو وضعیت حدی تقابل و سازش است، نشان میدهد در وضعیت جاری راهبرد مسلط؛ تأ کید بر حفظ توافق برجام است و بازیکنان مؤثر در بازی تحریم ایران در موقعیت چانه زنی قرار دارند و نه فضای رویارویی یا تسلیم. این بازی پس از هشت دوره چانه زنی در محدوده مذاکره در چارچوب سازوکار برجام به ثبات میرسد. جهت گیری ایالات متحده آمریکا و طیف حامی او در منطقه خاورمیانه، به سمت جهت گیری سایر بازیکنان در محدوده مذاکره در چارچوب سازوکار برجام تغییر می کند و جهت گیری حدی برخی بازیکنان داخلی را میتوان به عنوان یک تهدید معتبر در مناقشات ایالات متحده آمریکا علیه ایران در نظر گرفت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The Behavioral Analysis of the agents in the US sanction against Iran: The agent based approach

نویسندگان [English]

  • kobra sangarimohazzab 1
  • hossein raghfar 2
  • mirhossein musavi 3
1 Alzahra University
2 رئیس پژوهشکده اقتصاد
3 معاون آموزشی دانشکده علوم اجتماعی و اقتصاد دانشگاه الزهرا
چکیده [English]

The sanctions which have been imposed against Iran by foreign countries and some international bodies have been oconsidered as one of the most important economic challenges facing our country in recent years. The sanction consists of a set of planned measures which have been taken by one or more governments in order to curtail economic relations of the target state as well as exert pressure on it for different economic and political reasons. The accompaniment of other major economic and political acors with the boycotting state will play an effective role in achieving its objectives. This coordination aggrevates the complexities of actors’ relations in the international sanctions environment. Therefore, the method of agent-based approach and game theory are used to analyze the problem of sanctions as well as predict the possible equilibrium in these relations. Due to the networking and breadth of the issue of sanctions as well as looking for the optimal solution to widespread interactions arising from competition, coordination and negotiation, an agent-based approach is used in this paper. Presenting a multidisciplinary approach including game theory, agent-based systems, artificial intelligence and mechanism design in order to analyze the complicated problems of the US sanctions against Iran as well as providing results of the simulation of actors’ behaviors, the paper attempts to introduce a new approach to modeling of political-economic phenomana.To this end, actors as well as their effective features on the sanctions game, scope of the game strategies have been identified as well as the simulation of actors’ behaviors have been conducted within the (above) mentioned framework. Results of the simulation of the actors’ behaviors on the proposed spectrum which includes two extremes of capitulation and confrontation shows that dominant strategy in the current situation is only emphasizing on the maintenance of the current nuclear deal/agreement formally known as JCPOA (Joint Comprehensive Plan of Action) as well as effective actors’ on the sanctions game against Iran should continue bargaining in a Cartesian Coordinate System not confrontation and capitulation. Finally, this game will be stablized after eight rounds of JCPOA negotiation are held. Over the periods, the orientation of US and its alignments in the Middle East region are shifted towards accepting (position of) other actors to continue Nuclear Deal (JCPOA) negotiation. But the limited orientation of some of the domestic agents might be considered as a credible threat in US–Iran standoff. 

کلیدواژه‌ها [English]

  • Sanctions
  • Game Theory
  • Mechanism Design
  • Agent-based Modeling
  • Computer Simulation
  • Artificial Intelligence
منابع و مآخذ
Afesorgbor, S. K. and R. Mahadevan (2016). The Impact of Economic Sanctions on Income Inequality of Target States, World Development, 83.
Beladi, H., and R. Oladi (2015). On Smart Sanctions, Economics Letters, 130.
Charumbira, M. (2008). "Applying the Gravity Model to Trade Flow in Country Under Sanctions: Case of Zimbawe (1998-2006)", Department of Political and Administration, Redeemers University, Nigeria.
Drezner, Daniel W. (1999). The Sanction Paradox: Economic Statecraft and International Relations, Cambridge Studies in International Relations, No. 65. Cambridge: Cambridge University Press.
Eftekhari, Z. and S. Rahimi (2014). Preana: Game Theory Based Prediction with Reinforcement Learning. Natural Science, 6(13).
Evans, G. and J. Newnham (1998). The Penguin Dictionary of International Relations London: Penguin Books.
Epstein, J. M. (2006). Generative Social Science. Studies in Agent-Based Computational Modeling, Princeton University Press.
Feder, S. (1987). Factions and Policon: New ways to Analyze Politics, Inside CIA’s Private World: Declassified Articles from the Agency’s Internal Journal, 1992.
Fudenberg, Jean Tirole (1995). Game theory. The MIT Press.
Howitt, P. (2012). "What Have Central Bankers Learned from Modern Macroeconomic Theory? ".  Journal of Macroeconomics, 34(1), 11-22.
Hufbauer, Gary Clyde, Jeffrey J. Schott, Kimberly Ann Elliott, and Barbara Oegg. (2007). Economic Sanctions Reconsidered, 3d ed. Washington, Peterson Institute for International Economics.
Jesse, E. (2011). Forecasting the Future of Iran. RAND Institute.
Kaempfer, W. H. and A. D Lowenberg (2007). "The Political Economy of Economic Sanctions". Handbook of defense economics, 2.
Katzman, K. (2015). Iran Sanctions, Congressional Research Service.
Keynes, J.M. (1936). The General Theory of Employment, Interest, and Money, Harcourt Brace Jovanovich, New York.
Mesquita, B. D. (1984). "Forecasting Policy Decisions: an Expected Utility Approach to Post-Khomeini Iran". Political Science and Politics, 17(2).
--- (1997). "A Decision Making Model: Its Structure and Form".International Interactions, 23(3-4).
--- (2010). The Predictioneer's Game: Using the Logic of Brazen Self-Interest to See and Shape the Future. Random House Incorporated.
--- (1984). "The Conflict Forecasting Project". Defense Technical Information Center (DTIC): University of Rochester Department of Political Science.
--- (2011). Applications of Game Theory in Support of Intelligence Analysis, Intelligence Analysis: Behavioral and social scientific foundations. 57–82, Washington, DC: The National Academies Press.
Mesquita, B. B. D., D. Newman and A. Rabushka (1985). Forecasting Political Events: The Future of Hong Kong, Yale University Press.
Mesquita, B. B. D. and D. Lalman (1992). War and Reason, Yale University Press.
Mesquita, B. B. D. and F. N. Stokman (Eds.). (1994). European Community Decision Making: Models, Applications, and Comparisons, Yale University Press.
Murphy, M. K. (1998). "Consensus Development Methods and Their Use in Clinical Guideline Development". Health technology assessment, 2(3).
Nash J. (1950). The Bargaining Problem. Econometrica: Journal of the Econometric Society.
Nephew, R. (2018). The Art of Sanctions: A View from the Field, Columbia University Press.
Neuenkirch, M., and F. Neumeier (2016). "The Impact of US Sanctions on Poverty", Journal of Development Economics, 121.
--- (2015). "The Impact of UN and US Economic Sanctions on GDP Growth", European Journal of Political Economy, 40.
Oechslin, M. (2014). "Targeting Autocrats: Economic Sanctions and Regime Change", European Journal of Political Economy, 36.
Powell, C. (2003). "The Delphi Technique: Myths and Realities", Journal of Advanced Nursing, 41(4).
Rowe, David M. (2000). "Economic Sanctions, Domestic Politics and the Decline of Rhodesian Tobacco", 1965-79: In Steve Chan and A. Cooper Drury (Eds), Sanctions as Economic Statecraft: Theory and Practice, Macmillan.
Shahabi, S., H. Fazlalizadeh, J. Stedman, L. Chuang, A. Shariftabrizi and R. Ram (2015). "The Impact of International Economic Sanctions on Iranian Cancer Healthcare", Health Policy, 119(10).
Somerville, Jerry A (2008). "Effective Use of the Delphi Process in Research: Its Characteristics, Strengths and Limitations", Oregon: Corvallís.
Taghavi, M, B. Shayegani, F. Gaffari, M. Abdolali and A. Niakan Lahiji (2012). "Does Gravity Model Work for the Selection of Trade Partners Among SCO Members? The Case Study of Iran", Journal of American Science, 8 (10).
Ueng, B. (2012). Applying Bruce Bueno de Mesquita’s Group Decision Model to Taiwan’s Political Status: a simplified Model, The Visible Hand: A Cornell Econom Ics Society Publication, Ithaca, NY.  
Whang, T. (2010). "Structural Estimation of Economic Sanctions: From Initiation to Outcomes", Journal of Peace Research, 47(5).
Williams, P.L. and C. Webb (1994). "The Delphi Technique: A Methodological Discussion", Journal of Advanced Nursing, 19 (1).