شناسایی و تحلیل روابط علی بین متغیرهای کلان اقتصادی موثر بر رشد اقتصادی ایران با روش نقشه علی بیزین(BCM)

نوع مقاله: علمی - پژوهشی

نویسندگان

1 دانشیار گروه اقتصاد کشاورزی دانشکده کشاورزی دانشگاه تبریز، ایران

2 دانشجوی کارشناسی ارشد اقتصاد کشاورزی دانشکده کشاورزی دانشگاه تبریز ،ایران

چکیده

دستیابی به رشد اقتصادی بالا یکی از اهداف اصلی تمامی جوامع و سیاست‌گذاران اقتصادی است و اقتصاددانان پیوسته در تلاش‌اند تا با استفاده از روش‌های مختلف نظری و تجزیه و تحلیل تجربی عوامل موثر بر رشد را شناسایی کنند. اهمیت این موضوع در کشور ما نیز به دلیل نوسانات درآمد نفتی، تورم بالا و سایر مشکلات و نابسامانی‌ها برجسته‌تر است. بنابراین هدف مطالعه حاضر شناسایی و تحلیل روابط علی بین متغیرهای کلان اقتصادی است که بر رشد اقتصادی اثر دارند که ابتدا روابط علی بین متغیرها با استفاده از الگوی GES در نرم افزار Tetrad شناسایی سپس با انجام اصلاحات لازم احتمالات در نرم افزار Netica برای ایجاد نقشه علی بیزین محاسبه گردید. طی سناریوهای مختلف تحلیل حساسیت برای عوامل موثر صورت گرفت و در نهایت جایگزینی درآمدهای مالیاتی و فروش اوراق قرضه به جای درآمد نفتی برای جلوگیری از بروز مشکلات پیوسته نظیر افزایش بدهی، کسری بودجه، افزایش استقراض از بانک مرکزی، افزایش نقدینگی و در نهایت افزایش تورم پیشنهاد گردید

کلیدواژه‌ها


عنوان مقاله [English]

Identifying and Analyzing the Causal Relationships between the Effective Macroeconomic Variables on Iran’s Economic Growth Using Bayesian Casual Map Method

نویسندگان [English]

  • Esmaeil Pishbahar 1
  • Parisa Pakrooh 2
چکیده [English]

Achievement high economic growth in all societies is main purpose of the policy makers and because of that economists are trying to use different theoretical and empirical methods to analyze and identifying the economic growth and the effective factors on it. Because of oil revenues volatility, high inflation, debt of government to Central Bank and other problems, the mentioned subject is more highlighted in Iran. We used casual relations approaches and Bayesian Casual Map (BCM) method for investigation relationships among macroeconomic variables that have affected on the economic growth in Iran. We investigated the causal relation among variables by using GES algorithm in the Tetrad software and after modifying casual relationships, we determined the variable probabilities by Netica Software. Based on first scenario analysis, increases in oil revenue have a direct and positive effect on economic growth, but tax and debts scenarios indicate that have an direct and negative effect on economic growth. Eventually replace the tax revenues and the sale of saving bonds instead of oil revenues for avoiding continual failures such as debt, deficit, increased borrowing from the central bank to increase liquidity and ultimately inflation was proposed.

کلیدواژه‌ها [English]

  • Bayesian Casual Map
  • Casual relationship
  • Economic Growth
  • GES Algorithm
  • inflation
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