پیش بینی تاثیر شرایط آب و هوایی بر تولید اقتصادی استان های ایران با رویکرد الگوریتم جنگل تصادفی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکترای علوم اقتصادی دانشگاه فردوسی مشهد

2 دانشیار اقتصاد دانشگاه فردوسی مشهد

چکیده

اهمیت اقلیم به عنوان یکی از واقعیت‌های زیستی بشر در حوزه مسائل کلان اقتصادی و اجتماعی، هیچ زمانی به اندازه امروز مدنظر نبوده است. بررسی اثرات اقتصادی تغییرات اقلیم نیازمند تحلیل‌های دقیق در سطوح ملی و محلی است. هرچند مطالعات جهانی متعددی وجود دارد که تأثیرات اقتصادی تغییرات آب و هوایی را مورد بررسی قرار می‌دهند، اما تاکنون مطالعات محدودی در سطوح محلی در داخل کشورها، به ویژه در مورد ایران، انجام شده‌ است. در این مقاله سعی شده است تا با بهره‌گیری از مجموعه داده جدید از شرایط آب و هوایی استان‌های کشور در دوره زمانی 1379تا 1399 از طریق الگوریتم جنگل تصادفی از زیرمجموعه‌های یادگیری ماشین، تحلیلی جامع از تاثیرپذیری تولید اقتصادی استان­های کشور از تغییرات آب و هوایی ارائه شود. نتایج نشان می­دهد که دما و بارش در همه استان‌های کشور بر تولید تاثیرگذارند. پیش‌بینی تغییرات تولید استان‌های کرمان، سمنان، خراسان شمالی، ایلام، قزوین و کهگیلویه و بویراحمد نسبت به سایر استان‌ها با تاثیرپذیری بیشتر ارائه شده و همچنین تاثیرگذاری بارش نسبت به دما با اهمیت بالاتری در مدل ارائه شده است ضمن اینکه اهمیت تاثیرگذاری دما بر تولید در ماه‌های گرم سال کمتر از ما‌های سرد سال پیش‌بینی شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Predicting the Impact of Climate Conditions on the Economic Production of Iranian Provinces with The Approach of Random Forest Algorithm

نویسندگان [English]

  • Lotfali Azari 1
  • Aliakbar Naji meidani 2
  • Narges Salehnia 2
1 Ph.D. Candidate in Economics, Ferdowsi University of Mashhad
2 Associate Professor of Economics, Ferdowsi University of Mashhad
چکیده [English]

Climate change is among the vital phenomena related to human societies, and its consequences have been demonstrated, particularly in recent decades, with varying intensity in many regions of the world. The importance of climate as one of the fundamental aspects of human life has never been as significant as it is today in macroeconomic and social issues. Analyzing climate change's economic impacts necessitates precise national and local analyses. Although numerous global studies examine the economic effects of climate change, limited research has been conducted at local levels within countries, especially concerning Iran. This article attempts to provide a comprehensive analysis of the susceptibility of the country's provincial economic production to climate change by utilizing a new dataset of weather conditions in the provinces from 2000 to 2020 through the random forest algorithm of machine learning subsets. Studies indicate a significant relationship between weather and sectors beyond agriculture, forestry, food security, tourism, health, fisheries, livestock, mining, and energy. Weather conditions can directly or indirectly impact various economic sectors, and their effect on economic activities is inevitable. However, research results regarding the impact of weather fluctuations face varied findings. Drought, with a higher recurrence than floods, poses more significant challenges to the economy on scales beyond local levels.

کلیدواژه‌ها [English]

  • Climate change
  • Production
  • Economic Impact
  • Climate Impacts
  • Random Forest

مراجع

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