تجزیه رشد بهره‌وری کل عوامل تولید بخش کشاورزی ایران با تأکید بر متغیرهای آب و هوایی

نوع مقاله : مقالات پژوهشی به زبان انگلیسی

نویسندگان

قادر دشتی

محمد قهرمان زاده

کوثر قلی پور

سعیده محمدپور

گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

https://doi.org/10.22067/jead.2025.91643.1328

چکیده

شرایط اقلیمی از عوامل تعیین­کننده بهره­وری تولید محصولات کشاورزی است که ضمن تأثیر بر سطح تولید، بر امنیت غذایی نیز مؤثر می­باشد. بنابراین هدف مطالعه حاضر تجزیه رشد بهره‌وری کل عوامل تولید بخش کشاورزی در ایران با لحاظ متغیرهای آب و هوایی است. برای این منظور، از مدل TRP-SPF و روش حداکثر درست‌نمایی برای برآورد پارامترها در دو سناریو با لحاظ متغیرهای آب و هوایی ( ) و بدون آن ( ) بهره گرفته شد. نتایج نشان می‌دهند که در هر دو مدل، متغیرهای سطح زیرکشت، تراکتور و فناوری تأثیر مثبت و معناداری بر تولید دارند که بیشترین تأثیر مربوط به متغیر سطح زیرکشت است. همچنین در مدل ، متغیرهای دما و بارش نیز به­طور معناداری اثر مثبت بر تولید دارند. میانگین کارایی فنی در مدل   برابر با 5/56 درصد برآورد شد و در مدل با متغیرهای اقلیمی به 3/43 درصد کاهش یافت که ضمن تأیید تأثیر قابل­توجه متغیرهای اقلیمی بر تولید، موید امکان افزایش تولیدات بخش کشاورزی با همان منابع و تکنولوژی به میزان بالغ بر 50 درصد می­باشد، درصورتی‌که عوامل عدم کارایی و تأثیر سوء متغیرهای اقلیمی به کمترین مقدار خود تقلیل داده شوند. تجزیه شاخص CATFP به چهار جزء، اثرات  اقلیمی، اثرات مقیاس، کارایی فنی و پیشرفت فناوری، نشان داد که اثرات اقلیمی با سهم 4/26 درصدی بیشترین تاثیر و سه جزء دیگر سهم تقریبا یکسانی در ارتقای بهره­وری عوامل تولید داشته­اند. نظر به تأثیر قابل توجه متغیرهای آب و هوایی بر عملکرد بخش کشاورزی، اتخاذ تدابیری که انطباق بیشتری با شرایط اقلیمی مناطق مختلف داشته باشد، توصیه می­گردد.

کلیدواژه‌ها

بهره‌وری کل عوامل تولید

تأثیرات آب و هوایی

کارایی فنی

کارایی مقیاس

کشاورزی

موضوعات

• اقتصاد کشاورزی

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عنوان مقاله English

Decomposing Total Factor Productivity Growth in Iran's Agriculture Sector with Consideration of Climatic Variables

نویسندگان English

G. Dashti

M. Ghahremanzadeh

K. Gholipour

S. Mohammadpour

Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

چکیده English

Climatic conditions are key determinants of agricultural productivity, affecting both production levels and food security. This study aims to decompose total factor productivity growth in Iran’s agricultural sector by explicitly incorporating climatic variables. True Random Parameters Stochastic Production Frontier (TRP-SPF) model and the Maximum Likelihood method were used to estimate parameters in two scenarios, with and without climate variables which are evaluated by  and  models, respectively. The results showed that the variables of cultivated area, tractors, and technology have a positive and significant impact on production in both models, and the highest effect observed for cultivated area. In the  model, the variables of temperature and precipitation also made significant contributions to higher production. The average technical efficiency in the  model was estimated at 56.5%, and in the model with climatic variables, it decreased to 43.3%. These results confirmed the significant impact of climatic variables on production and suggested that agricultural output could be increased by more than 50% with the same resources and technology, minimizing inefficiency factors and the adverse effects of climatic variables. Decomposition of the Climatic Adjusted Total Factor Productivity (CATFP) index into four components, including climatic effects, scale effects, technical efficiency, and technological progress, revealed that climatic effects have the greatest impact, accounting for 26.4%, while the other three components contributed almost equally to improving productivity. Given the significant impact of climatic variables on agricultural productivity, this study recommends strategies adapting better with climatic conditions of different regions.

کلیدواژه‌ها English

Agriculture

Climatic effects

Scale effects

Technical efficiency

Total factor productivity

Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

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