با همکاری انجمن اقتصاد کشاورزی ایران

نوع مقاله : مقالات پژوهشی به زبان انگلیسی

نویسندگان

1 گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه زابل، زابل، ایران

2 گروه اقتصاد کشاورزی، دانشکده علوم کشاورزی‬، دانشگاه گیلان، گیلان، ایران

چکیده

تأثیر منفی و مخرب پدیده تغییر اقلیم بر عملکرد و بهره‌وری عوامل تولید کشاورزی در بسیاری از مناطق جهان به‌خصوص در مناطق خشک و نیمه­خشک به اثبات رسیده است. در این راستا، اتخاذ راهبرد‌های نوآورانه برای افزایش انعطاف‌پذیری و سازگاری کشاورزان به منظور تطبیق با تغییرات اقلیمی گسترش یافته است. بنابراین، آگاهی از میزان اثرگذاری راهبردهای تطبیق با اقلیم بر میزان کارایی و عملکرد زراعین حائز اهمیت است. بر این اساس، در پژوهش حاضر، تأثیر راهبردهای تطبیق با تغییر اقلیم همراه با مصرف نهاده‌ها و عوامل خارج از کنترل کشاورز برکارایی فنی با استفاده از مدل مرزی تصادفی اصلاح­شده درونزا (EMSF) ارزیابی شد. داده­ها ازطریق تکمیل 265 پرسشنامه درسال زراعی 1401-1400 و به روش نمونه­گیری تصادفی چندمرحله‌ای برای تولیدکنندگان گندم در منطقه سیستان جمع­آوری شد. به‌ منظور ساختن شاخص تطبیق از روش تجزیه و تحلیل مؤلفه اصلی (PCA) استفاده شد. نتایج PCA نشان داد تغییر اندازه زمین (812/0) خاکورزی حفاظتی (797/0) و تغییر تاریخ کشت (619/0) بیشترین بار عاملی و استفاده از آب باران (219/0) و استفاده از کودهای زیستی (327/0) کمترین بار عاملی راهبردهای تطبیق در بین کشاورزان را دارند. دراین مطالعه، میانگین کارایی فنی گندمکاران 82 درصد محاسبه شد. نتایج برآورد مدل نشان داد که مساعدت نهاده‌های نیروی کار، سموم شیمیایی، کود شیمیایی، آب و ماشین‌آلات به کارایی تولید گندم از نظر آماری مثبت و معنی‌دار است و با اجرای راهبردهای تطبیق با اقلیم توسط کشاورزان، میزان ناکارایی فنی کاهش می‌یابد. همچنین، متغیرهای سطح تحصیلات، تجربه کشاورزی، دسترسی به اطلاعات اقلیمی و دسترسی به اعتبارات در کاهش ناکارایی فنی مؤثرند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Impact of Adopting Strategies to Cope with Climate Change on the Technical Efficiency of Wheat Farmers in Sistan Region-Iran

نویسندگان [English]

  • H. Naruei 1
  • M. Ahmadpour Borazjani 1
  • M. Salarpour 1
  • A. Keikha 1
  • R. Esfanjari Kenari 2

1 Department of Agricultural Economics, Agricultural College, University of Zabol, Zabol, Iran

2 Agricultural Economics Department, Faculty of Agricultural Sciences, University of Guilan, Guilan, Iran

چکیده [English]

The negative and destructive impact of climate change on the efficiency and productivity of agricultural inputs has been demonstrated in many regions of the world, particularly in arid and semi-arid areas. In this context, the adoption of innovative strategies to increase farmers' flexibility and adaptability to climate change has increased. Hence, understanding the impact of climate adaptation strategies on agricultural efficiency and yields is crucial. This study examined the effects of climate change adaptation strategies, input utilization, and external factors beyond farmers' control on technical efficiency using the Endogenous Modified Stochastic Frontier (EMSF) model. Data were collected from 265 questionnaires distributed among wheat farmers during the 2022-2023 cultivation period, using a stratified random sampling approach. The climate adaptation strategy index was formulated using the Principal Component Analysis (PCA) technique. The PCA revealed that changes in farm size (0.812), adaptation of conservation tillage (0.797), and adjustments in planting dates (0.619) were the most influential factors. Conversely, rainwater harvesting (0.219) and biofertilizer application (0.327) emerged as the adaptation strategies with the lowest factor loadings among farmers. In this study, the average technical efficiency of wheat farmers was calculated to be 82%. The model estimation results showed that labor input, chemical pesticides, chemical fertilizers, water, and machinery significantly and positively contribute to wheat production efficiency. Additionally, the implementation of climate adaptation strategies by farmers reduces technical inefficiency. Variables such as education level, farming experience, access to climate information, and access to credit also effectively reduce technical inefficiency.

کلیدواژه‌ها [English]

  • Logit regression
  • Principal components analysis
  • Socio-economic characteristics
  • Stochastic frontier model

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

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