1- Gorgan University of Agricultural Sciences and Natural Resources
Abstract: (62 Views)
Abstract
Introduction and Objective: Efficiency is a crucial factor in enhancing the productivity of production factors, particularly for developing countries. These countries face challenges of limited resources and opportunities for development and the adoption of better technology. Generally, considering the recognition of capabilities and limitations in the agricultural sector of Iran's economy, it can be said that the most suitable solution for increasing production and income of farmers is the proper utilization of existing production factors, improving technical efficiency, or achieving maximum output from a fixed set of production factors. Therefore the most essential prerequisite for achieving economic growth and prosperity in the agricultural sector is the assessment of the efficiency of agricultural units. This study aims to measure the technical, allocative, and economic efficiencies of wheat producers in selected provinces of the country.
Materials and Methods: The required data for this research, including the consumption level and prices of chemical fertilizers, pesticides, seeds, labor, machinery, cultivated area, and wheat production, were obtained from the Ministry of Agriculture Jihad's agricultural cost bank and agricultural information bank for the year 2019. Data envelopment analysis (DEA) with an input-oriented approach was used to measure efficiency. Data Envelopment Analysis (DEA) is a linear programming method used to measure the relative efficiency of decision-making units (DMU) with multiple inputs and outputs. This method is widely used to evaluate efficiency in various economic sectors, including agriculture. In this study, each province is considered as a decision-making unit. The inputs of the model include the cultivated area (hectares), the amount of chemical fertilizers (Kg.), the amount of poison (liters), the amount of seeds (Kg.), the hours of using machinery (hours), and the number of workers (man-day) and the output of the model is the amount of irrigated wheat production (kilogram). The DEA model is implemented with the assumption of constant return to scale (CRS) and variable return to scale (VRS). The CRS model assumes that an increase in inputs leads to a proportional increase in outputs, while the VRS model does not and allows returns to scale to vary.
Results: Among 30 provinces of the country, the lowest technical efficiency was 72.5% in Khorasan Razavi province, while the highest technical efficiency was 100% in provinces such as Khuzestan, Golestan, Kermanshah, East Azerbaijan, Hamadan, Ilam, Tehran, Kurdistan, Mazandaran, Kohgiluyeh and Boyer-Ahmad, South Khorasan, Hormozgan, Bushehr, Alborz, Yazd, and Qom. Moreover, the average technical efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 94.3%. Additionally, among 30 provinces, the lowest allocative efficiency was 54.5% in Sistan and Baluchestan province, while the highest allocative efficiency was 100% in provinces such as Khuzestan, Golestan, Tehran, and Qom. The average allocative efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 81.8%. The lowest economic efficiency was 47.7% in Sistan and Baluchestan province, while the highest economic efficiency was 100% in provinces such as Khuzestan, Golestan, Tehran, and Qom. The average economic efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 77.3%.
Conclusion: Among 30 wheat-producing provinces, Khuzestan, Golestan, Tehran, and Qom simultaneously had the highest technical, allocative, and economic efficiencies at 100%, while Khorasan Razavi province had the lowest technical efficiency at 72.5%, and Sistan and Baluchestan province had the lowest allocative and economic efficiencies at 54.5% and 47.7% respectively. Considering the difference between the best and worst producers, it is recommended to provide a platform for successful provinces to share their experiences and methods with others. The results suggest that extension and agricultural service centers should organize educational and promotional classes to optimize the use of inputs, especially chemical fertilizers and pesticides. Land consolidation programs should be seriously pursued in each region to not only save on inputs such as labor and machinery but also reduce costs and utilize modern technology over large land areas. It is suggested to support applied research in the field of improving the management of input consumption in the production of irrigated wheat according to the climatic and socio-economic conditions of each region. This can be done by allocating research funds and motivating
Introduction and Objective: Efficiency is a crucial factor in enhancing the productivity of production factors, particularly for developing countries. These countries face challenges of limited resources and opportunities for development and the adoption of better technology. Generally, considering the recognition of capabilities and limitations in the agricultural sector of Iran's economy, it can be said that the most suitable solution for increasing production and income of farmers is the proper utilization of existing production factors, improving technical efficiency, or achieving maximum output from a fixed set of production factors. Therefore the most essential prerequisite for achieving economic growth and prosperity in the agricultural sector is the assessment of the efficiency of agricultural units. This study aims to measure the technical, allocative, and economic efficiencies of wheat producers in selected provinces of the country.
Materials and Methods: The required data for this research, including the consumption level and prices of chemical fertilizers, pesticides, seeds, labor, machinery, cultivated area, and wheat production, were obtained from the Ministry of Agriculture Jihad's agricultural cost bank and agricultural information bank for the year 2019. Data envelopment analysis (DEA) with an input-oriented approach was used to measure efficiency. Data Envelopment Analysis (DEA) is a linear programming method used to measure the relative efficiency of decision-making units (DMU) with multiple inputs and outputs. This method is widely used to evaluate efficiency in various economic sectors, including agriculture. In this study, each province is considered as a decision-making unit. The inputs of the model include the cultivated area (hectares), the amount of chemical fertilizers (Kg.), the amount of poison (liters), the amount of seeds (Kg.), the hours of using machinery (hours), and the number of workers (man-day) and the output of the model is the amount of irrigated wheat production (kilogram). The DEA model is implemented with the assumption of constant return to scale (CRS) and variable return to scale (VRS). The CRS model assumes that an increase in inputs leads to a proportional increase in outputs, while the VRS model does not and allows returns to scale to vary.
Results: Among 30 provinces of the country, the lowest technical efficiency was 72.5% in Khorasan Razavi province, while the highest technical efficiency was 100% in provinces such as Khuzestan, Golestan, Kermanshah, East Azerbaijan, Hamadan, Ilam, Tehran, Kurdistan, Mazandaran, Kohgiluyeh and Boyer-Ahmad, South Khorasan, Hormozgan, Bushehr, Alborz, Yazd, and Qom. Moreover, the average technical efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 94.3%. Additionally, among 30 provinces, the lowest allocative efficiency was 54.5% in Sistan and Baluchestan province, while the highest allocative efficiency was 100% in provinces such as Khuzestan, Golestan, Tehran, and Qom. The average allocative efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 81.8%. The lowest economic efficiency was 47.7% in Sistan and Baluchestan province, while the highest economic efficiency was 100% in provinces such as Khuzestan, Golestan, Tehran, and Qom. The average economic efficiency of wheat-producing provinces in variable returns to scale (VRS) condition is 77.3%.
Conclusion: Among 30 wheat-producing provinces, Khuzestan, Golestan, Tehran, and Qom simultaneously had the highest technical, allocative, and economic efficiencies at 100%, while Khorasan Razavi province had the lowest technical efficiency at 72.5%, and Sistan and Baluchestan province had the lowest allocative and economic efficiencies at 54.5% and 47.7% respectively. Considering the difference between the best and worst producers, it is recommended to provide a platform for successful provinces to share their experiences and methods with others. The results suggest that extension and agricultural service centers should organize educational and promotional classes to optimize the use of inputs, especially chemical fertilizers and pesticides. Land consolidation programs should be seriously pursued in each region to not only save on inputs such as labor and machinery but also reduce costs and utilize modern technology over large land areas. It is suggested to support applied research in the field of improving the management of input consumption in the production of irrigated wheat according to the climatic and socio-economic conditions of each region. This can be done by allocating research funds and motivating
Type of Study: Research |
Received: 2024/02/23 | Accepted: 2024/07/22
Received: 2024/02/23 | Accepted: 2024/07/22
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