technical efficiency

Seed is one of the most important agricultural inputs, which plays a key role in achieving optimal yield and quality of the product. Ever since mankind realized the role of the suitable seed in economic profit and food security, it has always made breeding efforts to provide cultivars with desired genetic characteristics. For the maximum effectiveness of other production inputs such as water, fertilizer and pesticides, access and use of new high-yielding and compatible cultivars is a necessity. In the present study, using the metafrontier frontier function, the technological gap ratio of certified seed of Hashemi rice variety was analyzed. The information of 531 farmers was used for the research. This information was obtained in 2018 using the cluster sampling method according to the size of the population. In this study, data envelopment analysis (DEA) model was used to estimate the technical efficiency relative to the group frontier, and the metafrontier method was used to estimate the technological gap ratio (TGR). The results of the frontier production function estimation showed that the technical efficiency for farmers who used certified seeds is 0.88 and for farmers who did not use certified seeds is 0.82. It means that these producers with a certain amount of inputs averagely produce about 88 percent and 82 percent of product respectively, which using the available input and the type of seed could be produced. The technical efficiency compared to the metafrontier production function was 0.82 in the group that used the certified seeds and 0.72 in the group that did not use this type of seed. The technological gap ratio for the above two groups was 0.93 and 0.86 respectively. In other words, farmers who used certified seeds had better technical performance and had a higher technological gap ratio. This is a promising point for policymakers in the agricultural sector that by promoting the use of certified seeds and taking necessary measures to encourage farmers to use this type of seed, the level of production can be improved.

This study was conducted to investigate the effective components in the fluctuations of the total factor productivity of rainfed wheat production with emphasizing the role of climate change in the important provinces that produce rainfed wheat in Iran.

For this purpose, a True Random Parameter Stochastic Production Frontier (TRP-SPF) Model was estimated using panel data and the obtained coefficients were used for calculating the proposed productivity index .

The results of estimation of True Random Parameter Stochastic Production Frontier (TRP-SPF) Model show that the variables of seed, pesticides, labor force, cultivated area, technological progress, square of air temperature, effective rainfall and square of effective rainfall have a significant and positive effect on the production of rainfed wheat while the air temperature has a negative and significant effect on the production of rainfed wheat. The results of calculating CATFP index of rainfed wheat show the existence of fluctuations in it. The analysis of the contribution of factors affecting changing the CATFP index showed that this index is mainly influenced by technological changes and then climate changes. After that, scale efficiency and technical efficiency are in the third and fourth places of influencing the CATFP index.

The purpose of this study is to estimate the environmental and technical efficiency of grape production in Bijar County. In this research, stochastic Frontier Analysis (SFA) method used to estimate input-oriented technical and environmental efficiency. Chemical fertilizer, pesticides and sulfur inputs were considered as environmentally detrimental inputs for estimating environmental efficiency. data were collected from 170 grape orchards at year 2018. The average technical efficiency (70%), shows that orchards under consideration can increase their efficiency up to 30%. The minimum and maximum technical efficiencies were 26% and 93%, respectively, which indicates a large gap (67%) between the efficiencies. While the average environmental efficiency is 92%, the lowest and highest efficiencies are 49% and 99%, respectively. Based on the results, it is possible to increase environmental efficiency on average by 8%. Due to the high average environmental efficiency of this grape orchards, it is concluded that environmental impacts of detrimental inputs were considered when using fertilizers and pesticides. So, encouraging these grape producers and introducing them to other producers can play a positive role in sustainable development in this county.

Energy consumption has increased directly and indirectly in the agriculture sector to meet the needs of growing population. Regarding the scarcity of production resources including energy, the present study aimed to measure the technical efficiency of rainfed wheat farms and its effective factors. For this purpose, the required data collected from 217 farmers in Ahar county and input and output (wheat) quantities converted to energy equivalents. The results of estimating the translog stochastic frontier production function along with the inefficiency function showed that the energy factors of labor, pesticides and machinery have a significant effect on output energy of wheat. Meanwhile, factors such as distance from fields to village, land slope, number of rainfed wheat farms and the cultivated land of wheat are affective on inefficiency use of energy. The mean of energy efficiency of wheat producers was 51%. Therefore, the output energy can increase by 49 % if efficient use of input energy and principal component of field operation followed. Considering the existence of suitable methods for improving energy efficiency is recommended with increasing information of farmers, holding extension courses and applying modern technologies

Honey is a healthy, nutritious and natural food that contains minerals, enzymes, and vitamins that give a person nutritious and organoleptic properties. It is produced on all five continents and its consumption varies from country to country due to cultural reasons and eating habits (FAO, 2022). Honey production in the world has increased from 771,114 tons in 1971 to 1,770,119 tons in 2020, with an annual growth rate of 1.84 percent (Knoema, 2022). Honey plays an effective role in ensuring global food security, and its market structure is dictated by its production efficiency. Given the limited resources of the agricultural sector, the optimal use of natural resources by improving technological efficiency in honey production would help ensure sufficient food for the increasingly growing world population (kavand et all., 2014; Hosseinzad & Koopahi, 1999). One of the factors affecting the efficiency of honey production is competitive and efficient markets. Therefore, the main objective of the present study is to determine the structure of the honey market in the provinces that produce this product and its relation to the technical efficiency of the producers.

This study uses the Herfindahl-Hirschman index (HHI) to study the market structure of honey-producing provinces in Iran. The Herfindahl-Hirschman index is calculated by squaring the market share of each competing production unit in the industry and then summing the resulting numbers. For this purpose, two different scenarios are considered. In the first scenario, the HHI was calculated based on the share of production of the counties and in the second scenario, it was calculated based on the number of apiaries in each county. To estimate the technical efficiency, the stochastic frontier Cobb-Douglas production function was used. For this purpose, first, the HHI values were considered as inefficient function variables and then the inefficiency function along with the Cobb-Douglas frontier function using maximum likelihood method was estimated and the technical efficiency values of the provinces were calculated. The data used in this study for 2019-20 have been obtained from the results of the census of Iranian apiaries. Excel2013 software was used to calculate Herfindahl-Hirschman index values and Stata15 software was used to estimate the Cobb-Douglas stochastic frontier production function.

Our findings show that the mean value of the Herfindahl-Hirschman index based on the first scenario in 2019 is 0.23 and in 2020 is 0.24. Therefore, Iran’s honey market during the studied years turns out to be monopolistic competition. The mean value of the Herfindahl-Hirschman index according to the second scenario for 2019 and 2020 was calculated as 0.16 and 0.17, respectively, which indicates that the country's honey market was competitive during the years under review. According to the results of Cobb-Douglas Stochastic frontier production function, inputs including; apiary, labor and hive have a positive and significant impact on honey production. The average efficiency during 2019-20 according to the first scenario is 61.2% and according to the second scenario is 64.2%. According to the first and second scenarios, it is possible to increase the efficiency by 38.8% and 35.5%, respectively. The results of the inefficiency function also confirmed that increasing the value of the Herfindahl-Hirschman index (i.e. increasing the degree of monopoly and distance from the competitive market) has a positive effect on inefficiency (negative effect on efficiency).

In conclusion, the results indicated that Iran’s honey market in recently years was has changed to monopolistic situation. This event has caused to decrease the efficiency of apiaries. So it can be possible to increase the efficiency of apiaries through stablishing competitive structure in honey market. In this case motivating for investment in modern production technologies and related industries can help to competitive circumstances in the honey market. market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency market structure and technical efficiency

Analyzing technical efficiency is particularly important in any economic sector, including the livestock industry and broiler production. By analyzing the efficiency of units, it is possible to help improve the use of resources and increase domestic production. Given the special importance of the livestock and broiler production industry in the country, it is necessary to analyzing technical efficiency and optimizing production in this area. Especially in Kurdistan province, which is one of the most important regions of broiler production in the country (3.8% of production in 2020), analyzing the efficiency and optimization of Arian race broiler production can be one of the solutions to increase domestic production and improve the country's economy. The current study aimed to assess the technical efficiency and identify the key determinants affecting the production of Arian broiler chicken in Kurdistan province using a parametric approach known as the Stochastic Frontier production function (SFP) method. 

The level of technical inefficiency within the studied units was estimated by applying the functional form of Translog and employing the maximum likelihood method. A proportional sampling technique was employed to select a sample of 21 broiler farms for the study. The selection of farms was based on a proportionate representation of the target population. Subsequently, comprehensive input-output data were collected through the administration of a structured questionnaire in the year 2021.This function has been estimated using the Ttranslog function form and with the help of the maximum likelihood method, and units have been investigated the main factors explaining the level of technical inefficiency of the studied. A proportional sampling method was used to select 21 broiler farms, and input-output data were collected by completing a questionnaire in 2021.

In this study, using the translog function, has been investigated the relationship between different variables and technical efficiency in the production of Arian broiler in Kurdistan province. The results showed that feed consumption, the number of hatchlings and the cost of medicine and health were important variables that had a direct and significant effect on the amount of meat production. In addition, the estimated technical efficiency at the farm level ranged from 43% to 90% with an average of 75%. This result indicates that the poultry farms of Kurdistan province have relatively high technical efficiency. Also, the evaluation of the factors related to inefficiency showed that among the seven investigated factors, the variables of age, experience of the poultry owner and the labor force, the length of the breeding period and the degree of mechanization of the units had a negative and significant effect on the inefficiency. The age and experience of the poultry owner, there were two of the most important influencing factors that were observed in this research.

Considering the importance of broiler feed in increasing efficiency and its high share of variable costs, measures to stabilize its price are essential. To do this, contract farming may help broiler farmers to reduce price fluctuations in the feed market. Additionally, in case of shortage, the government can intervene and regulate the feed market. Also, considering that the age and experience of the poultry owner are two important factors on production efficiency, designing appropriate training programs for them can help improve their experience and skills in broiler production.

Extension and education of farmers in the innovative use of production resources plays an important role in the optimal use of resources. The main purpose of this study was to compare the technical efficiency of wheat production between the provinces implementing the new agricultural extension system and other provinces in Iran. The required data were obtained from the Ministry of Agriculture's website for the period of 2015-2019 and their analysis was performed using data envelopment analysis method. The results showed that the mean of input-oriented technical efficiency under constant and variable efficiency in the provinces implementing the new agricultural extension system was 0.59 and 0.75 and in other provinces was 0.56 and 0.72, respectively. Also, the amount of technical efficiency under constant and variable efficiency in the provinces implementing the new agricultural extension system is 0.58 and 0.66 and in other provinces was 0.55 and 0.62, respectively. Since the technical efficiency of input-oriented in two group of provinces has been statistically different, it can be said that the implementation of the new promotion system has reduced the consumption of wheat production inputs. Considering the success of the implementation of the new extension system, it is recommended that the government pay attention to the implementation of this system in all provinces and not unilateral support for a limited number of specific provinces.

Among agricultural activities, aquaculture has shown the highest growth among food production sources in the last two decades. According to the F.A.O., aquaculture is the best supply of the maximum motivation for poverty alleviation. Uncertainty and risk in the aquaculture subsector, like other agricultural subsectors, are formed due to unfavorable weather conditions, the prevalence of diseases, and price fluctuations. Naturally, due to uncontrollable factors and risks, the efficiency of production units is expected to decline. Identifying sources of these risk in aquaculture activities is one of the key points for risk management. It is clear that risk can never be eliminated, but it can be managed by identification. Zanjan province is one of the major fish farming regions of the country and among them is the city of Mahneshan which accounts for about 65% of the total fish production of this province.

The purpose of this study is to the identification of risk management tools in fish farms and their effect on the technical efficiency of these farms in Mahneshan county. To this end, the stochastic frontier production function was applied and the required data were collected by surveying a questionnaire by stratified proportional random sampling from salmon farms in three-zone including Central, Angoran, and Oryad in Mahneshan county in 2020. In general, risk management strategies in the agriculture sector were divided into two categories: in-farm risk management strategy and off-farm risk management strategy. These two categories are classified into 8 risk management tools and then measured by the Likert spectrum. The Cobb-Douglas functional form was selected to estimate the stochastic frontier production function.

The results showed that among the in-farm risk management strategies, the selection technology with less risk tool is the most popular and the tool of the financing method is very common in the off-farm risk management strategies. In address to the comparison between In-farm and Off-farm’s risk management strategies, the fish farmers are more likely to use in-farm risk management strategies. The estimated results of the Cobb-Douglas production function showed that the total area of pools, number of baby fish, labor, and feed cost, Floating usage, and Aerator usage have a significant effect on fish production. According to the results, if the total pools area increases by one percentage, the frontier fish production will increase by 0.06 percentages, and if the number of baby fish increase by one percentage, the fish production will increase more than one percent. After estimating the frontier production function, the technical inefficiency model was estimated. The results showed that with increasing age, the technical efficiency rise and enhancing the participation to the fish training courses and being fish breeding as the main job, have a positive effect on the technical efficiency so that it improves significantly. Also, increasing the number of pools and being fish farming as the main job has a positive effect on the technical efficiency of farms. Regarding the impact of risk management tools on the technical efficiency of fish farms, it was observed that the technology selection with fewer risk tools has a negative impact, and the flexibility tools, and the use of marketing contracts tools have a positive effect on breeders' technical efficiency. So, by using these tools, the technical efficiency of the farms also increases. Finally, the technical efficiency of the farms was calculated and results revealed that about 50% of farms have an efficiency of more than 90%, and farms with a pool area of 1000-1500 square meters with 89% efficiency, have the highest technical efficiency.

The results showed that among the in-farm risk management strategies, the selection technology with less risk tool is the most popular and the tool of the financing method is very common in the off-farm risk management strategies. In address to the comparison between In-farm and Off-farm’s risk management strategies, the fish farmers are more likely to use in-farm risk management strategies. The estimated results of the Cobb-Douglas production function showed that the total area of pools, number of baby fish, labor, and feed cost, Floating usage, and Aerator usage have a significant effect on fish production. According to the results, if the total pools area increases by one percentage, the frontier fish production will increase by 0.06 percentages, and if the number of baby fish increase by one percentage, the fish production will increase more than one percent. After estimating the frontier production function, the technical inefficiency model was estimated. The results showed that with increasing age, the technical efficiency rise and enhancing the participation to the fish training courses and being fish breeding as the main job, have a positive effect on the technical efficiency so that it improves significantly. Also, increasing the number of pools and being fish farming as the main job has a positive effect on the technical efficiency of farms. Regarding the impact of risk management tools on the technical efficiency of fish farms, it was observed that the technology selection with fewer risk tools has a negative impact, and the flexibility tools, and the use of marketing contracts tools have a positive effect on breeders' technical efficiency. So, by using these tools, the technical efficiency of the farms also increases. Finally, the technical efficiency of the farms was calculated and results revealed that about 50% of farms have an efficiency of more than 90%, and farms with a pool area of 1000-1500 square meters with 89% efficiency, have the highest technical efficiency.

Given that producers use risk-reduction tools rather than transferring risk on farms and this also harms the technical efficiency, so it is recommended that in a progressive world to take advantage of modern production technology, a great facility should be provided.

The purpose of this study is to compare the experimental results obtained from estimating the technical and profit efficiency of rice farmers in Guilan province and determining the effect of efficiency improvement on pollution caused by overuse of chemical fertilizers in 2018-2019.

For analysis of technical and profit efficiency, the directional distance function has been used. Farms were classified into three groups according to region (east, center and west). Also, the farms were divided into 5 groups based on rice varieties (Hashmi variety, Ali Kazemi variety, Shiroudi variety, Jamshidi variety and Khazar variety). R, GAMS and Excel software were used in this study.

The results showed that improving the technical efficiency lead to the reduction of nutrients surplus discharged into the environment. But, the profit efficiency mostly increases the amounts of nutrients surplus discharged into the environment. Base on results, technical efficiency improvement reduces the amount of nutrients surplus discharged into the environment for Hashemi variety by 3.5 to 38.8 kg/ha, Ali Kazemi variety by 0.4 to 23.3 kg/ha, Jamshidi variety by 7.6 to 42 kg/ha, Khazar variety by 2.9 to 20.7 kg/ha and Shiroudi variety by 18 to 48.6 kg/ha.

If the rice farmers of Gilan province become technically efficient, this will lead to the reduction of pollution in all areas.  Considering that the excessive use of chemical fertilizers leads to the discharge of nutrients surplus into the environment, therefore encouraging rice farmers to perform soil test and optimum use of chemical fertilizers can lead to reduced pollution and increased technical efficiency.

Today one of the most important issues of human societies is the growing population of the world and the provision of healthy and sufficient food for this growing population. Due to the limited resources of agricultural sector, the most appropriate solution to increase production and income in the agricultural sector is the optimal use of inputs by improving efficiency and productivity. In addition, the level of technology is also one of the factors affecting productivity growth. Studies show that most of the people in the world, and especially developing countries suffering from scarce of protein, so animals protein has important role in humans health and life and its quality and amount must be optimal. The poultry industry is the one of the most important protein source. Identifying the components of total factor productivity (TFP) and examining its changes in the poultry industry during the production process leads to more efficient production and productivity growth. Moreover, improving the total factor productivity can save production resources.

The objective of this research is analyze the total factor productivity growth, technical efficiency and technological change in the Iranian poultry industry. This study uses data envelopment analysis (DEA) method and Malmquist index to calculate the total factor productivity changes and analyze its components as well as the technical efficiency of broiler production units during the study period. Based on output oriented approach, Malmquist TFP index decomposed into technical efficiency changes (Maximum output from minimal input quantities), technological changes (changes in technology that lead to an increase in productivity), pure efficiency changes and scale efficiency changes. The Malmquist TFP index measures the TFP change between two data points by calculating the ratio of the distances of each data point relative to a common technology. An advantage of the Malmquist TFP index method is that it does not require price data for the analysis. The data used in this study are information about the amounts of inputs used in the production of chicken meat, including poultry feed, labor and energy, as well as the amount of production of this product for the period 1996-2017 that are taken from the Statistics Center of Iran about 28 provinces. DEEp 2.1 software was used to measure and analyze the TFP index.

The results showed that the technical efficiency average under the assumption of variable return to scale was 0.796. This means that production units can increase their production by 20.4% without changing the amount of their consumption inputs. Only the provinces of East Azerbaijan, Isfahan, Bushehr, Kohgiluyeh and Boyer-Ahmad, Mazandaran, Markazi and Hormozgan have achieved full technical efficiency. The average of scale efficiency for the studied provinces was 0.901. The highest scale efficiency is (1.000) belongs to East Azerbaijan and markazi provinces; as well as Hormozgan province with value of 0.563 has the lowest scale efficiency among the studied provinces. The results as well as showed that annual average growth of total factor productivity in Iran broiler farms is 17.7%, which is different in provinces. Kermanshah province has the highest TFP equal to 0.461 and Yazd and Ghom have the lowest TFP respectively. Total factor productivity growth has been negative only in Kohgiluyeh, Boyer-Ahmad and Markazi provinces. The study of productivity components indicate that the technology change with an average value of 14.1% is the most important factor in term of increasing the productivity of broiler farms during the study period. Technical efficiency change with an average value of 3.2% is the second factor affecting of TFP growth. Pure efficiency change and scale efficiency change with the average values of 2% and 1.1%, respectively are in the third and fourth place in terms of impact on productivity.

The findings from the analyses are that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. In general, the development and promotion of technological symbols such as improved breeds, improve air conditioning, lighting and feeding systems can be considered to improve the total factor productivity. Also according to the findings poultry farms show a relatively large range to improve technical efficiency. Therefore, more efficient production methods, observance of educational and sanitary principles in order to reduce losses to improve technical efficiency seems necessary. Also low scale efficiency in some provinces is a serious problem and it is suggested to increase their efficiency by determining the optimal size of their performance. The findings from the analyses are that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. In general, the development and promotion of technological symbols such as improved breeds, improve air conditioning, lighting and feeding systems can be considered to improve the total factor productivity. Also according to the findings poultry farms show a relatively large range to improve technical efficiency. Therefore, more efficient production methods, observance of educational and sanitary principles in order to reduce losses to improve technical efficiency seems necessary. Also low scale efficiency in some provinces is a serious problem and it is suggested to increase their efficiency by determining the optimal size of their performance. The findings from the analyses are that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. In general, the development and promotion of technological symbols such as improved breeds, improve air conditioning, lighting and feeding systems can be considered to improve the total factor productivity. Also according to the findings poultry farms show a relatively large range to improve technical efficiency. Therefore, more efficient production methods, observance of educational and sanitary principles in order to reduce losses to improve technical efficiency seems necessary. Also low scale efficiency in some provinces is a serious problem and it is suggested to increase their efficiency by determining the optimal size of their performance