Agricultural Economics
Mahsa Ghasabi; Mahmood Haji Rahimi; Hamed Ghaderzadeh; Razieh Shankayi
Abstract
IntroductionAgriculture has always involved various degrees of risk, with farmers contending with numerous potential threats that can disrupt their livelihoods and productivity. These risks are compounded by agriculture's high dependency on climatic conditions, rendering it particularly vulnerable to ...
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IntroductionAgriculture has always involved various degrees of risk, with farmers contending with numerous potential threats that can disrupt their livelihoods and productivity. These risks are compounded by agriculture's high dependency on climatic conditions, rendering it particularly vulnerable to the adverse effects of climate change. Shifting weather patterns, extreme temperatures, and unpredictable rainfall can drastically affect crop yields, posing a serious threat to both farmers’ income and food security. Additionally, the agricultural sector faces ongoing challenges from pests, diseases, and fluctuations in market prices, further destabilizing the livelihoods of farmers who rely on steady production for economic sustainability.Beyond environmental factors, agricultural activities are influenced by a host of political, social, and economic risks. Environmental challenges, production limitations, legal constraints, financial hardships, and marketing uncertainties all represent significant risk categories that can impact farming operations. Natural disasters, such as floods, droughts, and storms, often lead to reduced productivity, directly diminishing farmers’ incomes. Furthermore, health and well-being concerns for farmers add another layer of risk, as labor-intensive farming activities require both physical resilience and long-term health, which can be compromised by lack of access to medical services and health risks associated with exposure to pesticides and other chemicals. As the global population grows, demand for food continues to rise, but the essential resources needed for agriculture, such as arable land and water, are finite. This increasing demand coupled with limited resources has placed substantial pressure on farmers, who must navigate these compounding risks while striving to meet production needs. These challenges underscore the need for effective risk management tools that can support farmers in making informed decisions regarding crop selection, resource allocation, and overall farm management strategies. One of the most versatile risk management tools available is the cropping pattern, or the arrangement of crops within a given agricultural area over a specific time period. Determining an optimal cropping pattern that takes risk factors into account is crucial for enhancing profitability and resilience in farming. Therefore, this study aims to determine the optimal cropping pattern for farms in the Dehgolan Plain, located in Kurdistan Province, under both risk-free and risk-sensitive conditions. By focusing on maximizing farmers' gross income while accounting for factors such as water availability and market conditions, this research seeks to provide practical recommendations for sustainable agricultural practices.Materials and MethodsThis study examines the cropping patterns of major crops cultivated in the Dehgolan Plain, Kurdistan Province, using data spanning the agricultural years from 2014 to 2023. To establish an optimal cropping pattern, the analysis considers various production constraints and resource limitations specific to this region. The goal is to develop a cropping model that maximizes gross income for farmers under both risk and no-risk scenarios. Several mathematical programming techniques were employed to achieve this objective. The Linear Programming (LP) model, widely used in agricultural studies for determining optimal cropping patterns under conditions of certainty, served as the foundation for this analysis. The LP model optimizes crop selection to maximize gross income while adhering to constraints such as water availability, land area, and resource limitations specific to the Dehgolan Plain. In addition to the LP model, nonlinear programming approaches, specifically Quadratic Programming and the Minimization of Total Absolute Deviation (MOTAD) model, were implemented to assess the cropping pattern under conditions of risk. These models allow for the incorporation of income volatility and risk into decision-making, helping to capture the trade-offs between risk and income potential. The Quadratic Programming model, which can handle non-linear relationships, is suitable for cases where increasing returns or diminishing marginal gains are present. Meanwhile, the MOTAD model assists in achieving minimum income variability, thus offering farmers a more stable income flow in unpredictable economic and climatic conditions.Results and DiscussionThe analysis revealed notable differences in the cropping patterns under risk and no-risk scenarios. Under no-risk conditions, as optimized by the Linear Programming model, the cropping pattern favored crops with higher gross incomes per hectare. This led to a significant reduction in the cultivation of wheat, barley, and potatoes, as these crops did not yield the highest economic returns. However, despite their relatively low profitability, wheat and barley remain essential for their lower water requirements and the security provided by government-guaranteed purchase programs. As a result, farmers may be reluctant to reduce the acreage of these crops due to their inherent risk-mitigation benefits. In the risk-sensitive scenario, modeled through Quadratic Programming and MOTAD, a positive correlation was found between risk levels and gross income. As farmers sought to maximize their income, the cropping pattern initially reflected a concentration of higher-income crops. However, as income maximization goals became tempered by risk considerations, crop diversity increased, indicating a clear trend toward diversification as a viable risk management strategy. This finding aligns with previous studies that emphasize crop diversification as a way to stabilize income and mitigate yield risks in agricultural systems prone to volatility. The MOTAD model, in particular, highlighted the trade-offs between risk and expected income. For example, a modest income increase of approximately 0.59% (from 1,700,000 million tomans to 1,710,000 million tomans) resulted in a substantial increase in risk, with the standard deviation, a measure of income variability, rising by 17.65%. This illustrates that achieving marginal income gains in agriculture often comes at a steep cost in terms of heightened risk. Furthermore, the cropping pattern varied significantly at different risk levels. At the highest risk threshold, which yielded an expected income of 1,780,133 million tomans, the cropping pattern included high-value crops such as cucumber, alfalfa, and canola, while reducing lower-value crops. Conversely, as the income expectation decreased and risk levels were minimized to 1,060,285 million tomans, these higher-income crops were scaled back, favoring more stable, government-backed crops like wheat, barley, and potatoes. This shift suggests that farmers, when presented with risk-reducing incentives, may gravitate toward crops with guaranteed purchase agreements and lower input costs, prioritizing stability over potential profit. Both risk models underscore the importance of balancing income maximization with risk minimization, as farmers seek to secure stable returns in an environment where crop failures or price declines could have significant impacts on household livelihoods.ConclusionRisk is an inevitable aspect of agriculture, and the findings of this study suggest that risk-sensitive models, such as MOTAD, enhance cropping pattern decision-making by incorporating income variability. The results demonstrate that under high-risk scenarios, increasing the cultivation area of crops like wheat aligns with government policies aimed at food security, as these crops provide a stable, government-supported income stream. This study also recommends adopting multi-cropping systems and crop rotation as effective strategies for reducing income variability and enhancing resilience. By diversifying cropping patterns, farmers can manage risk more effectively and contribute to the long-term sustainability of agricultural systems in regions like the Dehgolan Plain, where climate, market, and resource limitations impose unique challenges. Future studies could build upon these findings by examining the impact of additional risk factors, such as climate projections and market trends, to further refine optimal cropping strategies for vulnerable agricultural regions.
Agricultural Economics
H. Fouladi; H. Amirnejad; S. Shirzadi Laskookalayeh
Abstract
IntroductionIn recent decades, the issue of climate change has become one of the global issues and has affected the agricultural sector. The continuation of agriculture regardless of the water shortage crisis has had an inappropriate effect on the sustainability and growth of this sector. On the other ...
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IntroductionIn recent decades, the issue of climate change has become one of the global issues and has affected the agricultural sector. The continuation of agriculture regardless of the water shortage crisis has had an inappropriate effect on the sustainability and growth of this sector. On the other hand, the destructive effect of excessive use of chemical fertilizers and pesticides on water, soil, health of ecosystems, humans and other living beings is undeniable. For this reason, the void of using an efficient model that can provide all economic and environmental aspects at the same time was completely felt. The aim of this study was to provide an optimal cropping pattern using the integrated method of Goal and Grey planning. For this purpose, the farmers of the agronomy sub-sector of Tajan Basin were selected as the statistical population. In this regard, time series information was collected from the aggregation of the average data of 401 settlements located in this area during the years 2017-2021 from the annual reports of experts. Materials and MethodsThe Linear Programming (LP) Model quantifies an optimal way of integrating constraints to satisfy the objective function to optimize crop production and profits for irrigation farmers. To use LP, one must convert the problem into a mathematical model. To do this, an objective such as maximizing profit or minimizing losses is required. The model must also include decision variables that affect those objectives, and constraints that limit what user can do. Therefore, the LP Model is a single-objective method. Goal Programming (GP) is an extension of LP in which targets are specified for a set of constraints. GP is used to perform three types of analysis: Determining the required resources to achieve a desired set of objectives. Determining the degree of attainment of the goals with the available resources. Providing the best satisfying solution under a varying amount of resources and priorities of the goals. Thus, the GP model is a multi-objective method. The Grey system theory is identified as an effective methodology that can be used to solve uncertain problems with partially known information. Grey modelling approach uses accident data for estimating the model parameters. The model can reflect the dynamics, balance the conflicting the multidimensional targets of cropping patterns, and promoting the sustainable use of cultivated land. For achieving different goals in unstable economic and environmental conditions, we used a Goal-Grey model that was obtained from the integration of Goal programing and Grey Programing. The Goal-Grey model, by considering the uncertainty in the data, leads to overlap between the economic and environmental goals and provides the scope of cultivation for the selected products. Results and DiscussionBy estimating the Linear Programming (LP) Model, crops like wheat and canola are removed from the cropping pattern, while the cultivation areas for barley and high-yielding long-grain rice increase by 644% and 31%, respectively. In contrast, the cultivation areas for high-quality long-grain rice and maize decrease by 89% and 10%, respectively. Implementing this model boosts the gross profit of farmers in the Tajan region by 14% solely through adjusting the crop composition, without altering the current input levels. Additionally, the findings show that applying the LP Model results in fertilizer savings of 5%, 13%, and 10% for phosphate, nitrogen, and potash, respectively. The amount of herbicide and fungicide consumption in the LP Model is exactly equal to the current model of the region. However, the implementation of this model will lead to a 5% increase in the consumption of insecticides poison. The amount of irrigation water consumption in the LP Model was calculated to be 2% less than the current model of the region. In addition, the results indicate that by estimating the Goal-Grey Model, only canola is removed from the cropping pattern. Also, in order to achieve the defined goals in this study, the cultivation area of wheat and maize should be equal to 208 and 7356 hectares respectively. However, the flexibility of input usage enables adjustments to other crop cultivation areas, facilitating high-quality long-grain rice production on 970 to 18,157 hectares. Plus, the cultivation area of long-grain rice can vary from 7654 to 9995 hectares. In this model, barley can be removed from the crop composition like the linear pattern or cultivated on a maximum of 2553 hectares. The implementation of the Goal-Grey model will lead to a maximum 2% increase in the gross profit of the farmers of Tajan region compared to the current model of this region. Also, by implementing the Goal-Grey Model, on average, phosphate, nitrogen, and potash fertilizer consumption is saved by 16, 27, and 20 percent, respectively. In addition, with the implementation of the Goal-Grey Model, the consumption of agricultural pesticides will decrease from 733 to 355 thousand liters on average. ConclusionThe LP Model is designed based on current regional conditions; however, as a single-objective model with fixed parameters, it lacks the flexibility to offer an adaptable program for farmers during drought or wet periods or when inputs are limited. Findings indicate that under current conditions, there is excessive use of chemical inputs and irrigation water. By accounting for data uncertainty, the Goal-Gray model addresses these limitations, balancing economic and environmental objectives and defining a cultivation range for selected crops. Acknowledgement We are grateful to the experts of agronomy management and plant conservation management of Mazandaran Province Agricultural Jihad Organization and Sari City Agricultural Jihad Management who cooperated in data collection. This article is taken from the preliminary results of a doctoral dissertation with material and intellectual rights related to Sari Agricultural Sciences and Natural Resources University, which is gratefully acknowledged.
Agricultural Economics
P. Sarani; A. Shahraki; S.A. Banihashemi
Abstract
IntroductionThere is no doubt that the Covid-19 pandemic has had numerous adverse impacts on every aspect of human existence. In times of crises like epidemics throughout history, ensuring a sufficient food supply has always been a crucial concern. Given that the agricultural sector plays a vital role ...
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IntroductionThere is no doubt that the Covid-19 pandemic has had numerous adverse impacts on every aspect of human existence. In times of crises like epidemics throughout history, ensuring a sufficient food supply has always been a crucial concern. Given that the agricultural sector plays a vital role in the food supply chain and maintaining sustainability in this sector is essential for food security, this study aims to identify and prioritize the factors that influence the sustainability of the agricultural supply chain, specifically focusing on the wheat crop, during and after the Corona era. Materials and MethodsBased on the research background, the factors that impact the sustainability of the agricultural supply chain were determined. In the agricultural sector, like previous studies on supply chain sustainability, the study focused on the three dimensions of sustainability: economic, social, and environmental. However, experts suggest that the study is more centered on these three dimensions, which are particularly significant in the agricultural industry. By utilizing the Fuzzy Delphi method, 28 sub-criteria related to these hidden sustainability variables were identified. The Fuzzy DEMATEL method was then employed to examine cause-and-effect relationships and the interaction between criteria. Finally, the Fuzzy method was used to determine the degree of importance and weight of these criteria. Results and DiscussionTo achieve sustainable agriculture, research centers should prioritize the necessary research in this field, as highlighted by Sharghi et al. (2010). Farmers who possess more information about sustainability have been found to have more sustainable farms, confirming a direct correlation between these two factors (Afrous & Abdollahzadeh, 2011). The outcomes of the present study align with previous research, demonstrating that the level of attention given by research organizations to required research on sustainability is the most influential criterion within the causal group of sustainable procurement with a weight of 3.34, it holds the highest importance in the ranking according to the SWARA method. Updating and sharing information in DEMATEL's method has the fourth highest impact on other factors in the cause-and-effect group. However, in the SWARA's method was found to be the second most important factor, with a weight of 0.2403. Another study confirmed that the three main limitations of sustainable wheat production are the farmers' limited knowledge, lack of approved and resistant seeds, and inadequate management systems, especially for weeds. The use of local suppliers, specifically utilizing stored seeds from farmers, can lead to the spread of diseases and an increase in weed populations (Husenov et al., 2017). The proliferation of weeds leads to the squandering of production resources and a decrease in production levels. The most impactful factor for the sustainability of the wheat supply chain, as determined by the causal group, is the requirement of collaborating with an ISO-certified supplier. This criterion holds a significant weight of 0.4915 and is essential for achieving sustainable supply and design. Recognizing the significance of this criterion is crucial to enhance production and mitigate the risk of potential diseases. However, farmers, due to the expensive cost of modified seeds, resort to utilizing seeds from their previous crop. Based on the Fuzzy DEMATEL method, water consumption management ranked fifth among the criteria that influence other criteria. However, according to the Fuzzy SWARA method, it ranked second with a weight of 0.251. With water resources being scarce in the region, it is crucial to use water efficiently and prevent wastage, as this will positively impact productdid not support the significance of stopping gray marketing of products. According to experts, this study determined that the most effective criteria for the causal group in stabilizing the agricultural supply chain of wheat products during the Covid-19 era is to stop gray marketing. This criterion received the highest degree of importance, with a weight of 0.4469, in the dimension of sustainable distribution.Imports decreased because of the restrictions and quarantine measures, which led to a shortage of seeds for crops like wheat that relied on imports. Social distancing measures also caused a shortage of labor in agriculture, leading to a significant reduction in farming activities. By focusing on supply and sustainable design during epidemics and crises, there is an ability increased to manage the supply chain and positively impact other aspects of production sustainability. ConclusionBased on the results obtained, increasing farmers' awareness, and utilizing approved seeds can prevent resource wastage and enhance the stability of the supply chain. Additionally, reducing gray market activities can contribute to the supply chain's stability and ultimately enhance food security. Effective management of water consumption is also crucial for ensuring the sustainability of the supply chain, particularly due to the water scarcity crisis in the region. Enhancing the stability of the supply chain not only facilitates resilience during crises like Covid-19 but also promotes self-sufficiency in producing agricultural products essential for Iranian households, including wheat, which is a fundamental necessity.
Agricultural Economics
M. Mirchooli; M. Ghorbani; M. Sabouhi Sabouni
Abstract
IntroductionThe dependence of agriculture on environmental conditions has caused the activity in this sector to face natural and unnatural risks. After several years of agricultural insurance activity in Razavi Khorasan province, most of the pistachio farmers are not insured. Drought insurance is one ...
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IntroductionThe dependence of agriculture on environmental conditions has caused the activity in this sector to face natural and unnatural risks. After several years of agricultural insurance activity in Razavi Khorasan province, most of the pistachio farmers are not insured. Drought insurance is one of the methods that has become important to cover the risks of drought and lack of water resources in order to compensate part of the gardeners' losses. The main issue from a managerial perspective is risk management. The use of agricultural insurance, which is one of the risk management tools, will ensure financial security and stability for farmers. Given that insurance is a tool for risk management, and given the uncertainty and risks of climate change in agriculture, insurance can be a very adaptable tool to water scarcity. Agricultural insurance is considered as a useful and appropriate solution to deal with natural hazards. . Drought insurance is an important factor in off-farm drought risk management that can mitigate the effects of this inevitable phenomenon. Insurance as one of the risk management tools can increase the risk-taking of farmers and, consequently, increase the sense of security in farmers, the necessary ground for proper and efficient use of factors of production and investment in the use of new technology and thus increase productivity in agriculture provide. The effects of water scarcity can be summarized as follows; Loss of production and income, abandonment of busy crops (with high water demand) and decline in agricultural employment, on the other hand, intensifies the over-exploitation of groundwater aquifers, which has tempted many farmers to do so meet your water needs. Access to water in the study area is one of the important variables affecting pistachio yield and quality as well as the survival of pistachio trees. This variable directly affects the profitability of producers and gardeners may suffer losses from this vital input. For this reason, gardeners' behavior in relation to regular pistachio insurance can affect access to water and make more farmers inclined to drought insurance. Materials and MethodsThis research seeks to answer the question that with 5% reduction in available water, pistachio growers in Sabzevar city, whether these people are willing to accept pistachio drought insurance or not, and if so, what is the extent of this desire. The Probit pattern is one of the most suitable econometric patterns for censored observations. This model was first proposed by Tobin (1958) to estimate the demand for durable goods. Subsequently, Arab Mazar and Schmidt (1979), Brown and Mufit (1982), Madela and Nelson (1982), and Hard (1975) worked on and developed the model, validating its high capability. This pattern was named by Goldberger (1964) as the Tobit or Probin Tobin model. Assume that y is the level of activity or action desired and xi are factors that generally affect the level of activity or action in question, namely:Also assume that one group of the observed observations performs the desired activity and the other group (the rest) does not perform the desired activity. As mentioned earlier, the values of xi and yi are visible for the first group. While for the second group only xi values are available and yi values are zero.In Hackmann's proposed two-step method for estimating the Tobit model, it is assumed that one set of variables may influence the decision to participate in the activity and another set of variables may affect the amount of activity performed after the decision is made. Therefore, two different sets of variables can be included in the Probit model, which are not necessarily barriers to aggregation. Therefore, two different sets of variables can be included in the Tobit model, which are not necessarily barriers to aggregation. Because it does not have a one-step model of this flexibility, it assumes that the variables influencing a person's decision to engage in an activity are the same as the variables that determine the amount of activity, if this is not necessarily the case. Hackman's two suggested steps are:Step 1: In the first step, the variables that affect the decision of gardeners in accepting pistachio drought insurance are identified and placed in a model with a binary dependent variable (zeros and ones); This means that the positive values of the dependent variable that indicate the tendency to accept pistachio drought insurance become the number one, and the dependent variable that does not tend to accept the drought insurance is set to zero. The number one means the decision to perform the activity and zero means the non-performance of the activity. At this stage, in order to identify the factors influencing the individual's decision, the Probit Model is used and estimated by the maximum likelihood method. The first step is to create a new variable inverse of the Mills ratio to enter the second step. In other words, this variable is the first and second stage communication bridge.Step 2: In the second stage, the measures affecting the willingness to participate in drought insurance after the decision is made along with the inverse Mills ratio variable are placed in a classical regression model. The dependent variable in the second stage is the amount of garden area likely to be allocated to drought insurance.Reasons to use the Tobit model: Many econometric models face two types of errors, either due to the use of specific observation data or due to the structural features of the models: first, the error due to incorrect sample selection, which usually occurs in using classical regression models, and second, the same error Assuming effective variables in the decision stage and the amount of activity performed after the decision is made (decision and action or intention and action), which usually occurs in regression models with binary and multiple responses. The Tobit model has been developed to prevent the occurrence of these two types of errors in studies.The first error is the error of incorrect sample selection; in the sense that in many econometric models, information is obtained only from observations that have acted on the activity and omits observations that have refused to do that activity. Therefore, these models are not able to assess the reaction of observations that did not act on the independent variable changes. Tobit model (type one) solves this problem in terms of observations that have performed the desired activity as well as other observations. Under these conditions, the effect of changes in independent variables on both the total observations and on the observations of the activity can be calculated separately.The second error means that the factors that influence a person's decision to perform an activity are not necessarily the same as the factors that determine the amount and level of activity desired, and can be two different sets of variables. The Tobit model (type two, Hackett or Hackman two-stage) solves this problem by separating the factors influencing the decision and the amount of activity. Results and DiscussionThe data show that the response of pistachio growers to the reduction of available water in the next 2 and 5 years is that all gardeners will insure their pistachio orchards with a 5% reduction in available water, but in terms of area under cultivation, only 39% Gardeners will increase their arable land in the next 2 years and 33% of gardeners in the next 5 years. The reaction of gardeners who did not have a history of pistachio insurance to accept pistachio insurance and increase or decrease the area under pistachio orchard in exchange for a 5% reduction in available water in the next 2 and 5 years shows that about 51% of gardeners face a 5% reduction in water in 2 And in the next 5 years, they will insure their pistachio orchards, and about 60% of gardeners will increase their cultivation in the next 2 or 5 years in the face of a 5% reduction in available water. The results of the evaluation of gardeners' reaction to the continuation of the horticultural profession in the face of a 5% reduction in available water in the next 2 years will cause 34% of gardeners not to continue this profession and 51% of gardeners will not continue this profession in the next 5 years. In the long run, water shortages can reduce the incentive for gardeners to grow pistachios. The reaction of gardeners to pistachio insurance against the reduction of available water quality shows that only 1.38 percent of the total population in the face of reduced quality of available water reduce the level of their insured garden and about 30% of them faced with declining available water quality, they will increase the level of their insured garden; And the rest of the gardeners (about 68.6%) do not change their insured level in the face of declining water quality.ConclusionAccording to the obtained information, the variables as gardener's age, ownership, relationship between gardener's field of study and agriculture, location, variety of cultivation, existence of insured pistachio garden in the neighborhood, frequency of risk, total water available to each gardener and garden life of each gardener in the first stage (Probit Model) have positive coefficients; which indicates the positive effect of these variables on the probability of willingness to accept pistachio drought insurance. In the second stage (linear regression), the variables of pistachio horticulture history, frequency of risk, garden life and total number of water hours available to gardeners have positive coefficients, which indicate the positive effect of these variables on the dependent variable of the second stage, is the tendency to accept pistachio drought insurance.
Agricultural Economics
N. Seifollahi; R. Mohammadkhani
Abstract
The lack of a comprehensive information system and application model in the supply chain of agricultural products in Iran has caused this part of the country's economy to be ineffective despite its potential.Therefore, the aim of the current research was to investigate the Barriers against the orchards ...
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The lack of a comprehensive information system and application model in the supply chain of agricultural products in Iran has caused this part of the country's economy to be ineffective despite its potential.Therefore, the aim of the current research was to investigate the Barriers against the orchards production chains in Meshginshahr located at Ardabil province, Iran. To reach the aim of the study, the semi-structured interviews were used to collect research data from 16 interviews including farmers, faculties and managers in the field of farming production chains. Then we analyzed the data by applying the Strauss and Corbin method and the paradigm model through Max QDA software. Sampling was theoretical sampling and was done using targeted and snowball methods. Based on that, 16 interviews were conducted with gardeners, university professors and managers in the field of Barriers to the development of agricultural production chains. The open codes included 38 concepts and the core codes also included 44 major categories, which were finally identified into four groups of selective categories including Barriers to i) product production; ii) input supply; iii) product distribution; and iv) customers . Based on the findings of the research on the risk of supply of input resources, the weakness of regulations and rules in supply of inputs, production information barriers, strategic production barriers, competition barriers in production, environmental risks, planning-management, financial-credit, technical-technical barriers, Product distribution cost barriers, lack of regulations in the distribution system, and sales barriers; Barriers related to the production sector are of the Barriers to the development of production chains of agricultural products. Barriers related to the production sector are one of the Barriers to the development of production chains of agricultural products.
Agricultural Economics
H. Shabanali Fami; S.M.S. Teymoori Sendesi; N. Motee; M. Motaghed
Abstract
Introduction
In order to meet the increasing demands of the growing population, it is essential to boost rice production. This not only ensures food security but also helps maintain environmental well-being. To achieve these goals, it is crucial for crop management research to focus on increasing rice ...
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Introduction
In order to meet the increasing demands of the growing population, it is essential to boost rice production. This not only ensures food security but also helps maintain environmental well-being. To achieve these goals, it is crucial for crop management research to focus on increasing rice yields while minimizing water usage. In Iran, particularly in the Rudbar region, recognizing the significance of rice cultivation in agriculture is of utmost importance. To improve rice field management, various aspects such as water and soil resource management, pest and disease control, nutrition management, sales and marketing strategies, human resources and social capital management, as well as technical and agricultural improvements need to be addressed. Therefore, the aim of the present study was to identify more effective methods for managing the rice fields in Rudbar county, Iran. Materials and Methos Initially, the researchers conducted a comprehensive analysis of available national and international databases to gather background information for the study. This analysis aimed to establish an initial list of components that could contribute to improving the management of rice fields. The statistical population of the study consisted of all 850 rice farmers in Rudbar City. Using the Karjesi-Morgan table, a statistical sample size of 265 participants was estimated, which corresponded to the size of the population. Eventually, 252 questionnaires were collected after distributing them to the participants, resulting in an 88% response rate. The opinions of faculty members from Tehran University's Department of Agricultural Management and Development were sought to assess the content validity of the questionnaire which was finally confirmed. To assess the reliability or internal consistency of the questionnaire, Cronbach's alpha coefficient was calculated for each of its components. All coefficients were found to be above 0.7, indicating good reliability of the study tool. The data obtained from the questionnaires was subjected to statistical analysis using the LISREL 8.8 software. A confirmatory factor analysis model was applied to examine the data. The reliability of the indicators loaded on each structure was evaluated using the t statistic. Indicators with values exceeding the critical limit of 1.96 were considered to have the required precision for measuring the relevant structure. Additionally, significant factor loadings were determined by extracting values greater than 0.5 from the factor loadings. It is important to note that Cronbach's alpha (with values higher than 0.7) was utilized to assess the reliability of the constructs.
Results and Discussion
The research findings highlighted several significant factors that have a substantial impact on improving the management of rice farms. These factors encompassed various aspects, including water and soil management, human resources and social capital, nutrition management, pest, disease, and weed management, technical and agricultural management, as well as sales and marketing management. Regarding water and soil management, the study emphasized the importance of optimal application of water resources, consideration of water quality, sediment control, and prevention of toxins and sewage from entering rice fields. Given the submerged nature of some rice stalks and the perpetually swampy conditions of rice fields, it is crucial to ensure the quality of incoming water and prevent the presence of mud and sediments. In terms of nutrition management, the research findings stressed the significance of using fertilizers effectively to enhance rice productivity. This involved post-planting strengthening, adherence to appropriate fertilizer consumption guidelines, and the utilization of plant and animal residues. Nutrition management, along with pest and disease control, played a vital role in successful rice field management. Another factor contributing to effective rice field management was the control of pests, diseases, and weeds. The study highlighted the benefits of employing an integrated approach to manage rice plant diseases and pests, which yielded better outcomes. The research findings also emphasized the role of technical and agricultural management in enhancing rice field operations. This included the use of transplanting machinery and improved seeds, mechanization of cultivation activities, and the application of fertilizer spraying machinery. These measures underscored the need for innovation in rice fields, emphasizing the importance of mechanization and the utilization of modern agricultural instruments. It was recommended that rice producers embrace technological advancements to optimize their technical and agricultural practices. Furthermore, the management of human resources and social capital played a significant role in rice field management. This encompassed fostering the growth of social capital, enhancing knowledge and skills, and utilizing mass media for skill and career development. The findings suggested that increasing cooperation, trust, and organization among rice farmers could be a strategy to revive social capital and enhance management practices. Lastly, the study highlighted important features of rice sales and marketing, such as employing an appropriate distribution system, excluding profit-seekers from the marketing cycle, and establishing regular customer relationships. Overall, the research findings emphasized the importance of addressing various factors, including water and soil management, nutrition management, pest and disease control, technical and agricultural management, human resources and social capital, as well as sales and marketing management, in order to effectively manage rice fields. Implementing these strategies would contribute to improved productivity and sustainable management practices in rice cultivation.
Conclusion
The findings of the study indicated the significance of several measures to improve the management of rice fields. These measures included the utilization of additional fertilizers and adherence to fertilizer usage guidelines, as well as the adoption of mechanized planting and harvesting equipment. It was also recommended to provide skill training programs for rice farmers and introduce online marketing platforms to facilitate the sale of rice. Furthermore, the study highlighted the importance of establishing specialized communication channels and implementing a contract system for rice production and sales through dedicated local organizations. This approach would ensure efficient coordination and enhance the management of rice fields. Additionally, private businesses were recognized for introducing new technologies, while the government played a crucial role in providing the necessary infrastructure and platforms to support rice field management. Improving the skills of rice farmers, especially in terms of market innovations, was identified as a key factor in enhancing the management of rice fields. This aspect should be considered alongside institutional and policy-making advancements to ensure comprehensive improvements in rice field management.
Agricultural Economics
P. Rezaie; A. Mahmoudi; T. Sharghi
Abstract
Introduction One of the basic needs of the people is to meet food security. Reports indicate that global demand for agricultural goods will increase over the next decade, with a large share of this demand occurring in developing countries. The importance of poultry products in the human diet is ...
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Introduction One of the basic needs of the people is to meet food security. Reports indicate that global demand for agricultural goods will increase over the next decade, with a large share of this demand occurring in developing countries. The importance of poultry products in the human diet is significant because the supply of animal protein in the diet is a key criterion in ensuring food security in society. In fact, poultry is considered one of the most widely consumed protein-rich foods in our country today due to its high production rate, its availability throughout the year and its importance as a white meat. Therefore, considering that East Azerbaijan province, as one of the main center of the poultry industry, has the third place in the closure of broiler chickens compared to the total among the provinces of the country, so this study examines the situation of the poultry industry using chain theory Porter Value aims to analyze the value chain activities of poultry products in order to identify challenges and inadequacies in creating a competitive advantage in East Azerbaijan Province. The value chain of poultry products was based on five components of poultry feed production: mother poultry farms, incubators, laying hens and broiler farms.Material and Methods The statistical population of this study was 63 experts, specialists and poultry industry experts. Due to the limited number of the statistical population, the census method was used to collect data. Data were collected through a questionnaire in 2021, validity was confirmed through a panel of professors and experts in the poultry industry in the province and the reliability of the instrument was assessed through a pilot test. Cronbach's alpha coefficient was obtained from 0.701 to 0.833, which indicates acceptable reliability. SPSS22 and SmartPLS3 software were used for data analysis. Also, in order to level the descriptive findings in terms of low, medium and high levels, ISDM index was used.Result and DiscussionThe average level of activities within the entire chicken value chain in East Azerbaijan province, excluding poultry feed production, was found to be predominantly low and moderate. Specifically, in mother hen farms, the highest frequency (39.7%) was at the low level, followed by the moderate level (38.1%). In the hatchery unit, the highest frequency (41.3%) was at the moderate level, while the poor level accounted for only 7.31%. For broiler farms, the highest frequency (41.3%) was at the moderate level, with 33.3% at the poor level. Similarly, in laying hen farms, the highest frequency (44.4%) was at the moderate level, and the poor level accounted for 31.7%. Only in poultry feed production was the level estimated to be good (36.5%) or moderate (33.3%).Furthermore, significant relationships were observed between certain components of the chicken value chain. Specifically, there was a direct, positive, and significant relationship between poultry feed production factories and laying hen farms. Similarly, the hatchery unit component showed a direct, positive, and significant relationship with laying breeding farms. However, the component of broiler farms did not demonstrate meaningful and effective integration within the provincial-level broiler chicken production. This was due to the lack of significant relationships with the poultry feed production factories and hatchery unit components. Experts in mother poultry farms highlighted weaknesses in government protection policies, inadequate knowledge in feed control, and a lack of research focused on creating favorable conditions for consistent chicken production. These challenges indicated significant obstacles in terms of manpower training, effective research, government support, and optimal production within these units. The analysis of the chicken value chain revealed that only two out of six defined paths showed significant positive relationships: the path between poultry feed production units and laying hen farms, as well as the path between incubation units and laying hen farms. However, the other paths within the chicken value chain, which are expected to play significant roles, did not demonstrate significant positive relationships due to their low and moderate levels. This indicates the existence of challenges within the chicken value chain in East Azerbaijan province.Conclusion The results showed that the components of the chicken value chain in order to create a competitive advantage face serious challenges in the implementation of the main activities and support; So that the level of main activities and support of most of the components involved in this chain was medium and low, and this situation cannot create a competitive advantage for the industry. Considering the key role of support activities on the main activities of each component in the chicken value chain, it is suggested that the necessary measures be taken to strengthen and improve staff training, especially in hen farms, as well as applied research programs. Focus on the research policies of the poultry sector of East Azerbaijan province to respond to the changes in the technologies required by the broiler industry and the pathology of the causes of weakness in the use of technology.
Agricultural Economics
M. Mardani; A. Abdeshahi; F. Yavari; F. Naghibeiranvand
Abstract
Introduction: The cultivation of edible mushrooms is expanding rapidly due to its nutritional and medicinal values as well as its economic benefits. However, lack of knowledge and principled management may cause many problems for producers or even bring them closer to the bankruptcy brink. The first ...
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Introduction: The cultivation of edible mushrooms is expanding rapidly due to its nutritional and medicinal values as well as its economic benefits. However, lack of knowledge and principled management may cause many problems for producers or even bring them closer to the bankruptcy brink. The first step to improve the efficiency of units is finding an appropriate method to measure it. Data Envelopment Analysis (DEA) is one of the methods that is widely used to evaluate the relative efficiency of a homogenous set of DMUs. Despite the many advantages of this model, the high sensitivity of DEA to even a small change in the data reduces the validity of its results. In fact the conventional DEA assumes that input and output data are without any deviation. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. So In this paper, to deal with uncertainty in data the linear robust optimization framework of Bertsimas and Sim (2004) was used to compare technical efficiency of Iranian mushroom-producing provinces and determine the optimum use of inputs.
Materials and Methods: According to the purpose of this study, a robust data envelopment analysis (RDEA) model with imprecise inputs and outputs was used. The method is based on the robust optimization approach of Bertsimas and Sim (2004) which with the introduction of the conservative parameter (Γ) for each constraint, adjusts robustness in an optimisation model against the level of conservatism of the solution. The value of Γ is dependent on the maximum probability of constraint violation (p) and numbers of uncertain data in every constraint (n). So this RDEA model allows adjustment of level of robustness of the solution to trade-off between protection against constraint violation and conservatism of efficiency scores. In order to estimate the models, the GAMS software was used and related data was gathered from Statistical Center of Iran.
Results and Discussion: In this paper to distinguish the causes of technical inefficiency, pure technical efficiency and scale efficiency were measured. According to the results of this model, at all levels of P, the pure technical efficiency was higher than the scale efficiency and technical efficiency, and its value was higher than 98% in all cases. This indicates that mushroom producers have a high level of knowledge and skills in this field and shows that the cause of low technical efficiency of the producers is their non-optimal scale. In addition, according to the results of both RDEA and DEA models, the most important input that has caused the inefficiency of the units is the "seed cost" input and with optimal use of this input, the cost of that can be reduced by about 70% (in ε=0.1 and P=1). Another result of this study is that with the reduction of the Probability of constraint violation, the rate of technical efficiency has decreased. For example in ε=0.1, if P is reclined from 1 (no protection against uncertainty) to 0.8 and 0.1, the average technical efficiency is reduced from 93% to 89% and 85% respectively. Also when ε is increased from 10 to 20 and 30 percent (in P=0.1) the average technical efficiency is reduced from 85 to 83 and 82 percent. On the contrary by reducing P, the percentages of reduction compare to the actual value is increased. For instance by reducing P from 1 to 0.8 and 0.1 the percentages of reduction of "seed cost" are decreased from 70% to 78% and 80% respectively. This results highlights the importance of using RDEA models to more conformity of the results to the real world.
Conclusion: Based on the results the low technical efficiency of the producers is because of their non-optimal scale. Therefore, it is recommended to consider the optimal size unit for those who want to enter this activity. On the other hand, the policymakers should improve access to facilities so the small units could enlarge their unit if it's necessary. Also considering the experience of successful mushroom farms, self-reliance in production of mushroom seeds can greatly reduce inefficiency of the units. Eventually considering that the level of uncertainty has a great impact on the efficiency results and the optimal level of inputs, future researches on the appropriate level of uncertainty according to the real conditions of production can improve the results of the RDEA model.
Agricultural Economics
F. Fathi; E. Ghorbanian
Abstract
Introduction: Iran imported 9 million tons of corn, from Switzerland, Emirate, England and, Netherlands in 2017 so these regions are now the major sources of corn import for Iran. Among the multiple risks, Iran's corn imports encountered systematics and unsystematic risk. Systematic risks are the risks ...
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Introduction: Iran imported 9 million tons of corn, from Switzerland, Emirate, England and, Netherlands in 2017 so these regions are now the major sources of corn import for Iran. Among the multiple risks, Iran's corn imports encountered systematics and unsystematic risk. Systematic risks are the risks carried by entire assets within a system and cannot be diversified. They are also called non-diversifiable risks, beta risks, and market risks. Specific risks are risks that are unique to an individual asset. In a portfolio, specific risks can be mitigated by using a diversification strategy. Terms or phrases which can be used conterminously with specific risks are diversifiable, unique, unsystematic, or idiosyncratic risks. International price fluctuation and internal policy comprise the risk of Iran's corn imports. Risk specification and management of Iran's corn imports are important since corn, as an input of livestock production, makes the risk of these industries and hence the price of red meat and poultry. The corn imports systematic risks refer to the risks caused by global corn price fluctuations. The systematic risks usually result from the unpredictable fluctuation of global corn demand or a concerted action taken by major corn exporters. All corn importing countries are liable to these risks. Global corn prices fluctuate when the global consumption of corn grows quickly and an imbalance of supply and demand ensues. Worldwide fluctuation is the risk brought about which cannot be avoided by diversification; all the corn importing countries will be affected by this risk. The specific risks to corn imports refer to the risks resulting from corn exporting countries. When a corn exporting country stops its exports due to the policies, climate, production decrease as a result of disease and the other production risk, or other factors, it will bring losses to the corn importing countries. These failures result in a specific risk to corn imports. Since such failures cannot take place in all countries at the same time, and most of them have delayed effects on global corn prices, diversification can be adopted in order to reduce the specific risks to corn importing countries.This paper tries to answer the following questions: What risks will Iran face in terms of corn import systematic or unsystematic risk? What is the relationship between global corn prices and the import prices of Iran's corn imports? Can diversification really minimize Iran's corn import risks?Materials and Methods: This paper applies an improved portfolio model and diversification theory to quantify the risks for Iran's corn import risk during 2000-2019. Diversification theory often applied to the analysis of Iran's corn risks, is considered as a powerful instrument in this field of study. Firstly, for considering the systematic risk like the relationship between Iran's corn import prices and global corn prices is estimated. The Ease of Doing Business Index grading system is employed to represent the risk weight relative to each of source country, which should be able to better reflect the extent of each country's influence on Iran's corn risk. Secondly, the diversification index will be calculated and then the systematic and unsystematic risk is estimated. Finally risk index as an import ratio from source countries in order to replace the volume of imports from a country is used to solve the rapidly increasing risk as well as increasing import volume. Results and Discussion: Empirical results show that ever-increasing global corn prices, price fluctuations, and the increasing volume of imports are the root causes of the growth of Iran's corn import risks. The systematic risks are the primary risks to Iran's corn import risk, which the highest systematic risk accrued in 2011. The diversification indexes remain between 0.4 and 0.5, with no evidence that a linear relationship exists between the diversification index and the specific risk index. Therefore, it is not enough to just reduce the specific risks by increasing the number of source countries. It is of equal importance to import corn from countries with low-risk weights and to strike a balance among countries and regions with similar risks. From 2006 to 2011, Iran's corn import risk index remained steady, between 2.8 and 11. As the Ease of Doing Business Index grading system indicates, Iran should import less from countries with low Ease of Doing Business Index grades such as Singapore and import more from those with higher Ease of Doing Business Index grades, maintain balanced imports from countries with similar risks.
Agricultural Economics
Sh. Shamsoddini; S. Ghobadi; S. Daei-karimzadeh
Abstract
Introduction: One of the most important variables effective on the PPI of agricultural products is the exchange rate. With the change in the exchange rate, the relative prices of exports and imports have changed, and given that the major part of the imports in agricultural sector is the inputs required ...
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Introduction: One of the most important variables effective on the PPI of agricultural products is the exchange rate. With the change in the exchange rate, the relative prices of exports and imports have changed, and given that the major part of the imports in agricultural sector is the inputs required for the production of this sector, this will change the cost of agricultural products. The exchange rate directly affects the export and import of agricultural products and agricultural inputs and indirectly affects production, income, costs, profits and investment in the agricultural sector. Thus, the exchange rate affects the price index in this sector due to its effect on the supply and demand of products and inputs in the agricultural sector. Monetary policy is one of the factors that can affect the price of food and agricultural products. One of the main goals of monetary policy is to stabilize the general level of prices in the economy. In a situation where society is exposed to inflationary pressures and the CPI is rising, the application of a contractionary monetary policy can play an important role in inflation control. Materials and Methods: In this study is used the nonlinear autoregressive distributed lags (NARDL) method for estimating of PPI agricultural products equation using Eveiws12 software. The data required for this study are related to the period 2009 (Chapter 4) to 2019 (Chapter 4), which is mainly collected from domestic library sources, including the Statistical Center of Iran, the Ministry of Agriculture-Jihad, the Central Bank of Iran and the Ministry of Economic Affairs and Finance. The data on the effective real exchange rate has been extracted from the IMF web site. Based on the theoretical foundations and fulfilled studies, the long-run relationship exists between the PPI of agricultural products and the explanatory variables such as real effective exchange rate, GDP, CPI and money supply. This equation is transformed into an unbound error correction model (UECM) using the functional form ARDL (p, q) and is estimated using the ordinary least squares (OLS) method. In this study, the Bounds test has used for investigating the existence of a long-term relationship (co-integration) between independent and dependent variables. Also the Wald test has used for investigating the symmetric or asymmetric effects of independent variables (exchange rate and money supply) on the dependent variable. Results and Discussion: The results of the augmented Dickey-Fuller (ADF) test show that all variables are stationary in first difference. In other words, the variables are integrated from the first degree and in this research, the NARDL approach can be used. The results of Bounds test indicate that in both the linear symmetric model (ARDL) and the nonlinear asymmetric model (NARDL), the calculated F-statistic is greater than the critical values of the upper bound. Thus, the long-run equilibrium relationship between the variables of both models is accepted with 99% confidence. The results of linear model (ARDL) indicate that the real effective exchange rate with a time lag, in the short term has a positive and significant effect on the PPI of agricultural products. The GDP variable only in the long run has a negative and significant effect on the PPI of agricultural products. In addition, the CPI in the short term with a time lag and in the long term has a positive and significant effect on the PPI of agricultural products. Also, in the linear model, money supply (monetary policy) has had a positive and significant effect on the PPI of agricultural products only in the long run. The results of the NARDL model show that in the short run, only the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. Accordingly, the GDP variable in the short run has a negative and significant effect on the PPI of agricultural products. In the short run, the CPI with a time lag has a positive and significant effect on the PPI of agricultural products. In addition, in the short run, the positive and negative shocks of money supply have not had a significant effect on the PPI of agricultural products. In the long run, the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. In addition, the negative shock of the real effective exchange rate in the long run has a negative and significant effect on the PPI of agricultural products. Also, positive shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. Negative shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. In the long run, GDP has had a negative and significant effect on the PPI of agricultural products. Conclusion: The results indicate that the positive shock of the real effective exchange rate, both in the short run and in the long run, has a positive and significant effect on the PPI of agricultural products. Therefore, the depreciation of national currency always increases the PPI of agricultural products. Therefore, the most important step forward for the policymakers and planners to control the rising trend of prices is to prevent the depreciation of the national currency. Based on these results, positive and negative shocks of money supply (expansionary and contractionary monetary policies) have a positive and significant effect on the PPI of agricultural products only in the long run. Therefore, application of monetary policy in the agricultural sector is like a double-edged sword, and the use of these instruments by monetary authorities requires consideration of all aspects.