Research Article-en
Agricultural Economics
M. Ghasabi; M. Haji Rahimi; H. Ghaderzadeh; R. 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.
Research Article
Agricultural Economics
mahdi pendar; mohammad rezvani; eyed Safdar Hosseini; Hamed Rafiee
Abstract
IntroductionThe economy of countries are always exposed to shocks, including the Covid-19 pandemic, which cause various problems. The epidemic of Covid-19 has had various effects and consequences in various sectors, including the agricultural sector. So that the decrease in income and production and ...
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IntroductionThe economy of countries are always exposed to shocks, including the Covid-19 pandemic, which cause various problems. The epidemic of Covid-19 has had various effects and consequences in various sectors, including the agricultural sector. So that the decrease in income and production and the loss of customers according to health quarantines and border closures have severely affected the business of farmers and created many problems for activists of various sectors of the agriculture. One of the most important effects of the Covid-19 pandemic is the reduction of economic growth worldwide. This issue has resulted in to an increase in unemployment and a decrease in the people's purchasing power in the community and a decrease in demand. According to the impact of the covid-19 pandemic on food demand as a result of disorder in the supply chain and income impulses, the purpose of this research is to investigate the existence of a structural failure in the preferences of livestock products (red meat, chicken, eggs and milk) of Iranian consumers using the Quadratic almost ideal demand system and the switching regression framework developed by Ohtani & Katayama (1986) in the period of spring 2015 to winter 2022.Materials and MethodsNonparametric and parametric approaches are used to investigate structural failure in consumer preferences. The parametric approaches and Quadratic almost ideal demand system is employed to assess the structural failure. The switching regression framework proposed by Ohtani and Katayama (1986) is utilized to model structural changes in preferences. In fact, a time transition function enters the demand system. Based on the characteristics of demand in the literature of structural changes, Bewley likelihood-ratio test is applied to select an appropriate model.In order to evaluate the structural failure and calculate the price and income elasticities, the price and per capita consumption data of livestock products are needed, and in this research, seasonal time series data for the period of spring 2015 to winter 2022 have been used. The information related to the price of livestock products was obtained from the Joint Stock Company of the Support of Livestock Affairs. To get the per capita consumption, first, the information on the amount of production of red meat, chicken, milk, and eggs was received from the joint stock company for livestock affairs. Then, by summing the amount of production and the amount of import of red meat, chicken, milk and eggs and deducting the amount of export from the said amount and dividing it by the population of the country, the amount of consumption per capita was calculated. The amount of export and import of red meat, chicken, milk and eggs is taken from the export and import report of the Ministry of Agriculture (Jihad), which is published monthly. Results and DiscussionIn order to estimate the system equations, one of the equations was removed and other ones were solved based the previous one, followed by estimation. Accordingly, the equation related to the removed milk and the QAIDS with 33 parameters and three equations including those related to red meat, chicken and egg were estimated using the maximum likelihood estimator non-linearly. The results show the Based on the statistics of log-likelihood and DW the existence of a gradual structural failure as a result of the Covid-19 pandemic. Comparing the statistics of Bewley likelihood ratio test calculated for an unlimited QAIDS (with structural failure) and a limited one (without structural failure) with a critical χ^2 value with degrees of freedom of nine at the probability level of 5% indicates that the unlimited QAIDS is selected as the appropriate functional one. Also, the results show that after the Covid-19 epidemic, the price of red meat and chicken has increased dramatically. Considering the high elasticity of the price of red meat, chicken and eggs after the Covid-19 epidemic, it is suggested that the government use price tools to support consumers. ConclusionDue to the high cross-elasticity coefficients of demand for red meat, chicken and eggs after the Covid-19 pandemic, it can be expected that a change in the price of one of the red meat, chicken and egg products will significantly change the demand for the other product. slow, therefore, in the application of optimal demand management and consumption pattern planning, the use of substitute product price policies can be useful.Keywords: Change of Preference, quadratic almost ideal demand system, structural failure
Research Article-en
Agricultural Economics
Morteza Molaei; Masoomeh Rashidghalam; Bagher Hosseinpour
Abstract
IntroductionDigital marketing in agriculture has evolved significantly over the past decade, driven by advancements in technology and the increasing internet accessibility in rural areas. The Integrating of digital tools has enabled farmers to access real-time market information, weather forecasts, and ...
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IntroductionDigital marketing in agriculture has evolved significantly over the past decade, driven by advancements in technology and the increasing internet accessibility in rural areas. The Integrating of digital tools has enabled farmers to access real-time market information, weather forecasts, and best practices, thereby enhancing productivity and profitability. Understanding consumer intentions towards digital marketing is crucial in today's rapidly evolving digital landscape. As businesses increasingly rely on digital channels to reach and engage their target audience, comprehending the underlying motivations and attitudes of consumers becomes essential for effective strategic development. This research investigates the factors influencing consumer intentions to engage with digital marketing of agricultural products in Urmia, Iran, a region where agriculture plays a central role in the local economy. Literature ReviewDigital marketing in agriculture encompasses online and technology-driven promotional activities, such as social media, content marketing, and e-commerce (Tiago & Veríssimo, 2014; Michaelidou et al., 2011; Yadav & Rahman, 2017). These strategies aim to increase brand awareness, enhance customer engagement, and drive sales of agricultural products (Kutter et al., 2011). The adoption of digital marketing is driven by consumers' growing reliance on digital channels (Dlodlo & Dhurup, 2013). Successful implementation requires an understanding of the unique characteristics and challenges of the agricultural sector, including perishability, seasonality, and producer diversity (King et al., 2010). Existing research highlights both the potential benefits and barriers, such as infrastructure constraints and data privacy concerns. Data and MethodsOur study utilized a structured questionnaire to gather cross-sectional data on factors influencing digital marketing engagement in agriculture. The questionnaire encompassed three main groups of variables: (1) Perceptions and Trust, including perceived usefulness (PU), perceived ease of use (PEOU), trust (TR), information quality (IQ), and social influence (SI); (2) Demographic and Economic Factors, comprising age (AGE), education level (EDU), income (INC), and price sensitivity (PS); and (3) Experience and Behavioral Intention, covering prior online purchase experience (EXP) and the intention to engage with digital marketing of agricultural products. To ensure a representative sample, we employed a multi-stage sampling technique, selecting regions based on agricultural activity and accessibility, and then randomly choosing participants from lists provided by local agricultural associations. Following data cleaning to address incomplete or inconsistent responses, we analyzed a final sample of 385 valid questionnaires. To empirically analyze the factors influencing Zi, the following logistic regression model is employed (Greene, 2019):(4)where, logitP(Zi = 1) denotes the log odds of Zi equating to one, thereby indicating a preference for digital marketing option j. Xi represents a vector of control variables that could potentially influence the consumer's choice, encompassing demographic characteristics, prior experience, and other pertinent factors. The terms and correspond to the intercept and the coefficient for the control variables, respectively. signifies the error term, encapsulating unobserved factors that may impact the decision-making process. The Logit model can be estimated using maximum likelihood (MLE) process. The MLE of the logit model involves finding parameter estimates that maximize the likelihood function, which is derived from the probability distribution of the logistic function. This approach ensures that the estimated coefficients best fit the observed data by maximizing the probability of obtaining the observed outcomes, as discussed by McFadden (1974) and Greene (2019).ResultsThe findings reveal that “Perceived Usefulness’, ‘Perceived Ease of Use’, ‘Trust’, “Information Quality’, and “Social Influence” are all significant predictors of consumer engagement with digital agricultural platforms. Demographic factors, such as “age”, “education”, and “income’, also impact consumer behavior. Younger individuals are less likely to engage, while higher education and income levels positively correlate with greater engagement. “Prior Online Purchase Experience” was a strong predictor of engagement, emphasizing the importance of familiarity with digital platforms, while “Price Sensitivity” showed a slight negative influence on engagement intentions. The study highlights that trust and ease of use are critical for consumers when considering the adoption of digital marketing platforms, suggesting that marketers should focus on creating user-friendly and trustworthy systems to foster engagement. Additionally, demographic segmentation is important for targeting, as different groups exhibit varying levels of digital engagement based on their characteristics. This research provides valuable insights into the specific behaviors of consumers in developing economies, offering empirical evidence that can guide future marketing strategies for agricultural products. The study adds to the limited literature on digital agricultural marketing in Iran and offers practical recommendations for optimizing consumer engagement.
Research Article
Agricultural Economics
hasan Mehmandoost; Alireza Sargazi; Alireza Keikha; Saman Ziaee; Alireza sani heidari
Abstract
The research investigates the capacities and factors influencing the development of entrepreneurship in rural areas of Hamoun County. Given the significance of entrepreneurship in generating employment, reducing poverty, and enhancing the quality of life in rural regions, identifying and analyzing key ...
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The research investigates the capacities and factors influencing the development of entrepreneurship in rural areas of Hamoun County. Given the significance of entrepreneurship in generating employment, reducing poverty, and enhancing the quality of life in rural regions, identifying and analyzing key factors in this domain is essential. The study employed stratified random sampling, involving 278 entrepreneurs and individuals active in rural business sectors. The influential factors on entrepreneurship development were categorized into six main dimensions: human and individual factors, infrastructural, cultural, economic, and social. Data analysis utilized factor analysis and ordered logit modeling. The results from the factor analysis indicated that "government support and subsidies for production," "income," and "diversification of rural products" significantly contribute to the economic dimension of rural entrepreneurship development. In terms of cultural and social aspects, factors such as "experience," "consultation and support services," "awareness level," and "interest in village improvement" played a crucial role. For infrastructural factors, "access to services and facilities" and "access to a dynamic rural environment" were found to be pivotal in explaining overall variance. Lastly, individual factors like "motivation," "education," "psychological resilience," and "management creativity" were identified as significant contributors to this dimension. Additionally, the results from the ordered logit model revealed that among the influencing factors and barriers to entrepreneurship development, economic, cultural and social, institutional and educational, as well as infrastructural factors had a significant positive effect. Conversely, economic barriers and social obstacles negatively impacted the likelihood of individuals achieving high levels of entrepreneurial motivation. This research provides critical insights for policymakers, suggesting that they should prioritize determining factors for rural entrepreneurship development in their programs. Furthermore, it is recommended that policymakers reduce barriers to rural entrepreneurship and investment risks through subsidized support, low-interest loans, and micro-insurance funds.This research investigates the capacities and factors influencing entrepreneurship development in the rural areas of Hamun County. Given the importance of entrepreneurship in creating employment, reducing poverty, and improving the quality of life in rural regions, identifying and analyzing key factors in this context is essential. The significance of rural entrepreneurship lies not only in its potential to stimulate local economies but also in its ability to foster social cohesion and community development. As highlighted by Petrin (1992), entrepreneurship serves as a central force for economic growth in rural areas, and without it, other developmental efforts may prove ineffective. Thus, understanding the dynamics of rural entrepreneurship is crucial for policymakers and stakeholders aiming to enhance the livelihoods of rural communities. In light of the challenges and opportunities present in rural entrepreneurship, this article aims to identify effective factors influencing entrepreneurial development while reviewing existing literature. By categorizing these factors into human and individual, infrastructural, cultural, economic, and social dimensions, the study seeks to provide a comprehensive analysis that can inform future initiatives aimed at strengthening entrepreneurship in these areas. The findings are expected to offer practical recommendations for enhancing the entrepreneurial ecosystem in Hamun County. Materials and MethodsThe present study utilized a stratified random sampling method, involving 278 entrepreneurs and individuals active in rural business sectors. The research categorized influential factors into six primary groups: human and individual factors, infrastructural factors, cultural factors, economic factors, and social factors. Data analysis was conducted using Stata and Excel software to model relationships among these variables effectively. This structured approach allows for a nuanced understanding of how different factors contribute to or hinder entrepreneurial development in rural contexts. Results and DiscussionThe results indicate that "government support and subsidies for production," "income," and "diversification of rural products" play significant roles in explaining and influencing entrepreneurial behavior from an economic development perspective. In terms of cultural and social aspects, "experience," "consultation and support services," "awareness levels," and "interest in village improvement" were found to have substantial impacts on entrepreneurial behavior. From an infrastructural standpoint, "access to services and facilities" along with "access to a dynamic rural environment" emerged as critical determinants explaining the variance among extracted factors. Furthermore, regarding individual aspects of entrepreneurial development, findings revealed that "motivation," "education," "psychological resilience," and "management creativity" significantly contribute to explaining variations in behavior among entrepreneurs. The results indicated that among various influencing factors on entrepreneurship development, economic factors, cultural and social factors, institutional and educational factors, as well as infrastructural factors had positive and significant effects on the likelihood of individuals achieving high levels of entrepreneurial motivation. ConclusionAmong the identified indicators, government support and subsidies for production had a more substantial impact on income levels while diversification of rural products significantly influenced entrepreneurial behavior from an economic development perspective. In terms of cultural and social dimensions, experience, consultation services, awareness levels, and interest in village improvement were crucial for explaining variations in entrepreneurial behavior. From an infrastructural perspective, access to services and facilities alongside access to a dynamic rural environment played a decisive role in explaining the variance among extracted factors. Finally, individual development aspects revealed that motivation, education, psychological resilience, and management creativity significantly contributed to variations in behavior among entrepreneurs. The findings suggest that within the studied villages—specifically Mohammadabad, Ali Akbar Town, Dek Dehmardeh Town, Sanjoli Town, Mir Town, Bandei Town, and Kermani—there are ideal conditions for entrepreneurship compared to other assessed villages. Furthermore, using an ordered logit model revealed that economic indicators along with cultural-social factors significantly influence individuals' motivations for entrepreneurship. This expanded introduction provides a comprehensive overview of your research topic while highlighting its significance within the broader context of rural entrepreneurship development.Keywords: Entrepreneurship Development, Factor Analysis, Ordered Logit, Rural Areas, Hamun County
Research Article
Agricultural Economics
Masomeh bahadori; Bita Rahimi Badr; Alireza Nikouei; Rooya Eshraghi Samani
Abstract
Extended AbstractThe seed control and certification process is considered as a key tool to confirm the quality of the produced seeds. Considering the unique position of wheat in the agricultural and consumption system of the country, this process plays a special role in the sustainability of healthy ...
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Extended AbstractThe seed control and certification process is considered as a key tool to confirm the quality of the produced seeds. Considering the unique position of wheat in the agricultural and consumption system of the country, this process plays a special role in the sustainability of healthy seed production and food security. The present study investigated factors affecting the development of the wheat seed control system and identified the most important components affecting it with the aim of designing a conceptual model.The current research used the grounded theory, and analytic network process. The results of the semi-structured interview in the qualitative stage of 20 cereal seed experts led to the identification of 47 concepts, 11 core categories and four broad categories in the form of six core classes of the paradigm model.In the following, a targeted sample was formed to perform pairwise comparisons with eight members of the academic staff specializing in seed control. The validity and reliability of the research was evaluated at the optimal level. Regarding the semantic interpretation of the conceptual model, regulatory factors and government support policies were identified as solutions with positive consequences, improving the quality of wheat seeds and the stability of the seed market.Moreover, the results showed that the quality of seed kernels and balancing the sale price of healthy seeds were more important than the costs of seed production among the components of technical and economic criteria. In addition, the ranking of seed producing units for providing incentive facilities in the top units and supporting the entry of knowledge-based companies in the supply of seed production were among the strategies developed for the development of this process.IntroductionThe seed industry is a growing industry in the world, and the role of processed seeds in increasing the production performance is undeniable. Due to the population growth, the importance of achieving food security is increasing. Healthy seed is one of the important factors in the development of agricultural production. Although agricultural production systems have increased their production, it does not seem to be enough, though. The basic problems of the seed market and insufficient supply of seeds required by farmers have made it necessary to identify samples of seed quality development. The current research was the first research at the national level dealing with the design of a conceptual model for the development of control and certification of wheat seeds using the grounded theory method and prioritization of effective factors.Materials and MethodsThis research had a fundamental-applicative goal and was applied in two stages. In the first stage, after designing the interview questions, the grounded theory was carried out in three stages of open, central, and selective coding using a systematic approach in order to design a conceptual model. After designing the paradigm model and identifying the factors affecting the development of seed control and certification, the prioritization of the components was done including technical, social, economic and structural criteria using analytic network process.Results and DiscussionAfter analyzing the interviews, 140 initial codes were identified and the initial codes were reduced to 94 and then to 47 concepts. In the following parts, 11 core categories including processed seed production standards, laws and regulations, environmental factors, regulatory factors, equipment and technology, stability in the seed market, government support policies, human factors, wheat seed quality, attitude and awareness, and economic infrastructure were identified. The results of prioritization among the four effective criteria on the development of seed certification indicated that the technical criterion was more important than the other three criteria. In terms of the prioritization of the components, the quality of the seed kernel having a weight of 0.49, the performance of the responsible expert having a weight of 0.44, the cost of producing processed seeds having a weight of 0.39 were the first priority of technical, social, and economic criteria. Applying the ranking of production units with a weight of 0.57 and making the seed market competitive with a weight of 0.26 were more important than other components of structural criteria.ConclusionAccording to the results of this study, and the first priority of the technical criterion, it is suggested to monitor the quality of seed kernels and select appropriate farm inspectors. Moreover, in order to strengthen the human resources system, it is recommended to hold continuous courses in the field of seed quality. To implement the solutions of the paradigm model, it is recommended to prevent buying and selling unhealthy seeds and balance the costs of producing and selling processed seeds.
Research Article-en
Agricultural Economics
Shirin Zarif Moradian; mahmoud daneshvar; mahmoud sabouhi sabouni
Abstract
One of the essential goals of societies, primarily developing and underdeveloped countries, is to eradicate poverty and achieve sustainable development. As vulnerable individuals in various communities increasingly face various economic, environmental, and political challenges, governments and policymakers' ...
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One of the essential goals of societies, primarily developing and underdeveloped countries, is to eradicate poverty and achieve sustainable development. As vulnerable individuals in various communities increasingly face various economic, environmental, and political challenges, governments and policymakers' pre-crisis management to increase the productivity of different economic sectors, such as the agricultural sector, is considered inevitable. The efficiency of the farm sector is not only crucial for ensuring food security in the country, but it will also affect the livelihoods, incomes, and resilience of rural smallholders. Given the above, the purpose of this study is to investigate the impact of agricultural support policies on the resilience of rural farmers in the Fariman region. In this regard, The Resilience Index Measurement and Analysis (RIMA) introduced by the FAO has been used to determine the resilience of rural farmers.Additionally, the distribution of subsidized fertilizers to farmers as a common agricultural support policy in the country has been chosen. The impact of this agricultural support policy on the resilience of rural farmers has been estimated using the propensity score matching method in this study. The study area is the Hossein Abad Rekhneh Gol village, located in Fariman County, and the data were collected through documentation and questionnaires. The study results indicate that households eligible to receive subsidized fertilizers have higher resilience on average compared to households that are not eligible. One of the factors that have a significant impact on improving the yield of agricultural products, including wheat, is the use of chemical fertilizers (including nitrogen, phosphorus, and potassium). In the crop year in which the data was collected, these fertilizers were the only subsidized input distributed by the government to farmers. Due to the price difference between subsidized fertilizers and the market, many of the farmers studied who were unable to receive this subsidy due to lack of agricultural water were unable to buy it in the market in cash, too. This can have a significant impact on reducing the yield of their products and consequently affect their resilience. So for the study area, it is recommended that rural smallholders be prioritized in the allocation of subsidized fertilizers, which is constrained by quantity and budget limitations imposed by the government, compared to large-scale farmers. Additionally, the number of agricultural wells available for rent to rural farmers should be increased as much as possible.One of the essential goals of societies, primarily developing countries, is to eradicate poverty and achieve sustainable development. As vulnerable individuals in various communities increasingly face various economic, environmental, and political challenges, governments and policymakers' pre-crisis management to increase the productivity of different economic sectors, such as the agricultural sector, is considered inevitable. The efficiency of the farm sector is not only crucial for ensuring food security in the country, but it will also affect the livelihoods, incomes, and resilience of rural smallholders. Given the above, the purpose of this study is to investigate the impact of agricultural support policies on the resilience of rural farmers in the Fariman region. In this regard, The Resilience Index Measurement and Analysis (RIMA) introduced by the FAO has been used to determine the resilience of rural farmers. Additionally, the distribution of subsidized fertilizers to farmers as a common agricultural support policy in the country has been chosen. The impact of this agricultural support policy on the resilience of rural farmers has been estimated using the propensity score matching method in this study. The study area is the Hossein Abad Rekhneh Gol village, located in Fariman County, and the data were collected through documentation and the use of questionnaires. The study results indicate that households eligible to receive subsidized fertilizers have higher resilience on average compared to households that are not eligible. Based on the research findings for the study area, it is recommended that rural smallholders be prioritized in the allocation of subsidized fertilizers, which is constrained by quantity and budget limitations imposed by the government, compared to large-scale farmers. Additionally, the number of agricultural wells available for rent to rural farmers should be increased as much as possible.Based on the research findings for the study area, it is recommended that rural smallholders be prioritized in the allocation of subsidized fertilizers, which is constrained by quantity and budget limitations imposed by the government, compared to large-scale farmers. Additionally, the number of agricultural wells available for rent to rural farmers should be increased as much as
Research Article-en
Agricultural Economics
Haniye Kazmi Shabanzade Aflaki; ozra javanbakht; Khadijeh Alefi
Abstract
Given today’s existing limitations, providing a healthy, adequate and high-quality food for the fast-growing population of the world is a great challenge. The limitations exist in all fields, including resources and factors affecting production in the agricultural sector. The only solution to guarantee ...
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Given today’s existing limitations, providing a healthy, adequate and high-quality food for the fast-growing population of the world is a great challenge. The limitations exist in all fields, including resources and factors affecting production in the agricultural sector. The only solution to guarantee food security is the use of available sources effectively to deliver more and higher-quality products i.e., improving efficiency. The assessment of the efficiency of agricultural productions is also an important issue in the process of development in countries. On the other hand, agriculture is a risky activity and is affected by various factors such as climatic conditions, pests and diseases, fluctuations in inputs and outputs prices, financial risk, human risk, and input risk in production. Among these, the risk of inputs in production is important because of creating variation in production and yield of the output. Therefore, Agricultural activities are risky in comparison with other production activities, and the risk is also often accompanied with inefficiency. So, simultaneous study of risk and inefficiency can lead to more productive production. The method of analysis proposed for this study is consistent with the stochastic frontier approach which was independently proposed by Aigner et al. (1977) and Meeusen and Vanden Broeck (1977). This model proposes inputs have a similar effect on mean and variance outputs. But Just and Pope (1978) production function proposed separate effects of the inputs on the mean and variance outputs whilst Kumbhakar (2002) further incorporates technical inefficiency model. Technical efficiency of the i-th farm is the ratio of observed output given the values of its inputs and its inefficiency effects to corresponding maximum feasible output if there were no inefficiency effects. This study used cross-sectional data from 221 rice paddy fields which is a fair representation of the paddy fields in the region. A two-stage cluster random sampling method was employed to fulfill the questioners for obtaining the data on the relevant variables of this study including output and inputs as well as the farmers socio- economic variables.According to the collected data, the average area under cultivation in the area was 1.33 hectares and rice farmers used on average 98.92 kilograms of rice seed, 29.50 man-days of labor, 258.35 kilograms of nitrate fertilizer, 142.28 kilograms of phosphate fertilizer, 4.51 liters of pesticide and 65.68 hours of agricultural machinery to produce 4.94 tons of output.Also, according to completed questionnaires, the average age of rice farmers in the sample was 51 years old and more than 97% were married. The average size of the households was 3 people and 92% were male and the rest were female. Rice farming is the main job of more than 53% of respondents and more than 81% of them are the land owners. About the ownership of machinery, only 10% of farmers owned the machinery and the rest used rental machineries. More than 48% of farms were insured and 21% of them had participated in educational programs. According to the results, the elasticity of land input is positive and equals to 1.04 showing one percent increase in the usage of this input will increase output by 1.04 percent and this input was used in the first stage of production in the studied area. The elasticities of nitrate and phosphate fertilizers, herbicide and machinery inputs had a positive sign, meaning that one percent increase in the usage of these inputs will increase output by 0.258, 0.033, 0.058 and 0.0003 percent respectively. The value of these elasticities is between zero and one indicating that farmers are currently operating in the second stage of production with respect to these inputs. The negative elasticity of production of seed and labour inputs means that one percent increase in the usage of these inputs will lead to the reduction of production, so these inputs are used in the third stage of production. The returns to scale coefficient is estimated at 1.092. This value is greater than one showing the increasing returns to scale structure of rice production in the studied area. The results of estimating production risk function showed that rice production was significantly affected by land, seed and labour inputs. Also, land, water, age, and gender variables are risk increasing, and seed, herbicides, machinery, farmer’s education, family size, and farming experience are risk reducing inputs. In addition, seed, labour, membership in the agricultural cooperatives and insurance, increase technical inefficiency. Nitrate fertilizer, water, gender, rice cultivating experience and participation in educational and promotional classes reduce technical inefficiency in the studied area. The results of estimating technical efficiency showed that the average technical efficiency of the rice paddy field with risk component was 93.47% and without risk component, it was 96.27%. Therefore, it’s obvious that estimating the model without risk component leads to magnification error in the amount of technical efficiency. In conclusion, it is recommended to consider the risk component in measuring technical efficiency of paddy fields in order to achieve a sound risk management and highly efficient production.
Research Article-en
Agricultural Economics
saeed jalalian; Alireza Karbasi
Abstract
Title: Rural-Urban Disparities in Animal-Source Food Demand and Welfare Losses During COVID-19 in Iran: A QUAIDS Approach Introduction: This study investigates how the COVID-19 pandemic, marked by declining incomes and rising food prices, impacted the expenditure share and consumption patterns of animal-source ...
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Title: Rural-Urban Disparities in Animal-Source Food Demand and Welfare Losses During COVID-19 in Iran: A QUAIDS Approach Introduction: This study investigates how the COVID-19 pandemic, marked by declining incomes and rising food prices, impacted the expenditure share and consumption patterns of animal-source foods (ASFs) in Iranian households. ASFs, including meat, dairy, eggs, and aquatic products, are vital for protein and essential nutrients, particularly during crises, but are costly and sensitive to supply chain disruptions. The research explores how economic and health-related shocks altered household budgets and food consumption, focusing on ASFs due to their nutritional importance and budgetary impact. Using the Quadratic Almost Ideal Demand System (QUAIDS) model, the study provides a nuanced analysis of short-term pandemic effects, distinguishing between urban and rural areas to capture regional disparities. It also estimates welfare losses through compensating variation and analyzes Hicksian price elasticity, offering actionable insights for policymakers to address nutritional deficits and mitigate welfare losses. This research fills a critical gap by providing empirical evidence on pandemic-induced food demand disruptions in Iran, contributing to broader efforts to improve food security and ensure access to nutrient-rich diets for vulnerable populations.Data:The analysis uses cross-sectional household expenditure data from 2019 (pre-pandemic) and 2020 (peak pandemic) in Iran, covering 38,099 households in 2019 (52% urban, 48% rural) and 37,294 households in 2020 (51.4% urban, 48.6% rural). Variables include ASF expenditure shares (livestock meat, poultry, dairy, eggs, etc.), household demographics, and income levels. Method:1. QUAIDS Model: A structural demand system is employed to estimate price and expenditure elasticities, capturing nonlinear Engel curves and substitution effects. 2. Welfare Loss Calculation: Hicksian (compensated) price elasticities measure welfare losses due to pandemic-induced price and income shocks, using CV.3. Software: Stata/MP14.0 was used for econometric analysis. Results: 1. Descriptive Insights: - Rural households allocated 53.4% of food expenditure to ASF in 2019, compared to 31.4% in urban areas. By 2020, rural ASF expenditure dropped to 41.8%, while urban spending fell to 34.3%. - Poultry consumption dominated ASF expenditure (32.3% urban, 34.9% rural in 2019), but dairy and eggs saw significant declines during the pandemic. 2. Elasticities: - ASF demand was income-elastic (1.41–1.48 for urban, 1.48–1.60 for rural), indicating ASFs are normal goods. - Price Elasticities: Rural households exhibited higher sensitivity (e.g., livestock meat: -0.48 rural vs. -0.86 urban), suggesting greater vulnerability to price hikes. 3. Welfare Losses: - Rural households faced larger losses (IRR 122,915 vs. IRR 118,908 for urban households annually), driven by reduced access to livestock meat and dairy. - Eggs and aquatic meat showed the highest welfare losses, reflecting supply chain disruptions. Conclusion: This study highlights the economic impact of the COVID-19 pandemic on Iranian households, particularly their consumption of animal-source foods (ASFs). Using the QUAIDS model, the research reveals significant disparities between rural and urban areas, with rural households facing higher welfare losses and greater price sensitivity. Eggs, poultry meat, and dairy products were classified as necessary goods, while livestock meat, aquatic meat, and animal oils were more income-sensitive, indicating luxury status. Rural households, despite lower price increases, were more vulnerable due to limited budgetary flexibility, emphasizing their reliance on ASFs for protein intake. The findings align with studies from other middle-income countries, such as China and Sub-Saharan Africa, where rural populations were disproportionately affected by price volatility and allocated larger shares of their budgets to food during crises. This research underscores the precarious state of food security during economic shocks, particularly for rural communities, and provides valuable insights for policymakers to address nutritional deficits and mitigate welfare losses in future crises.Policy Implications: This study underscores the need for targeted policies to enhance food security and economic resilience in the post-COVID-19 era. The findings highlight the critical role of animal-source foods (ASFs) in Iranian diets, particularly their sensitivity to income and price changes, which disproportionately affect rural households due to limited income sources and market access. To address these challenges, policies should focus on strengthening ASF supply chains through infrastructure investment, storage improvements, and financial support for producers. Urban households, facing rising food costs, would benefit from price controls and subsidies on essential items, while rural areas require enhanced social services, such as healthcare and financial assistance, to bolster economic resilience. Additionally, promoting plant-based protein alternatives could offer a sustainable, cost-effective solution to reduce dependency on ASFs and improve long-term food security. The study advocates for a multi-faceted approach, combining targeted interventions, supply chain resilience, and dietary diversification, aligning with broader academic discourse on sustainable food systems and crisis management. These measures can mitigate the lingering economic impacts of the pandemic and ensure equitable access to nutritious food for all households.Keywords:COVID-19; Animal-source food; Welfare losses; QUAIDS model; Iran