Journal of Agricultural Economics & Development

Abstract Ahar County, as one of the main agricultural production areas, produces a considerable share of rainfed wheat in East Azerbaijan Province. Improving technical efficiency (TE) in this region can have a significant impact on farmers' productivity and economic sustainability. Therefore, the present study was conducted with the aim of applying data mining to analyze the efficiency of rainfed wheat farmers in Ahar County. To this end, farmers' TE was calculated using Data Envelopment Analysis (DEA), and those with efficiency scores above the regional average (0.59) were classified as the high-efficiency group, while the rest were categorized as the low-efficiency group. Subsequently, t-tests and chi-square tests were employed to identify variables likely to influence TE. Machine learning algorithms, including logistic regression, support vector machines (SVM), k-nearest neighbors (k-NN), and random forest (RF), were then applied for classification and analysis of TE. The results indicated that logistic regression outperformed the other algorithms. The output of this algorithm revealed that factors such as herbicides, weed control, manure, land rental value, nitrate fertilizers, number of farm plots, pesticides, farmer's age, combined harvesting method, experience, household members with university education, seed procurement from the Agricultural Organization, and residence in rural areas have a positive effect on TE. Conversely, factors including mixed landownership (personal-rental), seed procurement from personal sources, and non-agricultural income exerted a negative influence on efficiency. Based on the findings, it is recommended that farmers receive necessary training on the optimal management of influential agricultural inputs, including herbicides, manure, nitrate fertilizers, and pesticides. Furthermore, policymakers are advised to enhance the motivation of farmers operating on rented lands by providing financial incentives and advisory services. The development of supportive programs for the supply of quality seeds and agricultural inputs through the Agricultural Jihad Organization is also proposed.

Abstract The agricultural sector is one of the areas where smart agricultural technologies are widely used. Smart farming technologies offer the potential to analyze agricultural data on a scale not previously possible. Adoption of smart farming technologies has the potential to improve productivity and profitability in agriculture, while also improving sustainability. Achieving this potential requires not only technological advancements, but also a thorough understanding of the consequences that the adoption of smart agricultural technologies should have. The aim of the present study is to study the consequences of adopting smart agricultural technologies with the moderating role of government policies and regulations. The statistical population of the research includes managers, experts, and specialists in the field of smart agriculture in Tehran and Alborz provinces, Iran. One of the methods for determining the minimum sample size is the ratio of the number of sample members to the number of questions in the research model or the N:q theory. Accordingly, considering the number of questionnaire items (27 questions), the sample size was estimated to be 270 people. The data collection tool is a questionnaire. The validity of the questionnaire was assessed in diagnostic, convergent and divergent terms, and the reliability of the questionnaire was also assessed using Cronbach’s alpha coefficient and composite reliability. The research model was tested using the partial least squares method and Smart-PLS 3 software. The results of data analysis showed that the adoption of smart agricultural technologies has a positive and significant impact on workforce, economic, and environmental outcomes. Furthermore, government policies and regulations play a positive moderating role in the relationship between the adoption of smart agricultural technologies and workforce, economic, and environmental outcomes.

Abstract We have strived to present a fresh definition of the water-energy-food-environment-decision makers (WEFED) nexus through the creation of a comprehensive and interconnected system. In this study, we considered criteria for consumption, mass productivity, and economic productivity related to irrigation water, renewable and non-renewable energy, as well as the criteria of fertilizer and pesticide use, CO₂ emissions, and wetland conservation to elucidate the water-energy-food-environment (WEFE) nexus. We then assessed the impact of decision-makers’ perspectives on the nexus criteria under seven different management scenarios: water consumption management (WCM), energy consumption management (ECM), water economic management (WEM), energy economic management (EEM), environmental management (ENM), management with equal weight given to criteria (WEFE), and management with weight based on the opinions of decision makers in the study area (WEFED), employing TOPSIS method. To explicitly integrate decision-makers’ perspectives into this system (the WEFED approach), the weights assigned to each sustainability criterion in one scenario were determined directly based on a survey of local decision-makers using the Fuzzy Analytical Hierarchical Process (FAHP) method. The study findings revealed that in the WCM, ECM, and ENM scenarios, barley cultivation held the highest priority, yet despite improvements in environmental parameters, a decrease in water and energy economic productivity was observed compared to the current pattern. Conversely, in the WEM and EEM scenarios, tomato cultivation took precedence, and despite the deterioration of environmental conditions, enhanced mass and economic water and energy productivity were demonstrated compared to the current pattern. The discrepancy in results among the various sustainable scenario patterns underscored the substantial impact of decision-makers’ perspectives on sustainable agricultural management. Finally, it was determined that the WEFE scenario returned the greatest number of improvements (11 out of 13 criteria) in sustainable management criteria compared to the current pattern. Therefore, the findings revealed that a holistic, equally-weighted nexus approach (WEFE), while increasing water consumption, delivers the most balanced sustainability outcomes, though its implementation must be coupled with robust water governance.

Abstract Food security, as a key pillar of sustainable development and social welfare, is particularly sensitive to price fluctuations and income volatility in rural communities. In Iran, recent inflationary pressures and declining household purchasing power have highlighted the need for a scientific analysis of food demand patterns and the evaluation of policy interventions. This study aims to provide a policy-oriented analysis of food demand patterns among rural households in Iran and to assess the potential impacts of alternative policy interventions. Data were drawn from the 2023 Household Income and Expenditure Survey, and the Quadratic Almost Ideal Demand System (QUAIDS) was employed to estimate consumption patterns while accounting for theoretical constraints and household demographic characteristics. Eight main food groups—cereals, proteins, dairy, oils and fats, fruits and nuts, vegetables and legumes, sugar and confectionery, and spices and beverages-were analyzed. Results indicate that cereals and proteins function as necessities with low income and price elasticities, whereas vegetables and legumes exhibit more luxury-like characteristics, with consumption increasing at higher income levels. Cross-price elasticities reveal both substitution and complementarity among food groups, providing important insights for the design of pricing and fiscal policies. Demographic factors, including household size, education, and age, significantly influence consumption patterns. Welfare analyses further show that low-income rural households are the most vulnerable to rising food prices. Overall, the findings not only corroborate previous domestic and international studies but also provide new evidence on the sensitivity of food demand to income and price changes in Iran. Based on the estimated income and own-price elasticities, the findings suggest that food subsidy reforms should focus on staple goods with low income and price elasticities to protect low-income rural households, while targeted income support and price stabilization policies are more appropriate for food groups exhibiting high income and own-price responsiveness, such as vegetables and legumes. Furthermore, the presence of significant cross-price substitution effects implies that price interventions in one food group may have spillover effects on the consumption of other foods, which should be considered in policy design.

Abstract This study investigates the effects of structural and behavioral shocks on market power across 17 four-digit ISIC subsectors of Iran's food industry from 2002 to 2022. We employ a Panel Structural Vector Autoregression (PSVAR) model within the Structure-Conduct-Performance (SCP) framework, enabling a dynamic analysis of the interactions between structural and behavioral shocks. The variables examined include the exchange rate, energy costs, market concentration, value added, advertising expenditures, and intermediate input costs. Variance decomposition results reveal that structural and cost-related factors—intermediate input costs, value added, energy, and the exchange rate—account for over 80% of the variation in market power (Lerner index). Intermediate input costs emerge as the most significant negative driver of market power. Market concentration exerts a positive effect, while value added has a reinforcing effect through innovation. In contrast, behavioral factors such as advertising play a purely marginal role, contributing less than 1%. Owing to institutional constraints and consumer price sensitivity, these factors fail to significantly influence firms' pricing power. These findings confirm that market power in Iran's food industry is primarily shaped by cost structure, industrial concentration, and macroeconomic policies rather than by firms' behavioral strategies. Accordingly, given the key role of structural and cost factors, policy recommendations include managing production costs, fostering innovation and value added, mitigating exchange rate risk, regulating market structure, rethinking advertising strategies, and strengthening market regulation policies.

Abstract  Rice, as the second most important crop after wheat, plays a central role in sustaining rural livelihoods and generating income for farmers in Iran. Despite its importance, structural, institutional, and market-related constraints continue to limit effective commercialization among paddy producers. This study aimed to identify the determinants of both the participation decision and participation intensity in the paddy market of Golestan province. Data were collected during the 2023–2024 cropping season from 150 paddy farmers using a structured and validated questionnaire. The analysis employed a generalized two-part fractional regression model (GTP-FRM), which jointly estimates the binary participation decision and the value-based share of paddy marketed while accounting for the bounded nature of the dependent variable and potential interdependence between stages. The explanatory variables included human capital characteristics (education and household size), asset endowment (cultivated area and mechanization) and institutional and market access variables (milling services, storage facilities, market information, and marketing channels). The results show that 64% of farmers participate in the paddy market, and on average 49% of the gross value of production is sold. Education is negatively associated with paddy market participation, reflecting a strategic shift toward value addition, as more educated farmers tend to process paddy into rice rather than sell raw paddy. In contrast, larger farm size and greater surplus significantly increase participation probability and participation intensity. Institutional and market factors also play differentiated roles: access to market information enhances participation probability, while access to milling facilities encourages rice marketing instead of paddy sales. Overall, the findings suggest that commercialization in Golestan province is shaped not only by production capacity but also by value-addition strategies and transaction-cost considerations within existing policy and market structures. Policies aimed at improving rural processing infrastructure, strengthening market information systems, enhancing surplus generation, and reducing institutional barriers can more effectively support market-oriented behavior and sustainable commercialization among paddy producers in Golestan province.