Agricultural Economics - In Press
Empowering Farmers Through Agricultural Supply Chains: An ESR and IVQR Analysis of Income Effects in ChinaOriginal Paper
Zhao Ding, Qianyu Zhang
Integrating farmers into the modern agricultural industrial system is key to sustaining rural household income growth. Based on field survey data from rural areas in three western Chinese provinces, this study uses an endogenous switching regression (ESR) model to analyse the impact of farmers’ participation in agricultural supply chains on their income, and explores the heterogeneous effects of credit constraints and agricultural loans on the incomes of participating and non-participating farmers. The results show that supply chain participation significantly increases farmers’ total and operational income, while driving the modernisation of agricultural production methods. Specifically, supply chain participation enables farmers to use agricultural loans efficiently to drive income growth and alleviate income constraints caused by credit restrictions. Furthermore, the positive effect of supply chain participation on operational income is more prominent, especially for low- and middle-income farmers. In contrast, the income-increasing benefits of agricultural loans are more pronounced among middle- and high-income farmers, reflecting differences in loan utilisation capacity across income groups.
Sustainable agricultural performance in the European Union in the context of ecological transition, economic fairness, and support policiesOriginal Paper
Valentin Marian Antohi, Jean Vasile Andrei, Costinela Fortea, Dumitru Nancu
This paper investigates the structural determinants of sustainable agricultural performance in the 27 European Union Member States over the period 2012–2023, with a focus on the interplay between economic efficiency, environmental sustainability, and social equity. Using a panel quantile regression approach, the study captures the heterogeneous effects of variables such as organic farming practices, public support for agricultural research and development, income inequality, and environmental emissions on multiple dimensions of agricultural performance. The results indicate that the influence of these factors varies significantly across the performance distribution, with stronger effects observed in lower-performing contexts. Higher agricultural income is consistently associated with enhanced value-added efficiency and reduced ecological intensity, suggesting a structural decoupling between economic growth and environmental pressure. The findings underscore the importance of differentiated and evidence-based policy interventions that promote innovation, resilience, and inclusive rural development. In alignment with key European strategies, such as the Common Agricultural Policy 2023–2027, the European Green Deal, and the Farm to Fork Strategy, this study provides a robust empirical framework to support the design of integrated agricultural policies aimed at achieving long-term sustainability and competitiveness in the European agricultural sector.
Assessing the links between Climate Change Resiliency and Food Security in Northwestern Region BangladeshOriginal Paper
Abhi Sarker, Salman Ibn Yasin, Bikash Chandra Ghosh, Gershom Endelani Mwalupaso, Asma Akter, Emmanuel Kiprop, Liu Zhenzhen, Farjana Eyasmin, Geng Xianhui
Climate change is intensifying threats to food security across the developing countries, pushing vulnerable nations like Bangladesh toward a breaking point—where resilience is no longer an option but a survival imperative. Despite growing concerns, limited empirical research exists on how climate resilience influences food security across rural and urban farming households. This study examines climate resilience in northwestern Bangladesh and its impact on farming households' food security. Using multistage random sampling, 498 households across 16 villages in extreme climate zones were surveyed. A Climate Resilience Index (CRI) was developed to assess resilience, and a binary logistic model analyzed its effect on food security. Findings indicate that urban households exhibit greater resilience than rural ones, with 38.7% and 32.8% classified as food secure, respectively. Overall, only 35.74% of households in the study area were food secure. Key determinants of food security include household income, non-farm employment, crop diversity, education level of the household head, farm size, and individual CRI. Enhancing climate resilience through adaptive strategies can improve food security, while off-farm activities provide critical financial support. Policy interventions, such as government or NGO-led agricultural financing, could further strengthen food security.
The Impact and Mechanisms of Animal Epidemics on Pork Prices: Evidence from a Multi-Period DIDOriginal Paper
Wen Zhizheng, Li Yi
This study uses the outbreak of African swine fever as a quasi-natural experiment to assess its impact on pork prices and the underlying mechanisms. Using panel data from 30 Chinese provinces between January 2017 and December 2022, we employ a multi-period difference-in-differences (DID) approachcombined with a moderated-effects model. Additionally, the DID-quantile regression (QR) model is utilised to investigate how the epidemic affected price volatility under varying initial pork price growth rates and agricultural institutional conditions. The results indicate that the epidemic led to a significant increase in pork prices, with an average rise of approximately 6%. In this context, pig stock levels moderated the price changes, with prices rising more rapidly in regions experiencing a decline in stock. The outbreak exacerbated regional price disparities, with larger price increases occurring in areas where initial pork prices were already rising rapidly and where the agricultural economy was more developed. Consequently, the government should implement targeted strategies to control price fluctuations based on regional differences. Furthermore, enhancing coordination across the pork industry and optimising public information platforms could help mitigate the impact of sudden animal disease outbreaks on the market.
Corn price forecasts in the shadow of the Russian-Ukrainian conflictOriginal Paper
László Vancsura, Arnold Csonka
The conflict between Russia and Ukraine has caused serious disruption to agricultural markets, affecting both food prices and food security. In our study, we examine how global economic problems such as Covid19 or war conditions affect the price of corn and its predictability. We have used deep neural network models (RNN, LSTM, GRU), experimenting with both simple and hybrid versions, as well as univariate and multivariate types. The results show that the LSTM model outperformed the others in the prediction of corn prices. It was also found that multivariate models tend to give more accurate results than their univariate counterparts, suggesting that the quality of forecasts can be significantly improved by including additional variables. In the robustness analysis of the models, it was shown that the Covid19 crisis in 2020 and Russian-Ukrainian conflict in 2022 led to a deterioration in model performance. The research can also contribute to the development of forecasting methods for the corn market and provide a basis for the development of long-term decision strategies by market players.
Effects of different tillage practices on cropland carbon efficiency under wheat-maize rotation croppingOriginal Paper
Yu Wang, Boqian Wang, Xiuguang Bai
Under the goals of carbon peak and carbon neutrality, the unique dual attributes of cropland use—carbon emissions and carbon sinks—has attracted widespread scientific attention. With the survey data of wheat-maize growers in Yellow River Basin of China in 2020, our study evaluates farmers’ cropland carbon efficiency (CCE) by using the minimum distance to strong efficient frontier with undesirable outputs model (MinDS-U), and then examine the effect and the mechanism of different tillage practices in influencing CCE. The results show that the average CCE is 0.5926, and the largest average CCE is reduced tillage with straw returning (RTS), followed by no-tillage with straw returning (NTS), and the smallest is conventional tillage with straw returning (CTS). Both NTS and RTS significantly improve CCE, with NTS being more effective. Furthermore, mechanism tests indicate that NTS and RTS enhance CCE by increasing yield and net carbon sequestration. Additionally, NTS significantly reduces energy input, decreases carbon emissions, and thus bootsts CCE, while RTS leads to a slight increase in carbon emissions due to higher fertilizer and energy use, and a consequent decrease in CCE. In terms of heterogeneity, the benefits are more pronounced for small-to-medium-scale, less-educated, and elderly farmers.
The opinions of first adopters in the introduction of Bt maize in Spain: a success storyOriginal Paper
Maria Mercè Clop-Gallart, Esther Estruch-Bosch, María Isabel Juárez, Montserrat Viladrich-Grau
Spain is one of the few EU countries that adopted genetically modified (GM) maize as a crop (in 1998) and has continued to harvest it ever since. This article aims to contribute to the writing of the history of the adoption of transgenic maize in the EU. Our aim is to identify Spanish farmers' motivations, opinions and beliefs on adopting this technology. The surveyed regions represented 74% of the national surface dedicated to transgenic maize. The questionnaire included questions related to characteristics of the farm, the farmers, and their opinions and beliefs. Our statistical model is a binary logistic regression that estimates the probability of adopting GM maize. The findings reveal that while farmers were aware of the potential problems associated with GM crops, their main concern was the economic threat posed by corn borer infestations. The expectation of increased economic benefits from transgenic maize served as an incentive for adoption. Attitudes toward GM maize did not differ significantly between adopters and non-adopters, with non-adopters showing that their concerns about the health risks of GM maize were not particularly strong, suggesting that the varying rates of adoption were not rooted in different beliefs.