Tao Xiong

China's ageing rural population presents a significant challenge to the country's development. This article uses data from the 2013, 2015 and 2018 China Health and Retirement Longitudinal Study to examine how pension receipt of the elderly parents in rural China affects the labour mobility of their adult children. The estimation results from a fuzzy regression discontinuity design indicate that the pension receipt increases the labour mobility of adult children. The effects are more pronounced when the elderly parents have better health, have more living children and are both alive. Mechanism analysis indicates that pension receipt reduces regular financial transfers from adult children, but does not affect grandparental childcare for the adult children. This article reveals how a public pension programme affects the labour mobility of the younger generation and offers valuable insights for other developing countries facing similar challenges with an ageing population.

Aflatoxin B1 (AFB1), one of the most hazardous environmental and foodborne mycotoxins, is a major contributor to the global burden of hepatocellular carcinoma owing to its potent hepatocarcinogenicity and persistence throughout food systems. Although risk assessment and monitoring programs for aflatoxins have been established worldwide, the dynamic patterns of AFB1-related disease burden from production to consumption have been largely overlooked, limiting the development of truly risk-based monitoring strategies. Here, we present an integrated framework that quantifies seasonal and regional occurrence of AFB1 contamination and disease burden, and applies these insights to optimize monitoring strategies under resource constraints. Using official monitoring records of AFB1 and health risk data, our analysis estimated an average burden of 3.51 disability adjusted life years per 100,000 population across China. Interprovincial transfers of peanuts and peanut oil accounted for 52% more local disease burden than in-province production. By reallocating monitoring batches along these high-risk pathways, the optimized monitoring strategy reduced the national health burden by 25 percentage points relative to current monitoring. Beyond AFB1, our study provides a transferable framework for enhancing mycotoxin management in complex food systems, enabling policymakers to better protect public health under resource constraints.

The extraordinary fluctuations in China's hog prices, particularly since the outbreaks of the African swine fever in 2018, have brought tremendous risks to hog producers' production planning. This study proposes a decision framework for hog price prediction and production planning. Specifically, we use six forecast combination strategies to integrate multi‐step‐ahead forecasts of the hog price generated by 11 econometric and machine learning methods. Furthermore, we design a practical production plan based on the obtained hog price forecasts to determine the number of piglets purchased and fattened pigs sent to slaughter every month. Our results show that the forecast combinations consistently generate more accurate forecasts across six prediction horizons and three accuracy measures than individual forecasting methods. No model consistently performs best among the 11 individual forecasting models. The least absolute deviation strategy is particularly well‐suited for predicting hog prices. Concerning economic performance, the cumulative returns of hog producers who use the proposed production plan are consistently higher than those who use a naïve production plan. Experimental results indicate that our decision framework is a promising and practical tool for price forecasting and production planning in the hog industry.

Aflatoxin B1 (AFB1), one of the most hazardous environmental and foodborne mycotoxins, is a major contributor to the global burden of hepatocellular carcinoma owing to its potent hepatocarcinogenicity and persistence throughout food systems. Although risk assessment and monitoring programs for aflatoxins have been established worldwide, the dynamic patterns of AFB1-related disease burden from production to consumption have been largely overlooked, limiting the development of truly risk-based monitoring strategies. Here, we present an integrated framework that quantifies seasonal and regional occurrence of AFB1 contamination and disease burden, and applies these insights to optimize monitoring strategies under resource constraints. Using official monitoring records of AFB1 and health risk data, our analysis estimated an average burden of 3.51 disability adjusted life years per 100,000 population across China. Interprovincial transfers of peanuts and peanut oil accounted for 52 % more local disease burden than in-province production. By reallocating monitoring batches along these high-risk pathways, the optimized monitoring strategy reduced the national health burden by 25 percentage points relative to current monitoring. Beyond AFB1, our study provides a transferable framework for enhancing mycotoxins management in complex food systems, enabling policymakers to better protect public health under resource constraints.

Department of Agriculture on a quarterly basis. During disruptions in the pork value chain, such as the initial outbreak of porcine epidemic diarrhea virus and the COVID-19 pandemic, there is a need for more frequent reporting of inventory levels. These more frequent estimates, if accurate, would improve production and marketing decisions, aid in policy assessments, and help reduce price volatility. This study proposes a mixed-frequency dynamic factor model to nowcast inventory estimates published in Quarterly Hogs and Pigs reports from 1993 to 2024, using more frequent published hog production and price data. In each round of nowcasting between two consecutive Quarterly Hogs and Pigs reports, we obtain ten nowcasting predictions of hog and pig inventory with progressively updated data. Our results show that reasonably accurate predictions can be obtained as early as two months before the release of a Quarterly Hogs and Pigs report, and they improve further as new information becomes available. The dynamic factor model outperforms several alternative methods and yields superior forecasts compared to analysts' pre-report expectations during extreme events. Government agencies and market participants could utilize our nowcasting model framework to publish inventory estimates more frequently and at relatively low cost.

Purpose: This paper aims to analyze the dynamic relationships between spot and futures prices of Chinese agricultural markets by considering different time scales and market conditions and explore the predictive ability of these futures products. Design/methodology/approach: This paper proposes a new ensemble empirical mode decomposition (EEMD)-based quantile framework that integrates EEMD, quantile-on-quantile (QQ) regression and causality in quantiles (CQ) methods to analyze the dynamic relationships between the spot and futures prices of corn, soybean oil, cotton and live hogs. Findings: Results show that QQ coefficients in cotton, live hog and soybean oil markets are significantly positive, indicating robust price dependence and hedging properties. In most cases, QQ coefficients in corn markets are close to 0, suggesting a weak hedging property. Furthermore, the dependence structure of spots and futures are more robust in average markets than in bullish and bearish markets and significantly more robust in the medium and long term than in the short term. The CQ results show the predictability of these four futures and further support the QQ conclusions. Futures are likely to be more predictive under average market conditions and this predictability is more significant in the medium and long term. Originality/value: Relative to previous studies on a single time scale and market condition, our study provides new insights for investors seeking to better manage risk in agricultural commodity markets. The agricultural futures examined are suitable for hedging in certain market conditions for long-term investors with sufficient risk tolerance.

Promoting sustainable, innovation‐driven growth is crucial for achieving high‐quality economic development in the new era. As a key indicator of companies' sustainability, ESG practices have gained significant attention. However, the lack of a unified ESG evaluation framework and standardized disclosure regulations has led some companies to exaggerate or misrepresent their ESG performance—an issue known as “ESG decoupling.” This study examines the impact of ESG decoupling on agri‐food companies' innovation, using panel data from 2011 to 2022. The results show that ESG decoupling undermines a company's credibility, hindering innovation. However, independent directors mitigate the negative effects of ESG decoupling on innovation. Further analysis reveals that the impact of ESG decoupling is less severe in companies with low digital transformation levels and state‐owned enterprises (SOEs). In contrast, the negative effects are more significant in large companies and the food industry. These findings contribute to a deeper understanding of the relationship between ESG decoupling and innovation. It offers empirical evidence and expands the theoretical framework linking ESG behavior with innovation. Ultimately, the study highlights the need for improved ESG disclosure systems and enhanced companies' credibility to foster a more innovation‐friendly environment.