Copula specifications.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.</div

Descriptive statistics for the returns.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.</div

The regression results during the period of the COVID-19 pandemic and the Russia-Ukraine war in 2022.

The regression results during the period of the COVID-19 pandemic and the Russia-Ukraine war in 2022.</p

The regression results during the US-China trade war (only including the period before the COVID-19 pandemic).

The regression results during the US-China trade war (only including the period before the COVID-19 pandemic).</p

Table_1_Transition patterns of weight status: A cohort study of Chinese school-age children.docx

BackgroundChildhood overweight and obesity are increasing public concerns. However, little is known about the transition patterns of childhood weight status, especially in developing countries. In this study, we aimed to evaluate patterns of change in weight status and the risk factors among Chinese school-age children.MethodsThis retrospective cohort study included 2,334 children aged 6 years with complete 5-year (2012–2017) physical examination data in Minhang District, Shanghai. A time-homogeneous three-state Markov model was fit to the longitudinal data with dynamic outcomes (normal weight, overweight, and obesity).ResultsAccording to the Markov model, 42.3% of school-age children who were initially overweight transitioned to another weight status within 1 year, with 24.8% (95% confidence interval [CI]: 23.1, 27.0) transitioning to normal weight and 17.5% (95% CI: 15.9, 19.3) becoming obese. In contrast, children who were initially normal weight (92.9% [95% CI: 92.3, 93.5]) or obese (83.1% [95% CI: 81.1, 84.8]) tended to maintain their initial weight status. Male sex, semi-urban area, absence of late adiposity rebound, lower annual height increments, higher annual weight increments, and higher initial body mass index were significantly associated with a higher risk of developing or maintaining overweight and obesity (p ConclusionsThe weight status of Chinese school-age children is more likely to change among those who are initially overweight than in those who are initially obese. Interventions to promote healthy weight status may be more effective if key groups are targeted, such as overweight and pre-school-age children.</p

The selected optimal copula based on log-likelihood values.

The selected optimal copula based on log-likelihood values.</p

K-S test for the asymmetry of risk spillovers from the US to China and from China to the US.

K-S test for the asymmetry of risk spillovers from the US to China and from China to the US.</p

Pearson correlations of regression variables.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.</div

Estimated parameters of copula model.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.</div

Down ΔCoVaR from the US to Chinese agricultural futures markets.

All values of ΔCoVaR have been multiplied by a factor of 100.</p