This paper investigates the effect of crop insurance-subsidies on agricultural land-use allocation. Since the objective of crop insurance is to help farmers with risk management, the expected profit from crop production under crop insurance might be improved, leading farmers to allocate more land to crop production. In this paper, agricultural land-use type is classified by irrigated/unirrigated farmland and cropland/woodland/pastureland. The data come from counties from all the continental states. Considering the fractional outcome of land-use share, we apply a multinomial-fractional-logit model to estimate the effects. The results show that insurance subsidies have a significant effect on land-use allocation. An increase in insurance subsidies increases farmland-share, indicating insurance subsidies could be an efficient tool to adjust agricultural land-use allocation.

This paper aims to apply the time-varying Granger causality test (TVGC) and the DY Spillover Index (Diebold and Yilmaz, 2012) to measure the Granger causality and dynamic risk spillover effects of the international crude oil futures market on China’s agricultural commodity futures market from the perspectives of return and volatility spillovers. Empirical evidence relating to the TVGC test suggests the existence of unidirectional Granger causality between crude oil futures and agricultural product futures. This relationship shows a strong time-varying property, in particular for sudden or extreme events such as financial crises and natural disasters. On the other hand, the volatility spillover in crude oil and agricultural product futures markets responds asymmetrically and bidirectionally according to the result of the DY Spillover index, and the periodicity of total volatility spillover correlates closely with the occurrence of global economic events, which indicates that the spillover effect between crude oil and agricultural commodity futures markets will be exacerbated in turbulent financial and economic times. Such findings are expected to help in formulating policy recommendations, portfolio design, and risk-management decisions.

This study examines systemic connectedness and risk spillovers in the capital markets of Caribbean Rim countries using a Quantile Vector Autoregression (QVAR) framework and weekly equity returns from five economies (the U.S., Mexico, Jamaica, Colombia, and Venezuela) over 2019–2025. Unlike mean-based models, QVAR effectively captures risk transmission across the entire conditional distribution and identifies tail dynamics during extreme events. The empirical analysis yields three key findings. First, under normal market conditions (τ = 0.50), risk transmission exhibits a “core-periphery” hierarchy with a modest Total Connectedness Index (TCI of 24.92), where the U.S. acts as the dominant net transmitter while Jamaica and Venezuela serve as passive net receivers. In extreme regimes, however, connectedness surges to roughly 70, triggering a structural role reversal: Mexico transforms into the primary risk transmitter during market crashes (τ = 0.05), while Venezuela becomes a severe risk-absorption trap. Second, quantile-specific spillovers exhibit a U-shaped descriptive pattern, where the estimated extreme upside connectedness (τ = 0.95 TCI of 70.57) is descriptively slightly higher than the extreme downside connectedness (τ = 0.05, TCI of 69.47). This descriptive pattern may be statistically associated with the tendency of illiquid peripheral markets lacking pricing autonomy to be swept into synchronized co-movements during speculative capital inflows. Finally, the median dynamic TCI fluctuates between 13.52 and 34.38, indicating that the system’s baseline connectedness experienced a significant structural decline in mid-2023 and has since remained at a consistently low level; while 2023 Fed easing expectations coincided with lowered connectedness to annual troughs, the 2025 U.S. “reciprocal tariff” event was followed by a multi-month rebound, which might descriptively reflect transmission via the macro-expectations channel. By characterizing the descriptive patterns of tail connectedness and topological reconfiguration, this study provides vital empirical evidence for regional financial surveillance.