Wang Hao’s research while affiliated with Chinese Academy of Agricultural Sciences and other places

Against the backdrop of intensifying climate change, maize, as a critical global food and feed crop, plays a pivotal role in ensuring food security and promoting sustainable agricultural development. This study utilizes panel data from 116 prefecture-level cities across nine provinces in China from 2003 to 2019 to analyze the dynamic impacts of maize prices, fertilizer price indices, and monthly precipitation on maize planting area and yield, employing fixed-effects models and the GMM estimation method. The empirical model incorporates key variables such as the previous year’s maize price, fertilizer price index, precipitation from March to May (affecting planting area), and monthly precipitation from April to September (affecting yield), while also accounting for control variables including urban population density, effective irrigation rate, industrial structure, and mechanization level. The results indicate that the previous year’s maize price and fertilizer price index exert significant positive effects on yield, while the fertilizer price index positively influences planting area, and maize price shows a significant negative effect on planting area. The impact of precipitation varies by month: precipitation in July and August enhances yield, whereas precipitation in April and September negatively affects yield. Additionally, March precipitation has a significant negative effect on planting area, while April precipitation positively affects planting area. Robustness tests further confirm the reliability of these findings. Moreover, the study identifies a diminishing marginal effect of agricultural technological progress and proposes policy recommendations, including optimizing irrigation infrastructure, promoting stress-resistant crop varieties, and fostering technological innovation. These findings provide theoretical insights and empirical support for improving maize production efficiency and ensuring food security.

Agricultural production trusteeship, through a “service-driven large-scale operation,” provides a new pathway for improving agricultural production efficiency and reducing resource waste. Based on micro-survey data from farmers in Shandong Province, and employing a research approach that combines theoretical and empirical analysis, this study reveals the mechanism by which agricultural production trusteeship impacts agricultural production efficiency. The research finds that agricultural production trusteeship has a significant positive effect on agricultural production efficiency, and this conclusion remains robust even after accounting for endogeneity issues. Agricultural production trusteeship enhances agricultural production efficiency by strengthening economies of scale, with indirect effects from economies of scale accounting for 45.63% of the total effect on agricultural production efficiency. Under full trusteeship, economies of scale become more pronounced, with the indirect effects reaching 51.23%. This study also demonstrates that the pathway of “land transfer → large-scale operation → economies of scale → agricultural production efficiency” is not the only route. The “service-driven large-scale operation” model under agricultural production trusteeship has significant potential to improve efficiency, reduce resource waste, and better fit the context of China’s smallholder economy. The paper provides policy recommendations for promoting agricultural trusteeship services, including developing context-specific trusteeship models, strengthening the role of village collectives, and increasing subsidies for agricultural machinery and equipment to trusteeship service organizations, in order to promote sustainable agricultural development and enhance resource use efficiency.

Reducing carbon emissions in crop production not only aligns with the goal of high-quality agricultural development but also contributes to achieving the “dual carbon goals”. Based on panel data from 31 provinces in China between 2010 and 2019, this paper explores the impact of Agricultural Socialized Services on carbon emissions in China’s crop production. Utilizing the classical IPCC carbon emission calculation model and spatial econometrics models, this study analyzes the temporal and spatial distribution characteristics of crop production carbon emissions and their driving factors, with a particular focus on evaluating the role of Agricultural Socialized Services in reducing carbon emissions in crop production. The empirical results reveal a “reverse U-shaped” curve for carbon emissions in crop production from 2010 to 2019, with a peak in 2015. Agricultural Socialized Services significantly reduced carbon emissions in crop production, especially in terms of emissions reductions from fertilizer and pesticide use, although the impact on other carbon sources such as plastic mulch, diesel, and tillage was relatively limited. Furthermore, Agricultural Socialized Services exhibited significant spatial spillover effects, effectively reducing local carbon emissions and generating positive carbon reduction effects in neighboring regions through cross-regional services. Based on these findings, the paper suggests improving the Agricultural Socialized Services system according to regional conditions to fully leverage its positive role in reducing carbon emissions in crop production. It also advocates accelerating the innovation of low-carbon agricultural technologies, encouraging farmers’ participation, and utilizing the organizational advantages of village collectives to jointly promote the development of Agricultural Socialized Services and achieve carbon reduction goals.

The profound impact of climate change on agricultural production, and the government’s fiscal expenditure for agriculture, is considered a crucial means to address this challenge. This study utilizes panel data from all prefecture-level cities in Heilongjiang Province from 2000 to 2020. Drawing upon the Cobb–Douglas production function, an economic climate model is constructed to empirically analyze the impact of climate change on grain yield in Heilongjiang Province. Furthermore, the role of fiscal expenditure for agriculture in mitigating the effects of climate change on grain yield is explored. Feasible Generalized Least Squares (FGLS) estimation is employed to address issues of “heteroscedasticity,” “autocorrelation within groups,” and “cross-sectional contemporaneous correlation” present in the model. The results indicate that climate change has a positive impact on rice and corn yields, while exhibiting a negative impact on wheat yield. The influence of climate change on crop yield is both linear and nonlinear. Specifically, temperature demonstrates a linear relationship with rice and corn yields, whereas precipitation shows a significant inverted U-shaped relationship with rice and corn yields. The impact of climate change on grain production in Heilongjiang Province varies significantly across regions. Fiscal expenditure for agriculture has a significant positive effect on the yield of major grain crops in Heilongjiang Province. In addressing the impact of climate change on grain production, agricultural fiscal expenditure enhances the positive effect of precipitation on rice and corn yields, while diminishing the positive impact of temperature on corn yield.

Existing studies have primarily examined the impact of farmland fragmentation on agricultural production from the perspective of crop yield per unit of land. However, they generally overlook the effects of farmland fragmentation on the productivity of both labor and capital. Drawing upon micro-level data from rice, wheat, and maize farmers across 14 provinces in China for the years 2019 and 2020, this paper measures the effects of farmland fragmentation on the labor productivity, land productivity, and capital productivity of these three different crops, within the same temporal and spatial dimensions. We utilize the internal instrumental variable method (KV-IV) to address potential endogeneity issues in the model. The research findings indicate: (1) Farmland fragmentation hampers the use of machinery, resulting in a significant decrease in the labor productivity of farmers. On average, for every 1% increase in the level of farmland fragmentation, labor productivity for rice, wheat, and maize farmers drops by 21.3%, 19.9%, and 21.9% respectively. (2) Farmland fragmentation has significantly increased the land productivity of rice. With every 1% increase in farmland fragmentation, the land productivity of rice farmers increases on average by 3.4%. However, the impact of farmland fragmentation on the land productivity of wheat and maize is not significant. (3) The capital productivity of rice, influenced by farmland fragmentation, mirrors the changes seen in land productivity. Rice farmers with higher levels of farmland fragmentation exhibit greater capital productivity. On average, with every 1% increase in the level of farmland fragmentation, the capital productivity of rice farmers increases by 6.7%. Conversely, farmland fragmentation has a significant negative impact on the capital productivity of both wheat and maize farmers. On average, for every 1% increase in farmland fragmentation, the capital productivity of wheat and maize farmers drops by 9.1% and 7.0% respectively. Based on the empirical results of this paper, we propose corresponding policy recommendations. In the conclusion, we delve into the underlying causes of farmland fragmentation in China and ascertain that, to address the issue of farmland fragmentation in the country, the government must take a leading role. The significance of this paper lies in analyzing the varying degrees and directions of the impact of farmland fragmentation on different crops, providing a basis for the government to implement differentiated farmland fragmentation management policies in different crop-producing regions in the future.