Wei Jia

Purpose: China's grain subsidy policy was implemented nearly 20 years ago, and there have since been several changes in the subsidy content and methods. This study examines the impact of direct payment subsidies (DPS) on the economic effects of grain production for farmers. Design/methodology/approach: This study uses an instrumental variable fixed effect model to analyze the impact of DPS on the economic effects of grain production, based on data from the China Survey for Agricultural and Rural Economy from 2013 to 2020. Findings: The results indicate that DPS significantly enhance the economic effects of grain production for growers. The elasticity value of DPS and grain output, and DPS and technical efficiency (TE) of grain production are 0.636 and 0.073, respectively. These impacts exhibit significant heterogeneity across different age, income and planting scale. DPS also efficiently improve the structure of input factors to boost the economic effects of grain production. Our results indicate that these effects became more pronounced after agricultural policy reform, especially for large-scale farmers. Originality/value: This study measures the economic effects of grain production in two ways: grain output and TE. DPS has increased farmers’ enthusiasm for grain input and improved the structure of factor inputs, thereby promoting the economic effects of food production. The research results also confirm the positive effectiveness of China’s grain subsidy policy.

China's agricultural export has increased rapidly, but the export advantage has weakened. Agricultural enterprises (AEs) play a major role in China's agricultural export. Is there a bias in the export of AEs for improving either profit margin or productivity? The paper applies the panel data of Chinese AEs from 2014 to 2019 and uses the generalized method of moments and fixed effects (FE) model to test the impact of AEs’ export on profit margin and productivity. The results show that the productivity of Chinese agricultural export enterprises (AEEs) is significantly lower than that of agricultural non‐export enterprises (ANEs). The goal of AEs’ export is to increase profit margin rather than productivity; exports increase the profit margins of AEs, especially with a greater impact on the profit margin of low‐productivity AEs. The export scale has a higher impact on the profit margin of non‐continuous AEEs than that of continuous AEEs. However, the expansion of the export scale of AEs actually reduces their productivity. This study uses multiple methods to verify the robustness of the research conclusions.

I. Since joining the WTO, China’s agricultural trade has increased rapidly, but the trade deficit has become larger and the export advantage has become smaller. How to further improve the export ad...

This study aimed to analyze the impact of home bias on China’s trade border effects by constructing a pure exchange computable general equilibrium model. The results indicate that the border effects of external import, export, and trade in China are 6.96 times, 4.62 times, and 5.60 times their respective counterparts in interregional trade. On elimination of national bias, the border effects of China’s external import, export, and trade fell by 96.37%, 93.71%, and 95.18%, respectively, while border effects of China’s interregional trade became 8.06%. By eliminating regional bias, the border effects of China’s external imports, exports, and trade decreased by 3.63%, 6.29%, and 4.82%, respectively.

Guiding and encouraging farmers to adopt low-carbon agricultural technologies is highly significant for reducing greenhouse gas emissions, mitigating climate change, and achieving agricultural production development and food security. This study used survey data from 1843 grain farmers in 14 provinces of China to empirically analyze the impact of non-farm employment experience and risk preferences on grain farmers’ low-carbon agricultural technology (LCAT) adoption. The results show that for grain farmers: (1) non-farm employment experience significantly promoted the adopting of LCAT. The probability of adopting LCAT by those with non-farm experience is 23.5% higher than those without. (2) Non-farm employment experience reinforced their risk preferences and promoted the adoption of LCAT. The adoption probability of LCAT of those with high-risk preferences was 6.1% higher than those with low-risk preferences. (3) The impact of non-farm employment experience on adopting LCAT was more significant for those with high education and training. Non-farm employment experience outside the province and employment experience in the tertiary sector while working outside significantly affect grain farmers’ LCAT adoption.

The improvement of grain processing capacity is crucial to the realization of grain security. Enterprises are important grain processing bodies and their productivity directly determines grain processing capacity. Chinese grain processing enterprises still have difficulties, and how to further improve grain processing capacity and the total factor productivity of grain processing enterprises may be an important aspect. We used the meta-frontier Malmquist index to measure the total factor productivity of grain enterprises as well as judge the change trend and regional gap, applying the classical regression model to test the convergence of China’s overall and regional grain enterprises’ total factor productivity. This research finds that the total factor productivity of grain processing enterprises increased by 1.18% annually during the sample period, and that of the central region rose more quickly than the other areas of China. Technical progress contributes more to enterprises’ total factor productivity, but technical efficiency may become a key factor in determining it. The difference in the growth rate of the grain processing enterprises’ total factor productivity among different ones in the eastern and western regions is gradually narrowing, while that of the central region is gradually expanding; there is an obvious technological catch-up effect between and within the regions, especially in the central area of China.

Increasing grain production and ensuring food security are always major issues in China, which are related to the sustainable development of the nation. The sudden outbreak of COVID-19 in 2020 has brought new challenges to global food security, which highlights the “ballast stone” and “stabilizer” role of food. China’s food security must rely on domestic production. As an important production factor, the Internet is also an important channel for farmers to obtain agricultural information, which can effectively reduce the information search cost and information asymmetry. Existing studies have mainly focused on the impact of Internet use on agricultural inputs, agricultural prices, and agricultural efficiency; there are few studies on the impact of Internet use on grain production. To fill this gap, based on the micro survey data of 1242 maize farmers in 13 provinces in China, this paper employs linear regression models and PSM methods to deeply explore the impact of Internet use on farmers’ grain production. The results show that Internet use has a significant positive impact on the grain production of farmers. Compared with the farmers who do not use the Internet, Internet use increases the maize yield of farmers by 14.25%. The heterogeneity analysis further shows that the impact of Internet use on the grain production of different farmers varies significantly: the maize yield per ha after using the Internet for farmers of younger, low education level, large-scale, and living in well-developed villages had increased by 13.65%, 15.38%, 23.94%, and 10.64%, respectively, compared with the counterfactual scenario of farmers who do not use the Internet. The results of this paper have passed the robustness test.

Purpose: Market integration in China is still progressing, while the border effects of trade among regions still exist. The question of whether eliminating or weakening regional bias can promote of China's agricultural trade still remains an important issue. This paper analyzes the impact of regional bias on China's agricultural trade.Design/methodology/approach: This paper constructs a pure exchange computable general equilibrium model of nine regions and three sectors, and analyzes the impact of regional bias on China's regional agricultural trade; Comparing the differences of regional bias on China's inter-regional and external agricultural trade, the paper especially analyzes the impact of the agricultural imports and exports in eight regions of China.Findings: The results show that regional bias has had substantial impacts on China's agricultural trade. Elimination of regional bias would therefore increase China's agricultural exports and imports by factors of 1.32 and 1.63, respectively while its agricultural trade deficit would increase by 84%. Inter-regional agricultural trade in China would increase by 3.53 times. With the elimination of regional bias, the Northern coastal, Central and Northwestern regions would have the largest increase in inter-regional agricultural trade. Unlike the Northern coastal region, inter-regional agricultural import in the Central and Northwestern regions tends to be greater than inter-regional agricultural exports.Originality/value: This paper thus aims to fill existing gap in investigating the impacts of regional bias on China's agricultural trade. Firstly, the model proposed in this paper does not only consider the linkage between the agricultural and non-agricultural sectors, but also the inter-regional agricultural trade linkages of the different regions in China. Secondly, the authors decompose home bias into national and regional biases and assess how regional bias affects agricultural trade of the various regions of China.

There is an “export productivity paradox” in Chinese enterprises, which has been confirmed in agricultural enterprises. This paper attempts to explain this phenomenon from the perspective of the components of TFP. This paper uses the SFA-Malmquist method to decompose and compare the TFP of China’s agricultural export enterprises based on the data of the state-level leading agricultural enterprises from 2016 to 2017. The conclusions are as follows: firstly, China’s agricultural TFP shows a negative growth trend, and the growth rate of TFP of agricultural export enterprises is less than that of agricultural non-exported enterprises; secondly, the growth rate of TFP of grain and animal husbandry export enterprises is less than that of non-export enterprises; the growth rate of TFP of private agricultural export enterprises is lower than that of non-export enterprises of the same type; the growth rate of TFP of export enterprises in eastern and western regions is lower than that of non-export enterprises; and thirdly, technical progress is an important reason for the change of TFP of China’s agricultural enterprises. However, compared with agricultural non-exported enterprises, improving the technical efficiency of enterprises can more promote the TFP of agricultural export enterprises.