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Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

The purpose of this paper is to establish a synthetic evaluation index system of new socialist countryside (NSC) development at county level in China, and by which to evaluate the level of NSC construction among different regions in China. Then, some problems of rural development can be found and corresponding measures can be proposed, which could provide references for policymaking.

First, from agricultural, rural and farmers' perspective, a preliminary index system which containing 44 indicators was put forward. Then, combining with a series of subjective and objective indicator screening methods, such as fuzzy synthetic evaluation, clustering analysis, correlation and variation coefficient analysis, the final index system containing 22 indicators was established. Third, combining with factor analysis, the final index system was used to evaluate the level of NSC construction in 28 counties of China in 2007. Finally, we calculated district factor scores by a model and gave an aggregate index ranking of different regions.

NSC construction at county level is not well developed in China and there are significant geographical differences among different districts. First, NSC construction in Shanghai, Beijing, Nanjing, Guangzhou and Hangzhou is relatively better. Second, NSC construction of East China is better than that of North China and Central China. Northeast of China is better than Southwest and Northwest. Third, NSC construction in municipalities is higher than non‐municipalities. Rural development in Western regions of China needs to be paid special attention.

A final evaluation index system including 22 indicators was designed. These indicators are complete, independent, weakly correlative and stable. The index system can be further applied to evaluate other regions' NSC development. The evaluation results can provide useful references for NSC reform in the whole nation.