Agricultural production efficiency estimation and spatiotemporal convergence characteristic analysis in the Yangtze River Economic Belt: A semi‐parametric metafrontier approach

Abstract

The sustainable development goals regard improving agricultural production efficiency (APE) as the main method to solve food security problems. Based on the geographical cognition, combined with the functional positioning, we used meta semi‐parametric linear programming and spatial convergence models to analyze the spatiotemporal convergence characteristics of APE in the Yangtze River Economic Belt from 2000 to 2020. The results show that (1) under the framework of metafrontier analysis, the APE increases while maintaining an olive‐shaped stable structure of “sharp at both ends and wide in the middle”; (2) the efficiencies in agricultural production areas and the middle reaches has obviously declined compared with that of non‐agricultural production areas; and (3) non‐spatial factors and spatial factors jointly drive the convergence. The research results can provide references for clarifying the evolution law of regional agriculture and formulating differentiation macro policies.

Agricultural Production Efficiency and Ecological Transformation Efficiency in the Yangtze River Economic Belt

“…Among them, considering that the ecological index should have the dual requirements of the attribute of input factors of production activities and the description of land ecological change, NPP is used as the input variable to characterize land ecology in the calculation of APE. Therefore, according to the principles of representativeness, accuracy and conciseness, the number of employees in the primary industry, the amount of chemical fertilizer, the total power of agricultural machinery, the sown area and the total value of NPP are selected as input variables, and the added value of the primary industry, which comprehensively reflects the agricultural economic output, is selected as the output variable [7,[16][17][18]. The above data come from the China Regional Economic Statistical Yearbook, the statistical yearbooks of provinces and the Resource and Environmental Science Data Center of the Chinese Academy of Sciences.…”

“…Related studies provide strong support for the formulation of a series of policies on urban development, agricultural protection and ecological conservation. Guo et al [17] employed the semiparametric metafrontier approach and spatial convergence model to analyze the spatiotemporal convergence of APE in the Yangtze River Economic Belt (YREB). They discovered that there was a differential convergence law between agricultural production areas and nonagricultural production areas, emphasizing the need for regulating regional agricultural activities from both input and output to optimize the utilization of land resources.…”

“…The Yangtze River, as the mother river of the Chinese nation, supports the development of the Chinese nation [10]. The YREB includes two important grain-producing areas, the middle and lower reaches of the Yangtze River and the Sichuan Basin, as well as regional grain production bases such as Chengdu Plain, Jianghan Plain, Dongting Lake Plain, Poyang Lake Plain, Jianghuai region and Taihu Lake Plain, which shoulder the responsibility and mission of ensuring national food security [17]. However, with the continuous improvement of urban development and ecological priority, the stability and sustainability of agricultural production in the YREB are facing the dual threats of insufficient agricultural space and low output benefits.…”

Measurement of Agricultural Eco-Efficiency and Analysis of Its Influencing Factors: Insights from 44 Agricultural Counties in Liaoning Province

“…This has gradually become the mainstream method for evaluating AEE. Although the parameter method represented by stochastic frontier analysis (SFA) has been widely used in EE [13,14], few studies have applied it to measure AEE. Methods such as spatial autocorrelation and exploratory spatial data analysis (ESDA) are often used to further analyze spatial differences in AEE.…”

Spatial–Temporal Characteristics and Influencing Factors of Eco-Efficiency of Cultivated Land Use in the Yangtze River Delta Region

“…At present, relevant studies on the ECLU at home and abroad mainly discuss measurement methods, spatial and temporal evolution characteristics, and influencing factors [8][9][10][11][12][13]. In terms of efficiency measurement, research has mainly been based on the differences in research backgrounds and objectives and has used different methods to quantitatively measure the ECLU [14,15], such as the stochastic frontier production function method [16], the DEA model [17], the SBM model [18], the Malmquist model [19], the Bootstrap method of random sampling [20], and the SWAT model [21], among others. Scholars have used the spatial autocorrelation method [22], kernel density method [23], exploratory spatial data analysis (ESDA) method [18], G i * index [24], and other methods to detect spatial and temporal evolution characteristics of cultivated land utilization efficiency.…”