Spatial Dependence Evaluation of Agricultural Technical Efficiency—Based on the Stochastic Frontier and Spatial Econometric Model

Ziqi Yin,Jianzhai Wu

doi:10.3390/su13052708

Abstract

In recent years, through the implementation of a series of policies, such as the delimitation of major grain producing areas and the construction of advantageous and characteristic agricultural product areas, the spatial distribution of agriculture in China has changed significantly; however, research on the impact of such changes on the efficiency of agricultural technology is still lacking. Taking 11 cities in Hebei Province as the research object, this study examines the spatial dependence of regional agricultural technical efficiency using the stochastic frontier analysis and spatial econometric analysis. The results show that the improvement in agricultural technical efficiency is evident in all cities in Hebei Province from 2008 to 2017, but there is scope for further improvement. Industrial agglomeration has statistical significance in improving the efficiency of agricultural technology. Further, there is an obvious spatial correlation and difference in agricultural technical efficiency. Optimizing the spatial distribution of agricultural production, promoting the innovation, development, and application of agricultural technology, and promoting the expansion of regional elements can contribute to improving agricultural technical efficiency.

Highlights

Belmonte-UreñaWhile agricultural development has greatly increased food supply over the past half century, it has consumed nearly 75% of fresh water resources; farmland or pasture occupies more than 50% of the global ice-free land area [1,2,3]
Production frontier analysis is commonly used to measure technical efficiency. It can be divided into non-parametric and parametric methods according to whether the specific form of the production function is known. The former is represented by data envelopment analysis (DEA), while the latter by stochastic frontier analysis (SFA)
EFi,t is the agricultural technical efficiency of city i at time t; Controlit is a matrix composed of control variables, including the industrial agglomeration index, logarithm of the number of rural science and technology practitioners, proportion of the tertiary industry, logarithm of effective irrigation area, logarithm of per capita gross domestic product (GDP), per capita sown area, proportion of grain-sown area, and annual average temperature. ui is the intercept term of the spatial fixed effect; wij is the element of row i and column j of the spatial weight matrix. wij plays a different role in Equations (3)–(5)

Summary

Introduction

Belmonte-UreñaWhile agricultural development has greatly increased food supply over the past half century, it has consumed nearly 75% of fresh water resources; farmland or pasture occupies more than 50% of the global ice-free land area [1,2,3]. The development of green and efficient modern agriculture requires that technical efficiency be improved to increase future agricultural supply [8,9]. Given that the concept of green development has been thoroughly implemented, only by improving its efficiency of agricultural production can the increasing demands for food due to population growth and economic development be met [12]. In this context, it is of great practical significance to explore the influencing factors and mechanisms of agricultural technical efficiency in the new period

Methods

Results

Discussion

Conclusion