农业技术效率对农业碳排放的影响基于空间溢出效应与门槛效应分析

Effects of agricultural technical efficiency on agricultural carbon emission: Based on spatial spillover effect and threshold effect analysis

  • 摘要: 农业技术是促进农业产业发展的根本力量, 探究其对农业碳排放的影响机制, 对实现我国“双碳”目标具有重要意义。本文基于2001—2020年我国31个省、直辖市和自治区(港澳台地区以外)的面板数据, 使用随机前沿模型对农业技术效率进行测算, 并对各地区农业碳排放总量与强度进行核算, 构建空间杜宾模型和以农业技术效率为门槛变量的门槛模型, 探究农业技术效率和农业碳排放的空间效应与非线性关系。结果表明: 全国农业碳排放总量与强度近年来呈下降趋势。中部地区农业碳排放总量高于东西部地区, 东部地区农业技术效率高于中西部地区, 而农业碳排放强度则低于中西部地区。农业碳排放强度与农业技术效率具有空间自相关性, 并表现为集聚特征, 集聚类型以高高聚聚和低低聚集为主。农业碳排放强度具有正向空间溢出效应, 而农业技术效率对农业碳排放强度则表现为负向空间溢出, 此外城镇化、人力资本水平和人均耕地面积对农业碳排放强度具有负向影响, 农业经济发展水平和农业受灾程度为正向影响。农业技术效率与农业碳排放强度存在双门槛效应, 当农业技术效率达到“拐点”后, 其对农业碳排放强度的影响转变为负向, 当进一步提升农业技术效率水平后, 其影响力会因边际效应递减而减弱。本研究为探索实现“双碳”目标的路径提供理论基础与政策依据。

     

    Abstract: Global warming, caused by the greenhouse effect, has triggered numerous unprecedented extreme weather events globally. Agricultural technology is the fundamental force that promotes the development of the agricultural industry. Studying the impact mechanism of agricultural technology on agricultural carbon emissions will help transform traditional agriculture into ecological, green, and low-carbon modern agriculture, and it is of great significance to the realization of carbon neutrality and carbon peaks. This study used panel data from 31 provinces and cities in China from 2001 to 2020. First, the stochastic frontier model was used to extend existing research from a broad and narrow sense of agricultural technical progress to agricultural technical efficiency. The total agricultural carbon emissions and intensity of agricultural carbon emissions were then calculated and compared. Finally, we constructed the spatial Dubin model and the threshold model with agricultural technical efficiency as the threshold variable, which revealed the spatial effect and non-linear relationship between agricultural technical efficiency and agricultural carbon emissions. The results showed that the total and intensity of agricultural carbon emissions had decreased in recent years. Central China had more agricultural carbon emissions than eastern and western China, and eastern China had a higher technical efficiency of agriculture and a lower carbon emission intensity of agriculture than central and western China. Agricultural carbon emission intensity and technical efficiency had spatial autocorrelation and agglomeration characteristics, and high-high clustering and low-low clustering are the main factors among the provinces. Agricultural carbon emission intensity had a positive spatial spillover effect on itself, but agricultural technical efficiency had a negative spatial spillover effect, which was conducive to the overall reduction of agricultural carbon emissions. Additionally, urbanization, human capital level, and per capita cultivated land area also had negative effects on agricultural carbon emission intensity, but the level of agricultural economic development and the degree of agricultural disaster had positive effects. There was a double threshold effect between agricultural technical efficiency and agricultural carbon emission intensity, which meant that when agricultural technical efficiency reached the “inflection point”, its impact on agricultural carbon emission intensity became negative, and after the level of agricultural technical efficiency was further improved, its influence weakened due to the diminishing marginal effect. Most existing research began with a broad or narrow definition of technological progress, but this study used technical efficiency as the research object after the decomposing technological progress in a broad sense, which further validated the indisputable and decisive role of technological progress in agricultural energy conservation and emission reduction. This study provides a theoretical and policy basis for exploring the path to achieving the “double carbon” goal.

     

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