空间视角下城镇化对农业碳生产率的直接作用与间接溢出效应研究

THE DIRECT INFLUENCE AND INDIRECT SPILLOVER EFFECT OF URBANIZATION ON AGRICULTURAL CARBON PRODUCTIVITY BASE ON THE SPATIAL DURBIN MODEL

关键词:  农业碳生产率多维城镇化随机前沿生产函数空间杜宾模型空间溢出

Key words:  agricultural carbon productivity  multi dimensional urbanization  stochastic frontier production function  spatial Durbin model  spatial spillover

摘要:

［目的］发展低碳农业的核心在于全面提高农业碳生产率，而城镇化是影响农业碳生产率增长的重要因素。［方法］文章以1997—2014年中国31省区面板数据为样本，将城镇化划分为人口、经济、土地和社会4个维度，借助空间杜宾模型分别探讨其对农业碳生产率的作用及差异。［结果］1997—2014年，中国省域农业碳生产率存在空间正自相关性，邻近省区间集聚分布特征明显。控制其他变量后，城镇化是影响农业碳生产率的重要因素； 其中，人口城镇化与社会城镇化不利于当地农业碳生产率的提高，而土地城镇化则具有正向促进作用； 邻近地区人口城镇化对本地区农业碳生产率存在间接的正向溢出效应，其他城镇化并无此效应。而在利用熵值法构建综合城镇化变量后，仍发现城镇化不利于农业碳生产率的改善。［结论］因此，制定区域农业碳减排及污染治理政策时，应在优化农业产业结构及要素配置的同时，强化空间综合治理与区域联动机制建设，推动新型城镇化与农业现代化的协同发展，进而实现低碳转型与可持续发展。

Abstract:

The core of developing low carbon agriculture is to comprehensively improve agricultural carbon productivity, and urbanization is an important factor affecting the growth of agricultural carbon productivity. Taking the panel data of 31 provinces in China from 1997 to 2014 as a sample, this paper introduced spatial Durbin model to comparatively analyze the different effects of population urbanization, economic urbanization, space urbanization and social urbanization on agricultural carbon productivity. The results showed that there was a significant spatial auto correlation phenomenon in China′s provincial agricultural carbon productivity from 1997 to 2014, which reflected the strong agglomeration distribution characteristic of agricultural carbon productivity in neighboring provinces. After controlling the other variables, urbanization was an important factor influencing the increase of agricultural carbon productivity in general. And population urbanization and social urbanization had a negative effect on the improvement of agricultural carbon productivity in the local region of one province, while provincial space urbanization would promote the increase of agricultural carbon productivity in local area. At the same time, it was important that population urbanization in neighboring areas had a significant positive spillover effect on local agricultural carbon productivity, but economic urbanization, social urbanization and space urbanization in neighboring areas had no such effect. When the comprehensive urbanization variables was constructed by employing the entropy method, urbanization was not conducive to the improvement of provincial agricultural carbon productivity. Therefore, in the formulation of policies on regional agricultural carbon emission reduction and pollution control, it is not only necessary to further optimize the agricultural industry structure and the allocation factors, but also to strengthen the comprehensive management of space and regional linkage and coordination, so as to promote the coordinated development of new urbanization and agricultural modernization, and to further achieve low carbon transformation and sustainable development of the society.