摘要
研究目的:中国工业发展与土地资源现状均对工业土地集约利用提出了迫切需求,而工业企业的土地集约利用则是实现区域工业土地集约利用的微观基础。研究方法:在现有研究多集中于中、宏观层面的背景下,本文将研究深入至企业微观层面,先从理论角度分析了各个驱动因素及其传导机理。然后选取中国工业化进程较快的两个省份(广东和江苏)作为研究区域,以1999—2009年1290家工业企业面板数据为样本进行实证检验,实证结果与理论分析相互印证。研究结果:在所有驱动因素中,工业用地价格对集约用地促进作用最明显;中国目前处于土地边际报酬递增阶段,单位土地要素投入的增加可促进企业集约用地,其中劳动投入的系数最大;外资企业相较于其他所有制企业,集约用地水平较高。研究结论:企业规模和企业距港口距离与集约用地水平呈倒U型关系;良好的地理区位、盈利水平及经济环境等均能在一定程度上促进企业集约用地。
With rapid industrialization in China, the land resource is increasingly scarce. It is important to reveal the driving factors on intensive land use of industrial enterprises, which can effectively improve relevant land policies and reduce the extensive land use. Under the background of existing research focusing on the macro or median level, this article analyzed the driving factors from the view of theory and explored its transmission mechanism in the micro level of the enterprises. And then, based on 1290 industrial enterprises from 1999 to 2009 in Guangdong and Jiangsu provinces, this article studied the driving factors of intensive land use. The empirical results were in accordance with theoretic analysis. The results showed that industrial land price is the most significant driving factors, and input factor can improve the land use intensity significantly, especially the labor input, because China is on the stage of increasing marginal land returns, and the land use intensity of foreign capital enterprises is higher than other ownership enterprises. In addition, the enterprise size and distance from ports presents an inverted U-shaped relationship with land use intensity,and the land use intensity can be enhanced effectively by good location, level of profitability and economic environment.
作者
张琳
王亚辉
郭雨娜
刘冰洁
ZHANG Lin WANG Ya-hui GUO Yu-na LIU Bing-jie(Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China)
出处
《中国土地科学》
CSSCI
北大核心
2016年第10期20-28,共9页
China Land Science
基金
国家自然科学基金"微观视角下工业企业集约用地的动力机制和政策优化"(71403038)
中央高校基本科研业务费"产业升级中的土地资源协调保障机制研究"(DUT16RW128)
关键词
土地利用
工业
集约
驱动因素
land use
industry
intensive
driving factors