学术界近期开始关注人工智能技术对收入不平等的影响,但其收入分配效应的形成机理研究尚处于初始阶段,而且定量评估明显不足,尤其缺乏来自发展中国家的经验证据。本文基于Acemoglu and Restrepo(2018a)的人工智能技术模型,引入高技术与...学术界近期开始关注人工智能技术对收入不平等的影响,但其收入分配效应的形成机理研究尚处于初始阶段,而且定量评估明显不足,尤其缺乏来自发展中国家的经验证据。本文基于Acemoglu and Restrepo(2018a)的人工智能技术模型,引入高技术与低技术两部门分类,推演人工智能技术的收入分配效应,结合中国2001—2016年全国及省级层面数据,分类测算其劳动收入分配的岗位更迭效应和生产率效应。结果发现:①人工智能技术在引发劳动岗位更迭的同时,非对称地改变不同技术部门生产率影响劳动收入分配,诱致高、低技术部门劳动收入差距年均扩大0.75%。②人工智能技术的岗位更迭效应倾向于在低技术部门通过自动化扩张、在高技术部门以新岗位创造方式,加剧收入不平等,而生产率效应存在门槛特征。③人工智能技术在资本和非技术密集型地区的收入分配效应更为突出,且对劳动和技术密集型地区的影响不断增大。为应对人工智能技术对劳动力市场就业结构和收入不平等的冲击,政府应健全就业培训和失业保障制度,制定差异化的区域政策,积极引导人工智能技术朝人机协作和收入平等方向发展。展开更多
Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental e...Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental externalities. This paper quantiifes the productivity effect and the optimal amount of pesticides in rice, cotton and maize production in China from the economic perspective. Using survey data col ected in 2012 and 2013, both Cobb-Douglas and Weibul damage control speciifcations are used to estimate the production function. Results show that pesticides have statistical y signiifcant pro-ductivity effect on crop yield. On the condition of Weibul damage control speciifcations, the marginal products of 1 kg of the active ingredients of pesticides for rice, cotton and maize are 71.06, 22.73 and 98.45 kg, respectively. However, 57, 64 and 17%of the actual amount of pesticides are overused for rice, cotton and maize, respectively. Moreover, the productivity effect of pesticides would be overestimated using Cobb-Douglas speciifcation without incorporating a damage control agent.展开更多
文摘学术界近期开始关注人工智能技术对收入不平等的影响,但其收入分配效应的形成机理研究尚处于初始阶段,而且定量评估明显不足,尤其缺乏来自发展中国家的经验证据。本文基于Acemoglu and Restrepo(2018a)的人工智能技术模型,引入高技术与低技术两部门分类,推演人工智能技术的收入分配效应,结合中国2001—2016年全国及省级层面数据,分类测算其劳动收入分配的岗位更迭效应和生产率效应。结果发现:①人工智能技术在引发劳动岗位更迭的同时,非对称地改变不同技术部门生产率影响劳动收入分配,诱致高、低技术部门劳动收入差距年均扩大0.75%。②人工智能技术的岗位更迭效应倾向于在低技术部门通过自动化扩张、在高技术部门以新岗位创造方式,加剧收入不平等,而生产率效应存在门槛特征。③人工智能技术在资本和非技术密集型地区的收入分配效应更为突出,且对劳动和技术密集型地区的影响不断增大。为应对人工智能技术对劳动力市场就业结构和收入不平等的冲击,政府应健全就业培训和失业保障制度,制定差异化的区域政策,积极引导人工智能技术朝人机协作和收入平等方向发展。
基金financial support from the National Natural Science Foundation of China (71173014 and 71210004)the China Scholarship Council (201306030053)
文摘Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental externalities. This paper quantiifes the productivity effect and the optimal amount of pesticides in rice, cotton and maize production in China from the economic perspective. Using survey data col ected in 2012 and 2013, both Cobb-Douglas and Weibul damage control speciifcations are used to estimate the production function. Results show that pesticides have statistical y signiifcant pro-ductivity effect on crop yield. On the condition of Weibul damage control speciifcations, the marginal products of 1 kg of the active ingredients of pesticides for rice, cotton and maize are 71.06, 22.73 and 98.45 kg, respectively. However, 57, 64 and 17%of the actual amount of pesticides are overused for rice, cotton and maize, respectively. Moreover, the productivity effect of pesticides would be overestimated using Cobb-Douglas speciifcation without incorporating a damage control agent.
