人口老龄化正在成为当代全球最受关注的社会变革之一,它对世界范围内的所有经济与社会领域产生着愈加重要的影响,这一趋势的蔓延促使国内外经济学者关注其带来的诸多效应。本文借助Cite Space软件,以Web of Science数据库中经济学领域...人口老龄化正在成为当代全球最受关注的社会变革之一,它对世界范围内的所有经济与社会领域产生着愈加重要的影响,这一趋势的蔓延促使国内外经济学者关注其带来的诸多效应。本文借助Cite Space软件,以Web of Science数据库中经济学领域的人口老龄化英文文献为研究对象,使用共词聚类分析方法,对2000-2015年间人口老龄化经济学领域的研究成果进行统计分析,并通过战略坐标进一步图示人口老龄化经济学领域的研究现状和热点,以此展现全球范围内国际学者所关注的人口老龄化问题与方向,总结人口老龄化研究的前沿成果、高产国家、高产研究机构、高产作者、主要英文期刊分布等科学研究信息。文献计量分析结果发现:在人口老龄化所涉及到的问题中,"临终成本"展开更多
This paper investigates a non-Bayesian social learning model, in which each individual updates her beliefs based on private signals as well as her neighbors＇ beliefs. The private signM is involved in the updating pro...This paper investigates a non-Bayesian social learning model, in which each individual updates her beliefs based on private signals as well as her neighbors＇ beliefs. The private signM is involved in the updating process through Bayes＇ rule, and the neighbors＇ beliefs are embodied in through a weighted average form, where the weights are time-varying. The authors prove that agents eventually have correct forecasts for upcoming signals, and all the beliefs of agents reach a consensus. In addition, if there exists no state that is observationally equivalent to the true state from the point of view of all agents, the authors show that the consensus belief of the whole group eventually reflects the true state.展开更多
文摘人口老龄化正在成为当代全球最受关注的社会变革之一,它对世界范围内的所有经济与社会领域产生着愈加重要的影响,这一趋势的蔓延促使国内外经济学者关注其带来的诸多效应。本文借助Cite Space软件,以Web of Science数据库中经济学领域的人口老龄化英文文献为研究对象,使用共词聚类分析方法,对2000-2015年间人口老龄化经济学领域的研究成果进行统计分析,并通过战略坐标进一步图示人口老龄化经济学领域的研究现状和热点,以此展现全球范围内国际学者所关注的人口老龄化问题与方向,总结人口老龄化研究的前沿成果、高产国家、高产研究机构、高产作者、主要英文期刊分布等科学研究信息。文献计量分析结果发现:在人口老龄化所涉及到的问题中,"临终成本"
基金supported by the National Natural Science Foundation of China under Grant Nos.61074125 and 61104137the Science Fund for Creative Research Groups of the National Natural Science Foundation of China under Grant No.61221003the National Key Basic Research Program (973 Program) of China under Grant No.2010CB731403
文摘This paper investigates a non-Bayesian social learning model, in which each individual updates her beliefs based on private signals as well as her neighbors＇ beliefs. The private signM is involved in the updating process through Bayes＇ rule, and the neighbors＇ beliefs are embodied in through a weighted average form, where the weights are time-varying. The authors prove that agents eventually have correct forecasts for upcoming signals, and all the beliefs of agents reach a consensus. In addition, if there exists no state that is observationally equivalent to the true state from the point of view of all agents, the authors show that the consensus belief of the whole group eventually reflects the true state.
