我国经济周期波动的非对称性和持续性研究

本文利用1979年至2004年之间中国GDP季度数据,采用三区制马尔可夫均值和方差转移的二阶自回归(MSMV(3)-AR(2))模型和贝叶斯Gibbs抽样非参数估计方法,对我国经济周期波动的非对称性和持续性进行了实证分析。实证结果表明,MSMV(3)-AR(2)模型对我国经济状况提供了很好的拟合,显著支持增长率序列具有三区制状态:低速增长阶段,适速增长阶段和高速增长阶段。我国经济周期的非对称性主要体现在各个增长阶段的均值、方差、阶段性之间的转移概率的不同。我国经济周期的持续性主要体现在各个增长阶段的自维持概率和阶段性之间的转移概率的不同。此外,我国经济"适速增长阶段"的稳定性最高,"高速增长阶段"的平均持续期最长。     

旅游者关系生命周期与目的地关系营销策略——以主题公园为例

从顾客关系生命周期角度实施关系营销策略对旅游服务提供商和旅游者建立长期关系非常重要.本文在顾客关系生命周期3阶段模型的基础上,结合旅游服务业和旅游者的特性,同时考虑了时间要素和网络环境要素,补充了在旅游者"消费阶段"之后的"评估阶段",提出了旅游服务业适用的旅游者关系生命周期4阶段动态模型:Dynamic Attention-Transaction-Experience-Evaluation Model(简称DATEE模型).该模型为旅游目的地服务提供商在互联网环境下制定关系导向的营销策略提供了框架支持.本文并结合国内外典型的主题公园营销实例进行了分析.     

经济周期与证券市场波动关联性——基于向量SWARCH模型的新证据

本文认为关于经济周期与证券市场波动关联性研究结论的分歧源自仅注重样本区间内整体关联性的检验,忽视了分析经济增长不同阶段与证券市场波动的特定关联性。基于向量SWARCH模型,本文实证检验了我国GDP增长率与证券收益率间的关联性,结论表明,虽然“整体关联性”检验不支持经济周期与市场波动间存在显著相关性的结论,但“状态相关系数”却显示两者间的关联性具有“区制转移”特征,并体现了对前者依赖的“门限效应”和“非对称效应”。     

V-Matrix: A wave theory of value creation for big data

This paper examines the “V-Matrix” and provides a wave theory life cycle model of organizations’ adoption of big data. The V-Matrix is based on the big data five “V’s”: Volume, Velocity, Variety, Veracity, and Value and captures and enumerates the different potential states that an organization can go through as part of its adoption and evolution towards big data. We extend the V-Matrix to a state space approach in order to provide a characterization of the adoption of big data technologies in an organization. We develop and use a wave theory of implementation to accommodate a firm’s movement through the V-Matrix. Accordingly, the V-Matrix provides a life cycle model of organizational use of the different aspects of big data. In addition, the model can help organizations’ plan for decision-making use of big data as they anticipate movement from one state to another, as they add big data capabilities. As part of this analysis, the paper examines some of the issues that occur in the different states, including synergies and other issues associated with co-occurrence of different V’s with each other. Finally, this paper integrates the V-Matrix with other data analytic life cycles and examines some of the implications of those models.     

Real exchange rate misalignment and business cycle fluctuations in the Asia-Pacific

Real exchange rate (RER) misalignment, which is the deviation between the actual real exchange rate from its equilibrium, occurs frequently among developing countries. Studies have shown that RER misalignment may have negative economic implications, such as a decline in economic growth, exports, and export diversification and an increased risk of currency crises and political instability. Using quarterly data for 22 sample countries from 1990 to 2018, this paper investigates the impact of RER misalignment on business cycles in the Asia-Pacific by employing a panel vector autoregression involving consumer price index (CPI) inflation, output gap, short-term interest rates, and RER misalignment. We find that RER overvaluation may reduce CPI inflation and short-term interest rates. We also find that the Asia-Pacific region is highly heterogeneous in that the output gaps of some countries, particularly from the Southeast Asian region, are more susceptible to RER misalignment shocks.     

重压力下的中国金融发展

2021年,百年变局与世纪疫情交织,我国经济发展和疫情防控保持全球领先地位。中央坚持以人民为中心推动金融发展,国内货币金融环境从极度宽松回归相对中性,宏观杠杆率降幅明显,货币政策空间明显拓宽。2022年,面临需求收缩、供给冲击、预期转弱三重压力,我国风险挑战明显增多。国内方面,房地产市场快速去杠杆导致经济下行压力加大和金融市场波动加剧,中小银行资产质量恶化和盈利能力弱化并存,隐性债务严监管下弱资质城投的再融资风险和违约风险趋升。国际方面,中美两国经济金融周期开始错位,需警惕美联储加速退出超寬松货币政策和大宗商品价格高位盘整造成的外部冲击。应对三重压力要求金融宏观调控坚持稳字当头、稳中求进,加大货币政策总量宽松力度,结构性货币政策着力提振最终需求,防范化解重点领域风险稳定市场信心。