中间品进口会促进企业生产率增长吗——基于中国企业微观数据的分析

本文运用2000-2005年中国工业企业数据库和海关数据库的匹配数据,分析进口中间品的使用对中国企业全要素生产率影响。研究发现:与非进口企业对比,进口企业在反映企业经营状况的各项指标上都强于非进口企业,一直进口的企业在各项指标上最高,东部地区企业和高人均资本行业的企业表现最佳;进口中间品对企业层面全要素生产率有显著促进作用,企业从非进口状态转为进口状态能促进全要素生产率提高7.49个百分点,这种促进作用对低人均资本行业企业和西部企业尤为明显。这一结论的政策含义在于,后金融危机时代,中国须重新调整"出口主导,进口从属"外贸发展思路,实施积极的进口贸易战略,促进企业全要素生产率的提高和技术创新,鼓励中、西部企业和低人均资本行业企业参与到经济全球化,边干边学,促进企业全要素生产率水平更快提高。     

异质机构、企业性质与关联交易

基于2007-2009年3618家A股上市公司数据,本文从关联交易密度和关联交易频率两个维度对机构持股、企业性质和关联交易之间的关系进行了实证研究。结果发现：机构持股对企业关联交易的抑制作用并不显著,这种不显著性主要归因于证券投资基金;不同性质的机构对企业关联交易的抑制作用不同,其中证券投资基金对企业关联交易基本不存在抑制作用,而险资和合格的境外机构投资者则相反;企业性质对异质机构和关联交易间的关系有显著的调节作用,民营上市公司中机构投资者的抑制作用要强于国有上市公司。     

资产价格泡沫研究述评:实验金融学视角

本文从实验金融学的视角介绍了资产泡沫最新的定义和分类,阐述了投机性泡沫、理性泡沫与非理性泡沫之间的区别和联系,着重从信息对称、信息不对称、有限套利泡沫、异质信念和实验金融五个方面系统评述了资产价格泡沫理论的发展历程和新进展,指出该领域进一步的研究方向和中国开展资产价格泡沫研究的重要意义。研究表明,随着现代金融学的高速发展,学界对资产泡沫的研究日益深入。特别是非理性和实验金融学视角的引入,突破了传统金融框架的束缚,为这一课题研究带来了新的认知和理解。即便如此,目前仍无法根除资产泡沫产生的可能性。很多相关问题,如资产泡沫产生的时间和根本原因,仍然等待着学者们去探索和研究。     

经济波动对城乡居民的间接福利效应差异研究

本文将经济波动对经济增速的负面影响引入福利损失模型,构建了量化经济波动对居民福利的间接影响模型,并采用1985-2007年全国以及28个省市区的城乡居民消费数据对异质居民在经济波动过程中承受的间接福利损失进行测度。研究结果表明,经济波动通过负面影响经济增速给居民带来了不容忽视的间接福利损失,忽略经济波动与经济增速的联系得到的福利损失估算值存在低估问题;无论是全国层面,还是省级层面,农村居民承受的间接福利损失都倾向于大于城镇居民。因此,为了切实提高居民的福利水平,中国政府应在保持经济增长的同时,更要重视保持城乡差异化经济的平稳性。     

异质信念对股价波动的非对称性影响研究

本文利用上市公司的相关数据,实证研究了异质信念对我国股票市场股价波动的 影响,探讨了在不同的市场行情和企业性质下异质信念对股价波动的非对称性影响,并对融资 融券推出前后异质信念对股价波动的非对称性影响进行了研究。研究结果表明：（1）股票投 资者异质信念的差异程度越大,股价偏离其股票的内在价值就越大,进而导致股价的波动程度 更剧烈;（2）异质信念对股价波动的影响呈非对称性,在熊市行情下异质信念对股价波动的 影响要高于牛市,在国有企业背景下异质信念对股价的波动程度大于非国有企业;（3）融资 融券推出后在一定程度上可以减缓异质信念对股价波动的影响。     

Has local informational advantage disappeared?

This study examines how changes in the information environment affect the informational advantage of geographically proximate agents. The long‐term advantage of local agents disappeared at the turn of the millennium. This is accompanied by the reduction in local bias of institutional investors and equity analysts. However, institutional investors continue to trade local stocks disproportionately more often than non‐local stocks; moreover, their local trades outperform non‐local trades in the short term—even for large and liquid stocks. Our results are consistent with improvements in the information environment shortening the horizon of proximity‐based informational advantage.     

Speculative dynamics and price behavior in the Shanghai Stock Exchange

This article examines the extent to which the trading behavior of heterogeneous investors manifests in stock price changes of asset portfolios which constitute the Shanghai Stock Exchange. There are three major findings that materialize. Firstly, reliable statistical evidence of a negative relation between the conditional first and second moments of the return distributions of stock prices lends support to the volatility feedback effect. Secondly, ‘feedback’, or momentum-type investors, are not present in this market as is often detected from the daily price changes of other industrialized markets. Finally, trade volume as a proxy for ‘information-driven’ trading suggests that such investors play a statistically significant role in stock price movements. Parameter estimates from this latter group of investors imply that a rise in stock prices from a high volume trading day is more likely than a rise resulting from a low volume trading day.     

Heterogeneous beliefs with herding behaviors and asset pricing in two goods world

We construct a incomplete information equilibrium model with heterogeneous beliefs and herding behaviors to identify their joint effects on the dynamics of asset prices. Herding behaviors make investors revise some of their estimations about expected growth rates of goods streams toward to the other one’s by a manner of weighted average of their own forecast and the other’s. As we expected, herding behaviors generate influences on the Radon Nikodym derivative, that is so-called “sentiment” as in Dumas et al. (2009), and in turn not only impact the dynamics of asset prices but also generate influences on investors’ survivals. We also show that introducing heterogeneous beliefs with herding behaviors permits to explain both the Backus–Smith puzzle and the mixed results about the influences of herding behaviors on asset prices. Moreover, we uncover that herding behaviors have positive influences on stocks’ risk premiums.     

Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis

The main goal of this research is to provide a comprehensive understanding of the actual progresses in artificial intelligence, with emphasis on chatbots as emerging forms of customer assistance in online retailing. Drawing upon an analysis of the chatbot patents in the past 20 years, our findings show the increasing technology push towards the adoption of new conversational agents based on natural language. Findings also highlight the extent to which the research and development efforts are attempting to improve artificial intelligence systems that characterize chatbots. To this end, technology advancements are mainly focusing on: (i) improving chatbot ability to automatically draw inferences on users starting from multiple data sources, and (ii) using consumers’ knowledge adaptively to provide more customized solutions. Finally, results show the tight relationship between the digital assistants’ analytical skills and their ability to automatically interact with the users.