浅析物流产业的发展途径

探讨了物流在经济生活中的作用和现阶段我国物流产业方面存在的问题。提出了发展我国物流产业的基本途径。指出了我国的物流企业应该适时调整经营战略。顺应世界经济的发展趋势。不断提高自身的生存和发展能力。以应对未来更为激烈的竞争局面。     

我国自然垄断产业的民营化改革

在自然垄断产业,国有企业垄断经营低效是一个世界性的问题。自然垄断产业在一定范围内具有可竞争性,即使是在不可竞争性的领域,也可以通过建立潜在的竞争性替代机制,形成模拟竞争环境。自然垄断产业的可竞争性为民营化提供了可能。自然垄断产业民营化就是通过产权制度变革,提高垄断企业的效率。     

An Examination of the Interaction Between Modelling and Its Relationship with Construction Kits: Lessons from the Past and for the Future

Construction kits have played a significant part in nurturing the growth and development of the minds and manipulation-based skills of children (and adults) in formal and non-formal education settings. These kits have origins rooted in the representation of the built world and now have a diversity of form and function, including technical versions with moving parts. This article examines some of the historically based ideas that lie behind the role that kits may have in terms of physical modelling. The article traces the transformation of kits from simple bricks and blocks into more complicated pieces for space-filling and achieving the transfer of forces and motion. This transformation occurred during the Victorian era when the influence of the ideas of educationalists and, perhaps rather strangely, exponents of early aviation, played major roles in determining the diversity of forms of construction kit and modelled possibilities that are now to be seen in classrooms and homes. The article ends with a review of some of the lessons from the past and present that will need to be considered in relation to concrete modelling in schools for the future. This revised version was published online in July 2006 with corrections to the Cover Date.     

对我国风险投资组织模式选择的研究

有限合伙制以其特有的产权和责任安排而被认为是最符合风险投资行业特点和要求的组织形式。我国在对建立有限合伙制风险投资企业的认识上存在一定的分歧，本认为随着我国经济的不断向前发展，相关法律法规的完善，有限合伙制必然会成为我国风险投资企业组织模式的首选。     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.