销售时信息披露的公平原则与互利原则

本文通过对销售商向消费者披露产品的信息的责任和义务的分析,比较了信息披露道德的公平原则和互利原则.指出了信息披露的伦理要求,应根据各种具体问题的不同适当地在公平原则和互利原则之间定位.     

利益细分变量研究与消费者市场细分

在当今激烈的市场竞争环境中,市场细分理论对企业市场营销活动的指导作用已为越来越多的企业所认同,并引起市场营销研究人员的关注。本文从市场细分变量入手,通过对市场细分变量的四大类型和消费者市场细分组合的多样性进行分析,并以针对国内牙膏市场上主要品牌所进行的利益细分调研为例,论述了进行利益细分研究对市场营销的指导意义。     

南方习俗与边疆民族文化产业的整合

文化产业是人类通过各种文化活动,借助文化基因,获取经济效益,满足人们的物质和精神需要的一种行为和举动。这些文化基因又比较集中地体现于不同地域、不同民族多姿多彩的习俗文化。通过它,可以使人类获得高标准、高层次的享受。边疆地区文化产业发展的目标是根据本土、本民族的特点,选择好自己的项目和类别,把握文化产业的运作工序,获取较大的经济效益,促进边疆地区经济的繁荣和发展,推动民族地区的四化建设。     

Which Factors are Risk Factors in Asset Pricing? A Model Scan Framework

Abstract

A key question for understanding the cross-section of expected returns of equities is the following: which factors, from a given collection of factors, are risk factors, equivalently, which factors are in the stochastic discount factor (SDF)? Though the SDF is unobserved, assumptions about which factors (from the available set of factors) are in the SDF restricts the joint distribution of factors in specific ways, as a consequence of the economic theory of asset pricing. A different starting collection of factors that go into the SDF leads to a different set of restrictions on the joint distribution of factors. The conditional distribution of equity returns has the same restricted form, regardless of what is assumed about the factors in the SDF, as long as the factors are traded, and hence the distribution of asset returns is irrelevant for isolating the risk-factors. The restricted factors models are distinct (nonnested) and do not arise by omitting or including a variable from a full model, thus precluding analysis by standard statistical variable selection methods, such as those based on the lasso and its variants. Instead, we develop what we call a Bayesian model scan strategy in which each factor is allowed to enter or not enter the SDF and the resulting restricted models (of which there are 114,674 in our empirical study) are simultaneously confronted with the data. We use a Student-t distribution for the factors, and model-specific independent Student-t distribution for the location parameters, a training sample to fix prior locations, and a creative way to arrive at the joint distribution of several other model-specific parameters from a single prior distribution. This allows our method to be essentially a scaleable and tuned-black-box method that can be applied across our large model space with little to no user-intervention. The model marginal likelihoods, and implied posterior model probabilities, are compared with the prior probability of 1/114,674 of each model to find the best-supported model, and thus the factors most likely to be in the SDF. We provide detailed simulation evidence about the high finite-sample accuracy of the method. Our empirical study with 13 leading factors reveals that the highest marginal likelihood model is a Student-t distributed factor model with 5 degrees of freedom and 8 risk factors.     

产业融合促进农民共同富裕:作用机理与政策选择

产业融合作为我国农村生产方式的重要变革形态,对农民就业和增收带来深远影响。其机理在于,产业融合发展促进了农村资本要素投入、人力资本积累、农业技术效率提升和生产组织模式创新,不仅提高了资源要素配置效率和农业劳动生产率,而且通过构建合理的利益分享机制,使农民在参与产业链建设中提高了创富能力、实现了收入增长。从农村产业融合发展实践看,反向定制带动了农业产业化模式创新,产业链耦合促进了技术加速扩散,混合经营推动了农村集体经济组织的激活再造,这些新变量和新变化从不同方面、以不同的形式对农民增收致富带来影响。然而,目前我国农村产业融合的整体层次和水平还不高,对农民富裕的促进作用发挥还不够充分,主要原因是生产要素跨界配置面临制度性障碍、农村市场存在功能性缺陷、政府有效激励和规制缺位以及基础服务体系不健全。应加快突破制度障碍、健全市场功能、强化利益分配、夯实基础支撑,促进农村产业深度融合,强化兴农富民带动效应。     

Some recent developments for regression analysis of multivariate failure time data

Cox's seminal 1972 paper on regression methods for possibly censored failure time data popularized the use of time to an event as a primary response in prospective studies. But one key assumption of this and other regression methods is that observations are independent of one another. In many problems, failure times are clustered into small groups where outcomes within a group are correlated. Examples include failure times for two eyes from one person or for members of the same family.This paper presents a survey of models for multivariate failure time data. Two distinct classes of models are considered: frailty and marginal models. In a frailty model, the correlation is assumed to derive from latent variables (frailties) common to observations from the same cluster. Regression models are formulated for the conditional failure time distribution given the frailties. Alternatively, marginal models describe the marginal failure time distribution of each response while separately modelling the association among responses from the same cluster.We focus on recent extensions of the proportional hazards model for multivariate failure time data. Model formulation, parameter interpretation and estimation procedures are considered.     

A procedure to select a ML-II prior in a multivariate normal case

Berger (1985) derived a procedure to select a maximum likelihood II prior distribution. In this paper a method is suggested to construct such a prior distribution from a multivariate ε-contamination class of distributions. The method is illustrated by the conetruction of a ML-II prior in the multivariate normal case.     

Real-Time Forecasting With a Mixed-Frequency VAR

This article develops a vector autoregression (VAR) for time series which are observed at mixed frequencies—quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time dataset, we evaluate forecasts from the mixed-frequency VAR and compare them to standard quarterly frequency VAR and to forecasts from MIDAS regressions. We document the extent to which information that becomes available within the quarter improves the forecasts in real time. This article has online supplementary materials.     

Partial central subspace and sliced average variance estimation

Sliced average variance estimation is one of many methods for estimating the central subspace. It was shown to be more comprehensive than sliced inverse regression in the sense that it consistently estimates the central subspace under mild conditions while slice inverse regression may estimate only a proper subset of the central subspace. In this paper we extend this method to regressions with qualitative predictors. We also provide tests of dimension and a marginal coordinate hypothesis test. We apply the method to a data set concerning lakes infested by Eurasian Watermilfoil, and compare this new method to the partial inverse regression estimator.     

预期收益最大化与“蚁族”现象

蚁族现象的本质是大学毕业生选择在大城市还是中小城镇就业的问题。从理性人假设的角度来看,"蚁族"现象的原因在于"蚁族"们为了获得更多的就业机会、更高的就业质量等经济收益,和更多的教育收益、消费收益、心理收益和健康收益等非经济收益,从而主动选择在大城市就业的结果。减少"蚁族"现象的思路在于提高大学毕业生收入、促进教育公平和均衡发展、重视发展中小城镇、引导大学毕业生到中小城镇就业。