论食品安全事件中的良性媒体应对

食品安全事件是近年来全球公共安全问题中的热点,由于食品安全的重要性、食品安全事件的公众效应以及基于传媒的属性,媒体常将其作为关注的热点。媒体在食品安全事件中发挥着监测预警、沟通信息、舆论引导等功能,同时也存在关注视角的选择性和职业自律的松懈等不足。作为一种社会公共资源和社会监督力量,基于传媒良知和职业操守,媒体在食品安全事件中必须形成一套良性的应对机制,包括建立信息有效传播机制、建立食品安全事件相关方的沟通协调机制、建立媒体自律机制等。     

中国工业行业碳强度的因素分析——基于超越对数生产函数

为探究工业行业碳强度变化的成因,基于Kaya恒等式的碳强度分解,以碳强度表示产出,以经济增长、能源消费量、能源消费结构和技术进步为投入要素构建超越对数生产函数,通过各要素的碳强度产出弹性反映各要素对碳强度的贡献;并运用通径分析法进一步揭示各要素间的相互关系及其与碳强度的直接和间接关系。结果表明:能源消费结构的优化和技术进步抑制了工业行业碳强度的增长,能源消费量的增长和工业增加值的增长拉动了碳强度的增长,其中能源消费结构和能源消费量对工业行业碳强度的影响显著,因此降低工业行业碳强度的关键在于减少能源消费结构和能源消费量的碳强度产出弹性;能源消费量、工业增加值和能源消费结构对能源消费量的碳强度产出弹性起直接推动作用,技术进步起直接抑制作用;工业增加值和能源消费量对能源消费结构的碳强度产出弹性起直接推动作用,技术进步和能源消费结构起直接抑制作用。可见,工业行业对能源消费的依赖性较强,降低工业行业碳强度应主要依靠技术进步转变能源利用方式,提高能源效率,优化能源消费结构。     

Inference in Semi‐Parametric Dynamic Models for Repeated Count Data

This paper deals with a longitudinal semi‐parametric regression model in a generalised linear model setup for repeated count data collected from a large number of independent individuals. To accommodate the longitudinal correlations, we consider a dynamic model for repeated counts which has decaying auto‐correlations as the time lag increases between the repeated responses. The semi‐parametric regression function involved in the model contains a specified regression function in some suitable time‐dependent covariates and a non‐parametric function in some other time‐dependent covariates. As far as the inference is concerned, because the non‐parametric function is of secondary interest, we estimate this function consistently using the independence assumption‐based well‐known quasi‐likelihood approach. Next, the proposed longitudinal correlation structure and the estimate of the non‐parametric function are used to develop a semi‐parametric generalised quasi‐likelihood approach for consistent and efficient estimation of the regression effects in the parametric regression function. The finite sample performance of the proposed estimation approach is examined through an intensive simulation study based on both large and small samples. Both balanced and unbalanced cluster sizes are incorporated in the simulation study. The asymptotic performances of the estimators are given. The estimation methodology is illustrated by reanalysing the well‐known health care utilisation data consisting of counts of yearly visits to a physician by 180 individuals for four years and several important primary and secondary covariates.     

Analysis of some ruin-related quantities in a Markov-modulated risk model

In this paper, we study the joint Laplace transform and probability generating function of some random quantities that occur in each environment state by the time of ruin in a Markov-modulated risk process. These quantities include the duration spent in each state, the number of claims and the aggregate amount of claims that occurred in each state by the time of ruin. Explicit formulae for the joint transforms, given the initial surplus, and the initial and terminal environment states, are expressed in terms of a matrix version of the scale function. Moments and covariances of these ruin-related quantities are obtained and numerical illustrations are presented. The joint transform of the duration spent in each state, the number of claims, and the aggregate amount of claims that occurred in each state by the time the surplus attains a certain level are also investigated.     

我国居民文化消费影响因素探析

运用我国1983—2012年的数据,通过实证分析考察了可支配收入、教育水平、金融发展和政府文化事业支出对我国居民文化消费的影响。长期均衡分析结果表明,教育水平和金融发展对我国居民文化消费具有显著的促进作用;教育水平提高1%,居民文化消费增加0.454%;金融机构信贷提高1%,居民文化消费增加0.363%;可支配收入和政府文化事业支出对居民文化消费的影响不显著。脉冲响应分析结果表明,可支配收入冲击对居民文化消费的影响在短期由正向转为负向,教育水平冲击和金融发展冲击对居民文化消费短期具有正向影响,政府文化事业支出冲击对居民文化消费短期具有负面影响。根据实证分析的结论,文章提出了扩大我国居民文化消费的政策建议。     

论汉魏六朝仪式歌辞的文化功能与传播特点

仪式歌辞是为满足封建王朝各种仪式活动需要而创作音乐歌辞,因其满足仪式活动之需的特殊功能,内容上强调其与仪式活动符号象征的一致性,形式上多采用典雅的四言正格,在传播方式上呈现出程序性、依附性、组织性和共时性特点。仪式歌辞特殊的文化功能和传播特点决定了其传播效果的局限性,在传播范围的拓展性、传播时间的延续性方面均不能与娱乐歌辞相比,人们对仪式歌辞的接受,也主要是从其内容的“象征图式”和“意象结构”出发的,是否美听悦耳不是接受重点。     

A New Quantile Function with Applications to Reliability Analysis

In this article, we propose a new class of distributions defined by a quantile function, which nests several distributions as its members. The quantile function proposed here is the sum of the quantile functions of the generalized Pareto and Weibull distributions. Various distributional properties and reliability characteristics of the class are discussed. The estimation of the parameters of the model using L-moments is studied. Finally, we apply the model to a real life dataset.     

Oracle Inequalities for Convex Loss Functions with Nonlinear Targets

This article considers penalized empirical loss minimization of convex loss functions with unknown target functions. Using the elastic net penalty, of which the Least Absolute Shrinkage and Selection Operator (Lasso) is a special case, we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target is linear, this inequality also provides an upper bound of the estimation error of the estimated parameter vector. Next, we use the non-asymptotic results to show that the excess loss of our estimator is asymptotically of the same order as that of the oracle. If the target is linear, we give sufficient conditions for consistency of the estimated parameter vector. We briefly discuss how a thresholded version of our estimator can be used to perform consistent variable selection. We give two examples of loss functions covered by our framework.     

Temporal Disaggregation: Methods,Information Loss,and Diagnostics

This research provides a generalized framework to disaggregate lower-frequency time series and evaluate the disaggregation performance. The proposed framework combines two models in separate stages: a linear regression model to exploit related independent variables in the first stage and a state–space model to disaggregate the residual from the regression in the second stage. For the purpose of providing a set of practical criteria for assessing the disaggregation performance, we measure the information loss that occurs during temporal aggregation while examining what effects take place when aggregating data. To validate the proposed framework, we implement Monte Carlo simulations and provide two empirical studies. Supplementary materials for this article are available online.