传播议程经济的乘数效应

传媒经济的实质是议程经济,只有议程经济可以联系传媒传受即供需双方,实现传媒经济均衡。议程经济发挥作用的机制是传播的乘数效应,在传统媒体和新媒体融合的生态下,媒介生产方式体现出全新的特征。信息的倍增效果产生的正反作用对传播的议程经济的取得提出了新的挑战,值得高度重视,有必要深入研究以网络信息传播为代表的新媒体的规制原则和方法,才能确保传媒经济和社会双重效益的实现。     

Conditional variance estimation in heteroscedastic regression models

First, we propose a new method for estimating the conditional variance in heteroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of the local linear and local likelihood estimators. Secondly, we apply a variance reduction technique to improve the inference for the conditional variance. The proposed methods are investigated through their asymptotic distributions and numerical performances.     

A variable-neighbourhood search algorithm for finding optimal run orders in the presence of serial correlation

The responses obtained from response surface designs that are run sequentially often exhibit serial correlation or time trends. The order in which the runs of the design are performed then has an impact on the precision of the parameter estimators. This article proposes the use of a variable-neighbourhood search algorithm to compute run orders that guarantee a precise estimation of the effects of the experimental factors. The importance of using good run orders is demonstrated by seeking D-optimal run orders for a central composite design in the presence of an AR(1) autocorrelation pattern.     

地方政府支出与农村居民消费需求：基于1998-2007年省级 面板数据的经验分析

 政府支出对居民消费需求产生挤出抑或挤入效应是理论界最近关注的焦点之一。本文在理论诠释地方政府支出对农村居民消费需求的传导机制以及模型建立的理论框架下,通过建立地方政府支出与农村居民消费支出之间的个体固定效应变截距模型,运用我国31个省份1998-2007年的经验数据进行实证检验,结果表明：地方政府财政支农支出对农村居民消费具有显著的挤入效应,而转移性支出与农村居民消费的相关程度并不明显。基于理论分析和实证检验结果,本文最后针对地方政府扩大农村居民消费提出相关建议。     

Local influence in seemingly unrelated regression model with ridge estimate

Local influence is a well-known method for identifying the influential observations in a dataset and commonly needed in a statistical analysis. In this paper, we study the local influence on the parameters of interest in the seemingly unrelated regression model with ridge estimation, when there exists collinearity among the explanatory variables. We examine two types of perturbation schemes to identify influential observations: the perturbation of variance and the perturbation of individual explanatory variables. Finally, the efficacy of our proposed method is illustrated by analyzing [13 A. Munnell, Why has productivity declined? Productivity and public investment, New Engl. Econ. Rev. (1990), pp. 3–22. [Google Scholar]] productivity dataset.     

Robust modal estimation and variable selection for single-index varying-coefficient models

In this article, we present a new efficient iteration estimation approach based on local modal regression for single-index varying-coefficient models. The resulted estimators are shown to be robust with regardless of outliers and error distributions. The asymptotic properties of the estimators are established under some regularity conditions and a practical modified EM algorithm is proposed for the new method. Moreover, to achieve sparse estimator when there exists irrelevant variables in the index parameters, a variable selection procedure based on SCAD penalty is developed to select significant parametric covariates and the well-known oracle properties are also derived. Finally, some numerical examples with various distributed errors and a real data analysis are conducted to illustrate the validity and feasibility of our proposed method.     

An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves

We propose an adaptive functional autoregressive (AFAR) forecast model to predict electricity price curves. With time-varying operators, the AFAR model can be safely used in both stationary and nonstationary situations. A closed-form maximum likelihood (ML) estimator is derived under stationarity. The result is further extended for nonstationarity, where the time-dependent operators are adaptively estimated under local homogeneity. We provide theoretical results of the ML estimator and the adaptive estimator. Simulation study illustrates nice finite sample performance of the AFAR modeling. The AFAR model also exhibits a superior accuracy in the forecast exercise of the California electricity daily price curves compared to several alternatives.     

区域性高校为地方经济社会发展服务探析

区域高校与地方经济社会关系密切。为地方经济和社会发展服务,是区域高校基本职能之一。高等教育与地方区域通过互动,求得双赢和发展,已成为一种必然趋势。区域性高校为地方经济社会发展服务的实现途径为：以区域经济社会发展为导向,培养各类应用型人才;发挥高校科研资源优势,提高区域创新能力;依托高校的“文化中心”功能,引领区域软实力的提升。