我国消费、投资、出口与物流发展动态关系研究

选取我国消费、投资、出口与物流发展表征指标,以1980～2012年时间序列数据为研究样本;利用Granger因果关系检验分析消费、投资、出口与物流发展间存在的内在联系;根据HP滤波法将各指标分为三阶段,即平稳发展期、波动显著期、调整过渡期;基于偏最小二乘法构建消费、投资、出口对物流发展三子周期的贡献测度模型。结果表明：在不同时期消费、投资、出口对物流业的产出弹性变化不一,与投资、出口的不稳定性相比,物流对消费的依赖性保持着持续上升的趋势。     

Effectuation or causation as the key to corporate venture success? Investigating effects of entrepreneurial behaviors on business model innovation and venture performance

Corporate Venturing sets the stage for entrepreneurial behavior in order to create business model innovation (BMI). Moreover, prior literature indicates the importance of BMI as a source of performance advantage, especially in growing industries. However, an empirical examination of the effectiveness of entrepreneurial behaviors for achieving BMI is still lacking. Hence, this study investigates the effectiveness of effectuation and causation as primary entrepreneurial logics to create BMI. Analyzing data obtained from 128 corporate ventures with partial least squares structural equation modeling, the effectiveness of both entrepreneurial logics for BMI with respect to different industry growth levels is clarified: The results point out that both behaviors lead to BMI in situations of moderate industry growth while effectuation (causation) is more effective in high (low) industry growth settings. Furthermore, the results point out that BMI in turn enhances corporate venture performance. Thus, corporate entrepreneurs should carefully align their entrepreneurial approach with industry growth projections to effectively develop BMI and achieve high venture performance.     

The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data

Widespread concern over the credibility of published results has led to scrutiny of statistical practices. We address one aspect of this problem that stems from the use of balance tests in conjunction with experimental data. When random assignment is botched, due either to mistakes in implementation or differential attrition, balance tests can be an important tool in determining whether to treat the data as observational versus experimental. Unfortunately, the use of balance tests has become commonplace in analyses of “clean” data, that is, data for which random assignment can be stipulated. Here, we show that balance tests can destroy the basis on which scientific conclusions are formed, and can lead to erroneous and even fraudulent conclusions. We conclude by advocating that scientists and journal editors resist the use of balance tests in all analyses of clean data. Supplementary materials for this article are available online     

Estimation of variance components in the mixed effects models: A comparison between analysis of variance and spectral decomposition

The mixed effects models with two variance components are often used to analyze longitudinal data. For these models, we compare two approaches to estimating the variance components, the analysis of variance approach and the spectral decomposition approach. We establish a necessary and sufficient condition for the two approaches to yield identical estimates, and some sufficient conditions for the superiority of one approach over the other, under the mean squared error criterion. Applications of the methods to circular models and longitudinal data are discussed. Furthermore, simulation results indicate that better estimates of variance components do not necessarily imply higher power of the tests or shorter confidence intervals.     

Liu estimator in partly linear regression models with correlated errors

This article is concerned with the parameter estimation in partly linear regression models when the errors are dependent. To overcome the multicollinearity problem, a generalized Liu estimator is proposed. The theoretical properties of the proposed estimator and its relationship with some existing methods designed for partly linear models are investigated. Finally, a hypothetical data is conducted to illustrate some of the theoretical results.     

电子服务质量与大学生网购满意度关系的实证研究

在回顾国内外相关文献的基础上,构建了适合于网上购物顾客满意度研究的概念模型。以在校大学生为研究对象,选择淘宝商城作为调查网站,以实地问卷调查的方式获取研究数据,运用结构方程模型的PLS建模方法验证了模型中提出的多重假设关系。通过研究得出以下结论：电子服务质量对顾客信任、感知价值、顾客满意和顾客忠诚有积极显著的影响;顾客信任和感知价值是电子服务质量影响顾客满意和顾客忠诚的过渡环节;顾客满意是形成顾客忠诚最直接的因素。     

Median regression model with left truncated and interval-censored data

We consider the problem of fitting a heteroscedastic median regression model from left-truncated and interval-censored data. It is demonstrated that the adapted Efron’s self-consistency equation of McKeague, Subramanian, and Sun (2001) can be extended to analyze left-truncated and interval-censored data. The asymptotic property of the proposed estimator is established. We evaluate the finite sample performance of the proposed estimators through simulation studies.     

Nearly Optimal Tests When a Nuisance Parameter Is Present Under the Null Hypothesis

This paper considers nonstandard hypothesis testing problems that involve a nuisance parameter. We establish an upper bound on the weighted average power of all valid tests, and develop a numerical algorithm that determines a feasible test with power close to the bound. The approach is illustrated in six applications: inference about a linear regression coefficient when the sign of a control coefficient is known; small sample inference about the difference in means from two independent Gaussian samples from populations with potentially different variances; inference about the break date in structural break models with moderate break magnitude; predictability tests when the regressor is highly persistent; inference about an interval identified parameter; and inference about a linear regression coefficient when the necessity of a control is in doubt.     

Nonparametric maximum likelihood estimators for ar and ma time series

The problem of estimating the parameters of moving average or autoregressive time series is studied when the error distribution is completely unknown. Four nonparametric maximum likelihood estimators (NPMLE) are presented for this purpose. These estimators are compared with the classical moment and least squares estimators in a simulation study. The behavior of these NPMLEs is much better than the classical ones, suggesting that they should be used extensively when no parametric information is known in advance about the error distribution. An application of these estimators to coal mining accidents data is also included.     

THE SMALL SAMPLE PROPERTIES OF THE PRINCIPAL COMPONENTS ESTIMATOR FOR REGRESSION COEFFICIENTS

ABSTRACT

Under the mean square error matrix (MSEM) criterion and Pitman closeness (PC) criterion, the principal components estimator (PRCE) is compared with the least square estimator (LSE) and the superiority of PRCE over LSE is achieved respectively. Finally, we examine the superiority of PRCE predictor over the LSE predictor based on these two criteria.