Inference with dependent data using cluster covariance estimators

This paper presents an inference approach for dependent data in time series, spatial, and panel data applications. The method involves constructing t and Wald statistics using a cluster covariance matrix estimator (CCE). We use an approximation that takes the number of clusters/groups as fixed and the number of observations per group to be large. The resulting limiting distributions of the t and Wald statistics are standard t and F distributions where the number of groups plays the role of sample size. Using a small number of groups is analogous to ‘fixed-b’ asymptotics of [Kiefer and Vogelsang, 2002] and [Kiefer and Vogelsang, 2005] (KV) for heteroskedasticity and autocorrelation consistent inference. We provide simulation evidence that demonstrates that the procedure substantially outperforms conventional inference procedures.     

Particle filters for continuous likelihood evaluation and maximisation

In this paper, a method is introduced for approximating the likelihood for the unknown parameters of a state space model. The approximation converges to the true likelihood as the simulation size goes to infinity. In addition, the approximating likelihood is continuous as a function of the unknown parameters under rather general conditions. The approach advocated is fast and robust, and it avoids many of the pitfalls associated with current techniques based upon importance sampling. We assess the performance of the method by considering a linear state space model, comparing the results with the Kalman filter, which delivers the true likelihood. We also apply the method to a non-Gaussian state space model, the stochastic volatility model, finding that the approach is efficient and effective. Applications to continuous time finance models and latent panel data models are considered. Two different multivariate approaches are proposed. The neoclassical growth model is considered as an application.     

姜黄素防治2型糖尿病的研究进展

姜黄素是从姜黄中提取的一种多酚类物质,具有抗癌,抗炎,抗氧化等多种生物学作用,最近研究发现姜黄素具有明显降低糖尿病大鼠血糖、血脂,明显改善2型糖尿病大鼠糖代谢,脂代谢紊乱的症状。     

B2C电子商务配送服务能力评价研究

在深入研究B2C电子商务环境下新型配送特征基础上,构建适用于B2C电子商务环境的配送服务能力评价指标体系,并用层次分析法进行了评价模型的建立,以期为B2C电子商务企业构建物流服务竞争力提供一定参考。     

管理教练、权变奖励、组织公民行为与B2B顾客满意

本文构建了一个有关主管行为、组织公民行为和B2B顾客满意的概念模型并加以检验。研究发现（1）销售人员的组织公民行为对于B2B顾客满意具有显著正向影响;（2）销售人员组织公民行为对B2B顾客满意的影响受环境不确定性的正向调节;（3）感知的管理教练行为和权变奖励均对销售人员的情感性组织承诺和组织公民行为具有正效应;（4）情感性组织承诺是主管行为对员工组织公民行为影响的中介变量;论文最后阐述了研究的管理内涵以及未来的研究方向。     

HEGY Tests in the Presence of Moving Averages*

We analyze the asymptotic distributions associated with the seasonal unit root tests of Hylleberg et al. (1990) for quarterly data when the innovations follow a moving average process. Although both the t‐ and F‐type tests suffer from scale and shift effects compared with the presumed null distributions when a fixed order of autoregressive augmentation is applied, these effects disappear when the order of augmentation is sufficiently large. However, as found by Burridge and Taylor (2001) for the autoregressive case, individual t‐ratio tests at the semi‐annual frequency are not pivotal even with high orders of augmentation, although the corresponding joint F‐type statistic is pivotal. Monte Carlo simulations verify the importance of the order of augmentation for finite samples generated by seasonally integrated moving average processes.     

浅析基于B2B模式的电子商务的发展

电子商务是指以互联网为整体架构,网络交易为主要内容,交易双方为主体,网上支付为手段,网络客户数据库为依托的全新的商务运作模式.我们着重分析基于B2B模式的电子商务在未来的巨大发展前景.     

超声测量虚拟仪器的设计与开发

文章基于超声测距的原理,利用4轴数控基础作为运动控制平台,结合超声采集卡设计并开发了超声测量系统实现复杂型面构件的测厚,利用Visual C++实现了超声测量的虚拟仪器软件功能,最后对标准试块进行了测厚实验,实验结果验证本超声测量系统的有效性。     

An instrumental variable approach for panel unit root tests under cross-sectional dependence

For dynamic panel models with cross-sectional dependence, several unit root tests are constructed using a Huber-type instrument, whose null asymptotics are standard Gaussian and do not depend on nuisance parameters. A Monte-Carlo simulation shows that the proposed tests have better sizes and comparable powers relative to other two existing tests developed for cross-sectionally dependent dynamic panel models.     

Blocked-Error-R 2: A Conceptually Improved Definition of the Proportion of Explained Variance in Models Containing Loops or Correlated Residuals

Bentler and Raykov (2000, Journal of Applied Psychology 85: 125–131), and Jöreskog (1999a, http://www.ssicentral.com/lisrel/column3.htm, 1999b http://www.ssicentral. com/lisrel/column5.htm) proposed procedures for calculating R ² for dependent variables involved in loops or possessing correlated errors. This article demonstrates that Bentler and Raykov’s procedure can not be routinely interpreted as a “proportion” of explained variance, while Jöreskog’s reduced-form calculation is unnecessarily restrictive. The new blocked-error-R ² (beR ²) uses a minimal hypothetical causal intervention to resolve the variance-partitioning ambiguities created by loops and correlated errors. Hayduk (1996) discussed how stabilising feedback models – models capable of counteracting external perturbations – can result in an acceptable error variance which exceeds the variance of the dependent variable to which that error is attached. For variables included within loops, whether stabilising or not, beR ² provides the same value as Hayduk’s (1996) loop-adjusted-R ². For variables not involved in loops and not displaying correlated residuals, beR ² reports the same value as the traditional regression R ². Thus, beR ² provides a conceptualisation of the proportion of explained variance that spans both recursive and nonrecursive structural equation models. A procedure for calculating beR ² in any SEM program is provided.