Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.     

ROBUST METHODS FOR DEPENDENT CELL PEDIGREE DATA

This paper studies a robust approach to the analysis of cell pedigree data, building on the work of Huggins & Marschner (1991) which discussed M-estimation for the so-called bifurcating autoregressive process. The study allows for incomplete observation of the pedigree, and incorporates the possibility of additive effects outliers, as discussed in the time series literature. Some properties of the proposed estimation procedure are studied, including a Monte Carlo investigation of robustness in the presence of contamination.     

中小企业CRM系统的OLAP设计与实现

根据中小企业CRM发展需求,构建了OLAP分析模型,为企业提供决策支持.     

Women's Changing Attitudes Toward Divorce, 1974–2002: Evidence for an Educational Crossover

This article examines trends in divorce attitudes of young adult women in the United States by educational attainment from 1974 to 2002. Women with 4‐year college degrees, who previously had the most permissive attitudes toward divorce, have become more restrictive in their attitudes toward divorce than high school graduates and women with some college education, whereas women with no high school diplomas have increasingly permissive attitudes toward divorce. We examine this educational crossover in divorce attitudes in the context of variables correlated with women's educational attainment, including family attitudes and religion, income and occupational prestige, and family structure. We conclude that the educational crossover in divorce attitudes is associated most strongly with work and family structure variables.     

当代家族小说的性别审视

在家族小说创作中,当代作家以现代意识与人道同情表现出对女性命运与妇女解放问题关注的热情,但由于受到男权社会文化传统与性别立场的影响,他们对女性不幸命运的同情之中又存在着性别上的隔膜,无论是对女性躯体的描写,男女两性关系模式的建构,叙述者与人物的性别话语,还是在性际关系价值评判中的厚此薄彼,都从不同的侧面流露出作家男权意识的传统积淀,都是男性对女性一厢情愿的想象性书写。     

存储区域网络iSCSI协议的通信机制研究

介绍了存储区域网络主要采用的组网协议,包括FC协议、FCIP协议、iFCP协议和iSCSI协议,着重研究了一种利用TCP/IPI网组建存储区域网络的协议-iSCSI协议,分析了iSCSI协议的通信机制,比较了在IP网络上实现iSCSI协议通信的3种方法,开发了一种iSCSI协议数据单元与TCP数据帧间的接口算法及其硬件设计,并用 VHDL语言成功进行了行为级的仿真。     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

基于移动代理的新型IDS维护更新机制设计

提出了一种基于移动代理的新型分布式入侵检测系统。该系统是针对广域网环境专门设计的,数据的处理通过各节点所设置的代理来进行分布式计算,不仅能实现全网络范围内的入侵检测功能,具有良好的可移植性;而且对网络系统和主机的资源占用较低,减少了出现网络瓶颈的可能。还建立了移动代理的新型分布式入侵检测系统的体系结构和理论分析模型,并讨论了该系统的维护更新机制。     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

A note on interval‐censored lifetime data and the constant‐sum condition of oiler,gómez & calle (2004)

Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process.