经济学研究的统计思想探讨

统计学是收集、整理和分析数据的方法论科学.经济学实证研究首先必须开展经济数据的收集和整理,在抽样调查及数据预处理过程中体现出"为何统计"及"统计什么"的思想;经济数据分析过程中描述及推断统计方法的应用,包含着"如何统计"的思想.总体上,经济学利用统计方法得到的结论不具有完全确定性,体现出或然性统计思想.     

论我国经济型饭店集团化的模式及对策

集团化是经济型饭店发展的必由之路。结合经济型饭店的界定和我国经济型饭店集团化发展的现状,比较国际经济型饭店集团化的基本模式与中国经济型饭店集团化模式的选择,提出对经济型饭店集团化发展的对策。     

Analyzing Group Data in MIS Research: Including the Effect of the Group

A review of recent group experimental research in three major MIS research journals indicates a lack of understanding of how to analyze group data measured at the individual level. This paper draws on statistical analysis literature from various disciplines to explain why current analysis of group data in MIS research is often incorrect and demonstrates how to analyze such data correctly.     

统计数据质量成本关系模型研究

在统计数据质量成本概念基础上,本文根据统计数据质量成本管理理论推导出统计数据质量成本模型的理论形式;结合统计数据生产过程的特点,具体论证了抽样设计阶段和统计信息生产阶段的统计数据质量成本与不同质量特性的质量成本关系模型,为有效地实施统计数据质量成本的管理,从而不断改进统计数据质量提供了理论基础。     

统计数据质量评价体系探讨

统计数据质量是统计工作的生命,统计数据质量的高低直接关系到各类经济主体和政府部门对经济形势的判断和决策。文章借鉴全面质量管理的思想,从满足用户和统计数据产生全过程的角度,系统地阐述了统计数据质量的内涵,在此基础上提出构建我国政府统计数据质量评价体系的设想,以期为相关决策部门提供参考。     

The Purposes of Multivariate Data Analysis Methods: an Applied Commentary

Unlike univariate and bivariate statistical methods, multivariate statistical methods are capable of analyzing more than one relationship at a time. There are a number of multivariate data analysis methods, each with its own purpose. For nonexperts in statistical analysis, it can be daunting to determine what method is appropriate for a given application. The goal of this commentary is to introduce the multivariate data analysis methods in practical terms that do not require a strong statistical background. The emphasis is describing the purpose of each method, so that readers can choose the methods appropriate for their research questions. The use of multivariate statistical methods in the Journal of African Business also is explored.     

浅析我国物流统计发展现状

近年来,我国国民经济持续飞速发展,推动了现代物流业的规模扩张。但物流统计没有与物流业同步发展,普遍存在着忽视物流服务,信息化的标准滞后以及统计方法不够完善等问题,设置合理、系统的物流统计指标体系和统计分析方法能够更好地促进物流业的发展。     

数据质量评估框架及其信息量分析

统计数据质量重要性催生出各国用于数据质量评估的框架、系统,IMF制定的数据质量评估框架因其结构完整性和较强归纳性受到成员国的广泛采用。文章通过运用信息熵理论对数据质量评估框架(DQAF)本身的维度、指标信息量问题进行研究,得出：(1) DQAF各维度、指标在账户内     

基于利益相关者视角的统计数据质量管理体系研究

统计数据质量涉及到数据的生产者、使用者、提供者和监督者等利益相关者,不同主体关注的数据质量维度各有侧重。文章提出作为统计数据质量评估主体的统计机构,应突破自身作为数据生产者的局限,兼顾数据生产者、使用者、提供者和监督者的不同质量要求,采取与之相应的评估指标、方法和多样化的评估形式,全面评估统计数据质量,实施有针对性的数据质量管理策略。最后,给出简短结论与未来展望。     

The Post-Promotion Dip Puzzle: What do the Data Have to Say?

One of the puzzles of store-level scanner data is the lack of a dip in quantity sold in the weeks following a promotion. Such a dip is predicted by a consumer inventory model. During a promotion consumers buy more, not only for current consumption, but stockpile for future consumption. The predictions of such a model have been confirmed by household-level data yet seem harder to find in aggregate brand- or category-level data. We re-examine this puzzle and reach two conclusions. First, the effects at the household-level are present, but are much smaller than previously found. Our estimates are different because we control for household heterogeneity in a more general way than most previous work. This suggests that since the effects are small they might be harder to spot in aggregate data. Second, we show that the dip is present in the aggregate data, once we control for additional promotional activity, like feature and display. The latter has an opposing dynamic effect that masks the existence of the post-promotion dip.     

Modeling Simultaneity in Survey Data

Responses to questions in a survey can reflect a behavior process that influences multiple response items. Respondent ratings of brand attributes, for example, can be affected by past purchases by making a brand more salient, or by respondents attributing higher performance to justify their purchases. When multiple response items are influenced by a common underlying process, there is simultaneity in the data. This paper proposes an approach to model the simultaneity in different survey responses by using common parameters and structural relationships motivated by behavioral theories on how consumers respond to surveys. Specifically, the proposed models show how brand usage and attribute perception responses are jointly determined by justification, order, and brand halo effects in two brand positioning studies. We detect a significant tendency for respondents to inflate their reported beliefs for particular brands as well as the selected brand across five countries in an international survey as well as in a domestic study. JEL Classification: C35, C53, D12, M31