多水平模型及静态面板数据模型的比较研究

对两水平模型与静态面板数据模型进行对比分析：多水平模型主要用于分析具有层次结构的统计数据,面板数据模型是针对面板数据而提出的一种应用广泛的计量经济模型。面板数据可以看成是具有截面水平与时间水平的两层数据,两水平模型也能对面板数据进行分析,在一定条件下具有一定的相似性。因此,提出多水平的静态面板数据模型,为分析具有多个层次结构的面板数据提供分析工具。     

Fill-in of missing data in univariate coastal data

An approach to fill-in of missing data where gaps exist within an otherwise continuous record is addressed. Ad hoc methods of past approaches are discussed and limitations noted. An approach for providing an estimate of data filling consistent with data having a correlation structure is presented. The method provided is an extension of parametric modelling along with additional constraints imposed via a linear filter to account for variance preservation. The method is applied and compared to real data in which a portion of the record has been removed to simulate missing data. Results show the method to provide realistic missing data that preserves the correlation structure and variance of the measured data.     

论网络统计的层次

随着互联网络的迅速发展和普及,并迅速成为获取和传播信息的十分重要的媒介,传统的统计活动有必要进行创新,网络统计应运而生。文章在作者以往研究网络统计相关问题的基础之上,认为网络统计在建设和发展过程中应该分为三个层次,并对其具体层次的结构进行简要分析。     

Finite-sample analysis of impacts of unlabeled data and their labeling mechanisms in linear discriminant analysis

It is widely believed that unlabeled data are promising for improving prediction accuracy in classification problems. Although theoretical studies about when/how unlabeled data are beneficial exist, an actual prediction improvement has not been sufficiently investigated for a finite sample in a systematic manner. We investigate the impact of unlabeled data in linear discriminant analysis and compare the error rates of the classifiers estimated with/without unlabeled data. Our focus is a labeling mechanism that characterizes the probabilistic structure of occurrence of labeled cases. Results imply that an extremely small proportion of unlabeled data has a large effect on the analysis results.     

劳动力流动与产业结构调整的空间效应研究

劳动力流动对产业结构调整存在重要影响,但基于空间效应视角对这一问题的实证研究目前还较为缺乏。本文通过构建中国2002～2012年30个省级行政单位的空间面板数据模型,分析农村劳动力流动对产业结构调整的影响方向与力度,并探讨其实现机制。本文证实了中国各地区产业结构的动态变化与临近地区之间确实存在显著正向的空间相关关系;劳动力的跨区域流动也显著促进了中国各地区产业结构的优化升级;而其他影响产业结构变化的因素在不同地区的影响效果存在明显分化。     

具有组群异方差结构的面板数据模型及其应用研究

面板数据由不同个体的时间序列数据汇聚而成。已有大量研究表明面板数据个体之间存在组群结构,并且普遍存在模型的异方差现象。本文借鉴组群异质性的研究成果,构建模型误差项组群结构的面板数据模型,基于模型假定条件,提出惩罚伪最大似然函数估计法(PQMLE),该方法能够同时进行结构识别和参数估计;证明了估计量具有Oracle渐近性质;蒙特卡洛模拟验证了该方法有效的样本性质;进一步应用该方法对我国股市进行Fama-French三因子模型的实证分析,验证了理论模型的应用效果。     

函数性数据的统计分析：思想、方法和应用

 摘　　要:实际中，越来越多的研究领域所收集到的样本观测数据具有函数性特征，这种函数性数据是融合时间序列和横截面两者的数据，有些甚是曲线或其他函数图像。虽然计量经济学近二十多年来发展的面板数据分析方法，具有很好的应用价值，但是面板数据只是函数性数据的一种特殊类型，且其分析方法太过于依赖模型的线性结构和假设条件等。本文基于函数性数据的普遍特征，介绍一种对其进行分析的全新方法，并率先使用该方法对经济函数性数据进行分析，拓展了函数性数据分析的应用范围。分析结果表明，函数性数据分析方法，较之计量经济学和其他统计方法具有更多的优越性，尤其能够揭示其他方法所不能揭示的数据特征     

Investigating emergent nested geographic structure in consumer purchases: a Bayesian dynamic multi-scale spatiotemporal modeling approach

Spatial modeling of consumer response data has gained increased interest recently in the marketing literature. In this paper, we extend the (spatial) multi-scale model by incorporating both spatial and temporal dimensions in the dynamic multi-scale spatiotemporal modeling approach. Our empirical application with a US company’s catalog purchase data for the period 1997–2001 reveals a nested geographic market structure that spans geopolitical boundaries such as state borders. This structure identifies spatial clusters of consumers who exhibit similar spatiotemporal behavior, thus pointing to the importance of emergent geographic structure, emergent nested structure and dynamic patterns in multi-resolution methods. The multi-scale model also has better performance in estimation and prediction compared with several spatial and spatiotemporal models and uses a scalable and computationally efficient Markov chain Monte Carlo method that makes it suitable for analyzing large spatiotemporal consumer purchase datasets.KEYWORDS: Clustering, dynamic linear models, empirical Bayes methods, Markov chain Monte Carlo methods, multi-scale modeling, spatial models     

Inference for Bivariate Survival Data by Copula Models Adjusted for the Boundary Effect

Copula models describe the dependence structure of two random variables separately from their marginal distributions and hence are particularly useful in studying the association for bivariate survival data. Semiparametric inference for bivariate survival data based on copula models has been studied for various types of data, including complete data, right-censored data, and current status data. This article discusses the boundary effect on these inference procedures, a problem that has been neglected in the previous literature. Specifically, asymptotic distribution of the association estimator on the boundary of parameter space is derived for one-dimensional copula models. The boundary properties are applied to test independence and to study the estimation efficiency. Simulation study is conducted for the bivariate right-censored data and current status data.     

中国对外直接投资的贸易结构效应

中国正在成为全球越来越重要的贸易大国和对外投资国。对外直接投资的贸易效应不仅反映在贸易规模扩张,更重要的意义在于对外直接投资对贸易结构的影响。本文对1982-2010年中国对外直接投资的贸易结构效应进行时间序列分析,发现中国对外直接投资存量滞后二期对货物贸易结构变化有积极影响;通过对2006-2010年间的七个具体行业对外直接投资的贸易结构效应进行面板数据分析,证实对外直接投资流量和存量对这些行业的进口贸易结构变化更显著,但由于数据的原因仅通过了KAO检验。两种检验结果说明,随着中国对外直接投资的发展,无论对外直接投资存量还是流量都具有一定的贸易结构效应。     

Bayesian Analysis of a Growth Curve Model with a General Autoregressive Covariance Structure

In this paper we consider from maximum likelihood and Bayesian points of view the generalized growth curve model when the covariance matrix has a Toeplitz structure. This covariance is a generalization of the AR(1) dependence structure. Inferences on the parameters as well as the future values are included. The results are illustrated with several real data sets.     

人力资本对外商直接投资的影响及其传导机制——基于中国数据的实证研究

本文利用中国1990—2006时间序列数据实证分析了人力资本存量、人力资本结构对我国FDI的直接与间接影响,结果表明人力资本存量及其结构不仅直接影响FDI,而且会通过与GDP、在岗职工平均工资交互作用而间接影响FDI。     

住户调查中代表性样本的一种探索获取方法——平衡抽样设计

住户调查是我国社会经济统计调查体系的重要组成部分,样本代表性直接决定统计数据质量。多阶段抽样中初级单元的方差对估计的影响是主要的,因此本文结合2010年全国第六次人口普查分县数据,采用平衡抽样设计获取初级单元的代表性样本-平衡样本。对代表性样本的事后评估结果表明,样本结构与总体结构吻合,目标估计的误差很小,说明了本文平衡设计的有效性。     

基于局部积差相关系数阵的纵向数据R型聚类分析——以现代服务业为例

在信息技术快速发展的今天,对问题和现象的研究已不再局限于单纯利用截面数据或时间序列数据进行分析。与之相比,纵向数据包含更多的信息,广泛而深入地挖掘其数据中的信息对于人类认识自然、认识社会有着重要意义。通过对纵向数据结构特征的研究,提出了纵向数据变量的局部积差相关系数矩阵。该相关阵不仅可以对变量的内部结构进行分析,更为重要的是,以此为基础来计算变量间相关系数,可以从一个新的视角,更为深入地揭示变量间的相关关系,进而可以对变量施以新型聚类分析。     

Cascade model with Dirichlet process for analyzing multiple dyadic matrices

Dyadic matrices are natural data representations in a wide range of domains. A dyadic matrix often involves two types of abstract objects and is based on observations of pairs of elements with one element from each object. Owing to the increasing needs from practical applications, dyadic data analysis has recently attracted increasing attention and many techniques have been developed. However, most existing approaches, such as co-clustering and relational reasoning, only handle a single dyadic table and lack flexibility to perform prediction using multiple dyadic matrices. In this article, we propose a general nonparametric Bayesian framework with a cascaded structure to model multiple dyadic matrices and then describe an efficient hybrid Gibbs sampling algorithm for posterior inference and analysis. Empirical evaluations using both synthetic data and real data show that the proposed model captures the hidden structure of data and generalizes the predictive inference in a unique way.     

互联网驱动产业结构高级化效应分析

经济新常态下,互联网已经成为中国经济转型升级的重要引擎。基于中国2003—2013年30个省市(区)的省级面板数据,实证分析互联网发展对中国产业结构高级化影响效应。研究结果表明:在静态上,互联网发展对产业结构升级具有显著的正向影响;互联网发展对产业结构高级化的溢出效应表现出地区差异;产业结构高级化受其前一期的显著影响,表明产业结构高级化进程具有显著的惯性。     

消费结构对产业结构与经济增长的空间效应——基于空间面板模型的研究

基于1997-2012年中国省域面板数据,采用空间自相关方法和空间计量模型,探讨了城乡居民消费结构对中国产业结构以及经济增长的空间效应。结果显示:中国省域城乡居民消费结构、产业结构和人均GDP的空间分布具有显著的空间集聚特征。城乡居民消费结构优化对本地区产业结构升级和经济增长具有积极的推动作用,城镇居民消费结构的空间溢出效应为显著负效应,农村居民消费结构的空间溢出效应则不显著。最后,根据城乡居民消费结构显示的不同空间效应,提出政策建议。     

区域金融发展规模、结构、效率与经济增长关系的动态分析

利用1991—2009年中国29个省份的面板数据,使用动态面板计量方法对金融发展规模、结构、效率与经济增长间的关系进行实证检验。结果表明:在控制住其他影响因素后,金融规模在中、西部地区对经济增长存在显著为正的影响,而在东部地区却表现出负方向的作用;金融结构和金融效率仅在东部地区呈现出显著为正的影响。进一步采用面板数据VAR模型探讨它们之间的因果关系,发现金融发展与经济增长之间的"需求跟随"模式发生在东部地区,"供给导向"模式在西部地区产生,而中部地区没有出现明显的金融发展模式。     

A model of uniform association plus two-diagonalsparameter and its application to occupational mobility table data

For the analysis of square contingency tables with ordered categories, Agresti (1988) introduced a model having the structure of uniform association plus a main-diagonal parameter. This paper extends that model. The extended model has the structure of uniform association plus two-diagonals-parameter, and it is a special case of the quasi-uniform association model introduced by Goodman (1979). The Danish occupational mobility table data are analyzed using the models introduced here.