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摘要： This dissertation has three essays on econometrics. Essay one is about the gravity model, which is one of the most popular applied econometric models in trade literature. The existing theory predicts that the coefficients of the national income variables should be unity. In the empirical application, either export or import flow are often used as the dependent variable. However, their estimated coefficients are different from unity. This essay shows that the conflicting results could be caused by misspecifications, which are the results of improper choice of dependent variables and simultaneous equation bias. Essay two considers an alternative cointegration test when the error term consists of two independent components, a white noise and a random walk. Such a dual composition of the error term is known as the adaptive regression model, which is a special case of the stochastic parameter variation model. This essay develops alternative test statistics and show they are distributed asymptotically as chi-square. Essay three introduces the nested AR(1) model which synthesizes two types of specifications of the residual term, the first-order autocorrelation and the adaptive regression model. The nested AR(1) model introduced in this essay has never been considered in econometric literature. In addition to exploring the theoretical properties of this specification, this essay also derives the critical values of the test statistics.

摘要： Several semiparametric estimators recently developed in the econometrics literature are based on the rank correlation between the dependent and explanatory variables. Examples include the maximum rank correlation estimator (MRC) of Han [1987], the monotone rank estimator (MR) of Cavanagh and Sherman [1998], the pairwise-difference rank estimators (PDR) of Abrevaya [2003], and others. These estimators apply to various monotone semiparametric single-index models, such as the binary choice models, the censored regression models, the nonlinear regression models, and the transformation and duration models, among others, without imposing functional form restrictions on the unknown functions and distributions. This work provides several new results on the theory of rank-based estimators. In Chapter 2 we prove that the quantiles and the variances of their asymptotic distributions can be consistently estimated by the nonparametric bootstrap. In Chapter 3 we investigate the accuracy of inference based on the asymptotic normal and bootstrap approximations, and provide bounds on the associated error. In the case of MRC and MR, the bound is a function of the sample size of order close to n --1/6. The PDR estimators, however, belong to a special subclass of rank estimators for which the bound is vanishing with the rate close to n--1/2. In Chapter 4 we study the efficiency properties of rank estimators and propose weighted rank estimators that improve efficiency. We show that the optimally weighted MR attains the semiparametric efficiency bound in the nonlinear regression model and the binary choice model. Optimally weighted MRC has the asymptotic variance close to the semiparametric efficiency bound in single-index models under independence when the distribution of the errors is close to normal, and is consistent under practically relevant deviations from the single index assumption. Under moderate nonlinearities and nonsmoothness in the data, the efficiency gains from weighting

摘要： The goal of this dissertation is to contribute to our understanding of how healthcare services adapt to varying levels of demand for hospital resources. As in many other service organizations, hospital capacity (beds, staff, and equipment) is fixed in the short term, while the arrival of patients and their demand for hospital resources is stochastic in nature. When confronted with an unexpected increase in demand for services, hospitals can adapt by either increasing their service rates, or by rationing capacity depending on the needs of individual patients. These adaptive responses can have implications for quality of care and access to services. It is this interplay between capacity utilization, productivity and quality in healthcare service delivery that is the primary focus of this dissertation.

ISBN: (纸本)9787811223903

关键词： 计量经济学   教学效果  

摘要： 对近年来通过《计量经济学》课程的讲授所发现的几点问题进行了阐述,提出了增加计量经济学课时,采用多媒体方式授课,重视计量软件的学习,重视实践教学以及加强师资力量培训等建议。

关键词： 经济学理论   北京信息科技大学   管理学院   梅森大学   乔治   美国   美利坚合众国   北美洲   经济学实验   数量经济学   计量经济学   经济计量学   学术研讨会   高级讲习班  

关键词： 猪肉   价格   人均可支配收入  

摘要： 随着生活水平的提高,人们对猪肉的需求量也在增加,通过建立猪肉需求量及其影响因素价格和人均可支配收入之间的计量经济学模型分析可以看出,猪肉的价格对其需求量的影响在统计上是不显著的,对人均可支配收入是显著的,这表明猪肉的需求量缺乏价格弹性,它已成为饮食中很重要的成分,所以稳定价格,保证供应量对构建和谐社会十分重要。

关键词： 空间计量经济学   地理信息系统   集成   插件  

摘要： 在地理信息科学领域,空间分析扮演着重要的作用。但在目前的地理信息系统软件中,空间分析功能仍是一个薄弱环节,即便是美国ESRI公司的ArcGIS,其空间分析模块也仅局限于探索性空间数据分析的功能,基于空间计量经济学的确认性空间数据分析功能依然缺失,从而极大地限制了地理信息系统作为空间问题研究支持平台的作用。本研究的目标就是解决这一问题。 论文从空间计量经济学与地理信息系统集成的角度,设计了以插件式开发模式来进行空间计量经济学软件SpData的开发,并通过空间计量建模计算的经典数据验证了本软件计算结果的可靠性。 本论文共分为五章,按照软件工程开发的过程来进行空间计量经济学软件的开发。 第一章“前言”部分进行了空间计量经济学发展概述,与相关学科如空间统计学、地理信息科学等学科的关系,并讨论了空间计量经济分析与地理信息系统(GIS)的集成,最后说明了本文的研究内容、研究目标和研究结构。 第二章“空间计量经济学模型”介绍中,详细描述了现有的空间计量经济学模型包括标准最小二乘法回归(OLS)及其空间影响诊断、空间位滞模型(spatiallag model)、空间误差模型(spatial error model)、异方差误差模型及其空间影响的诊断,并列出了每种模型的计算过程和公式。 第三章“系统设计”,按照软件工程学原理,从软件的需求分析(包括功能上的需求和非功能上的需求),到软件的结构设计和功能设计,并详细介绍了插件开发的原理和方法、连接点技术以及多视图动态链接窗口的实现。 第四章“软件计算实例”,采用空间计量经济学常用的入门数据:spacestat软件附带的美国Ohio州Columbus市数据,展示了软件SpData的各项功能,包括探索性空间数据分析和空间数据的可视化分析、动态链接窗口(盒线图、三维显示图、Moran'I散点图等)、空间计量经济学建模。对数据进行了空间权重文件的建立、OLS回归及其空间影响的诊断、空间位滞模型的建立、空间误差模型的建立等。 第五章“研究总结和展望”,列出了目前软件的不足部分,并对空间计量经济学的发展进行了一定的展望。

关键词： 计量经济学模型   总体回归模型   理论导向   数据导向   动力学关系导向  

摘要： 本文从计量经济学应用研究中总体回归模型设定的任务和目标出发，通过对总体模型设定的研究目的导向、经济学理论导向、数据关系导向的分析与评价，提出总体模型设定的唯一性、一般性、现实性和统计检验必要性原则；最后，提出总体回归模型设定的“经济主体动力学关系导向”原则和框架。

关键词： 平均商品房价格   可支配收入   经济增长速度   利率   计量经济学  

摘要： 本文在经济学的理论基础上建立了1995-2004年间的江苏省平均商品房价格的计量模型。通过对平均商品房价格的多因素分析,建立以平均商品房价格为应变量,以新增住宅面积,居民可支配收入,经济增长率,实际利率,居民人口数为自变量的多元线性回归模型,并利用模型对平均商品房价格的原因进行数量化分析,并对其如何变化提供一些参考性的意见。