A new method for finding hierarchical subgroups from networks

We present a new method for decomposing a social network into an optimal number of hierarchical subgroups. With a perfect hierarchical subgroup defined as one in which every member is automorphically equivalent to each other, the method uses the REGGE algorithm to measure the similarities among nodes and applies the k-means method to group the nodes that have congruent profiles of dissimilarities with other nodes into various numbers of hierarchical subgroups. The best number of subgroups is determined by minimizing the intra-cluster variance of dissimilarity subject to the constraint that the improvement in going to more subgroups is better than a network whose n nodes are maximally dispersed in the n-dimensional space would achieve. We also describe a decomposability metric that assesses the deviation of a real network from the ideal one that contains only perfect hierarchical subgroups. Four well known network data sets are used to demonstrate the method and metric. These demonstrations indicate the utility of our approach and suggest how it can be used in a complementary way to Generalized Blockmodeling for hierarchical decomposition.     

交强险的成本因素分析

 内容提要：本文应用聚类分析方法和Beta回归模型对2009年度交强险审计报告所披露的交强险经营数据进行了分析。结果表明,交强险在31个地区的赔付率差异显著,主要影响因素包括人均收入水平、物价指数、人均交通支出和人均车辆数。交强险9个业务类别之间的赔付率差异也很明显,表明现行保费水平存在严重的不公平。各地区的赔付率和费用率之间存在反常的负向相关关系,反映了交强险在费用分摊中存在某种不合理现象。保险公司的经营费用率在不同地区之间和不同业务类别之间都没有显著差异,主要受保险公司业务规模的影响,规模经济效应显著。     

地区与国家GDP核算总量数据衔接方法比较研究

 本文以国家数据为准,通过采用2005-2009年的数据为样本,从理论与实证上比较分析了地区与国家GDP数据衔接的三种方法即Geary和Stark的产出估算方法、线性调整法与辅助回归法,比较结果显示：（1）从理论上分析,三种方法都有其合理性,只是辅助回归法较另两种方法更具可取性。（2）从衔接效果上看,辅助回归法优于Geary和Stark的产出估算方法,Geary和Stark的产出估算方法又优于线性调整法。不过不同的方法皆有相应的适用场合与特点以及不同的衔接效果,因而只能说三种方法中有趋优的方法,但不能明确断定何种方法可以具体应用于实际数据衔接中并能达到良好的调整效果。     

半参数变系数回归模型的空间相关性检验

对半参数变系数回归模型,构造了新的空间相关性检验统计量,利用三阶矩 逼近方法导出了其检验 值的近似计算公式,蒙特卡罗模拟结果表明该统计量在检测空间相关性方面具有较高的准确性和可靠性。同时考察了误差项服从不同分布时的检验功效,体现出该检验方法的稳健性。进一步,我们还给出了检验统计量的Bootstrap方法以及检验水平的模拟效果。     

Method of Moments Estimation in Linear Regression with Errors in both Variables

Recently, in this journal, there has been revised attention on estimating the parameters of the errors in variables, linear structural model. For example, O’Driscoll and Ramirez (2011) used a geometric approach to give insight into the performance of various slope estimators for the linear structural model as introduced by the present author. This article aims to provide a unified method of moments approach for estimating the parameters in the linear structural model, concentrating attention on estimators using the higher moments, which to date has received only little attention in the literature.     

Simulation/Regression Pricing Schemes for CVA Computations on CDO Tranches

We devise simulation/regression numerical schemes for pricing the CVA on CDO tranches, where CVA stands for Credit Valuation Adjustment, or price correction accounting for the defaultability of a counterparty in an OTC derivatives transaction. This is done in the setup of a continuous-time Markov chain model of default times, in which dependence between credit names is represented by the possibility of simultaneous defaults. The main idea of this article is to perform the nonlinear regressions which are used for computing conditional expectations, in the time variable for a given state of the model, rather than in the space variables at a given time in diffusive setups. This idea is formalized as a lemma which is valid in any continuous-time Markov chain model. It is then implemented on the targeted application of CVA computations on CDO tranches.     

非线性参数异质Phillips曲线模型及应用

基于分位数回归理论与非线性回归方法,提出一个包容性较强的模型：非线性参数异质Phillips曲线模型,并给出其估计、检验与条件密度预测方法。该模型不仅可用于刻画Phillips曲线的非线性与非对称等典型特征,而且还可以揭示在不同经济环境下通货膨胀的完整分布变动规律,从而能够准确掌握通货膨胀的不确定性,便于科学决策。最后,将该模型应用于中国Phillips曲线特征研究,结果显示：该模型在拟合优度、结构分析、预测能力等方面优于其他Phillips曲线模型。     

一类基于非参数回归的条件异方差检验

现有基于参数模型构造的条件异方差检验往往存在模型设定偏误问题。为了避免模型误设对检验结果的影响,并且同时捕获多种条件异方差现象,本文基于非参数回归构造了不依赖于特定模型形式的条件异方差检验统计量。该统计量可视作条件方差和无条件方差之间差异的加权平均,在原假设成立时渐近服从标准正态分布。数值模拟结果一方面表明本文统计量具有良好的有限样本性质,另一方面也说明条件均值模型误设会导致错误地拒绝条件同方差的原假设,凸显了本文引入非参数方法构造条件异方差检验的必要性。实证分析采用本文统计量探讨了国际主要股指收益率的条件异方差现象,得到了与Engle (1982)不同的检验结果,可能意味着股指收益率呈现出非线性动态特征。     

Finite sample properties of ml and reml estimators in time series regression models with long memory noise

Finite sample properties of ML and REML estimators in time series regression models with fractional ARIMA noise are examined. In particular, theoretical approximations for bias of ML and REML estimators of the noise parameters are developed and their accuracy is assessed through simulations. The impact of noise parameter estimation on performance of t -statistics and likelihood ratio statistics for testing regression parameters is also investigated.