Analysis of some ruin-related quantities in a Markov-modulated risk model

In this paper, we study the joint Laplace transform and probability generating function of some random quantities that occur in each environment state by the time of ruin in a Markov-modulated risk process. These quantities include the duration spent in each state, the number of claims and the aggregate amount of claims that occurred in each state by the time of ruin. Explicit formulae for the joint transforms, given the initial surplus, and the initial and terminal environment states, are expressed in terms of a matrix version of the scale function. Moments and covariances of these ruin-related quantities are obtained and numerical illustrations are presented. The joint transform of the duration spent in each state, the number of claims, and the aggregate amount of claims that occurred in each state by the time the surplus attains a certain level are also investigated.     

我国居民文化消费影响因素探析

运用我国1983—2012年的数据,通过实证分析考察了可支配收入、教育水平、金融发展和政府文化事业支出对我国居民文化消费的影响。长期均衡分析结果表明,教育水平和金融发展对我国居民文化消费具有显著的促进作用;教育水平提高1%,居民文化消费增加0.454%;金融机构信贷提高1%,居民文化消费增加0.363%;可支配收入和政府文化事业支出对居民文化消费的影响不显著。脉冲响应分析结果表明,可支配收入冲击对居民文化消费的影响在短期由正向转为负向,教育水平冲击和金融发展冲击对居民文化消费短期具有正向影响,政府文化事业支出冲击对居民文化消费短期具有负面影响。根据实证分析的结论,文章提出了扩大我国居民文化消费的政策建议。     

论汉魏六朝仪式歌辞的文化功能与传播特点

仪式歌辞是为满足封建王朝各种仪式活动需要而创作音乐歌辞,因其满足仪式活动之需的特殊功能,内容上强调其与仪式活动符号象征的一致性,形式上多采用典雅的四言正格,在传播方式上呈现出程序性、依附性、组织性和共时性特点。仪式歌辞特殊的文化功能和传播特点决定了其传播效果的局限性,在传播范围的拓展性、传播时间的延续性方面均不能与娱乐歌辞相比,人们对仪式歌辞的接受,也主要是从其内容的“象征图式”和“意象结构”出发的,是否美听悦耳不是接受重点。     

A New Quantile Function with Applications to Reliability Analysis

In this article, we propose a new class of distributions defined by a quantile function, which nests several distributions as its members. The quantile function proposed here is the sum of the quantile functions of the generalized Pareto and Weibull distributions. Various distributional properties and reliability characteristics of the class are discussed. The estimation of the parameters of the model using L-moments is studied. Finally, we apply the model to a real life dataset.     

Oracle Inequalities for Convex Loss Functions with Nonlinear Targets

This article considers penalized empirical loss minimization of convex loss functions with unknown target functions. Using the elastic net penalty, of which the Least Absolute Shrinkage and Selection Operator (Lasso) is a special case, we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target is linear, this inequality also provides an upper bound of the estimation error of the estimated parameter vector. Next, we use the non-asymptotic results to show that the excess loss of our estimator is asymptotically of the same order as that of the oracle. If the target is linear, we give sufficient conditions for consistency of the estimated parameter vector. We briefly discuss how a thresholded version of our estimator can be used to perform consistent variable selection. We give two examples of loss functions covered by our framework.     

Temporal Disaggregation: Methods,Information Loss,and Diagnostics

This research provides a generalized framework to disaggregate lower-frequency time series and evaluate the disaggregation performance. The proposed framework combines two models in separate stages: a linear regression model to exploit related independent variables in the first stage and a state–space model to disaggregate the residual from the regression in the second stage. For the purpose of providing a set of practical criteria for assessing the disaggregation performance, we measure the information loss that occurs during temporal aggregation while examining what effects take place when aggregating data. To validate the proposed framework, we implement Monte Carlo simulations and provide two empirical studies. Supplementary materials for this article are available online.     

Imposing and Testing for Shape Restrictions in Flexible Parametric Models

In many economic models, theory restricts the shape of functions, such as monotonicity or curvature conditions. This article reviews and presents a framework for constrained estimation and inference to test for shape conditions in parametric models. We show that “regional” shape-restricting estimators have important advantages in terms of model fit and flexibility (as opposed to standard “local” or “global” shape-restricting estimators). In our empirical illustration, this is the first article to impose and test for all shape restrictions required by economic theory simultaneously in the “Berndt and Wood” data. We find that this dataset is consistent with “duality theory,” whereas previous studies have found violations of economic theory. We discuss policy consequences for key parameters, such as whether energy and capital are complements or substitutes.     

Indirect membership function assignment based on ordinal regression

In many fuzzy sets applications, fuzzy membership functions are commonly developed based on empirical or expert knowledge. The equation of a membership function is usually determined somewhat arbitrarily. This paper explores a novel membership function design method based on ordinal regression analysis. The estimated thresholds between ordinal measurement categories are applied to calculate the intersection points between fuzzy sets. These intersection points are further applied to determine the equations of the membership functions. Information distortion due to empirical guess can thus be reduced and more latent information in the fuzzy responses can therefore be captured. A case study investigating the relationship between foster mothers’ satisfaction and the foster time and information provided has been conducted in this research. The applicability and effectiveness of the proposed membership function assignment approach have been demonstrated through several case studies.