The status of women among the scheduled tribes in India

The scheduled tribes constitute about 8.2% of the total population in India. Although there is a large volume of anthropological literature describing the characteristics of and differences among the various tribes in India, little inter-disciplinary research has been done to uncover the status of women among the tribal population in India. This paper will analyze the status of women among the scheduled tribes in India. Frequent comparisons will be made to the social and cultural practices of the scheduled tribes, mainstream Hindus, as well as the scheduled caste population. Through this analysis, we will show the distinctiveness of the tribal cultures and the fact that many women from the scheduled tribes face less discrimination than Hindu women and those from scheduled castes.     

Conditional Likelihood Estimators for Hidden Markov Models and Stochastic Volatility Models

ABSTRACT.  This paper develops a new contrast process for parametric inference of general hidden Markov models, when the hidden chain has a non-compact state space. This contrast is based on the conditional likelihood approach, often used for ARCH-type models. We prove the strong consistency of the conditional likelihood estimators under appropriate conditions. The method is applied to the Kalman filter (for which this contrast and the exact likelihood lead to asymptotically equivalent estimators) and to the discretely observed stochastic volatility models.     

论对妇女就业机会歧视的法律规制

我国当前的对女性就业机会歧视的现象相当严重,表现在招收录用、职业培训、退休年龄、下岗等各方面.为了在法律上对之进行规制,我们应该在严格执行现行法律法规的基础上,进一步完善相关法律法规,尤其是完善<妇女权益保障法>的相关规定;同时要推行生育保险,促进就业.     

A Unified Approach to the Characterization of Equivalence Classes of DAGs, Chain Graphs with no Flags and Chain Graphs

Abstract.  A Markov property associates a set of conditional independencies to a graph. Two alternative Markov properties are available for chain graphs (CGs), the Lauritzen–Wermuth–Frydenberg (LWF) and the Andersson–Madigan– Perlman (AMP) Markov properties, which are different in general but coincide for the subclass of CGs with no flags . Markov equivalence induces a partition of the class of CGs into equivalence classes and every equivalence class contains a, possibly empty, subclass of CGs with no flags itself containing a, possibly empty, subclass of directed acyclic graphs (DAGs). LWF-Markov equivalence classes of CGs can be naturally characterized by means of the so-called largest CGs , whereas a graphical characterization of equivalence classes of DAGs is provided by the essential graphs . In this paper, we show the existence of largest CGs with no flags that provide a natural characterization of equivalence classes of CGs of this kind, with respect to both the LWF- and the AMP-Markov properties. We propose a procedure for the construction of the largest CGs, the largest CGs with no flags and the essential graphs, thereby providing a unified approach to the problem. As by-products we obtain a characterization of graphs that are largest CGs with no flags and an alternative characterization of graphs which are largest CGs. Furthermore, a known characterization of the essential graphs is shown to be a special case of our more general framework. The three graphical characterizations have a common structure: they use two versions of a locally verifiable graphical rule. Moreover, in case of DAGs, an immediate comparison of three characterizing graphs is possible.     

产品众筹中价格歧视策略的优化研究

产品众筹是一种常见的众筹形式,它要求企业为支持者提供创新型产品或服务作为回报。合理的定价策略是产品众筹的关键,本文分别从项目成功率和利润最大化角度研究价格歧视的优化问题。针对产品众筹全有或全无（All-or-Nothing,AoN）的机制下采用价格歧视策略时,价格差值和低价销售定额的最优决策问题。本文首先采用随机模型定义购买概率函数,分析支持者在购买过程中的影响因素;然后从项目支持者效用角度出发,应用两阶段模型讨论价格差值的相关影响因素,研究发现两级价格差值会受到级联效应、项目的特征以及支持者特征的影响。并且从支持者估值类型方向对基础模型进行了扩展,讨论了不同估值类型的支持者在不同价格差值范围内的选择行为;再则从项目的利润最大化角度出发讨论价格差值问题,研究发现价格差值受支持者数量和项目目标值的影响;最后通过计算相对利润函数解出最优低价销售定额的数量。     

Comparative probability for conditional events: A new look through coherence

We study, from the standpoint of coherence, comparative probabilities on an arbitrary familyE of conditional events. Given a binary relation ·, coherence conditions on · are related to de Finetti's coherent betting system: we consider their connections to the usual properties of comparative probability and to the possibility of numerical representations of ·. In this context, the numerical reference frame is that of de Finetti's coherent subjective conditional probability, which is not introduced (as in Kolmogoroff's approach) through a ratio between probability measures.Another relevant feature of our approach is that the family & need not have any particular algebraic structure, so that the ordering can be initially given for a few conditional events of interest and then possibly extended by a step-by-step procedure, preserving coherence.     

增长性市场条件下垄断定价的实物期权方法

许多研究垄断厂商定价的文献忽视了垄断厂商拥有的调整价格的权利. 事实上,这种调 价的权利等价于厂商拥有的一个实物期权. 基于此,应用实物期权的方法确定了增长性市场条 件下调价权利(调价期权) 的价值,进而研究了垄断厂商的定价行为,给出了企业价值最大化的 条件. 结果表明,在增长性市场中,需求状况的好坏决定了垄断厂商的定价决策是否考虑调价 期权. 并且,当垄断厂商定价考虑其拥有的调价期权的价值时,除一些特殊情形外,边际收益等 于边际成本,不再适用垄断厂商的定价决策     

中国单身女性的困境: 多元交叉的社会压力和歧视

随着中国单身人口比例的上升,单身人群特别是单身女性群体受到了社会各个层面的关注。目前国内对单身女性的研究主要通过深度访谈来探讨单身未婚女性的身心和生活状态,缺乏系统的理论观照,且访谈样本又大都局限于大城市的中产阶层单身未婚女性,因而限制了研究成果的代表性。从交叉性理论出发,分析中国单身女性面临的宏观(儒家文化和人口调控压力)、中观(媒体的形象控制和代际压力)和微观(性别歧视、年龄歧视和单身歧视)的多元交叉压力和歧视,厘清目前单身女性所受到的压力和歧视,从不同阶层单身女性的需求出发,才能为她们提供切实有效的帮助,并有助于解决目前我国单身人口比例上升的问题,缓解人口老龄化的压力。     

超高频数据的日内效应调整方法研究

日内效应在金融高频数据研究中已被广泛证实,是一种日内周期性运动的动态效应,它影响了以微观金融指标为参数的计量模型的准确估计。基于金融超高频持续期数据,本文首先论述了日内效应调整的重要性,然后引入自适应映射(SOM)的方法对日内效应进行调整。SOM是一种基于神经网络学习的特征提取方法,能够动态识别高维数据中的结构特征,克服了静态调整方法的不足。最后通过建立基于自回归条件持续期模型(ACD)的蒙特卡罗模拟实验,比较了三种日内效应调整方法的效果。模拟结果表明SOM方法在日内效应调整中更为有效和稳定,特别适合大数据条件下的周期性结构分析。     

基于条件概率积分变换的多元Copula函数选择

本文构建了基于条件概率积分变换的Copula函数选择方法,通过对条件概率积分变换下Anderson-Darling(AD)、Kolmogorov-Smirnov(KS)、Cramér-von Mises(CM)这三种统计量的比较,讨论在不同样本容量和变量维数下其对多种Copula函数的拟合效果。利用GSPTSE、INMEX.MX和NDX三大股指样本,将基于条件概率积分变换的Copula函数选择方法与核密度估计和极大似然估计选择法的效果进行系统比较。结果表明,基于条件概率积分变换的检验法可以有效解决多元Copula函数的选择问题,其拟合优度检验更精确、更稳定;核密度估计检验在大样本下比较稳定,而小样本下稳定性较差;相比之下,极大似然值检验法则不稳定。