The social benefits of water and sanitation projects in Northern Colombia: Cost‐Benefit Analysis,the Water Poverty Index and beyond

Water, and Sanitation projects play an important role in alleviating water‐related poverty in developing countries. There are several methodologies that will not only assess the performance of these projects but will also help to better identify the problem and its characteristics, and to improve the efficiency of the investment. The Water Poverty Index is one of them. It is a very useful tool that helps to measure water stress at the household level in a holistic way, and to identify priorities. It is important, however, to complement it with a Cost‐Benefit Analysis that will take into account the costs of the project. A case study in Northern Colombia illustrates this point.     

Generalized simultaneous confidence regions for regression coefficients and their ratios

This study constructs a simultaneous confidence region for two combinations of coefficients of linear models and their ratios based on the concept of generalized pivotal quantities. Many biological studies, such as those on genetics, assessment of drug effectiveness, and health economics, are interested in a comparison of several dose groups with a placebo group and the group ratios. The Bonferroni correction and the plug-in method based on the multivariate-t distribution have been proposed for the simultaneous region estimation. However, the two methods are asymptotic procedures, and their performance in finite sample sizes has not been thoroughly investigated. Based on the concept of generalized pivotal quantity, we propose a Bonferroni correction procedure and a generalized variable (GV) procedure to construct the simultaneous confidence regions. To address a genetic concern of the dominance ratio, we conduct a simulation study to empirically investigate the probability coverage and expected length of the methods for various combinations of sample sizes and values of the dominance ratio. The simulation results demonstrate that the simultaneous confidence region based on the GV procedure provides sufficient coverage probability and reasonable expected length. Thus, it can be recommended in practice. Numerical examples using published data sets illustrate the proposed methods.     

On robustness of the Shiryaev–Roberts change-point detection procedure under parameter misspecification in the post-change distribution

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-versus-“false-positive”-risk manner. When optimality is understood either in the generalized Bayesian sense or as defined in Shiryaev's multi-cyclic setup, the so-called Shiryaev–Roberts (SR) detection procedure is known to be the “best one can do”, provided, however, that the observations’ pre- and post-change distributions are both fully specified. We consider a more realistic setup, viz. one where the post-change distribution is assumed known only up to a parameter, so that the latter may be misspecified. The question of interest is the sensitivity (or robustness) of the otherwise “best” SR procedure with respect to a possible misspecification of the post-change distribution parameter. To answer this question, we provide a case study where, in a specific Gaussian scenario, we allow the SR procedure to be “out of tune” in the way of the post-change distribution parameter, and numerically assess the effect of the “mistuning” on Shiryaev's (multi-cyclic) Stationary Average Detection Delay delivered by the SR procedure. The comprehensive quantitative robustness characterization of the SR procedure obtained in the study can be used to develop the respective theory as well as to provide a rational for practical design of the SR procedure. The overall qualitative conclusion of the study is an expected one: the SR procedure is less (more) robust for less (more) contrast changes and for lower (higher) levels of the false alarm risk.     

广西农业剩余劳动力转移状况研究

广西要想在西部率先全面建成小康社会。必须解决好农业剩余劳动力的转移问题。本文使用抽样法测算广西2008年农业剩余劳动力总数,并按照劳动力转移去向进行统计分析,揭示转移中存在的突出性问题和提出对策建议。     

大学生社会文化价值观特征分析

一个民族的文化通常有其系统性与适用的价值观,在当今中西文化交融的时代背景下,作为未来栋梁的大学生选择何种价值观体系,一直受到学术界的普遍关注。借鉴相关价值观研究理论,通过因子分析的方法,归纳出大学生的7个价值观类型,并揭示出大学生社会文化价值观的主要特征,即儒家思想中的进取精神得到了大学生的普遍认同,而极端功利与利己主义受到大学生的强烈排斥,大学生的"自我意识"呈现出不统一的特点,实用主义观念在大学生中广泛存在,传统价值观中的"节俭观"和"宿命论"在大学生中受到了严峻的挑战。     

对耕地利用率影响因素及影响效应的统计分析

耕地承包农户的户主年龄、家庭非农收入、土地转让行为选择、农户择业意愿、耕地条件与环境等因素与耕地利用率之间存在显著相关。对此,政府首先必须加强对农民的重农教育,增强农民珍爱耕地的自觉性;其次,应创新耕地管理制度,引导土地合理流转;其三,推进农村土地流转规范,提升耕地资产价值效能;其四,加大支农惠农政策力度,提高农业比较收益;其五,扩大对农村投入,改善农村农业基础设施建设。     

农村留守儿童家庭教养方式的社会学分析

通过对农村"留守儿童"家庭教养方式的现状进行描述和归纳,分析产生不同类型的家庭教养方式的原因,以期引起社会各界对留守儿童群体的关注,更好地指导农村"留守儿童"的家庭教养方式,提高家庭教育质量,促进儿童的健康成长。     

基于因子分析的产学研合作教育影响因素研究

本文通过构建产学研合作教育影响因素的指标体系,运用因子分析法导出其中的主要影响因素,通过多元回归分析,进一步厘清各因子的影响程度,提出促进产学研合作教育人才培养机制的对策建议。     

STOCHASTIC COST-VOLUME-PROFIT ANALYSIS IN A COMPETITIVE OLIGOPOLY

Previous stochastic cost-volume-profit (CVP) models have assumed that the firm was operating under either perfect competition or monopolistic conditions. This paper presents a stochastic CVP model applicable to oligopolistic competition. Each firm is assumed to maximize a linear function of the expected value and the standard deviation of its random profits. The result is a game-theoretic model that is solved using the concept of a Nash equilibrium. The results of the model are used to examine a firm's competitive strength. The model can be easily modified to accommodate a measure of risk based on the capital asset pricing theory.     

MODELING THE ALLOCATION OF GRADUATE STUDENT FINANCIAL AID

Universities have always competed with one another for the relatively small number of highly qualified students interested in graduate education. This competition has been intensified recently by adverse demographic trends. This paper is concerned with the use of financial aid awards as a means of competition and with allocation of awards so that enrollments are maximized while satisfying academic standards and budget constraints. It also considers the randomness of actual aid disbursements and develops models of incremental aid allocation that increase enrollments but are within tolerance levels for budget overruns.