农村居民消费融资需求及影响因素分析——以陕西省渭南市为例

基于渭南市2 636户农户问卷调查数据,从农户分化与演变视觉分析农村居民消费融资需求状况。采用概率模型分析了影响农户融资消费的主要因素是收支的＂非均衡性＂、户主个性、消费环境、城乡融合程度和存贷款利率水平高低。建议调整国民收入分配结构,完善农村基本社会保障体系,推进农村居民生产生活集聚,构建以农户需求为导向的农村金融体系。     

Knowledge extraction from a large on-line survey: a case study for a higher education corporate marketing

For a higher education public institution, young in relative terms, featuring local competition with another private and both long-established and reputed one, it is of great importance to become a reference university institution to be better known and felt with identification in the society it belongs to and ultimately to reach a good position within the European Higher Education Area. These considerations have made the university governors setting up the objective of achieving an adequate management of the university institutional brand focused on its logo and on image promotion, leading to the establishment of a university shop as it is considered a highly adequate instrument for such promotion. In this context, an on-line survey is launched on three different kinds of members of the institution, resulting in a large data sample. Different kinds of variables are analysed through appropriate exploratory multivariate techniques (symmetrical methods) and regression-related techniques (non-symmetrical methods). An advocacy for such combination is given as a conclusion. The application of statistical techniques of data and text mining provides us with empirical insights about the institution members’ perceptions and helps us to extract some facts valuable to establish policies that would improve the corporate identity and the success of the corporate shop.     

引入TOPSIS法的风险预警模型能提高模型的预警准确度吗?——来自我国制造业上市公司的经验证据

样本选取2011年和2012年我国沪深A股制造业中因财务困境陷入ST的公司和按照1:2比例配比的正常公司作为研究对象,并选取反映企业盈利能力、股东获利能力、现金流量能力、营运能力、发展能力、偿债能力的30个财务指标以及股权结构、管理结构、公司所在地的8个定性指标,以2011年的样本作为训练集,2012年样本作为测试集,在主成分分析的基础上构建以Logit模型为基础的传统预警模型和引入TOPSIS法后的二重分类模型。结果表明,引入TOPSIS法后构建的Logit模型能显著提高模型的预警准确度:对ST公司的预警准确度能提高18.5%,对样本总体的预警准确度能提高11.1%,这说明二重分类法可以构建有效的风险预警模型。     

Eliciting expert judgements about a set of proportions

Eliciting expert knowledge about several uncertain quantities is a complex task when those quantities exhibit associations. A well-known example of such a problem is eliciting knowledge about a set of uncertain proportions which must sum to 1. The usual approach is to assume that the expert's knowledge can be adequately represented by a Dirichlet distribution, since this is by far the simplest multivariate distribution that is appropriate for such a set of proportions. It is also the most convenient, particularly when the expert's prior knowledge is to be combined with a multinomial sample since then the Dirichlet is the conjugate prior family. Several methods have been described in the literature for eliciting beliefs in the form of a Dirichlet distribution, which typically involve eliciting from the expert enough judgements to identify uniquely the Dirichlet hyperparameters. We describe here a new method which employs the device of over-fitting, i.e. eliciting more than the minimal number of judgements, in order to (a) produce a more carefully considered Dirichlet distribution and (b) ensure that the Dirichlet distribution is indeed a reasonable fit to the expert's knowledge. The method has been implemented in a software extension of the Sheffield elicitation framework (SHELF) to facilitate the multivariate elicitation process.     

How long is the queuing for public childcare facilities in Korea? An empirical analysis of Korean households' childcare mode choice with the limited availability of public childcare facilities

This paper empirically investigates Korean households' choice of childcare mode using the Korean Childcare Users Survey (2012). A multivariate logit model with partial observability (hereafter, PO‐logit model) is employed to address the issue of Korean households' demand for public childcare facilities exceeding capacity limits. Our estimation result rejects the hypothesis of no queueing at conventional significance levels to advocate use of the PO‐logit model in explaining Korean households' childcare choices. We decompose choice probabilities of public childcare facilities to estimate the size of queuing. Our results imply that 31.8% of parents preferring public childcare facility are forced to choose other childcare modes due to capacity limit.     

中国电动汽车配套基础设施布局需求侧研究——基于Logit回归的消费偏好分析

从消费者偏好角度出发,通过一系列实地访谈、问卷调研,获取需求侧第一手数据,综合利用因子分析及Logit回归方法,发现在电动汽车配套基础设施布局过程中,消费者比较重视社会环境效益、技术属性、内在条件及外在属性四大类因子.同时研究发现,消费者对汽车的消费意识也有所变化,从节能与减排的角度出发,消费者倾向于购买能源补给成本较低、环保效果更好的车型.在需求侧研究的基础上,立足中国电动汽车行业及其充电基础设施的实际情况,可从突破技术瓶颈、推广分散式充电桩、油电一体化加油、充换电站、充分考虑消费者偏好四个方面着手,进一步完善中国电动汽车配套基础设施布局,推动电动汽车的产业化和规模化.     

Attributions of Blame among Victims of Child Sexual Abuse: Findings from a Community Sample

ABSTRACT

According to the attribution theory, negative outcomes of child sexual abuse (CSA) are thought to vary depending on whether CSA victims attribute the abuse to internal or external factors, respectively, self-blame and perpetrator-blame. Therefore, the purpose of this study was to identify abuse characteristics and attitudes that influence blame attributions among CSA victims from a community sample. Data from respondents with a history of CSA (N = 1,496) have been used in predicting blame attributions; perpetrator-blame, self-blame, or both. Results from a multinomial logistic regression analysis showed that attitudes toward gender roles had a significant effect on blame: victims were more likely to blame themselves when they endorsed more conservative gender attitudes than victims with more liberal attitudes. Implications for this finding are discussed.     

Stochastic Choice and Consideration Sets

We model a boundedly rational agent who suffers from limited attention. The agent considers each feasible alternative with a given (unobservable) probability, the attention parameter, and then chooses the alternative that maximizes a preference relation within the set of considered alternatives. We show that this random choice rule is the only one for which the impact of removing an alternative on the choice probability of any other alternative is asymmetric and menu independent. Both the preference relation and the attention parameters are identified uniquely by stochastic choice data.     

安徽省农业保险需求影响因素调查与分析

基于历年安徽省统计年鉴和2007年在安徽部分地区的农业保险需求调查问卷,进行描述性统计分析,并利用logit模型对安徽省农业保险需求的影响因素进行实证分析。结果表明：农民的年纯收入、是否购买过农业保险对农业保险需求影响显著,并与其呈正相关关系,其他几个因素对农业保险需求影响不显著。在此基础上,提出相应的对策建议。     

Symbolic computation for approximating distributions of some families of one and two-sample nonparametric test statistics

A conditional saddlepoint approximation was provided by Gatto and Jammalamadaka (1999) for computing the distribution function of many test statistics based on dependent quantities like multinomial frequencies, spacing frequencies, etc. The considerable complexity of the formulas involved can be bypassed by symbolic computation. This article illustrates the effectiveness of symbolic computation to evaluate the saddlepoint approximation for the likelihood ratio, the exponential score, and the Wald-Wolfowitz test statistics. The case of composite hypotheses is also discussed.