A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covariates or regressors). Although multinomial logit is widely used in both the social and economic sciences, the interpretation of regression coefficients may be tricky, as the effect of covariates on the probability distribution of the response variable is nonconstant and difficult to quantify. The ternary plots illustrated in this article aim at facilitating the interpretation of regression coefficients and permit the effect of covariates (either singularly or jointly considered) on the probability distribution of the dependent variable to be quantified. Ternary plots can be drawn both for ordered and for unordered categorical dependent variables, when the number of possible outcomes equals three (trinomial response variable); these plots allow not only to represent the covariate effects over the whole parameter space of the dependent variable but also to compare the covariate effects of any given individual profile. The method is illustrated and discussed through analysis of a dataset concerning the transition of master’s graduates of the University of Trento (Italy) from university to employment.     

Women's employment decisions in Malaysia: Does religion matter?

Religion may influence female employment decisions because different religions specify different life styles. This study investigates whether religion is a significant determinant of married and single women's paid-work and full-time employment in Malaysia. Using the Second Malaysian Family Life Survey and a sequential logit approach, this paper finds that religion is less influential in urban areas than in rural areas.     

Binary Dynamic Logit for Correlated Ordinal: estimation,application and simulation

We evaluate the estimation performance of the Binary Dynamic Logit model for correlated ordinal variables (BDLCO model), and compare it to GEE and Ordinal Logistic Regression performance in terms of bias and Mean Absolute Percentage Error (MAPE) via Monte Carlo simulation. Our results indicate that when the proportional-odds assumption does not hold, the proposed BDLCO method is superior to existing models in estimating correlated ordinal data. Moreover, this method is flexible in terms of modeling dependence and allows unequal slopes for each category, and can be used to estimate an apple bloom data set where the proportional-odds assumption is violated. We also provide a function in R to implement BDLCO.     

公司治理影响债务期限结构类型吗?——来自中国上市公司的经验证据

本文采用面板数据,应用Logit模型和排序选择模型实证检验公司治理机制如何影响债务期限结构类型。研究发现公司治理确实对债务期限结构类型具有显著影响。经验结果大多支持治理水平高的公司,其内部人（管理者,控制股东）受到更严格的监督,债务供给者（银行）更愿意为其提供长期债务,其更倾向使用高的债务期限类型的论点。     

产融结合退出及影响因素分析——基于参股非上市金融公司视角的实证研究

以2007—2014年发生的我国A股上市公司参股非上市金融公司事件作为研究样本，对企业退出产融结合的现象进行了探讨，实证结果表明：每股收益越低、资产负债率越高、协同费用率越高、产融结合年限越短，企业越有可能退出产融结合。研究能帮助企业在实施产融结合后更有针对性地关注自身运营状况和财务状况，也为其建立健全风险监督与防范机制提供了一定的政策支持。     

Bounding Optimal Expected Revenues for Assortment Optimization under Mixtures of Multinomial Logits

We consider assortment problems under a mixture of multinomial logit models. There is a fixed revenue associated with each product. There are multiple customer types. Customers of different types choose according to different multinomial logit models whose parameters depend on the type of the customer. The goal is to find a set of products to offer so as to maximize the expected revenue obtained over all customer types. This assortment problem under the multinomial logit model with multiple customer types is NP‐complete. Although there are heuristics to find good assortments, it is difficult to verify the optimality gap of the heuristics. In this study, motivated by the difficulty of finding optimal solutions and verifying the optimality gap of heuristics, we develop an approach to construct an upper bound on the optimal expected revenue. Our approach can quickly provide upper bounds and these upper bounds can be quite tight. In our computational experiments, over a large set of randomly generated problem instances, the upper bounds provided by our approach deviate from the optimal expected revenues by 0.15% on average and by less than one percent in the worst case. By using our upper bounds, we are able to verify the optimality gaps of a greedy heuristic accurately, even when optimal solutions are not available.     

规模养殖户对疫病防控公共服务的满意度研究

利用霍邱、肥东、长丰三县调研数据,构建logit模型分析养殖户对疫病防控公共服务的满意度及其影响因素.研究结果表明,规模养殖户满意度受到养殖年数、预防免疫认知度、畜牧主管部门培训、畜牧兽医行政管理部门免疫消毒是否及时四个因素的高度影响,养殖时间越长、对预防免疫认知度越高、培训越规范、免疫消毒越及时,养殖户的满意表现越高;其次政府主导的防疫体系,其目标导向与养殖户自身的目标并不完全一致,是政府投入逐渐增加、防疫效果未能改善的主要原因.     

中国农村贫困人口多维特征分析

利用中国综合社会调查（CGSS）数据,从个体的基本特征、家庭特征、社会特征和其他特征4个维度,采用二值Logit模型,考察这些特征变量对于农村人口陷入贫困可能性的影响;并进一步通过分位数回归模型比较分析这些特征变量对农村贫困人口和非贫困人口不同收入水平的影响。研究发现,在中国农村,具有以下几个典型特征的人群陷入贫困的可能性较大：老年人、受教育程度较低（自身、配偶或父母）、身体健康状况较差、少数民族、未婚状态、家庭抚养负担过重、无宗教信仰、没有非农工作、周工作时间较短、使用电视或互联网频率较低（这里理解为获取与农业生产和非农就业相关信息）。此外,比较分析结果表明,对于贫困人口和非贫困人口,不同维度下特征变量对收入水平影响的大小和方向存在较大差异。     

城市景观河流生态修复的产出研究及有效性可靠性检验——基于上海城市内河水质改善价值评估的实证分析

意愿价值评估法(CVM)为具有显著外部性的生态环境服务的价值评估提供可能,但只有经过有效性和可靠性检验的CVM成果才能应用于环境公共政策与治理。本文以CVM评价上海市城市景观内河——漕河泾港的生态恢复的产出,在国内经常采用的线形对数模型基础上,加入二值响应的Logit概率模型对受访者社会经济变量进行回归分析,验证本次CVM应用的理论有效性。回归中首次引入反映我国特殊社会结构的户籍变量、收入差距变量两者的交互项,并纳入间接反映环境问题历史成因的居民沿河居住期变量,以验证调查结果与一般经济理论的相容性和与我国特殊社会构成、经济态势以及环境历史成因的吻合性。以预调查和正式调查为试验—复试样本验证了研究结果的可靠性。结果表明:平均支付意愿是160元/(a.户),改善漕河泾水环境的年经济效益至少在6.1×106元。     

Does work during childhood affect the health of Guatemalan adults?

The diversity of potential relationships between child labor and health makes the empirical disentanglement of the causal relationship a difficult exercise. This paper examines the long run impact of child labour on health by controlling for unobserved household specific characteristics. In order to control for the unobserved households specific effect, we estimate a conditional fixed effect model using data on siblings constructed from the Guatemalan National Survey of Living Condition. The estimation results reinforce the conventional wisdom that child labor is harmful for health in the long run. The results can be interpreted as a lower bound of the true impact since healthier children are most likely to offer themselves for employment and to be appointed. The views expressed in this paper are those of the authors and do not necessarily represent those of IMF and IMF policy.