Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Virtual reality and mixed reality for second chance tourism

The deterioration of attractions, landmarks, artefacts and destinations is a critical issue facing tourism across the world. The closure of tourism sites and attractions is increasingly more common due to the difficulty and expense of managing preservation with onsite tourism engagement. However, the closure or destruction of tourism sites presents challenges for tourism development. The inability to foster meaningful visitor engagement at sites has implications for the local communities. This paper aims to explore the efficacy of creating tourism experiences in destinations and sites that have succumbed to over-tourism, resultant deterioration and even, destruction. To achieve this objective, the paper introduces the concept of second chance tourism and the role of innovative preservation methods such as virtual and mixed reality. Based on the proposed framework, the collation of data will provide indications on site preservation and impact mitigation via a second chance to reduce pressure on inherently fragile destinations.     

A Dynamic Analysis of Fixed- and Adjustable-Rate Mortgage Terminations

This paper provides a side-by-side comparison of loan-level statistical models for fixed- and adjustable-rate mortgages. Multinomial logit models for quarterly conditional probabilities of default and prepayment are estimated. We find that the estimated impacts of embedded option values for prepayment and default are generally quite similar across both FRM and ARM loans, providing additional empirical support for the basic predictions of the options theory. We also find that differences in estimates of conditional probabilities of prepayment and default associated with mortgage age, origination period, original LTV, and relative loan size, indicate the continued significance of these other economic and demographic factors for empirical models of mortgage terminations.     

Environmental Valuation with Imperfect Information The Case of the Random Utility Model

This paper considers welfare analysis with therandom utility model (RUM) when perceptions ofenvironmental quality differ from objectivemeasures of environmental quality. Environmental quality is assumed to be anexperience good, so that while perceptions ofquality determine choices, ex postutility is determined by objective quality. Given this assumption, I derive a measure ofthe welfare impact of changes in environmentalquality, and I show how this new welfaremeasure differs from the traditional welfaremeasure developed by Hanemann (1982). This newwelfare measure provides an approach tomeasuring the value of information aboutenvironmental quality within the framework ofthe random utility model.     

SELECTION BIAS CORRECTIONS BASED ON THE MULTINOMIAL LOGIT MODEL: MONTE CARLO COMPARISONS

Abstract.  This survey presents the set of methods available in the literature on selection bias correction, when selection is specified as a multinomial logit model. It contrasts the underlying assumptions made by the different methods and shows results from a set of Monte Carlo experiments. We find that, in many cases, the approach initiated by Dubin and MacFadden (1984) as well as the semi-parametric alternative recently proposed by Dahl (2002) are to be preferred to the most commonly used Lee (1983) method. We also find that a restriction imposed in the original Dubin and MacFadden paper can be waived to achieve more robust estimators. Monte Carlo experiments also show that selection bias correction based on the multinomial logit model can provide fairly good correction for the outcome equation, even when the IIA hypothesis is violated.     

公开市场操作与利率期限结构行为——基于混频数据信息的研究视角

在混频数据信息环境中,精准识别公开市场操作(央行政策利率)和国债收益率曲线(基准利率体系)之间的关联机制至关重要,其影响了货币政策期限结构传导的有效性。本文在混频Nelson-Siegel(N-S)利率期限结构模型框架下,引入央行政策利率,揭示公开市场操作与利率期限结构(水平、斜率、曲度)因子之间的作用机制。实证结果表明:混频数据信息条件下,引入的公开市场操作信息显著改进国债收益率曲线的拟合效果;斜率因子冲击对公开市场操作具有显著的正向影响,而利率期限结构因子对政策调控的反应不敏感。进一步研究表明,2015年以来,公开市场操作对斜率因子的影响逐渐扩大,政策利率向国债收益率曲线的传导效率得到显著提高,我国现代货币政策框架日益健全。     

Evaluation of the social and economic impact of carbon dioxide (CO2) emissions on sustainable mobility using cumulative ordinal models: trend odds model

In the context of environmental sustainability evaluation, grouped under climate change, health and ecosystem themes, an impact that could be investigated is the Global Warming Potential (GWP), whose sources are a multitude. In urban areas the evaluation of real vehicles emissions is an essential activity in order to suggest possible solution to local administrators. They still express the need to improve and maintain the characteristics of the breathing air at the best possible quality level. Moreover, these solutions, such as planning measures or traffic control management in respect of pollution, would be apply at different geographical levels, i.e. national, regional or urban scale. Another factor to be investigated is the effect of technologies and emission control systems to comply more stringent limits (Euro 4/5/6) and improve air quality to a lower environmental impact. GWP, indicator of climate change, is measured in terms of CO₂ equivalency emission values variable. To perform this activity an experimental campaign was carried out with several vehicles from different manufacturers and with a wide variety in terms of mass, power, engine displacement and type approval technology. The experimental plan includes some repetitions of the urban section in Naples city centre.The purpose of this paper is twofold: first, to provide a strategy on the choice of a logistic model with ordinal data and with trend, and, second, to evaluate the usefulness of such models for environmental sustainability (CO₂ and other vehicular pollutant emissions), with particular emphasis on model formulation, the interpretation of model coefficients, and the implications of such models.     

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S_b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.     

影响农村三种非农就业途径的主要因素研究--对天津市农村社会的实证分析

文章探讨了影响农村劳动力非农就业倾向的主要因素。研究结果表明,区位条件对农村劳动力非农就业倾向的影响,主要表现为近城地区以大量企业及相对发达的各种要素市场为第一优势,吸纳了更多劳动力进入本地企业就业。教育总体上是影响农村劳动力非农就业倾向的最重要因素。但其在近城地区的影响却位居第二。在远城地区教育对增大农村非农就业倾向的作用更为显著,而且受教育程度越高这种倾向就越显著。各种文化水平的影响都普遍促进了劳动者到外地企业就业,但对进入本地企业就业和家庭非农经营的促进却并不普遍,其中初中教育对农民在本地企业就业的作用更显著些;高中教育提高农民从事非农家庭经营的倾向最为明显。耕地数量抑制农户劳动力外出务工,但对其在本地企业就业和家庭非农经营的影响也不显著。乡镇企业的发展增大了农民进入本地企业的就业倾向,劳动者供养的非劳动人口数量对农民非农就业的正向影响不显著,农户拥有的非农业和农业生产性资产对农村非农就业的影响不大。因此,加快推进农村城镇化;加强边远农村地区的中等教育,特别是职业技能教育;大力发展乡企和私企;完善农村社会保障体系;构建农村劳动供求信息系统等,是促进农村劳动力加速向非农产业转移的重要途径。     

Societal preferences for fertility treatment in Australia: a stated preference discrete choice experiment

Objective: To investigate preferences for fertility treatment from the Australian general population with the aims of calculating the willingness to pay in tax contribution for attributes (characteristics) that make up treatment and for an “ideal” fertility treatment program. We also assessed whether willingness-to-pay varies by the relationship status or sexual orientation of the patient.

Methods: A stated preference discrete choice experiment was administered to a panel of 801 individuals representative of the Australian general population. Seven attributes of fertility treatment under three broad categories were included: outcome, process, and cost. Attributes were identified through published literature, focus group discussions, expert knowledge, and a pilot study. A Bayesian fractional experimental design was used, and data analysis was performed using a generalized multinomial logit model. Further analyses included interaction terms and latent class modeling.

Results: Six of the seven attributes influenced the choice of a treatment program. Under process attributes, individuals preferred: continuity of care of clinic staff, where patients are seen by the same doctor but different nurses at each visit; “alternative” treatments being offered to all patients; and onsite clinic counseling and peer-support groups. Personalization and tailoring of the treatment journey were not important. Among outcome attributes, the improved success rate of having a baby per cycle and significant side-effects were considered important. Cost of treatment also influenced the choice of treatment program. Individual preferences for fertility treatment were not associated with patients’ relationship status or sexual orientation. Latent class modeling revealed sub-groups with distinct fertility treatment preferences.

Conclusion: This study provides important insights into the attributes that influence the preferences of fertility treatment in Australia. It also estimates socially-inclusive willingness-to-pay values in tax contributions for an “ideal” package of treatment. The results can inform economic evaluations of fertility treatment programs.