Coefficients of determinations for variable selection in the msae regression

Our objective is to modify a robust coefficient of determination for the minimum sum of absolute errors MSAE regression proposed by McKean and Sievers (1987) so that it satisfies all the desirable properties. We also propose an adjusted coefficient of determination that is appropriate for comparing several models with different number of variables. Further, it has the property that if it decreases with the addition of predictor variables to the model, then the contribution of these variables is statistically non-significant. We illustrate the results with an example.     

Gambling and Adverse Life Events Among Urban Adolescents

This study explored the cross sectional association between adverse life events and gambling in a sample of 515 urban adolescents (average age 17, 55% male, 88% African American). Approximately half of the sample had gambled in the past year (51%); 78% of the gamblers gambled monthly and 39% had a gambling-related problem. On the other hand, 88% of the sample had experienced at least one life event in the past year, and those experiencing events tended to live in more disadvantaged neighborhoods. The mere acknowledgement of experiencing a stressful life event in the past year (yes/no) was not associated with an increase in odds of being a gambler, with gambling more frequently, or with having a gambling problem. However, when the context of the event was considered, an association was found between directly experiencing threatening and deviant/violent types of events and frequent gambling (OR > 2). Additionally, the probability of being a gambler increased as the number of events experienced increased (aOR = 1.07, 95% CI = 1.01, 1.13, P = 0.013), but problems among gamblers were not associated with the number of events experienced (aOR = 1.01, 95% CI = 0.92, 1.11, P = 0.876). During adolescence, life events appear to be connected more with the frequency of gambling rather than with problems related to gambling.     

Leaders' relational self-concept and followers' task performance: Implications for mentoring provided to followers

Using a sample of 137 leader–follower dyads, this study investigated how leaders' relational self-concept relates to the mentoring (career support and psychosocial support) they provide to their followers, and whether followers' task performance moderates this relationship. As expected, leaders with a stronger relational self-concept provided more career support to followers who displayed higher (vs. lower) task performance. However, leaders' relational self-concept was unrelated to their provision of psychosocial support, irrespective of followers' task performance.     

Model Assessment for Predictive Classification Models

In this article, we present a novel methodology to assess predictive models for a binary target. In our opinion, the main weakness of the criteria proposed in the literature is not to take the financial costs of a wrong decision into account.

The objective of this article is to derive the optimal cut-off in predictive classification models and to improve model assessment on the basis of a general class of loss functions. We describe how our proposal performs in a real application on credit scoring.     

Fiducial distribution in a power series family

Abstract

In this article the interest is on finding the fiducial distribution of the parameter, when the probability distribution belongs to the power series family, as in Johnson et al. (1992 Johnson, N. L., S. Kotz, and A. W. Kemp. 1992. Univariate discrete distributions. New York, NY: John Wiley and Sons. [Google Scholar]). Recently in Nájera and O’Reilly (2017 Nájera, E., and F. O’Reilly. 2017. On fiducial generators. Communications Statistics - Theory Methods 46 (5):2232–2248. doi:10.1080/03610926.2015.1040505.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) an argument is given to obtain a unique fiducial in the Bernoulli case. An attempt is made here to define some sort of invariance in a power series distribution so that, as was done in the Bernoulli case, one may find a unique invariant fiducial for the parameter. The Bernoulli case is reviewed in detail and the Poisson and negative binomial cases are addressed.     

Metropolitan Governance: Which Policies for Globalizing Cities?

Today, for the first time in history, half the world’s people live in cities. This puts metropolitan areas to the test, especially in developing countries, where the greatest part of urban growth is occurring. In order to meet the new challenges linked to urbanization, today’s growing cities need appropriate metropolitan governance. The present paper wants to investigate this issue, through the definition of a general model of metropolitan governance, which can be adapted to every urbanization context according to its own specificities. Considerable emphasis will be given to concrete examples to test the consistency of our model. In particular, since water and sanitation supply is one of the key challenges affecting metropolitan areas, we will apply our model to urban water management. Furthermore, an important focus will be given to the contribution that Information and Communication Technologies can provide to the implementation of the model.     

The impact of job loss on family dissolution

The impact of involuntary job displacements on the probability of divorce is analysed using discrete duration models. The analysis uses the sample of couples from the British Household Panel Survey and distinguishes between types of displacements. Results show that couples in which the husband experiences a job loss are more likely to divorce. Redundancies have small, positive, often insignificant and short-lived effects while dismissals and temporary job endings have larger positive impacts. This is consistent with the interpretation of redundancies as capturing negative income shocks while other types of job loss also convey new information about potential future earnings and match quality.     

Economic Consequences of Union Dissolution in Italy: Findings from the European Community Household Panel

Union dissolution is a constantly increasing phenomenon across Europe—even in Italy where the prevalence of divorce has always been among the lowest. This poses several questions on the potential consequences of such an event on the families involved. Many studies show that women usually experience the worst financial consequences, although there are few analyses on Italy, given the relatively low levels of union instability. In this work we study the impact of separation on the economic well-being of men and women using data from the European Community Household Panel (ECHP), analyzed using both objective and subjective measures. By means of a matching method, we also estimate the effect of union dissolution, taking account of possible variations according to the different living arrangements adopted by ex-partners after separation. Results confirm that women experience worse economic distress than men. However, there is also a significant drop in economic well-being among non-custodial fathers who live alone after separation. In addition, it is found that income-based measures do not encapsulate all the dimensions of well-being, and therefore need to be complemented with other measures.     

Identifying Guttman Structures in Incomplete Rasch Datasets

In applications of IRT, it often happens that many examinees omit a substantial proportion of item responses. This can occur for various reasons, though it may well be due to no more than the simple fact of design incompleteness. In such circumstances, literature not infrequently refers to various types of estimation problem, often in terms of generic “convergence problems” in the software used to estimate model parameters. With reference to the Partial Credit Model and the instance of data missing at random, this article demonstrates that as their number increases, so does that of anomalous datasets, intended as those not corresponding to a finite estimate of (the vector parameter that identifies) the model. Moreover, the necessary and sufficient conditions for the existence and uniqueness of the maximum likelihood estimation of the Partial Credit Model (and hence, in particular, the Rasch model) in the case of incomplete data are given – with reference to the model in its more general form, the number of response categories varying according to item. A taxonomy of possible cases of anomaly is then presented, together with an algorithm useful in diagnostics.     

A threshold based approach to merge data in financial risk management

According to the last proposals by the Basel Committee, banks are allowed to use statistical approaches for the computation of their capital charge covering financial risks such as credit risk, market risk and operational risk.

It is widely recognized that internal loss data alone do not suffice to provide accurate capital charge in financial risk management, especially for high-severity and low-frequency events. Financial institutions typically use external loss data to augment the available evidence and, therefore, provide more accurate risk estimates. Rigorous statistical treatments are required to make internal and external data comparable and to ensure that merging the two databases leads to unbiased estimates.

The goal of this paper is to propose a correct statistical treatment to make the external and internal data comparable and, therefore, mergeable. Such methodology augments internal losses with relevant, rather than redundant, external loss data.