1,720,963 research outputs found
A Relative Measure of Economic Insecurity and the Nexus with Job Change
Full text linkEconomic insecurity is attracting growing attention in the social well-being literature. However, there is still debate about its definition and measurement which deserve further and in depth study. Assuming that economic insecurity relates to the forward-looking perception of future outcomes based on past experience, we suggest a class of relative indices measuring the individual feeling of economic insecurity by considering relative past resource fluctuations. The innovation we implement in this context consists in considering relative changes, supposing that individuals evaluate each fluctuation based on their previous resource level. We take advantage of the measures suggested to study how economic insecurity may affect job mobility. Obtained results show that economic insecurity has a significant impact on the probability of changing jobs, and that its effect differs by gender and working experience
Small Area Estimation of Relative Inequality Indices using Mixtures of Beta
No full textThe paper aims at proposing a small area estimation strategy for the Theil Index, an entropy-based inequality measure. Specifically, we have developed an area-level model of its relative index, i.e. Theil index over its maximum, which has more manageable support between 0 and 1. Classical proposals in area-level context for measures defined on the unit interval are mostly based on proportions modelling and show limitations when dealing with asymmetric heavy-tailed data, such as in our case. We propose a Hierarchical Bayes model with alternative likelihood assumptions based on a particular Beta mixture, providing a more flexible framework
Small-sample bias correction of inequality estimators in complex surveys
Full text linkIncome inequality estimators are biased in small samples, leading generally to an underestimation. This aspect deserves particular attention when estimating inequality in small domains and performing small area estimation at the area level. We propose a bias correction framework for
a large class of inequality measures comprising the Gini Index, the Generalized Entropy, and the Atkinson index families by accounting for complex survey designs. The proposed methodology does not require any parametric assumption on income distribution, being very flexible. Design based performance evaluation of our proposal has been carried out using EU-SILC data, their results show a noticeable bias reduction for all the measures. Lastly, an illustrative example of application in small area estimation confirms that ignoring ex-ante bias correction determines model misspecification
Flexible Small Area Estimation of Theil Index using Mixtures of Beta
No full textThe aim of the paper is to propose a small area estimation model
for Theil Index, an entropy-based measure used to quantify economic
inequality, industrial concentration and, in general, the disparity related
to economic phenomena. We developed an area-level model of its relative
index, i.e. Theil index over its maximum, which has a more manageable
support between 0 and 1. Classical proposals in area-level context for
measures on (0,1) are mostly based on proportions modelling and show
limitations when dealing with asymmetric heavy-tailed data, such as in
our case. We propose a model with alternative distributional assumptions
based on a particular Beta mixture with unconstrained mean modeling,
estimated under a Hierarchical Bayes approach. An application to ITSILC income data is provided, showing that our proposal yields a more
flexible framework in comparison with Beta regression with unmatched
sampling and linking models
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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