1,720,963 research outputs found
Automation, Job Polarisation, and Structural Change
No full textThe increasing automation of tasks traditionally performed by labour is reshaping the relationship between skills and tasks of workers, unevenly affecting labour demand for low, middle, and high-skill occupations. To investigate the economy-wide response to automation, we designed a multisector Agent-Based Macroeconomic model accounting for workers' heterogeneity in skills and tasks. The model features endogenous skill-biased technical change, and heterogeneous consumption preferences for goods and personal services across workers of different skill types. Following available empirical evidence, we model automation as a manufacturing-specific, productivity-enhancing, and skill-biased technological process. We show how automation can trigger a structural change process from manufactory to personal services, which eventually increases the share of high and low skilled occupations, while reducing the share of middle-skilled ones. Following the literature, we label this dynamics as job polarisation throughout the paper. Finally, we study how labour market policies can feedback in the model dynamics. In our framework, a minimum wage policy (i) slows down the structural change process, (ii) boosts aggregate productivity, and (iii) accelerates the automation process, strengthening productivity growth within the manufacturing sector.(c) 2022 Elsevier B.V. All rights reserved
A Simple Model of Business Fluctuations with Heterogeneous Interacting Agents and Credit Networks
No full textGoing 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
Heavy-tailed distributions for agent-based economic modelling
No full textThis chapter is devoted to the parametric statistical distributions of economic size phenomena of various types. Probability distributions of size variables are usually taken as the first quantitative characterization of complex systems, allowing one to detect the possible occurrence of regularities and to identify the underlying mechanisms at their origin - and thus at the origin of the behaviour of the complex system under study. A rapid survey covers the class of "heavy-tailed" distributions decreasing slower than exponentially at infinity. The fascination for "power laws" is then explained, starting from the statistical approaches for quantifying and testing a power-law distribution from your data, and ending with a (not exhaustive) list of mechanisms leading to power-law distributions. The description of distributions is ultimately enlarged by proposing the Laplace distribution, which has both tails - the upper and the lower - heavier than a standard Gaussian
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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