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No full textFINANCING UNEMPLOYMENT BENEFITS BY GOODS MARKET COMPETITION: FISCAL POLICY AND DEREGULATION WITH MARKET IMPERFECTIONS
No full textThe Impact of Fiscal Policies on GDP Growth in the Euro Area During the COVID-19 Pandemic
No full textWe estimate the impact of fiscal measures adopted in response to the Covid-19 crisis at the euro area level, combining standard macroeconomic data with an index on the strictness of ‘lockdown style’ policies. Given the multitude of shocks occurred simultaneously during the pandemic, the fiscal stimulus is identified together with other supply- and demand-side shocks using a sign and zero restricted Bayesian vector autoregressive (VAR) model. Our results show that during the two years 2020-2021, public spending and revenue-side measures avoided a further reduction of GDP equal to 2.8 and 0.9 percentage points, respectively
Financing Unemployment Benefits through Fiscal Policies and Increasing Competition
No full textWe consider a model in which the labor market is characterized by search frictions and there is monopolistic competition in the goods market. We introduce proportional income taxation and unemployment benefits with Government balanced budget constraint. We then evaluate the effects of both more competition in the goods market and higher unemployment benefits on labor market equilibrium and the equilibrium tax rate. We show that greater competition has a positive effect on equilibrium unemployment and the Government budget. Higher unemployment benefits can be financed by either raising the tax rate or increasing goods market competition. With liberalization policies it would be possible: a) to avoid an increase in unemployment if we allow some rise in the tax rate; b) to decrease unemployment if they are incisive enough to keep the tax rate unchanged
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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