1,720,967 research outputs found
Integrating rather than collecting: statistical matching in the data flood era
Full text linkStatistical matching is progressively emerging as a straightforward approach to data integration. This method of increasing importance and interest is useful to address the unsolved challenges posed by data shortage as well as the several opportunities occurring in the present data flood era. This paper offers an exhaustive review of the methodology from its early beginnings up to the most recent developments, considering also the most relevant applications. The links that statistical matching has with other integration methods are discussed, analysing how a 50-year-old method has been only recently proposed under a consistent but (yet) incomplete framework. Strengths and weaknesses of statistical matching are compared, considering different data features and sample representativeness frameworks, also, given future research ideas, always keeping an eye on uncertainty, the key problem to which statistical matching tries to answer
Farmland abandonment, public goods and the CAP in a marginal area of Italy
Full text linkLand abandonment is affecting several areas of Europe, and the issue has since some years become a policy objective. The consequences of land abandonment are however difficult to assess as both agriculture and land abandonment are linked to socio-environmental public goods, but the relationship between public good provision and land use, as well as their societal value, are unclear and debated. Policy such as the Common Agricultural Policy affects land abandonment and public good provision in different ways, by providing income support and targeting the provision of environmental public goods.The objective of the paper is to assess the land use, public good levels and welfare deriving from agricultural production and from the provision of three selected PGs, in three alternative scenarios. In a reference scenario land use allocation is driven by the maximization of agricultural income; we then compare these results with a scenario where land use decisions maximize the societal welfare, hence including the value generated by the three, and with a scenario that simulates Measure 13 of the Rural Development Programme (payment for Areas Facing natural or other specific Constraints). The method used is a land allocation model calibrated for the hill and mountain area of the province of Bologna (Italy), in which the public goods societal values are the results of a choice experiments taken in the Emilia-Romagna region. The main results is that the societal optimum is reached through a substantial change in land allocation (e.g. a strong reduction in land abandonment and an increase in forest areas) and in the composition of the welfare (from private agricultural income toward public good benefits) with respect to the private optimum. Moreover, generic income support reduces land abandonment but also total welfare as it has negative effects through the reduction of carbon sequestration and increase in soil erosion. More targeted policies, that more explicitly connect support to public good provision, have better welfare effects
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
Estimating Poverty Transitions from Repeated Cross-Sections: A Statistical Perspective
No full textStudying poverty transitions is challenging due to the limited availability of longitudinal data, leading to a growing interest in methods that estimate transition probabilities viacross-sectional data. These approaches can be grouped into two main strands: a parametric approach, which assumes a distributional model for income and leverages econometric techniques on pseudo-panels, and a semi-parametric approach, which employs matching procedures to construct synthetic panels. A critical step in both methodologies is estimating income correlation across time that is not directly available from cross-sectional data. Although these methods are popular in the economics literature, to the best of our knowledge, they have not been systematically reviewed or assessed from a statistical perspective. In this paper, we examine these methods and their limitations before proposing a novel scenario-based framework with two alternative approaches, each aligned with a distinct strand of literature. Specifically, the parametric proposal incorporates Bayesian models that use scenarios as prior information for income autocorrelation, while the semi-parametric approach is based on a matching-based procedure. The latter includes a tuning parameter that adjusts the number of neighbors to regulate autocorrelation. Finally, we evaluate and compare the discussed methods, including our newly proposed ones, through a Monte Carlo simulation study based on Italian EU-SILC data
Innovative contract solutions for the Agri-Environmental-Climate Public Goods provision: Which features meet the farmers' approval? Insights from Emilia-Romagna (Italy)
Full text linkThe agroecological transition promoted worldwide is supported by the European Union Common Agricultural Policy towards different strategies and policy tools. The agri-environmental schemes, offering farmers the possibility to adopt environment-friendly practices (thus mitigating negative externalities/providing positive ones) represent a straightforward example. However, there is dissatisfaction about their effectiveness and efficiency, while their improvement is envisaged through a flexible mix of new instruments: novel contract solutions fostering result-based payments, collective implementation, involving value chains and land tenure systems coupled to environmental conditionality. This paper investigates how farmers from Emilia-Romagna (Italy) perceive these innovative contract solutions as “easy to understand”, “applicable”, “economic beneficial”, and their willingness to enrol. The applied ordered logistic regression models include socio-demographic characteristics, structural features of the holdings, and the farmers’ preference(s) for 13 individual contract features. Farmers’ perceptions are driven by the previous experience acquired from similar measures, key socio-demographic characteristic/holding structural features, and peculiar contractual elements
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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