1,720,960 research outputs found
Measuring competitiveness differentials inside the same region: a propensity-score matching approach
Full text linkThis paper analyses regional competitiveness at the subregional level through a novel methodological approach that adopts a matching design. By comparing the performance of similar firms in different parts of the region, it is possible to detect whether different places provide different competitive territorial assets. Using data for Lombardy, a large and competitive European region, the analysis shows that the different territories of the region are differently competitive in different industries, even when they are similar in terms of total GDP per capita or specialization. The paper also confirms that measuring competitiveness on different indicators (Labour Productivity, TFP, Profitability) can provide different results, and this especially happens when comparing static and dynamic indicators. The methodology presented here is especially relevant to the design of regional policies, that are mostly deployed at the NUTS-2 level but would benefit from accounting for the presence of strongly dis-homogeneous territories inside the same region
The Counterfactual Challenge:How Machine Learning Can Enhance Policy Evaluation
No full textUnderstanding the impact of public policies and programmed actions is a complex and challenging task that deserves attention and resources. Even if the economic literature on counterfactual methods and identification is well established, conventional methodologies still struggles with holding up the unconfoundedness assumption in complex socio-economic and policy contexts. This paper sets up a ‘counterfactual challenge’, testing the ability of conventional matching versus a novel application of Supervised Machine Learning classification process to identify suitable counterfactuals. Working with high-dimensional data in complex socio-economic and policy contexts, results show that Machine Learning algorithms are better equipped to effectively balance treatment and control groups across a wide range of covariates compared to conventional matching methods. In the context of decision making and policy planning, we show the potential of Machine Learning to drastically improve the reliability and precision of information supporting policymakers in their choices. This is argued to have a positive impact on the effective use of public resources especially in complex and underdeveloped areas and contexts. Improvements in the precision of impact evaluation could result in significant gains in resource efficiency, both by generating realistic expectations of policy outputs, and improving scarce resource allocation we show that the use of Machine Learning algorithms for counterfactual identification consistently provides more precise results and supports policymakers in navigating complex contexts
Convergence through sustainable development: can EU developing regions make it happen? firm-level counterfactual evidence via Machine Learning
Full text linkThis work investigates whether EU cohesion policies aiming at environmental improvement and carbon reduction have an economic impact on adopters. By merging data from Opencoesione, with firms’ information from AIDA, we look at the changes in firms’ performance due to the sustain-ability-oriented technologies financed by the European cohesion funds during the 2007–13programming period. We include firms that participated in pilot programs and received public incentives to upgrade their production plants with sustainable technologies, and we use MachineLearning (ML) techniques to identify the most appropriate counterfactuals for a multilevel DiD setting. Our results indicate a strong and positive policy effect on firms’ profitability, with dissimilar dynamics for different levels of public support. Additionally, over time, the policy effect on treated firms tends to diminish, suggesting the possibility of a rebound effect where the gains in production efficiency and energy savings may be, at least partially, repurposed by firms to increase production (and profits) instead of reducing absolute emissions. This perfectly aligns with what one can expect from economic agents at the micro-level: firms’ actions are guided by the search for ways to obtain profit increases. However, at the macro-level, policymakers should question if the policy design could be improved through the adoption of conditional subsidies or regulatory mechanisms that, by limiting emissions, could foster more environmental benefits
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
Competitività, Infrastrutture e Politiche di Crescita: l'Effetto Moltiplicativo della Prossimità alle Infrastrutture di Trasporto e sulla Performance delle Imprese
No full textLo studio si inserisce all’interno di un vivo dibattito di politica economica: porta migliori risultati investire direttamente nella competitività delle imprese o nello sviluppo delle risorse territoriali?
Per rispondere a questa domanda di ricerca, nell’articolo si analizzano gli effetti mediatori della dotazione infrastrutturale sugli impatti delle politiche a sostegno diretto delle imprese. Per farlo, si utilizza un approccio innovativo basato sulla determinazione mediante geo-codificazione delle posizioni di imprese ed infrastrutture.
Lo studio integra intuizioni, metodologie e tecniche da tre diversi filoni di letteratura scientifica che, finora, erano rimasti separati: gli studi sui fattori di condizionamento delle politiche regionali, quelli sull’impatto delle politiche a livello di impresa e sulle misure di localizzazione basate su micro-dati.
I risultati indicano che, al netto dell’importanza di entrambi gli ambiti di investimento pubblico, l’impatto e l’efficienza delle politiche di supporto diretto alle imprese varia di intensità a seconda del territorio e delle sue caratteristiche infrastrutturali. L’analisi mostra una chiara complementarità tra la presenza di infrastrutture e l’impatto delle politiche di assistenza alle imprese, complementarità che diventa ancor più rilevante per quei territori, quali il Mezzogiorno, meno dotati di infrastrutture
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