231 research outputs found

    The Political Economy of European Merger Control: Evidence using Stock Market Data

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    The objective of this paper is to investigate the determinants of EU merger control decisions. We consider a sample of 164 EU merger control decisions and evaluate the anti-competitive consequences of these mergers from the reaction of the stock market price of competitors to the merging firms. We then account for the discrepancies between the actual decisions and what the stock market would have dictated in terms of the political economy surrounding the cases. Our results suggest that the commission’s decisions cannot be solely accounted for by the motive of protecting consumer surplus. The institutional and political environment does matter. As far as firms’ influence is concerned, however, our data suggests that the commission’s decisions are not sensitive to firms’ interests. Instead, the evidence suggests that other factors - such as country and industry effects, as well as market definition and procedural aspects - do play significant roles. ZUSAMMENFASSUNG - (Die politische Ökonomie der europäischen Fusionskontrolle: Evidenz anhand von Aktienmarkt-Daten) In diesem Beitrag werden die Bestimmungsfaktoren für Entscheidungen der EUFusionskontrolle untersucht. Für eine Auswahl von 164 Entscheidungen der EUFusionskontrolle werden die wettbewerbsbeschränkenden Folgen dieser Fusionen berechnet. Dies geschieht anhand der Reaktion des Börsenkurses der Konkurrenten auf die Fusion. Erklärt werden anschließend die Abweichungen zwischen den gegenwärtigen Entscheidungen und dem, was die Aktienmärkte im Hinblick auf die politische Ökonomie, in welche die Fälle eingebettet sind, vorgeschrieben hätten. In Bezug auf Fehler vom Typ I (dem Anschein nach Wettbewerb bejahende Fusionen, die verboten wurden) decken die Ergebnisse einige systematische Fehler auf, untermauern jedoch nicht die häufige Behauptung, dass die Kommission auf Kosten der Konsumenteninteressen von den Interessen der Wettbewerber beeinflusst wird. Es werden auch systematische Fehler in Richtung von Fehlern des Typ II (scheinbar wettbewerbseinschränkende Fusionen, die genehmigt wurden) festgestellt, welche von einer Anzahl institutioneller und politischer Eigenschaften der EUEntscheidungsfindung beeinflusst zu sein scheinen. Die Ergebnisse unterstützen die Auffassung, dass wettbewerbseinschränkende Fusionen mit größerer Wahrscheinlichkeit in Phase I genehmigt werden, wenn sie Unternehmen aus großen Mitgliedstaaten betreffen, jedoch mit geringerer Wahrscheinlichkeit, wenn der relevante Markt national ist. Zudem wird festgestellt, dass die Häufigkeit der genannten Fehler während der Amtszeit von Kommissar Monti gestiegen ist.Merger Control, European Commission, Political Economy, Lobbying, Stock Market Data

    Minimum Cost Design of Cellular Networks in Rural Areas with UAVs, Optical Rings, Solar Panels and Batteries

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    Bringing the cellular connectivity in rural zones is a big challenge, due to the large installation costs that are incurred when a legacy cellular network based on fixed Base Stations (BSs) is deployed. To tackle this aspect, we consider an alternative architecture composed of UAV-based BSs to provide cellular coverage, ground sites to connect the UAVs with the rest of the network, Solar Panels (SPs) and batteries to recharge the UAVs and to power the ground sites, and a ring of optical fiber links to connect the installed sites. We then target the minimization of the installation costs for the considered UAV-based cellular architecture, by taking into account the constraints of UAVs coverage, SPs energy consumption, levels of the batteries and the deployment of the optical ring. After providing the problem formulation, we derive an innovative methodology to ensure that a single ring of installed optical fibers is deployed. Moreover, we propose a new algorithm, called DIARIZE, to practically tackle the problem. Our results, obtained over a set of representative rural scenarios, show that DIARIZE performs very close to the optimal solution, and in general outperforms a reference design based on fixed BSs

    Implementation of Artificial Bee Colony Algorithm

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    Evolutionary algorithm is a stochastic search method that mimics the natural biological evolution and the social behavior of species. Artificial bee colony algorithm is also a kind of evolutionary algorithm which was proposed by Dervis karaboga in 2005.Such algorithms have been developed to arrive at near-optimum solutions of multimodal optimization problems, which may not be possible with traditional algorithms. This paper describes implementation of ABC algorithm on complex benchmark functions like rastrigin, rosenbrock; sphere and schwefel the analysis of the performance of ABC algorithm were compared for the optimization of above benchmark functions with Partical Swarm Optimization (PSO). The ABC algorithm was successfully implemented in software tool ‘c’.DOI: http://dx.doi.org/10.11591/ij-ai.v1i3.58
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