09.07.2019 • 17/2019
IWH mit „sehr gut“ bewertet und zur Weiterförderung empfohlen
Das Leibniz-Institut für Wirtschaftsforschung Halle (IWH) erzielt seit Jahren bemerkenswerte Leistungen in Forschung und Politikberatung und soll deshalb auch in Zukunft von Bund und Ländern gefördert werden. Zu diesem Ergebnis ist der Senat der Leibniz-Gemeinschaft in seiner heutigen Sitzung gekommen. Zum Abschluss der Evaluierung bekam das Institut in allen Bereichen die Note „sehr gut“.
Reint E. Gropp
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08.05.2019 • 11/2019
Erweiterung des IWH beschlossen
Die Gemeinsame Wissenschaftskonferenz (GWK) von Bund und Ländern hat dem Antrag des Leibniz-Instituts für Wirtschaftsforschung Halle (IWH) auf einen großen strategischen Sondertatbestand in Form einer strategischen Erweiterung zugestimmt. Ab dem Jahr 2020 erhält das Institut eine zusätzliche Grundfinanzierung in Höhe von 1,3 Millionen Euro jährlich. IWH-Präsident Reint E. Gropp zeigt sich außerordentlich erfreut über den großen Erfolg.
Reint E. Gropp
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Identifying Cooperation for Innovation – A Comparison of Data Sources
Michael Fritsch, Matthias Piontek, Mirko Titze
Abstract
The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidised collaborative Research and Development projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers. The key role of universities that connect many regional actors is identified in all three types of data.
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Urban Occupational Structures as Information Networks: The Effect on Network Density of Increasing Number of Occupations
Shade T. Shutters, José Lobo, Rachata Muneepeerakul, Deborah Strumsky, Charlotta Mellander, Matthias Brachert, Teresa Farinha, Luis M. A. Bettencourt
Plos One,
im Erscheinen
Abstract
Urban economies are composed of diverse activities, embodied in labor occupations, which depend on one another to produce goods and services. Yet little is known about how the nature and intensity of these interdependences change as cities increase in population size and economic complexity. Understanding the relationship between occupational interdependencies and the number of occupations defining an urban economy is relevant because interdependence within a networked system has implications for system resilience and for how easily can the structure of the network be modified. Here, we represent the interdependencies among occupations in a city as a non-spatial information network, where the strengths of interdependence between pairs of occupations determine the strengths of the links in the network. Using those quantified link strengths we calculate a single metric of interdependence–or connectedness–which is equivalent to the density of a city’s weighted occupational network. We then examine urban systems in six industrialized countries, analyzing how the density of urban occupational networks changes with network size, measured as the number of unique occupations present in an urban workforce. We find that in all six countries, density, or economic interdependence, increases superlinearly with the number of distinct occupations. Because connections among occupations represent flows of information, we provide evidence that connectivity scales superlinearly with network size in information networks.
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Differences Make a Difference: Diversity in Social Learning and Value Creation
Yiwei Fang, Bill Francis, Iftekhar Hasan
Journal of Corporate Finance,
2018
Abstract
Prior research has demonstrated that CEOs learn privileged information from their social connections. Going beyond the importance of the number of social ties in a CEO's social network, this paper studies the value generated from a diverse social environment. We construct an index of social-network heterogeneity (SNH) that captures the extent to which CEOs are connected to people of different demographic attributes and skill sets. We find that higher CEO SNH leads to greater firm value through the channels of better corporate innovation and diversified M&As. Overall, the evidence suggests that CEOs' exposure to human diversity enhances social learning and creates greater growth opportunities for firms.
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Does It Pay to Get Connected? An Examination of Bank Alliance Network and Bond Spread
Iftekhar Hasan, Céline Meslier, Amine Tarazi, Mingming Zhou
Journal of Economics and Business,
im Erscheinen
Abstract
This paper examines the effects of bank alliance network on bonds issued by European banks during the period 1990–2009. We construct six measures capturing different dimensions of banks’ network characteristics. In opposition to the results obtained for non-financial firms, our findings indicate that being part of a network does not create value for bank’s bondholders, indicating a dark side effect of strategic alliances in the banking sector. While being part of a network is perceived as a risk-increasing event by market participants, this negative perception is significantly lower for the larger banks, and, to a lesser extent, for the more profitable banks. Moreover, during crisis times, the positive impact on bond spread of a bank’s higher centrality or of a bank’s higher connectedness in the network is stronger, indicating that market participants may fear spillover effects within the network during periods of banks’ heightened financial fragility.
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Criminal Network Formation and Optimal Detection Policy: The Role of Cascade of Detection
Liuchun Deng, Yufeng Sun
Journal of Economic Behavior and Organization,
September
2017
Abstract
This paper investigates the effect of cascade of detection, how detection of a criminal triggers detection of his network neighbors, on criminal network formation. We develop a model in which criminals choose both links and actions. We show that the degree of cascade of detection plays an important role in shaping equilibrium criminal networks. Surprisingly, greater cascade of detection could reduce ex ante social welfare. In particular, we prove that full cascade of detection yields a weakly denser criminal network than that under partial cascade of detection. We further characterize the optimal allocation of the detection resource and demonstrate that it should be highly asymmetric among ex ante identical agents.
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09.08.2017 • 29/2017
Vernetzt und aufgefangen
Während der Finanzkrise flossen Milliarden, um Banken zu retten, die ihren Regierungen zufolge zu groß waren als dass man sie hätte untergehen lassen dürfen. Doch eine Studie von Michael Koetter vom Leibniz-Institut für Wirtschaftsforschung Halle (IWH) und Ko-Autoren zeigt: Nicht nur die Größe der Bankhäuser war für eine Rettung entscheidend. Wesentlich war auch, wie zentral ein Institut im globalen Finanznetzwerk war.
Michael Koetter
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05.01.2017 • 3/2017
Sekretariat des Forschungsnetzwerks CompNet künftig am IWH beheimatet
Das Leibniz-Institut für Wirtschaftsforschung Halle (IWH) hat das Sekretariat des Competitiveness Research Network CompNet übernommen, einem internationalen Netzwerk führender Wissenschaftler und Wissenschaftlerinnen sowie Fachleute, die erstklassige Forschung und Politikberatung auf den Gebieten der Wettbewerbsfähigkeit und Produktivität betreiben.
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Innovation Network
Daron Acemoglu, Ufuk Akcigit, William R. Kerr
Proceedings of the National Academy of Sciences of the United States of America (PNAS),
Nr. 41,
2016
Abstract
Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. Our analysis uses 1.8 million US patents and their citation properties to map the innovation network and its strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975–1994. The interaction of this preexisting network structure with patent growth in upstream technology fields has strong predictive power on future innovation after 1995. This pattern is consistent with the idea that when there is more past upstream innovation for a particular technology class to build on, then that technology class innovates more.
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