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
Pressemitteilung lesen
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.
Pressemitteilung lesen
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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Is the 'Central German Metropolitan Region' Spatially Integrated? An Empirical Assessment of Commuting Relations
Albrecht Kauffmann
Urban Studies,
Nr. 9,
2016
Abstract
The 'Central German Metropolitan Region' is a network of cities and their surroundings, located in the three East-German states of Saxony, Saxony-Anhalt and Thuringia. It was founded to bring the bundled strengths of these cities into an inter-municipal cooperation, for making use of the possible advantages of a polycentric region. As theory claims, a precondition for gains from polycentricity is spatial integration of the region. In particular, markets for high skilled labour should be integrated. To assess how this precondition is fulfilled in Central Germany, in the framework of a doubly constrained gravity model the commuting relations between the functional regions of the (until 2013) 11 core cities of the network are analysed. In particular for higher educated employees, the results display that commuting relations are determined not only by distance, but also by the state borders that cross the area.
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24.02.2016 • 8/2016
Regionale Verteilung von Flüchtlingen in Deutschland
Angesichts hoher Flüchtlingszahlen und der nicht funktionsfähigen gemeinsamen europäischen Asylpolitik muss die regionale Verteilung der Flüchtlinge in Deutschland nach Einschätzung des IWH neu überdacht werden. Soziale Netzwerke und die regionale Arbeitsmarktlage sind dabei wichtige Indikatoren. Eine optimale Verteilung ist mit bürokratischen Mitteln allerdings kaum zu erreichen. Letztlich müssen Marktkräfte einen interregionalen Ausgleich unterstützen. Dafür bedarf es aber entsprechender Anreize sowohl für die Flüchtlinge als auch für die politischen Entscheidungsträger vor Ort – eine Herausforderung für Regionalpolitik und Finanzausgleich.
Oliver Holtemöller
Pressemitteilung lesen
Networks and the Macroeconomy: An Empirical Exploration
Daron Acemoglu, Ufuk Akcigit, William R. Kerr
NBER Macroeconomics Annual,
2015
Abstract
How small shocks are amplified and propagated through the economy to cause sizable fluctuations is at the heart of much macroeconomic research. Potential mechanisms that have been proposed range from investment and capital accumulation responses in real business-cycle models (e.g., Kydland and Prescott 1982) to Keynesian multipliers (e.g., Diamond 1982; Kiyotaki 1988; Blanchard and Kiyotaki 1987; Hall 2009; Christiano, Eichenbaum, and Rebelo 2011); to credit market frictions facing firms, households, or banks (e.g., Bernanke and Gertler 1989; Kiyotaki and Moore 1997; Guerrieri and Lorenzoni 2012; Mian, Rao, and Sufi 2013); to the role of real and nominal rigidities and their interplay (Ball and Romer 1990); and to the consequences of (potentially inappropriate or constrained) monetary policy (e.g., Friedman and Schwartz 1971; Eggertsson and Woodford 2003; Farhi and Werning 2013).
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The Structure and Evolution of Inter-sectoral Technological Complementarity in R&D in Germany from 1990 to 2011
T. Broekel, Matthias Brachert
Journal of Evolutionary Economics,
Nr. 4,
2015
Abstract
Technological complementarity is argued to be a crucial element for effective R&D collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis. The results illustrate sectors being complements both from a dyadic and portfolio/network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
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On the Trail of Core–periphery Patterns in Innovation Networks: Measurements and New Empirical Findings from the German Laser Industry
Wilfried Ehrenfeld, Toralf Pusch, Muhamed Kudic
Annals of Regional Science,
Nr. 1,
2015
Abstract
It has been frequently argued that a firm’s location in the core of an industry’s innovation network improves its ability to access information and absorb technological knowledge. The literature has still widely neglected the role of peripheral network positions for innovation processes. In addition to this, little is known about the determinants affecting a peripheral actors’ ability to reach the core. To shed some light on these issues, we have employed a unique longitudinal dataset encompassing the entire population of German laser source manufacturers (LSMs) and laser-related public research organizations (PROs) over a period of more than two decades. The aim of our paper is threefold. First, we analyze the emergence of core–periphery (CP) patterns in the German laser industry. Then, we explore the paths on which LSMs and PROs move from isolated positions toward the core. Finally, we employ non-parametric event history techniques to analyze the extent to which organizational and geographical determinates affect the propensity and timing of network core entries. Our results indicate the emergence and solidification of CP patterns at the overall network level. We also found that the paths on which organizations traverse through the network are characterized by high levels of heterogeneity and volatility. The transition from peripheral to core positions is impacted by organizational characteristics, while an organization’s geographical location does not play a significant role.
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Taking the First Step - What Determines German Laser Source Manufacturers' Entry into Innovation Networks?
Jutta Günther, Muhamed Kudic, Andreas Pyka
International Journal of Innovation Management,
Nr. 5,
2015
Abstract
Early access to technological knowledge embodied in the industry’s innovation network can provide an important competitive advantage to firms. While the literature provides much evidence on the positive effects of innovation networks on firms’ performance, not much is known about the determinants of firms’ initial entry into such networks. We analyze firms’ timing and propensity to enter the industry’s innovation network. More precisely, we seek to shed some light on the factors affecting the duration between firm founding and its first cooperation event. In doing so, we apply a unique longitudinal event history dataset based on the full population of German laser source manufacturers. Innovation network data stem from official databases providing detailed information on the organizations involved, subject of joint research and development (R&D) efforts as well as start and end times for all publically funded R&D projects between 1990 and 2010. Estimation results from a non-parametric event history model indicate that micro firms enter the network later than small-sized or large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of geographical determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
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Netzwerke zwischen Hochschulen und Wirtschaft: Ein Mehrebenenansatz
Mirko Titze, Wilfried Ehrenfeld, Matthias Piontek, Gunnar Pippel
Schrumpfende Regionen - dynamische Hochschulen: Hochschulstrategien im demografischen Wandel,
2015
Abstract
Innovationen sind ein zentraler Treiber für das Wachstum von Unternehmen und Regionen. Es gibt daher eine breite Literatur, welche versucht, die Determinanten der Innovationsfähigkeit zu identifizieren. Kooperationen stellen einen wichtigen Faktor im Bereich Forschung und Entwicklung dar, da Verflechtungen den Fluss von Wissen zwischen den beteiligten Akteuren, wie beispielsweise Hochschulen und Unternehmen, unterstützen. Um derartige Verflechtungen abzubilden, haben sich in der Fachliteratur verschiedene Ansätze durchgesetzt. So können beispielsweise Informationen über Ko-Publikationen, Ko-Patente oder geförderte FuE-Vorhaben genutzt werden. Die verschiedenen Ansätze haben jedoch ihre individuellen Stärken und Schwächen. Zudem bilden sie jeweils verschiedene Facetten der Kooperation im Bereich Forschung und Entwicklung ab. Dieser Beitrag setzt an dieser Problematik an, indem er anhand von sechs Fallregionen einen Mehrebenenansatz vorstellt, welcher die genannten Ebenen von Kooperation zusammenführt. Dies ermöglicht, ein umfassendes Bild der Vernetzung in den Fallregionen zu erhalten.
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