Identifying Cooperation for Innovation―a Comparison of Data Sources
Michael Fritsch, Mirko Titze, Matthias Piontek
Industry and Innovation,
No. 6,
2020
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 subsidized collaborative R&D 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.
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01.07.2020 • 11/2020
New Horizon 2020 project: The Challenge of the Social Impact of Energy Transitions
Funded by the European Commission’s Framework Programme Horizon 2020, the ENTRANCES project recently closed its kick-off meeting with a high scientific and institutional participation, and taking on the challenge of modeling the social impact of the energy transition.
Oliver Holtemöller
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Drilling and Debt
Erik P. Gilje, Elena Loutskina, Daniel Murphy
Journal of Finance,
No. 3,
2020
Abstract
This paper documents a previously unrecognized debt‐related investment distortion. Using detailed project‐level data for 69 firms in the oil and gas industry, we find that highly levered firms pull forward investment, completing projects early at the expense of long‐run project returns and project value. This behavior is particularly pronounced prior to debt renegotiations. We test several channels that could explain this behavior and find evidence consistent with equity holders sacrificing long‐run project returns to enhance collateral values and, by extension, mitigate lending frictions at debt renegotiations.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
No. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Sinkendes Potenzialwachstum in Deutschland, beschleunigter Braunkohleausstieg und Klimapaket: Finanzpolitische Konsequenzen für die Jahre bis 2024
Andrej Drygalla, Katja Heinisch, Oliver Holtemöller, Axel Lindner, Christoph Schult, Matthias Wieschemeyer, Götz Zeddies
Konjunktur aktuell,
No. 4,
2019
Abstract
Nach der Mittelfristprojektion des IWH wird das Bruttoinlandsprodukt in Deutschland in den Jahren bis 2024 preisbereinigt um durchschnittlich 1% wachsen; das nominale Bruttoinlandsprodukt wird um durchschnittlich 2¾% zunehmen. Die Durchschnittswerte verschleiern die Tatsache, dass das Wachstum gegen Ende des Projektionszeitraums aufgrund der dann rückläufigen Erwerbsbevölkerung spürbar zurückgehen wird. Dies wird sich auch bei den Staatseinnahmen niederschlagen. Allerdings wird die Bevölkerung nicht regional gleichverteilt zurückgehen. Strukturschwache Regionen dürften stärker betroffen sein. Die regionalen Effekte auf die Staatseinnahmen werden zwar durch Umverteilungsmechanismen abgefedert, aber nicht völlig ausgeglichen. Regionen mit schrumpfender Erwerbsbevölkerung müssen sich auf einen sinkenden finanziellen Spielraum einstellen. Der beschleunigte Braunkohleausstieg wird diesen Prozess verstärken, das Klimapaket der Bundesregierung hat hingegen vergleichsweise geringe Auswirkungen auf die öffentlichen Finanzen.
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02.10.2019 • 21/2019
Thanks to robust domestic demand, the impact of the manufacturing sector on East Germany is less severe than in the west – Implications of the Autumn 2019 Joint Economic Forecast and official regional data for the eastern German economy
In its autumn report, the Joint Economic Forecast Project Group states that the German economy has cooled further in the current year. The manufacturing sector is the main reason for the economic weakness. This affects the economy in East Germany as well.
Oliver Holtemöller
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The Impact of Innovation and Innovation Subsidies on Economic Development in German Regions
Uwe Cantner, Eva Dettmann, Alexander Giebler, Jutta Günther, Maria Kristalova
Regional Studies,
No. 9,
2019
Abstract
Public innovation subsidies in a regional environment are expected to unfold a positive economic impact over time. The focus of this paper is on an assessment of the long-run impact of innovation and innovation subsidies in German regions. This is scrutinized by an estimation approach combining panel model and time-series characteristics and using regional data for the years 1980–2014. The results show that innovation and innovation subsidies in the long run have a positive impact on the economic development of regions in Germany. This supports a long-term strategy for regional and innovation policy.
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Do Diasporas Affect Regional Knowledge Transfer within Host Countries? A Panel Analysis of German R&D Collaborations
Lutz Schneider, Alexander Kubis, Mirko Titze
Regional Studies,
No. 1,
2019
Abstract
Interactive regional learning involving various actors is considered a precondition for successful innovations and, hence, for regional development. Diasporas as non-native ethnic groups are regarded as beneficial since they enrich the creative class by broadening the cultural base and introducing new routines. Using data on research and development (R&D) collaboration projects, the analysis provides tentative evidence that the size of diasporas positively affects the region’s share of outward R&D linkages enabling the exchange of knowledge. The empirical analysis further confirms that these interactions mainly occur between regions hosting the same diasporas, pointing to a positive effect of ethnic proximity rather than ethnic diversity.
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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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