Identifying Cooperation for Innovation―a Comparison of Data Sources
Michael Fritsch, Mirko Titze, M. Piontek
Industry and Innovation,
im Erscheinen
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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Intangible Capital and Productivity. Firm-level Evidence from German Manufacturing
Wolfhard Kaus, Viktor Slavtchev, Markus Zimmermann
IWH-Diskussionspapiere,
Nr. 1,
2020
Abstract
We study the importance of intangible capital (R&D, software, patents) for the measurement of productivity using firm-level panel data from German manufacturing. We first document a number of facts on the evolution of intangible investment over time, and its distribution across firms. Aggregate intangible investment increased over time. However, the distribution of intangible investment, even more so than that of physical investment, is heavily right-skewed, with many firms investing nothing or little, and a few firms having very large intensities. Intangible investment is also lumpy. Firms that invest more intensively in intangibles (per capita or as sales share) also tend to be more productive. In a second step, we estimate production functions with and without intangible capital using recent control function approaches to account for the simultaneity of input choice and unobserved productivity shocks. We find a positive output elasticity for research and development (R&D) and, to a lesser extent, software and patent investment. Moreover, the production function estimates show substantial heterogeneity in the output elasticities across industries and firms. While intangible capital has small effects for firms with low intangible intensity, there are strong positive effects for high-intensity firms. Finally, including intangibles in a gross output production function reduces productivity dispersion (measured by the 90-10 decile range) on average by 3%, in some industries as much as nearly 9%.
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19.09.2019 • 19/2019
Spätfolgen der Treuhand: Preisgekrönter US-Ökonom startet Forschungsprojekt am IWH
Es ist eine der wichtigsten Auszeichnungen des deutschen Wissenschaftsbetriebs: Der mit 1,5 Millionen Euro dotierte Max-Planck-Humboldt-Forschungspreis geht in diesem Jahr an den Volkswirt Ufuk Akcigit von der Universität Chicago. Am Leibniz-Institut für Wirtschaftsforschung Halle (IWH) will Akcigit mit innovativen Methoden untersuchen, warum die Wirtschaft in Ostdeutschland bis heute hinter der westdeutschen zurückbleibt – und welche Rolle die Treuhandanstalt dabei spielt.
Reint E. Gropp
Pressemitteilung lesen
Forschungscluster
Vier Forschungscluster ...
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Evidenzbasierte Politikberatung (IWH-CEP)
Zentrum für evidenzbasierte Politikberatung (IWH-CEP) ...
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IWH-FDI-Mikrodatenbank
IWH-FDI-Mikrodatenbank Die IWH-FDI-Mikrodatenbank (FDI = Foreign Direct Investment)...
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Identifying Cooperation for Innovation – A Comparison of Data Sources
Michael Fritsch, M. Piontek, Mirko Titze
IWH-Diskussionspapiere,
Nr. 1,
2019
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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Innovation Cooperation in East and West Germany: A Study on the Regional and Technological Impact
Uwe Cantner, Alexander Giebler, Jutta Günther, Maria Kristalova, Andreas Meder
International Journal of Computational Economics and Econometrics,
im Erscheinen
Abstract
In this paper, we investigate the impact of regional and technological innovation systems on innovation cooperation. We develop an indicator applicable to regions, which demonstrates the relative regional impact on innovation cooperation. Applying this method to German patent data, we find that regional differences in the degree of innovation cooperation do not only depend on the technology structure of a region but also on specific regional effects. High-tech oriented regions, whether east or west, are not automatically highly cooperative regions. East German regions have experienced a dynamic development of innovation cooperation since re-unification in 1990. Their cooperation intensity remains higher than in West German regions.
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Das IWH auf der ASSA-Jahrestagung 2020 in San Diego
Das IWH auf der ASSA-Jahrestagung 2020 in San Diego Die American Economic...
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