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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Intangible Capital and Productivity. Firm-level Evidence from German Manufacturing
Wolfhard Kaus, Viktor Slavtchev, Markus Zimmermann
IWH Discussion Papers,
No. 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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Structural Stability of the Research & Development Sector in European Economies Despite the Economic Crisis
Jutta Günther, Maria Kristalova, Udo Ludwig
Journal of Evolutionary Economics,
No. 5,
2019
Abstract
When an external shock such as the economic crisis in 2008/2009 occurs, the interconnectedness of sectors can be affected. This paper investigates whether the R&D sector experienced changes in its sectoral integration through the recession. Based on an input-output analysis, it can be shown that the linkages of the R&D sector with other sectors remain stable. In some countries, the inter-sectoral integration becomes even stronger. Policy makers can be encouraged to use public R&D spending as a means of fiscal policy against an economic crisis.
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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
IWH Discussion Papers,
No. 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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