Analyzing Innovation Drivers in the German Laser Industry: the Role of Positioning in the Social and Geographical Space
Muhamed Kudic, Peter Bönisch, Iciar Dominguez Lacasa
Abstract
Empirical and theoretical contributions provide strong evidence that firm-level performance outcomes in terms of innovativeness can either be determined by the firm’s position in the social space (network effects) or by the firm’s position in the geographical space (co-location effects). Even though we can observe quite recently first attempts in bringing together these traditionally distinct research streams (Whittington et al. 2009), research on interdependent network and geographical co-location effects is still rare. Consequently, we seek to answer the following research question: considering that the effects of social and geographic proximity on firm’s innovativeness can be interdependent, what are the distinct and combined effects of firm’s network and geographic position on firm-level innovation output? We analyze the innovative performance of German laser source manufacturers between 1995 and 2007. We use an official database on publicly funded R&D collaboration projects in order to construct yearly networks and analyze firm’s network positions. Based on information on population entries and exits we calculate various types of geographical proximity measures between private sector and public research organizations (PRO). We use patent grants as dependent variable in order to measure firm-level innovation output. Empirical results provide evidence for distinct effect of network degree centrality. Distinct effect of firm’s geographical co-location to laser-related public research organization promotes patenting activity. Results on combined network and co-location effects confirms partially the existence of in-terdependent proximity effects, even though a closer look at these effects reveals some ambiguous but quite interesting findings.
Read article
What Determines the Innovative Success of Subsidized Collaborative R&D Projects? – Project-Level Evidence from Germany –
Michael Schwartz, François Peglow, Michael Fritsch, Jutta Günther
IWH Discussion Papers,
No. 7,
2010
published in: Technovation
Abstract
Systemic innovation theory emphasizes that innovations are the result of an interdependent exchange process between different organizations. This is reflected in the current paradigm in European innovation policy, which aims at the support of collaborative R&D and innovation projects bringing together science and industry. Building on a large data set using project-level evidence on 406 subsidized R&D cooperation projects, the present paper provides detailed insights on the relationship between the innovative success of R&D cooperation projects and project characteristics. Patent applications and publications are used as measures for direct outcomes of R&D projects. We also differentiate between academic-industry projects and pure inter-firm projects. Main results of negative binomial regressions are that large-firm involvement is positively related to pa-tent applications, but not to publications. Conversely, university involvement has positive effects on project outcomes in terms of publications but not in terms of patent applications. In general, projects’ funding is an important predictor of innovative success of R&D cooperation projects. No significant results are found for spatial proximity among cooperation partners and for the engagement of an applied research institute. Results are discussed with respect to the design of R&D cooperation support schemes.
Read article
A First Look on the New Halle Economic Projection Model
Sebastian Giesen, Oliver Holtemöller, Juliane Scharff, Rolf Scheufele
Abstract
In this paper we develop a small open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model – the Halle Economic Projection Model (HEPM) – is closely related to studies recently published by the International
Monetary Fund (global projection model). Our main contribution is that we model the Euro area countries separately. In this version we consider Germany and France, which represent together about 50 percent of Euro area GDP. The model allows for country specific heterogeneity in the sense that we capture different adjustment patterns to economic shocks. The model is estimated using Bayesian techniques. Out-of-sample and pseudo out-of-sample forecasts are presented.
Read article
