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.

Finance has seen a spectacular growth in innovation and internationalization during the 20th century (Lane and Milesi-Ferretti, 2008; Shiller, 2013), resulting in a complex and highly interconnected network of financial entities spanning across jurisdictions (Allen and Gale, 1994; Popov and Udell, 2012). Meanwhile the challenges grow for policymakers to provide a framework which allows for the operation of a stable finan- cial system within their jurisdiction (Merton, 1995; Allen and Gale, 2000; Morrison and White, 2009; Ongena et al., 2013). The global financial crisis highlights that se- vere disruptions in the financial sector spread across jurisdictions (Wiggins and Met- rick, 2015) and can have large negative effects on the real economy (Chodorow-Reich, 2013). To contain systemic risk and contagion in the globalized financial system, sev- eral changes have been applied to the regulatory framework of international financial markets (G20, 2009). Regulatory efforts encompass among others the implementa- tion of macroprudential policies and the introduction of mandatory central clearing of derivatives. This thesis aims to contribute to the understanding of differential effects of financial policy reforms depending on the characteristics of the regulated financial entities and networks.

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.

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.