The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.

The spatial evolution of the German solar industry is analysed in the light of the “window of locational opportunity” and the “selection environment” approach. The paper argues that differences in the regions' ability to promote the emergence of local external economies contribute to increasing regional differentiation in the German structure of the industry. Applied empirical methods enclose longitudinal firm entry and network analysis. A special focus is given upon the realignment processes in the science system. Our findings show a relatively rapid spatial concentration of production in eastern Germany since the year 2000. This process is accompanied by intensified networking between firms and between firms and universities as well as research institutes. The responsiveness of regional institutions and the self-organizing capabilities of the solar firms substantiate some propositions of the “selection environment” approach.

Innovation is the result of an interactive process. Knowledge-intensive interactions among different partners are associated with a variety of advantages and disadvantages for the actors involved. Therefore, a rich body of literature investigating the impact of R&D collaboration networks on the innovation performance of firms and regions has developed over the last two decades. Those studies come to different results. The aims of this paper are manifold. First, the paper summarizes the results of the relevant literature. Second, a brief overview of the established methods and approaches used in the literature to investigate this research question is given. The third objective is to answer the question whether the achieved results in the literature are predetermined by the employed methods. Finally, relevant gaps for further research are identified. To answer these questions a meta-analysis of the relevant literature is conducted. This study shows that knowledge-intensive interactions have a rather positive impact on the performance of firms and regions. There is also evidence that the employed methods and approaches used in the literature to investigate this research question predetermine the outcome of the research.

Many economic decisions implicitly or explicitly rely on a projection of the medium- or long-term economic development of a country or region. In this paper, we provide a federal long-run projection model for Germany and the German states. The model fea-tures a top-down approach and, as major contribution, uses error correction models to estimate the regional economic development dependent on the national projection. For the medium- and long-term projection of economic activity, we apply a production function approach. We provide a detailed robustness analysis by systematically varying assumptions of the model. Additionally, we explore the effects of different demographic trends on economic development.

This study analyzes the impact of entrepreneurship education at universities on the intentions of students to become entrepreneurs or self-employed in the short-term (immediately after graduation) and in the long-term (five years after graduation). A difference-in-differences approach is applied that relates changes in entrepreneurial intentions to changes in the attendance of entrepreneurship classes in the same period. To account for a potential bias due to self-selection into entrepreneurship classes, only individuals having no prior entrepreneurial intentions are analyzed. Our results indicate a stimulating effect of entrepreneurship education on students’ intentions to become entrepreneurs or self-employed in the long-term but a discouraging effect on their intentions in the short-term. These results support the conjecture that entrepreneurship education provides more realistic perspectives on what it takes to be an entrepreneur, resulting in ‘sorting’. Overall, the results indicate that entrepreneurship education may improve the quality of labor market matches, the allocation of resources and talent, and increase social welfare. Not distinguishing between short- and long-term intentions may lead to misleading conclusions regarding the economic and social impact of entrepreneurship education.

The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite

indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.

Drawing on the systems perspective of innovation processes, this article proposes a conceptual approach for a comprehensive analysis of regional knowledge generation and transfer. Instead of focusing on one single indicator, the approach emphasizes the importance to take multiple channels of knowledge transfer into account. This provides valuable insights into the spatial structure of innovation processes on different levels. We disentangle the innovation process and consider four different layers: i.) publications in peer-reviewed journals, ii.) patent applications, iii.) formal R&D collaboration projects, the iv.) localized input-output relations. Further, we demonstrate the relevance of the „multi-layer approach‟ by applying it empirically to a specific regional innovation system: The Free State of Saxony – a federal state in Germany. We argue that the approach could be a valuable tool to inform policy-makers about knowledge-based regional development strategies.

This paper analyzes the process of real economic convergence in the New Member States (NMS) bein g formerly centrally planned economies, using nonparametric methods instead of conventional parametric measurement tools like beta and sigma models. This methodological framework allows the examining of the relative income distribution in different periods of time, the number of modes of the density distribution, the existence of “convergence clubs” in the distribution and the hypothesis of convergence at a single point in time. The modality tests (e.g. the ASH-WARPing procedure) and stochastic kernel are nonparametric techniques used in the empirical part of the study to examine the income distribution in the NMS area. Additionally, random effects panel regressions are used, but only for comparison reasons. The main findings of the paper are the bimodality of the income density distribution over time and across countries, and the presence of convergence clubs in the income distribution from 1995 to 2008. The findings suggest a lack of absolute convergence in the long term (1995-2008) and also when looking only from 2003 onwards. The paper concludes that, in comparison with the parametrical approach, the nonparametric one gives a deeper, real and richer perspective on the process of real convergence in the NMS area.

deutscher Titel: Makroökonomische Herausforderungen für die Eurozone und die Beitrittskandidaten

Abstract: The conduct of effective economic policy faces a multiplicity of macroeconomic challenges, which requires a wide scope of theoretical and empirical analyses. With a focus on the European Union, this doctoral dissertation consists of two parts which make empirical and methodological contributions to the literature on forecasting real economic activity and on the analysis of business cycles in a boom-bust framework in the light of the EMU enlargement. In the first part, we tackle the problem of publication lags and analyse the role of the information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A huge dataset of monthly indicators is used to estimate simple bridge equations. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We find that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. In the second part, we focus on the potential accession of the new EU Member States in Central and Eastern Europe to the euro area. In contrast to the discussion of Optimum Currency Areas, we follow a non-standard approach for the discussion on abandonment of national currencies the boom-bust theory. We analyse whether evidence for boom-bust cycles is given and draw conclusions whether these countries should join the EMU in the near future. Using a broad range of data sets and empirical methods we document credit market imperfections, comprising asymmetric financing opportunities across sectors, excess foreign currency liabilities and contract enforceability problems both at macro and micro level. Furthermore, we depart from the standard analysis of comovements of business cycles among countries and rather consider long-run and short-run comovements across sectors. While the results differ across countries, we find evidence for credit market imperfections in Central and Eastern Europe and different sectoral reactions to shocks. This gives favour for the assessment of the potential euro accession using this supplementary, non-standard approach.

This dissertation applies the theory of technology accumulation to explain the internationalisation of foreign and West German multinational enterprises (MNEs) into East Germany. This theory shifts the focus from technology transfer to the international diffusion of innovation within the MNE. It rejects the position that all MNEs offer the same technological opportunities to host economies. Yet, most of the existing empirical research on postcommunist transition economies including East Germany applies the traditional technology transfer perspective. Therefore, this dissertation provides a complementary and novel approach. We assume a dynamic interaction between existing location specific technological capabilities within the host country, MNEs’ location choice, their internationalisation of research and development (R&D) and innovation, and the potential for technological spillover effects from MNEs to the host economy. The dissertation exploits information from the IWH FDI micro database on the full population of MNEs that entered East German manufacturing until 2005 and corresponding survey data. Microeconometric estimation results generate a number of novel findings: We can show that existing location specific technological capabilities affect MNEs’ general location choice within East Germany. They are not powerful enough to attract MNEs’ technological activities. Instead, the location of MNEs’ innovation requires the joint presence of technological and industry specialisation within regions, whereas foreign R&D benefits from technological specialisation in combination with a diversified industry structure. Moreover, the location of technological activity differs depending upon the underlying motive for internationalisation. Our findings suggest that the potential for technological externalities from affiliates to local firms is subject to centrally and locally driven technological heterogeneity of MNEs. Existing location specific technological capabilities do not affect the spillover potential. This hints a limited dynamic interaction of ownership and locational advantages in firms’ internationalisation. We derive implications for the technology accumulation theory as well as for various fields of science and technology policy.