From small business promotion to creating an entrepreneurial society

Mittelstandspolitik, Unternehmer, Wissenstransfer, EU-Staaten, Deutschland, Small business policy, Entrepreneurs, Knowledge transfer, EU countries, Germany

Biases in FX-Forecasts: Evidence from Panel Data

In this paper, we use the Wall Street Journal poll of FX forecasts to analyze how the group of forecasters form their expectations. One focus is whether forecasters build rational expectations. Furthermore, we analyze whether the group of forecasters can be regarded as homogeneous or heterogeneous. The results from our regressions strongly suggest that some forecasters combine different models of exchange rate forecasting, while others rely solely on one model. We also find evidence that some forecasters underly a bias, while others do not. Overall, our regression results indicate a high degree of heterogeneity. In conclusion, we show that the expectation formation process is not the same among all economists polled. Our findings carry importance for macroeconomic modelling: The assumption of rational agents forming homogeneous expectations is not supported by our results. --Foreign exchange market,forecast bias,random walk

Capital emprendedor y crecimiento económico

Este trabajo muestra cómo y por qué el modelo de crecimiento de Solow es útil para relacionar capital emprendedor y crecimiento económico. El filtro del conocimiento impide la transmisión de conocimiento para su comercialización y por consiguiente debilita el impacto de las inversiones en conocimiento sobre el crecimiento económico. La actividad emprendedora es un importante mecanismo para la transmisión del conocimiento, que permite traspasar el filtro del conocimiento. La actividad emprendedora es el eslabón perdido entre las inversiones en nuevo conocimiento y el crecimiento económico. La cada vez más importante política de fomento de la actividad emprendedora promueve el crecimiento económico a través del capital emprendedor o de la capacidad de una economía para crear nuevas empresas o facilitar el crecimiento de las mismas

Who Do Scientists in Public Research Institutions Cooperate with Private Firms?

As public research institutions are increasingly pressured to transfer research results to industry, evaluation of their performance is not only based on their scientific output but also on their commercialization success. Although it is well known that research cooperation activities are an important channel of knowledge transfer, the knowledge about factors driving research cooperation is limited. This paper explicitly focuses on scientist perspective and investigates the relevance of academic values and perceived costs and benefits of cooperation for a scientist's decision to cooperate with private firms. Our analysis is based on two survey waves performed with scientists in the Max Planck Society in Germany which is a publicly funded research organization focusing on basic research. Our empirical results suggest that open science identity is an important determinant of scientist fundamental decision to cooperate with private firms at all. The decision to keep on cooperating with private firms is directly influenced by cost sharing incentives and by firms' confidentiality requirements. Besides these direct effects, our results suggest that perceived reputational reward, monetary benefits, and time costs associated with cooperation influence cooperation behavior indirectly through their impact on the attractiveness of cooperation. The latter is a strong and robust predictor of cooperation behavior.

It’s All in Marshall: The Impact of External Economies on Regional Dynamics

Marshall's student Pigou noted: “It’s all in Marshall.” From a static point of view, this seems rather bold in a constantly changing world. However, this statement becomes more plausible in a dynamic context, where principles are subject to change. Indeed, over time, Marshall's concept of external economies gained fresh perspective as new concepts of regional characteristics and agglomeration evolved. This paper focuses on the impact of region and industry on dynamics and growth, distinguishing between industrial districts, industrial agglomerations and urban agglomerations. Based on these three types, we use a comprehensive large dataset on German regions to test the following: (1) these regions can be characterized by given location variables describing geographic location, firm structure, and surrounding location factors and (2) every region's locational variables affects its potential for dynamics.regional and urban development, agglomeration, industrial districts, location factors, external economies

Entrepreneurship Capital and Economic Performance

The neoclassical model of the production function, as applied by Robert Solow to build the neoclassical model of growth, linked labor and capital to output. More recently, Romer and others have expanded the model to include measures of knowledge capital. In this paper we introduce a new factor, entrepreneurship capital, and link it to output in the context of a production function model. This paper explains what is meant by entrepreneurship capital and why it should influence economic output. A production function model including several different measures of entrepreneurship capital is then estimated for German regions. The results indicate that entrepreneurship capital is a significant and important factor shaping output and productivity. These results suggest a new direction for policy that focuses on instruments to enhance entrepreneurship capital

Entrepreneurial ecosystems in cities: establishing the framework conditions

This study focuses on regional entrepreneurial ecosystems and offers a complex model of start-ups, Regional Entrepreneurship and Development Index (REDI) and six domains of the entrepreneurial ecosystem (culture, formal institutions, infrastructure and amenities, IT, Melting Pot and demand). Altogether they capture the contextual features of socioeconomic, institutional and information environment in cities. To explain variations in entrepreneurship in a cross-section of 70 European cities, we utilize exploratory factor analysis and structural equation modelling for regional systems of entrepreneurship using individual perception surveys by Eurostat and the REDI. This study supports policymakers and scholars in development of new policies conducive to regional systems of innovation and entrepreneurship and serves as a basis for future research on urban entrepreneurial ecosystems

Artificial Intelligence and Big Data in Entrepreneurship: A New Era Has Begun

While the disruptive potential of artificial intelligence (AI) and Big Data has been receiving growing attention and concern in a variety of research and application fields over the last few years, it has not received much scrutiny in contemporary entrepreneurship research so far. Here we present some reflections and a collection of papers on the role of AI and Big Data for this emerging area in the study and application of entrepreneurship research. While being mindful of the potentially overwhelming nature of the rapid progress in machine intelligence and other Big Data technologies for contemporary structures in entrepreneurship research, we put an emphasis on the reciprocity of the co-evolving fields of entrepreneurship research and practice. How can AI and Big Data contribute to a productive transformation of the research field and the real-world phenomena (e.g., 'smart entrepreneurship')? We also discuss, however, ethical issues as well as challenges around a potential contradiction between entrepreneurial uncertainty and rule-driven AI rationality. The editorial gives researchers and practitioners orientation and showcases avenues and examples for concrete research in this field. At the same time, however, it is not unlikely that we will encounter unforeseeable and currently inexplicable developments in the field soon. We call on entrepreneurship scholars, educators, and practitioners to proactively prepare for future scenarios

Proof of Concept Centers: Accelerating the Commercialization of University Innovation

Examines two proof-of-concept centers -- the Deshpande Center at MIT and the von Liebig Center at UCSD -- and provides a template for universities to use in replicating the model