Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Research Clusters
Three Research Clusters Research Cluster "Economic Dynamics and Stability" Research Questions This cluster focuses on empirical analyses of macroeconomic dynamics and stability.…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
See page
Measuring the Impact of Household Innovation Using Administrative Data
Javier Miranda, Nikolas Zolas
Measuring and Accounting for Innovation in the Twenty-First Century,
NBER Studies in Income and Wealth, Vol 78 /
2021
Abstract
We link USPTO patent data to U.S. Census Bureau administrative records on individuals and firms. The combined dataset provides us with a directory of patenting household inventors as well as a time-series directory of self-employed businesses tied to household innovations. We describe the characteristics of household inventors by race, age, gender and U.S. origin, as well as the types of patented innovations pursued by these inventors. Business data allows us to highlight how patents shape the early life-cycle dynamics of nonemployer businesses. We find household innovators are disproportionately U.S. born, white and their age distribution has thicker tails relative to business innovators. Data shows there is a deficit of female and black inventors. Household inventors tend to work in consumer product areas compared to traditional business patents. While patented household innovations do not have the same impact of business innovations their uniqueness and impact remains surprisingly high. Back of the envelope calculations suggest patented household innovations granted between 2000 and 2011 might generate $5.0B in revenue (2000 dollars).
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Capital Misallocation and Innovation
Christian Schmidt, Yannik Schneider, Sascha Steffen, Daniel Streitz
SSRN Solutions Research Paper Series,
2020
Abstract
This paper documents that "zombie" lending by undercapitalized banks distorts competition and impedes corporate innovation. This misallocation of capital prevents both the exit of zombie and entry of healthy firms in affected industries adversely impacting output and competition. Worse, capital misallocation depresses patent applications, particularly in high technology- and R&D-intensive sectors, and industries with neck- and-neck competition. We strengthen our results using an IV approach to address reverse causality and innovation survey data from the European Commission. Overall, our results are consistent with externalities imposed on healthy firms through the misallocation of capital.
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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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Promoting Higher Productivity in China — Does Innovation Expenditure Really Matter?
Hoang Minh Duy, Filippo di Mauro, Jo Van Biesebroeck
Singapore Economic Review,
No. 5,
2020
Abstract
The slowing down of the global economy adds additional challenges to China? economic policies as the country orchestrates its transition to lower resource dependency and higher technology intensity of output. Are policies aimed at technologically advanced sectors the right answer? Drawing from a newly created dataset of firms? balance sheets over the period 1998?2013, matched with patents data until 2009, we uncover that expenditure in innovation had limited effect on boosting productivity, without generating a clear gain in overall productivity for the high-tech sector. As a matter of fact, there is a much higher dispersion in productivity outcomes in firms belonging to the low-technology sectors, which derives from a bunch of champions in those sectors scoring higher productivity dynamics than in the High-technology sectors. The paper finds those barriers to entry and in general, market power of incumbents in the high-tech generate less than optimal resource reallocation, which hampers the overall productivity. Policies should presumably aim at removing such obstacles rather than solely promote innovation expenditure.
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The Creation and Evolution of Entrepreneurial Public Markets
Shai B. Bernstein, Abhishek Dev, Josh Lerner
Journal of Financial Economics,
No. 2,
2020
Abstract
This paper explores the creation and evolution of new stock exchanges around the world geared toward entrepreneurial companies, known as second-tier exchanges. Using hand-collected novel data, we show the proliferation of these exchanges in many countries, their significant volume of Initial Public Offerings (IPOs), and lower listing requirements. Shareholder protection strongly predicted exchange success, even in countries with high levels of venture capital activity, patenting, and financial market development. Better shareholder protection allowed younger, less-profitable, but faster-growing, companies to raise more capital. These results highlight the importance of institutions in enabling the provision of entrepreneurial capital to young companies.
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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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Identifying Cooperation for Innovation – A Comparison of Data Sources
Michael Fritsch, Matthias Piontek, Mirko Titze
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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