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on Innovation |
| By: | Uluc Aysun (Department of Economics, College of Business Administration, University of Central Florida); Zeynep Yom (Department of Economics, Villanova School of Business, Villanova University) |
| Abstract: | This paper shows that technology shocks have the largest impact on economies when industries adopt innovations of other industries at a high rate, if costs of adopting new technologies and adjusting R&D expenditures are low, and if innovators face a high degree of competition. It is not the level but the spillover of innovations across industries that is the key determinant of these findings. Under the conditions mentioned above, R&D becomes less procyclical and smoother along the business cycle yet R&D driven innovations have a larger impact on output since these innovations spillover at a higher rate. These inferences are drawn from a dynamic stochastic general equilibrium framework describing a real economy with endogenous growth. The latter feature allows us to infer the welfare implications of R&D processes. |
| Keywords: | Research and development; spillover effects; endogenous growth |
| JEL: | E30 E32 O30 O33 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:vil:papers:43&r=all |
| By: | Acemoglu, Daron (MIT); Restrepo, Pascual (Boston University) |
| Abstract: | Artificial Intelligence is set to influence every aspect of our lives, not least the way production is organized. AI, as a technology platform, can automate tasks previously performed by labor or create new tasks and activities in which humans can be productively employed. Recent technological change has been biased towards automation, with insufficient focus on creating new tasks where labor can be productively employed. The consequences of this choice have been stagnating labor demand, declining labor share in national income, rising inequality and lower productivity growth. The current tendency is to develop AI in the direction of further automation, but this might mean missing out on the promise of the "right" kind of AI with better economic and social outcomes. |
| Keywords: | automation, artificial intelligence, jobs, inequality, innovation, labor demand, productivity, tasks, technology, wages |
| JEL: | J23 J24 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12704&r=all |
| By: | Caliendo, Marco (University of Potsdam); Künn, Steffen (Maastricht University); Weissenberger, Martin (University of Potsdam) |
| Abstract: | From an active labor market policy perspective, start-up subsidies for unemployed individuals are very effective in improving long-term labor market outcomes for participants. From a business perspective, however, the assessment of these public programs is less clear since they might attract individuals with low entrepreneurial abilities and produce businesses with low survival rates and little contribution to job creation, economic growth, and innovation. In this paper, we use a rich data set to compare participants of a German start-up subsidy program for unemployed individuals to a group of regular founders who started from non-unemployment and did not receive the subsidy. The data allows us to analyze their business performance up until 40 months after business formation. We find that formerly subsidized founders lag behind not only in survival and job creation, but especially also in innovation activities. The gaps in these business outcomes are relatively constant or even widening over time. Hence, we do not see any indication of catching up in the longer run. While the gap in survival can be entirely explained by initial differences in observable start-up characteristics, the gap in business development remains and seems to be the result of restricted access to capital as well as differential business strategies and dynamics. Considering these conflicting results for the assessment of the subsidy program from an ALMP and business perspective, policy makers need to carefully weigh the costs and benefits of such a strategy to find the right policy mix. |
| Keywords: | entrepreneurship, start-up subsidies, business growth, innovation, job creation |
| JEL: | L26 M13 J68 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12690&r=all |
| By: | Alessandra Perri (Dept. of Management, Università Ca' Foscari Venice); Daniela Silvestri (Dept. of Management, Università Ca' Foscari Venice); Francesco Zirpoli (Dept. of Management, Università Ca' Foscari Venice) |
| Abstract: | This study explores the evolution of the knowledge base of the automotive industry. Over the last decades, the knowledge base of this industry has experienced major changes. New and originally unrelated fields have increasingly become relevant in the industry. Using data on utility patent families granted in the period 1990-2014, we map the knowledge base of the automotive industry by reconstructing and analyzing the innovative portfolio of the top firms operating in this industry. The analysis documents exploration in new technical fields as well as persistence in industry-specific technical areas, pointing to the relevance of core competences that might be difficult to accumulate for industry outsiders. |
| Keywords: | knowledge base evolution, automotive industry, patent analysis |
| JEL: | L62 O34 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:vnm:wpdman:167&r=all |
| By: | Montinaro, Marta; Scrimitore, Marcella |
| Abstract: | In a context of product innovation, we study two-part tariff licensing between a patentee and a potential rival which compete in a differentiated product market characterized by network externalities. The latter are shown to crucially affect the relative profitability of Cournot vs. Bertrand when a per unit royalty is applied. By contrast, we find that Cournot yields higher profits than Bertrand under ad valorem royalties, regardless of the strength of network effects. |
| Keywords: | licensing, product innovation, bertrand vs. cournot, network effects |
| JEL: | D43 L13 L20 |
| Date: | 2019–03–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:96642&r=all |
| By: | Stephen G. Dimmock; Jiekun Huang; Scott J. Weisbenner |
| Abstract: | We study how access to high-skill labor affects the outcomes of start-up firms. We obtain exogenous variation in firms’ ability to access skilled labor by using win rates in H-1B visa lotteries. Relative to other firms that also applied for H-1B visas, firms with higher lottery win rates are more likely to receive additional venture capital funding and to have a successful exit via an IPO or acquisition. H-1B visa lottery winners also subsequently receive more patents and patent citations. Overall, our results show that access to high-skill labor is a critical determinant of success for start-up firms. |
| JEL: | D22 G24 G32 J23 J24 J61 O3 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26392&r=all |
| By: | Robert W. Fairlie; Frank M. Fossen |
| Abstract: | A proposed explanation for why business creation is often found to increase in recessions is that there are two components to entrepreneurship – “opportunity” and “necessity” – the latter of which is mostly counter-cyclical. Although there is some agreement on the conceptual distinction between these two factors driving entrepreneurship, there is little consensus in the literature on empirical definitions. The goal of this paper is to propose an operational definition of opportunity versus necessity entrepreneurship based on the entrepreneur’s prior work status (i.e. based on previous unemployment) that is straightforward, based on objective information, and empirically feasible using many large, nationally representative datasets. We then explore the validity of the definitions with theory and empirical evidence. Using datasets from the United States and Germany we find that 80-90 percent of entrepreneurs are opportunity entrepreneurs. Applying our proposed definitions, we document that opportunity entrepreneurship is generally pro-cyclical and necessity entrepreneurship is strongly counter-cyclical both at the national levels and across local economic conditions. We also find that opportunity vs. necessity entrepreneurship is associated with the creation of more growth-oriented businesses. The operational definitions of opportunity and necessity entrepreneurship proposed here may be useful for distinguishing between the two types of entrepreneurship in future research. |
| JEL: | J23 J64 L26 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26377&r=all |
| By: | Gaétan de Rassenfosse (Chair of Innovation and IP Policy, EPFL, Lausanne, Switzerland); Jan Kozak; Florian Seliger (KOF Swiss Economic Institute, ETH Zurich, Switzerland) |
| Abstract: | The dataset provides geographic coordinates for inventor and applicant locations in 18.8 million patent documents spanning over more than 30 years. The geocoded data are further allocated to the corresponding countries, regions and cities. When the address information was missing in the original patent document, we imputed it by using information from subsequent filings in the patent family. The resulting database can be used to study patenting activity at a fine-grained geographic level without creating bias towards the traditional, established patent offices. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:kof:wpskof:19-458&r=all |