|
on Innovation |
| By: | Daron Acemoglu (MIT and NBER); Pascual Restrepo (Boston University) |
| Abstract: | The standard approach to modeling inequality, building on Tinbergen’s seminal work, assumes factor-augmenting technologies and technological change biased in favor of skilled workers. Though this approach has been successful in conceptualizing and documenting the race between technology and education, it is restrictive in a number of crucial respects. First, it predicts that technological improvements should increase the real wages of all workers. Second, it requires sizable productivity growth to account for realistic changes in relative wages. Third, it is silent on changes in job and task composition. We extend this framework by modeling the allocation of tasks to factors and allowing richer forms of technological changes — in particular, automation that displaces workers from tasks they used to perform, and the creation of new tasks that reinstate workers into the production process. We show that factor prices depend on the set of tasks that factors perform, and that automation: (i) powerfully impacts inequality; (ii) can reduce real wages; and (iii) can generate realistic changes in inequality with small changes in productivity. New tasks, on the other hand, can increase or reduce inequality depending on whether it is skilled or unskilled workers that have a comparative advantage in these new activities. Using industry-level estimates of displacement driven by automation and reinstatement due to new tasks, we show that displacement is associated with significant increases in industry demand for skills both before 1987 and after 1987, while reinstatement reduced the demand for skills before 1987, but generated higher demand for skills after 1987. The combined effects of displacement and reinstatement after 1987 explain a significant part of the shift towards greater demand for skills in the US economy. |
| Keywords: | automation, demand for skills, displacement, inequality, labor share, new tasks, productivity, reinstatement, robots, skill-biased technological change, skill premium, tasks, task content of production, wage structure |
| JEL: | J23 J24 J31 O33 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:bos:iedwpr:dp-334&r=all |
| By: | Borrás, Susana; Edler, Jakob |
| Abstract: | The transformative turn of innovation policy has resulted in calls for a more entrepreneurial and directional role of the state. However, the multiple roles that the state might play in such processes remain underexplored. This paper studies the embedded role of the state in four distinct modes of governance in socio-technical systems. Using a three-pillar analytical model, the paper examines four illustrative cases: cryptocurrencies, smart cities, automated vehicles, and nuclear power. The paper identifies 13 different roles of the state, indicating relevant variation across the four modes of governance. We discuss whether some roles of the state are more transformative than others, and provide clues for policy implications, and a future research agenda. The concept developed in the paper contributes to a more differentiated understanding of the transformative roles of the state. |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fisidp:65&r=all |
| By: | Matthew S. Clancy; Paul Heisey; Yongjie Ji; GianCarlo Moschini |
| Abstract: | This chapter investigates the extent to which agricultural innovations draw on ideas originating outside of agriculture. We identify a large set of US patents for agricultural technologies granted between 1976 and 2018. To measure knowledge spillovers to these patents, we rely on three proxies: patent citations to other patents, patent citations to the scientific literature, and a novel text analysis to identify and track new ideas in the patent text. We find that more than half of knowledge flows originate outside of agriculture. The majority of these knowledge inflows, however, still originate in domains that are close to agriculture. |
| JEL: | O31 O34 Q16 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27011&r=all |
| By: | Stefano Baruffaldi (Max Planck Institute for Innovation and Competition); Brigitte van Beuzekom; Hélène Dernis; Dietmar Harhoff (Max Planck Institute for Innovation and Competition); Nandan Rao; David Rosenfeld; Mariagrazia Squicciarini |
| Abstract: | This paper identifies and measures developments in science, algorithms and technologies related to artificial intelligence (AI). Using information from scientific publications, open source software (OSS) and patents, it finds a marked increase in AI-related developments over recent years. Since 2015, AI-related publications have increased by 23% per year; from 2014 to 2018, AI-related OSS contributions grew at a rate three times greater than other OSS contributions; and AI-related inventions comprised, on average, more than 2.3% of IP5 patent families in 2017. China’s growing role in the AI space also emerges. The analysis relies on a three-pronged approach based on established bibliometric and patent-based methods, and machine learning (ML) implemented on purposely collected OSS data. |
| Date: | 2020–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaaa:2020/05-en&r=all |
| By: | John Edwards (European Commission – JRC); Eskarne Arregui-Pabollet (European Commission – JRC); Federico Biagi (European Commission - JRC); Koen Jonkers (European Commission - JRC) |
| Abstract: | This Science for Policy Report analyses the main factors influencing the potential of Higher Education Institutions to contribute to innovation and regional development. The analysis is structured around two groups of factors: The supply of knowledge and skills through education, research and external engagement, and the demand side concerning the ability of regional actors to absorb it. The report draws on both qualitative and quantitative data, including two sets of case studies from JRC projects related to the regional impact of universities and the role of HEIs in Smart Specialisation Strategies (S3), as well as a recent econometric study that compares flows of human capital and knowledge from HEIs with firm location. The report is part of the Commission's Knowledge Hub for Higher Education at the JRC which brings together a number of tools including University Multi Rank, from which data is analysed in this report. |
| Keywords: | higher education, innovation, regional development |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc119771&r=all |
| By: | Konrad B. Burchardi (Institute for International Economic Studies); Thomas Chaney (Sciences Po); Tarek A. Hassan (Boston University, NBER, and CEPR); Lisa Tarquinio (Boston University); Steohen Terry (Boston University) |
| Abstract: | We show a causal impact of immigration on innovation and dynamism in US counties. To identify the causal impact of immigration, we use 130 years of detailed data on migrations from foreign countries to US counties to isolate quasi-random variation in the ancestry composition of US counties that results purely from the interaction of two historical forces: (i) changes over time in the relative attractiveness of different destinations within the US to the average migrant arriving at the time and (ii) the staggered timing of the arrival of migrants from different origin countries. We then use this plausibly exogenous variation in ancestry composition to predict the total number of migrants flowing into each US county in recent decades. We show four main results. First, immigration has a positive impact on innovation, measured by the patenting of local firms. Second, immigration has a positive impact on measures of local economic dynamism. Third, the positive impact of immigration on innovation percolates over space, but spatial spillovers quickly die out with distance. Fourth, the impact of immigration on innovation is stronger for more educated migrants. |
| Keywords: | migrations, innovation, patents, endogenous growth, dynamism |
| JEL: | J61 O31 O40 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:bos:iedwpr:dp-339&r=all |
| By: | Runst, Petrik; Thomä, Jörg |
| Abstract: | Previous research has established that certain personality traits represent predictors of start-up activity. We argue that similar cognitive processes that affect entrepreneurship also play a role in firm-level innovativeness. For example, open-ness to novelty can be regarded as a key component of entrepreneurial alertness in terms of both business creation and the generation of innovations within existing businesses. Based on a large survey of less R&D-intensive SMEs from Germany, we show that certain Big Five personality traits as well as certain personality prototypes of business owners are positively related to innovation activity. More importantly, this relationship depends on the mode of innovation, where companies operating under the DUI mode (Doing-Using-Interacting) seem to benefit in particular from certain owners' personality characteristics. In addition, we present evidence that complementarities between entrepreneurs' personality traits exist in terms of self-selection into the DUI mode. To explain our findings, we argue that the personali-ty characteristics of small business owners affect whether or not absorptive capacity can mediate between external knowledge and firm-level innovativeness. |
| Keywords: | Innovation,Modes of innovation,Absorptive capacity,Personality Traits,Big Five,SMEs |
| JEL: | L26 O31 O33 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifhwps:242019&r=all |
| By: | OECD |
| Abstract: | This working paper seeks to contribute to the understanding of the public sector innovation process at an organisational or team level, and suggests areas for consideration for public sector organisations developing their innovation capabilities. It explores why a more sophisticated approach to public sector innovation is required and explains how an explicit innovation process (the innovation lifecycle) can support such an approach. The paper argues that organisations need to take a multifaceted portfolio approach, combined with a more deliberate recognition of other actors in their ecosystem. It finishes by examining how the innovation lifecycle plays out in practice, and suggests criteria to guide organisations and teams in selecting tools and methods to support them along the different stages of the innovation lifecycle. |
| Date: | 2020–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:oec:govaaa:37-en&r=all |
| By: | Lesley Potters (European Commission - JRC); Nicola Grassano (European Commission - JRC) |
| Abstract: | This fourteenth Survey on Industrial R&D investment trends is based on 134 responses of mainly large firms from a subsample of the 1000 EU-based companies in the 2017 EU Industrial R&D Investment Scoreboard. The participating EU firms have a total of €64.0 billion of R&D investments, 31% of the total R&D investments by EU firms in the 2017 EU R&D Scoreboard, and expect R&D investment to increase by 4.6% per year in 2018 and 2019. |
| Keywords: | Research and Development, R&D, innovation, expectations, drivers, trends, survey |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc119026&r=all |
| By: | Douglas L. Campbell (New Economic School); Karsten Mau (Maastricht University) |
| Abstract: | Bloom, Draca, and Van Reenen (2016) find that Chinese competition induced a rise in patenting, IT adoption, and TFP by 30% of the total increase in Europe in the early 2000s. We find that the average patents per firm fell by 94% for the most Chinacompeting firms in their sample, but also by 94% for non-competing firms (starting from an initially higher level), and that various intuitive controls, such as controls for sectoral trends, renders the impact on patents-per-firm insignificant. We also find that while TFP appears to be positively correlated with the rise in Chinese competition, IV estimates are inconclusive, and other measures of productivity, such as value-added per worker and profits, are not correlated. Various instrumental and proxy variable approaches also do not support a positive impact of the rise of China on European patents. |
| Keywords: | Patents, China, Europe, Textiles, Trade Shocks, Manufacturing |
| JEL: | F14 F13 L25 L60 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:abo:neswpt:w0252&r=all |
| By: | Andreas Irmen |
| Abstract: | This paper develops a static model of endogenous task-based technical progress to study how factor scarcity induces technological progress and changes in factor prices. The equilibrium technology is multi-dimensional and not strongly factor-saving in the sense of Acemoglu (2010). Nevertheless, labor scarcity induces labor productivity growth. There is a weak but no strong absolute equilibrium bias. This model provides a plausible interpretation of the famous contention of Hicks (1932) about the role of factor prices and factor endowments for induced innovations. It may serve as a micro-foundation for canonical macro-economic models. Moreover, it accommodates features like endogenous factor supplies and a binding minimum wage. |
| Keywords: | economic growth, endogenous technical change, direction of technical change, biased technology |
| JEL: | O31 D92 O33 O41 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8215&r=all |
| By: | Madsen, Jakob Brøchner; Strulik, Holger |
| Abstract: | In this paper we investigate the impact of technological change on inequalityin the presence of a landed elite using a standard unified growth model. We measure inequality by the ratio between land rent and wages and show that, before the onset of the fertility transition, technological progress increased inequality directly through land-biased technological change and indirectly through increasing population growth. Thefertility transition and the child quantity-quality trade-off eventually disabled the Malthusian mechanism, and technological progress triggered education and benefited workers. If the elasticity of substitution between land and labor is sufficiently high, the rent-wage ratio declines such that inequality is hump-shaped in the very long run. We use the publication of new farming book titles as a measure of technological progress in agriculture, and provide evidence for technology-driven inequality in Britain between 1525 and 1895. We confirm these results for a panel of European countries over the period 1265-1850 using agricultural productivity as a measure of technology. Finally, using patents in the period 1800-1980, we find a technology-driven inequality reversal around the onset of the fertility transition. |
| Keywords: | nequality,Malthus,Unified Growth Theory,Agriculture,Human Capital |
| JEL: | O40 O30 N30 N50 J10 I25 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cegedp:392&r=all |