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on Technology and Industrial Dynamics |
| 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: | Kyoo il Kim (Department of Economics, Michigan State University); Jin Ho Park (Economic Research Institute, Bank of Korea) |
| Abstract: | We study aggregate productivity growth of the Korean manufacturing industry for the 2007-2017 period. We find that the nature of such growth was quite different for two measures of productivity. For labor productivity, most of growth comes from productivity changes among surviving firms. On the other hand, for TFP, most of the productivity growth comes from that of new entrants in recent years. Our work illustrates the different nature of two productivity measures in terms of their growth paths. We also show interesting industry dynamics for both productivity measures, as exiting firms contributed positively to aggregate productivity growth with increasing trends, which suggests that the market had gradually eliminated firms of lower productivity. Using the dynamic Olley and Pakes (1996) decomposition, we also find that for both productivity measures, a substantial productivity growth after the 2008 global financial crisis was due to market share reallocations between firms, but this between-firm contribution has somewhat slowed or been decreasing since then. Our industry sector level study also shows that there has been fundamentally different heterogeneous productivity growth patterns and components across manufacturing sectors. Finally, we find that the wage level also plays a role in moderating or as an accelerating factor for different productivity growth paths among surviving, entering, and exiting firms. We find that higher wage groups had disproportionately higher entry and exit rates, and that the contributions of these industry dynamics to aggregate productivity growth were largest for the highest wage group while the productivity growth from the between firm component was substantially higher for lower wage groups. Therefore, we find that not only a timely change in input and output, but also in the wage, is a necessary ingredient for the pace and magnitude of reallocation to be effective in aggregate productivity growth. |
| Keywords: | Aggregate Productivity Growth, Labor Productivity, Total Factor Productivity, Resource Reallocation, Entry and Exit, Wage |
| JEL: | C14 C18 D24 |
| Date: | 2020–04–17 |
| URL: | http://d.repec.org/n?u=RePEc:bok:wpaper:2009&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: | Katharina Längle (CES - Centre d'économie de la Sorbonne - CNRS - Centre National de la Recherche Scientifique - UP1 - Université Panthéon-Sorbonne) |
| Abstract: | This paper investigates the question which aspects of offshoring harm low skilled workers using data from the WIOD for 14 manufacturing industries in 16 high income countries between 1995 and 2008. By considering the use of foreign production factors in domestic production, the paper shows that low skilled workers are directly and negatively affected by offshoring of low skilled tasks. Importantly, the paper determines a further indirect channel highlighting the role of growing foreign competition in domestic markets for intermediate goods. Accordingly, wage shares of low skilled workers decline when competition in domestic downstream value chains increases. Interpreting this channel in the light of the literature on defensive skill-biased innovation, the shift in wage shares away from low skilled workers might be provoked by skill intensive investments in response to tougher foreign competition in domestic markets for intermediate goods. JEL classification: F23, L23, L24, M11. |
| Keywords: | Global value chains,Input-Output Tables and Analysis,Organization of Production,Empirical Studies of Trade |
| Date: | 2020–04–20 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02548691&r=all |
| By: | Daron Acemoglu (MIT and NBER); Claire Lelarge (Paris-Saclay, CREST and CEPR); Pascual Restrepo (Boston University) |
| Abstract: | Using several sources, we construct a data set of robot purchases by French manufacturing firms and study the firm-level implications of robot adoption. Out of 55,390 firms in our sample, 598 have adopted robots between 2010 and 2015, but these firms account for 20% of manufacturing employment and value added. Consistent with theory, robot adopters experience significant declines in labor share and the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of their competitors (as automation reduces their relative costs). We show that the overall impact of robot adoption on industry employment is negative. We further document that the impact of robots on overall labor share is greater than their firm-level effects because robot adopters are larger and grow faster than their competitors. |
| Keywords: | automation, competition, labor share, manufacturing, productivity, reallocation, robots, tasks |
| JEL: | J23 J24 L11 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:bos:iedwpr:dp-335&r=all |
| By: | Jan Fagerberg (TIK, University of Oslo & UNU-MERIT); Bart Verspagen (UNU-MERIT) |
| Abstract: | Technological revolutions, i.e., clusters of technologies that collectively have a transformational impact on the global economy, are rare events that dramatically influence the opportunities facing countries at different levels of development. A central suggestion in the relevant literature is that countries that manage to adopt the new technologies associated with a specific technological revolution benefit economically from it. This is also assumed to go together with a changing specialization pattern in international trade. The paper considers the empirical merits of these suggestions, drawing on GDP and trade data for a large number of countries on different levels of development from the post-second-world-war period. The empirical analysis reveals a major divide in the global economy between a group of modern, industrialized countries, specialized in technology-based production, and another group of countries, specialized in commodities and resource-based products, and lagging behind both in terms of technology and income. More to the future, the paper also discusses the extent to which a new green technological revolution, with renewable energy as a central element, is currently emerging, and what impact this possibly might have for catching-up, structural change and economic growth for countries at different levels of development, e.g., China. |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:tik:inowpp:20200423&r=all |
| By: | Arza,Valeria Luciana; Cirera,Xavier; Colonna,Agustina; Lopez,Emanuel |
| Abstract: | Argentina's private investment in research and development is well below that of its peers. One important reason may be low and very heterogeneous returns to research and development activities on productivity. This paper uses novel microdata to estimate the returns to research and development and understand the contextual factors that shape their heterogeneity. The paper groups these context-based factors into knowledge complementary factors (that is, factors that affect the returns via learning capabilities from external sources of knowledge) and market complementary factors (factors that act via business capabilities to appropriate the returns to research and development investments). The paper hypothesizes that the effects of contextual factors depend on firms'management capabilities and attitudes (innovative capacity), which determine firms'ability to benefit from the context. The findings suggest that the returns are indeed heterogeneous across regions and sectors, and these results depend on some context-based factors, which can boost or depress the returns to R&D. The results have important policy implications, considering the effectiveness of innovation policies, need for adapting to specific regions and sectors, and maximization of the impact of these factors on the returns to research and development. |
| Date: | 2020–04–30 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:9219&r=all |
| By: | Kerstin H\"otte; Anton Pichler; Fran\c{c}ois Lafond |
| Abstract: | Successfully combating climate change will require substantial technological improvements in Low-Carbon Energy Technologies (LCETs). An efficient allocation of R&D budgets to accelerate technological advancement necessitates a better understanding of how LCETs rely on scientific knowledge. In this paper, we sketch for the first time the evolution of knowledge bases for key LCETs and show how technological interdependencies change in time. We use data covering almost all US patents as well as scientific articles published in the past two centuries to quantify the history of LCETs and their dependence on science. We show how the drivers of low-carbon innovations shifted from Hydro and Wind energy to Nuclear fission, and more recently to Solar PV and back to Wind. Our analysis demonstrates that 1) LCETs rely increasingly on science, 2) Solar PV and Nuclear fusion depend heavily on science, while Hydro energy does not, 3) renewable and nuclear energy technologies rely on a strikingly different kind of science, and 4) there is a remarkable convergence of scientific knowledge bases of renewables over recent decades. These findings suggest a need for technology-specific research policies, although targeted research in renewables is likely to cross-fertilize a wider range of LCETs. |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2004.09959&r=all |
| By: | Tom\'a\v{s} Evan; Vladim\'ir Hol\'y |
| Abstract: | The Hicks induced innovation hypothesis states that a price increase of a production factor is a spur to invention. We propose an alternative hypothesis restating that a spur to invention require not only an increase of one factor but also a decrease of at least one other factor to offset the companies' cost. We illustrate the need for our alternative hypthesis in a historical example of the industrial revolution in the United Kingdom. Furthermore, we econometrically evaluate both hypotheses in a case study of research and development (R&D) in 29 OECD countries from 2003 to 2017. Specifically, we investigate dependence of investments to R&D on economic environment represented by average wages and oil prices using panel regression. We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities. |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2004.07814&r=all |
| By: | Patricia Laurens (LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés - CNRS - Centre National de la Recherche Scientifique - ESIEE Paris - UPEM - Université Paris-Est Marne-la-Vallée - INRA - Institut National de la Recherche Agronomique) |
| Abstract: | The Corporate Invention Board (CIB2) database is designed for the analysis of technological knowledge creation of the worldwide top corporate R&D performers, using patents as a proxy. It includes 3992 companies. It focuses on the ‘priority patents' applied by the parent companies and the subsidiaries they control. For patents, it relies on the patent data included in the RISIS Patent Database (RPD) . The list of companies was elaborated using several editions of the EU Industrial R&D Investment Scoreboard and the lists of WIPO top applicants. CIB2 also gives basic data on the companies (locations, sectors, size, financial data). |
| Keywords: | Innovation,Patent,R&D,Firms |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02518301&r=all |
| By: | Federico Caviggioli (Politecnico di Torino); Antonio De Marco (Politecnico di Torino); Giuseppe Scellato (Politecnico di Torino) |
| Abstract: | This study proposes a framework for investigating the relevance of dual use inventions, i.e., military applications of civilian patents. The data collected extends the companion report that focused on the opposite direction of dual use: from military inventions to civilian applications (Caviggioli et al., 2018). The analyses focus on 10 million patent families from selected patent offices in the years 2002-2015. The method proposed identified 85,034 defence inventions (0.9%) that were compared with the civilian inventions along several dimensions (time, geography, technological clusters). This study operationalises dual use from both a civilian to a military application (CM dual use) and in the opposite direction (MC dual use). The presence of CM dual inventions is 1.4% of the total civilian sample, with a slightly decreasing trend. They are four times the MCs in absolute numbers. The geographical analysis reveals heterogeneity: the US is the origin of 58.7% of the total dual use inventions identified in the sample and shows the highest incidence of cases (4.7% of all civilian inventions). The results also indicate significant heterogeneity in the share of domestic knowledge flows. The domestic spillover for dual in most of the countries examined is lower than for non-dual: a military application of a civilian innovation is a relatively more frequent occurrence outside the borders of the country with the exceptions of the USA, France, and the Russian Federation. The share of domestic CM dual use in the EU28 area is 36%, smaller than the corresponding non-dual value (42%). |
| Keywords: | Dual-use technologies, Key enabling technologies, defence |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc120293&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: | Bjørnskov, Christian (Aarhus University and) |
| Abstract: | Politicians and international organisations advocate for increased regulation and government control of industry in order to handle climate change and reduce overall greenhouse gas emissions. However, it remains an open question how economic freedom is associated with environmental damage and whether deregulation is harmful to the environment or incentivises the use of green technology. On one hand, more government control and regulation may force firms and individuals to reduce their emissions. On the other hand, more economic freedom is likely to enable innovation and the adoption of green technological development. In this paper, I therefore combine data on growth in greenhouse gas emissions and GDP per capita with the Fraser Institute’s Economic Freedom of the World indices in order to test if economic freedom affects emissions. I do so in the context of estimating a standard Environmental Kuznets Curve in which economic freedom can both reduce overall levels as well as shift the shape of the curve. The results suggest that economic freedom reduces greenhouse gas emissions but also shifts the top point of the Kuznets Curve to the left. Part of this effect may be due to the effect of economic freedom on the adoption of renewable energy. |
| Keywords: | Economic freedom; Environmental performance; Greenhouse gases; Kuznets Curves |
| JEL: | H23 O31 P16 Q55 |
| Date: | 2020–04–20 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1331&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: | 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 |