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on Technology and Industrial Dynamics |
| By: | Giacomo Vaccario; Luca Verginer; Antonios Garas; Mario V. Tomasello; Frank Schweitzer |
| Abstract: | Firms' innovation potential depends on their position in the R&D network. But details on this relation remain unclear because measures to quantify network embeddedness have been controversially discussed. We propose and validate a new measure, coreness, obtained from the weighted k-core decomposition of the R&D network. Using data on R&D alliances, we analyse the change of coreness for 14,000 firms over 25 years and patenting activity. A regression analysis demonstrates that coreness explains firms' R&D output by predicting future patenting. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.07677&r= |
| By: | Stefan Jestl (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in EU countries. The empirical analysis relies on a harmonised comprehensive regional dataset, which combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001-2016. The results suggest relatively weak effects on regional total employment dynamics. However, employment effects differ between manufacturing and non-manufacturing industries. Industrial robots show negative employment effects in local manufacturing industries, but positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect operates in local service industries. IT investments show positive employment effects only in local manufacturing industries, while CT investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative impact on local employment in both local manufacturing and non-manufacturing industries. |
| Keywords: | Industrial robots, ICT, EU labour markets, employment effects |
| JEL: | J23 L60 O33 R11 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:wii:wpaper:215&r= |
| By: | Antonin Bergeaud; Cyril Verluise |
| Abstract: | Innovation is an important driver of potential growth but quantitative evidence on the dynamics of innovative activities in the long-run are hardly documented due to the lack of data, especially in Europe. In this paper, we introduce PatentCity, a novel dataset on the location and nature of patentees from the 19th century using information derived from an automated extraction of relevant information from patent documents published by the German, French, British and US Intellectual Property offices. This dataset has been constructed with the view of facilitating the exploration of the geography of innovation and includes additional information on citizenship and occupation of inventors. |
| Keywords: | history of innovation, patent, text as data |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1850&r= |
| By: | Lafond, François; Goldin, Ian; Koutroumpis, Pantelis; Winkler, Julian |
| Abstract: | We review recent research on the slowdown of labor productivity and examine the contribution of different explanations to this decline. Comparing the post-2005 period with the preceding decade for five advanced economies, we seek to explain a slowdown of 0.8 to 1.8pp. We trace most of this to lower contributions of TFP and capital deepening, with manufacturing accounting for the biggest sectoral share of the slowdown. No single explanation accounts for the slowdown, but we have identified a combination of factors which, taken together, accounts for much of what has been observed. In the countries we have studied, these are mismeasurement, a decline in the contribution of capital per worker, lower spillovers from the growth of intangible capital, the slowdown in trade, and a lower growth of allocative efficiency. Sectoral reallocation and a lower contribution of human capital may also have played a role in some countries. In addition to our quantitative assessment of explanations for the slowdown, we qualitatively assess other explanations, including whether productivity growth may be declining due to innovation slowing down. |
| JEL: | O40 E66 D24 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:amz:wpaper:2022-08&r= |
| By: | Chowdhury, Farhat (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics); van Hasselt, Martijn (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | We describe public support for AI research in small firms using data from U.S. Department of Defense-funded SBIR projects. Ours is the first collection of firm-level project information on publicly funded R&D investments in AI. We find that the likelihood of an SBIR funded research project being focused on AI is greater the larger the amount of the SBIR award. AI-focused research projects are associated with a 7.6 percent increase in average award amounts. We also find suggestive evidence that the likelihood of an SBIR project being AI-focused is greater in smaller-sized firms. Finally, we find that SBIR-funded AI research is more likely to occur in states with complementary university research resources. |
| Keywords: | Artificial intelligence; machine learning; Department of Defense; Small Business Innovation Research program; agglomeration; |
| JEL: | O31 O38 |
| Date: | 2022–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2022_003&r= |
| By: | Fletcher, Joshua (RTI International); Howard, Eric (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics); O'Connor, Alan (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | This paper explores the impact that external sources of information have on the effectiveness of R&D in small, entrepreneurial firms. The effectiveness of R&D is measured in terms of two probabilities; the probability that a firm that received and completed a Phase I SBIR-funded research project is invited to submit a proposal for a Phase II award, and given such an invitation, the probability that a firm receives the Phase II award. Information from competitors is an important, in a statistical sense, covariate with the probability of being asked to submit a Phase II proposal whereas information from suppliers and customers in an important covariate with the probability of receiving a Phase II award. |
| Keywords: | Small Business Innovation Research (SBIR) program; small firms; entrepreneurial firms; R&D; knowledge sources; program evaluation; |
| JEL: | H43 L26 O31 O32 O38 |
| Date: | 2022–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2022_002&r= |
| By: | Duygu Buyukyazici; Leonardo Mazzoni; Massimo Riccaboni; Francesco Serti |
| Abstract: | The literature reaches a unanimous agreement that industrial diversification is path-dependent because new industries build on preexisting capabilities of regions that are partly embodied and reflected in the skills of regions’ workforce. This paper explicitly accounts for regional capabilities as workforce skills to build skill relatedness and complexity measures, skill-spaces, for 107 Italian regions for the period 2013-2019. Data-driven techniques we use reveal that skill-spaces form two highly polarised clusters into social-cognitive and technical-physical skills. We show that industries have a higher (lower) probability of developing comparative advantage if their required skill set is (not) similar to those available in the region regardless of the skill type. We find evidence that similarity to technical-physical skills and higher complexity in social cognitive skills yields the highest probabilities of regional competitive advantage. |
| Keywords: | Skill relatedness; Economic complexity; Industrial specialisation; Regional capabilities; Regional diversification. |
| JEL: | J24 O18 R10 R23 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2210&r= |
| By: | Colin Davis (The Institute for the Liberal Arts, Doshisha University, JAPAN); Laixun Zhao (Research Institute for Economics & Business Administration (RIEB), Kobe University, JAPAN) |
| Abstract: | We study how tax policy affects economic growth through entrepreneurs' choice of commercialization mode. Introducing both heterogeneous quality jumps and a leapfrog versus sell choice into the quality-ladders model, we show that entrepreneurs use high-quality innovations to leapfrog incumbent firms and become new market leaders, but sell low quality innovations to incumbents. Tax incentives that promote leapfrogging slow the rate of innovation. A numerical analysis concludes surprisingly that corporate taxes, capital gains taxes, and subsidies to market entry all harm welfare. |
| Keywords: | Innovation based growth; Heterogenous quality improvements; Innovation sales; Corporate tax; Capital gains tax; Market entry subsidy |
| JEL: | O31 O33 O43 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:kob:dpaper:dp2022-28&r= |
| By: | de Souza, Gustavo |
| Abstract: | Developing countries rely on technology created by developed countries. This paper demonstrates that such reliance increases wage inequality but leads to greater production in developing countries. I study a Brazilian innovation program that taxed the leasing of international technology to subsidize national innovation. By exploiting heterogeneous exposure, I show that the program led firms to replace technology licensed from developed countries with in-house innovations, which led to a decline in both employment and the share of high-skilled workers. I explain these findings using a model of directed technological change and cross-country technology transactions. Firms in a developing country can either innovate or lease technology from a developed country, and these two technologies differ endogenously regarding productivity and skill bias due to factor supply disparities in the two countries. I show that the difference in skill bias and productivity can be identified using closed-form solutions by the effect of the innovation program on firms’ expenditure share with lowskilled workers and employ- ment. By calibrating the model to reproduce these effects, I find that increasing the share of firms that patent in Brazil by 1 p.p. decreases the skilled wage premium by 0.02% and production by 0.2%. |
| Keywords: | labor market, technology, wages |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:cpm:docweb:2208&r= |
| By: | Raffaele Danna; Martina Iori; Andrea Mina |
| Abstract: | The accumulation of knowledge and its application to a variety of human needs is a discontinuous process that involves innovation and change. While much has been written on major discontinuities associated, for instance, with the rise of new technologies during industrial revolutions, other phases of economic development are less well understood, even though they might bring into even sharper focus the mechanisms through which growth is generated by the systematic application of human knowledge to practical problems. In this paper, we investigate the transmission of new mathematical knowledge from the 13th to the end of the 16th century in Europe. Using an original dataset of over 1050 manuals of practical arithmetic, we produce new descriptive and quasi-experimental evidence on the economic importance of the European transition from Roman to Hindu-Arabic numerals (0, 1, 2, 3, 4, 5, 6, 7, 8, 9). This numerical revolution laid the foundations for the commercial revolution of the 13th century, and the diffusion of knowledge through organised learning had positive and significant effects on the growth of pre-modern European economies. |
| Keywords: | Human capital; knowledge diffusion; learning; economic growth. |
| Date: | 2022–06–22 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2022/18&r= |
| By: | Chowdhury, Farhat (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics); van Hasselt, Martijn (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | A spatial distributional analysis of the population of Phase II research projects funded by the U.S. SBIR program in FY 2020 shows differences across states in projects focused on Artificial Intelligence (AI). AI is a relatively new research field, and this paper contributes to a better understanding of government support for such research. We find that AI projects are concentrated in states with complementary AI research resources available from universities nationally ranked in terms of their own AI research. To achieve a more diverse spatial distribution of AI-related technology development, the availability of complementary AI research resources must be expanded. We suggest that the National Science Foundation’s National AI Research Institutes represents an important step in this direction. |
| Keywords: | Artificial intelligence (AI); Public sector program management; Small Business Innovation Research (SBIR); Agglomeration; University research; |
| JEL: | H54 O31 O38 R11 |
| Date: | 2022–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2022_004&r= |
| By: | Fabrizio Leone |
| Abstract: | This paper shows that multinational enterprises (MNEs) spur the adoption of industrial robots. First, I document a positive and robust correlation between multinational production and robot adoption using a new cross-country industry-level panel. Second, using detailed data about Spanish manufacturing, I combine a difference-in-differences approach with a propensity score reweighing estimator and provide evidence that firms switching from domestic to foreign ownership become about 10% more likely to employ robots. In terms of mechanism, increased foreign market access via the parental network generates incentives to scale-up production, and robot adoption is one way to achieve this goal. An empirical model of rm investment reveals that multinational-induced robot adoption raises productivity but decreases the labor share at the industry level. Theseresults provide new evidence about the efficiency versus equity trade-off that policymakers face when attracting MNEs. |
| Keywords: | Foreign Ownership, Industrial Robots, Total Factor Productivity, Factor-Biased Productivity, Labor Share |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/344246&r= |