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on Technology and Industrial Dynamics |
| By: | Nicholas Bloom; John Van Reenen; Heidi Williams |
| Abstract: | Economic theory suggests that market economies are likely to under-provide innovation due to the public good nature of knowledge. Empirical evidence from the US and other advanced economies supports this idea. We summarize the pros and cons of different policy instruments for promoting innovation and provide a basic "toolkit" describing which policies are most effective, based on our reading of the evidence. In the short-run, R&D tax credits or direct public funding seem the most productive, but in the longer-run increasing the supply of human capital (e.g. relaxing immigration rules or expanding university STEM admissions) are likely more effective. |
| Keywords: | Innovation, R&D, intellectual property, tax, competition |
| JEL: | O31 O32 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1634&r=all |
| By: | Zoltan Csefalvay (European Commission - JRC) |
| Abstract: | Three main policy responses to the labour market challenges posed by robotisation and automation have emerged in the research literature. The first is 'taxing robots' and using this revenue to introduce a basic income that could offset the negative impacts of replacing humans by robots. The second option highlights the ownership of robots so that taking part in the new source of wealth is possible. The third focuses on strengthening the comparative advantages, the creativity, and the social intelligence of humans that robots will never be able to match. All of these policy responses are supported by economic rationales and research findings but a systematic review shows that all of them raise further questions and challenges that should be carefully investigated in order to choose the right path. This paper offers a comprehensive overview of these questions. Furthermore, in a broader sense these policy options—redistributing the benefits of technological changes, increasing accesses to the benefits and utilisation of changes, and supporting the individual and institutional adjustment to changes—are relevant to every technological transformation. Hence, the lessons that are drawn from the current discussion of policy options driven by specific technologies, robotization, and automation might serve as a precursor to potential policy responses triggered by other technologies. |
| Keywords: | robotisation, automation, policies, industrial transformation, labour market, innovation, territorial development |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:wpaper:201902&r=all |
| By: | Giovanni Dosi (Institute of Economics, Scuola Superiore Sant’Anna, Pisa); Mariacristina Piva (DISCE, Università Cattolica); Maria Enrica Virgillito (DISCE, Università Cattolica); Marco Vivarelli (DISCE, Università Cattolica - UNU-MERIT, Maastricht, The Netherlands and IZA, Bonn, Germany) |
| Abstract: | This paper addresses, both theoretically and empirically, the sectoral patterns of job creation and job destruction in order to distinguish the alternative effects of embodied vs disembodied technological change operating into a vertically connected economy. Disembodied technological change turns out to positively affect employment dynamics in the “upstream’’ sectors, while expansionary investment does so in the “downstream’’ industries. Conversely, the replacement of obsolete capital vintages tends to exert a negative impact on labour demand, although this effect turns out to be statistically less robust. |
| Keywords: | Innovation, disembodied and capital-embodied technological change, employment, job-creation, job-destruction, sectoral interdependencies |
| JEL: | O14 O31 O33 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:ctc:serie5:dipe0005&r=all |
| By: | Knoblach, Michael |
| Abstract: | The evolution of the U.S. skill premium over the past century has been characterized by a U-shaped pattern. The previous literature has attributed this observation mainly to the existence of exogenous, unexpected technological shocks or changes in institutional factors. In contrast, this paper demonstrates that a U-shaped evolution of the skill premium can also be obtained using a simple two-sector growth model that comprises both variants of skill-biased technological change (SBTC): technological change (TC) that is favorable to high-skilled labor and capital-skill complementarity (CSC). Within this framework, we derive the conditions necessary to achieve a non-monotonic evolution of relative wages and analyze the dynamics of such a case. We show that in the short run for various parameter constellations an educational, a relative substitutability, and a factor intensity effect can induce a decrease in the skill premium despite moderate growth in the relative productivity of high-skilled labor. In the long run, as the difference in labor productivity increases, the skill premium also rises. To underpin our theoretical results, we conduct a comprehensive simulation study. |
| Keywords: | Skill-Augmenting Technological Change,Capital-Skill Complementarity,Skill Premium,Neoclassical Growth Model |
| JEL: | E24 J24 J31 O33 O41 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:tudcep:0319&r=all |
| By: | Stoyanov, Andrey (York University, Canada); Zubanov, Nick (University of Konstanz) |
| Abstract: | Matched worker-firm data from Danish manufacturing reveal that 1) industries differ in within-firm worker skill dispersion, and 2) the correlation between within-firm skill dispersion and productivity is positive in industries with higher average skill dispersion. We argue that these patterns are a manifestation of technological differences across industries: firms in the "skill complementarity" industries profit from hiring workers of similar skill level, whereas firms in the "skill substitutability" industries benefit from hiring workers of different skill levels. An empirical method we devise produces a robust classification of industries into the distinct complementarity and substitutability groups. Our study unveils hitherto unnoticed technological heterogeneity between industries within the same economy, and demonstrates its importance. Specifically, we show through simulations on a simple general equilibrium model that failing to take technological heterogeneity into account results in large prediction errors. |
| Keywords: | skill dispersion, complementarity, production technology, firm productivity |
| JEL: | D24 D58 J2 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12433&r=all |
| By: | Caroline Paunov; Sandra Planes-Satorra |
| Abstract: | Digital technologies impact innovation in all sectors of the economy, including traditional ones such as agriculture, the automotive industry, and retail. Similar trends across sectors include that the Internet of Things and data are becoming key inputs for innovation, innovation cycles are accelerating, services innovation is gaining importance and collaborative innovation matters more. Sector-specific dynamics are driven by differences in opportunities such technologies offer for innovation in products, processes and business models, as well as differences in the types of data needed for innovation and the conditions for digital technology adoption. The analysis calls for revisiting innovation policy mixes to ensure these remain effective and address emerging challenges. A sectoral approach is needed when designing innovation policies in some domains, especially regarding data access and digital technology adoption policies. The current focus of innovation policies on boosting R&D to meet R&D intensity targets also requires scrutiny. |
| Date: | 2019–07–18 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:74-en&r=all |
| By: | Paola Tubaro (LRI - Laboratoire de Recherche en Informatique - UP11 - Université Paris-Sud - Paris 11 - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - CNRS - Centre National de la Recherche Scientifique, TAU - TAckling the Underspecified - LRI - Laboratoire de Recherche en Informatique - UP11 - Université Paris-Sud - Paris 11 - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - CNRS - Centre National de la Recherche Scientifique - UP11 - Université Paris-Sud - Paris 11 - Inria Saclay - Ile de France - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique, CNRS - Centre National de la Recherche Scientifique); Antonio Casilli (I3, une unité mixte de recherche CNRS (UMR 9217) - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique - X - École polytechnique - Télécom ParisTech - MINES ParisTech - École nationale supérieure des mines de Paris, Télécom ParisTech) |
| Abstract: | This paper delves into the human factors in the "back-office" of artificial intelligence and of its data-intensive algorithmic underpinnings. We show that the production of AI is a labor-intensive process, which particularly needs the little-qualified, inconspicuous and low-paid contribution of "micro-workers" who annotate, tag, label, correct and sort the data that help to train and test smart solutions. We illustrate these ideas in the high-profile case of the automotive industry, one of the largest clients of digital data-related micro-working services, notably for the development of autonomous and connected cars. This case demonstrates how micro-work has a place in long supply chains, where tech companies compete with more traditional industry players. Our analysis indicates that the need for micro-work is not a transitory, but a structural one, bound to accompany the further development of the sector; and that its provision involves workers in different geographical and linguistic areas, requiring the joint study of multiple platforms operating at both global and local levels. |
| Keywords: | Artificial intelligence,Micro-work,Automotive industry,Digital platform economy,Organization of work |
| Date: | 2019–06–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02148979&r=all |
| By: | R. Maria del Rio-Chanona; Penny Mealy; Mariano Beguerisse-D\'iaz; Francois Lafond; J. Doyne Farmer |
| Abstract: | Many existing jobs are prone to automation, but since new technologies also create new jobs it is crucial to understand job transitions. Based on empirical data we construct an occupational mobility network where nodes are occupations and edges represent the likelihood of job transitions. To study the effects of automation we develop a labour market model. At the macro level our model reproduces the Beveridge curve. At the micro level we analyze occupation-specific unemployment in response to an automation-related reallocation of labour demand. The network structure plays an important role: workers in occupations with a similar automation level often face different outcomes, both in the short term and in the long term, due to the fact that some occupations offer little opportunity for transition. Our work underscores the importance of directing retraining schemes towards workers in occupations with limited transition possibilities. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.04086&r=all |
| By: | Bernhard Schmidpeter (Universtity of Essex); Rudolf Winter-Ebmer |
| Abstract: | We provide comprehensive evidence on the consequences of automation and o shoreability on the labor market career of unemployed workers. Using almost two decades of administrative data for Austria, we find that risk of automation is reducing the job finding probability; a problem which has increased over the past years. We show that this development is associated with increasing re-employment wages and job stability. For workers in occupations at risk of being offshored we find the opposite effect. Our results imply a trade-o between quantity and quality in these jobs. Provided training is in general beneficial for workers in automation-related jobs. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:jku:econwp:2019_14&r=all |
| By: | Massimo Anelli; Gaetano Basso; Giuseppe Ippedico; Giovanni Peri |
| Abstract: | Migration outflows, especially of young people, may deprive an economy of entrepreneurial energy and innovative ideas. We exploit exogenous variation in emigration from Italian local labor markets to show that between 2008 and 2015 larger emigration flows reduced firm creation. The decline affected firms owned by young people and innovative industries. We estimate that for every 1,000 emigrants, 10 fewer young-owned firms were created over the whole period. A simple accounting exercise shows that about 60 percent of the effect is generated simply by the loss of young people; the remaining 40 percent is due to a combination of selection of emigrants among highly entrepreneurial people, negative spillovers on the entrepreneurship rate of locals, and negative local firm multiplier effect. |
| JEL: | J61 M13 O3 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26055&r=all |
| By: | Mariana Colacelli; Gee Hee Hong |
| Abstract: | Productivity growth in Japan, as in most advanced economies, has moderated. This paper finds supportive evidence for the important role of small and medium-sized enterprises (SMEs) in explaining Japan’s modest productivity growth. Results show a substantial dispersion in firm-level productivity growth across sectors and even across firms within the same sector. SMEs, on average, exhibit lower productivity growth than non-SMEs in Japan, with smaller and older SMEs showing particularly low productivity growth. Estimates suggest that boosting productivity growth in all of the worst-performing SMEs could improve overall productivity growth by up to 1.8 percentage points. The SME credit guarantee system, SME financing constraints, demographic factors, and lack of intangible capital investment are discussed as contributors to the slow productivity growth of Japan’s small and old SMEs. |
| Date: | 2019–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:19/137&r=all |
| By: | Aleksandra Kordalska (Gdansk University of Technology, Gdansk, Poland); Magdalena Olczyk (Gdansk University of Technology, Gdansk, Poland) |
| Abstract: | This study examines labour productivity performance and its determinants in Eastern European and Central Asian (EECA) firms using micro-level data. We find significant differences in labour productivity among members of the European Union in Eastern Europe and other Eastern European and Central Asian countries. We also confirm the important impact of foreign ownership, exporter status, and highly skilled workers on productivity levels. However, we reveal a non-linear relationship between firm age and their labour productivity. Additionally, significant differences in labour productivity determinants between the services and manufacturing are found. The productivity of service firms, unlike manufacturing firms, is much more sensitive to changes in productivity factors. |
| Keywords: | Eastern Europe and Central Asia, firm-level analysis, labour productivity |
| JEL: | C21 J24 O52 O53 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:gdk:wpaper:55&r=all |