|
on Technology and Industrial Dynamics |
| By: | Dosi, Giovanni (Sant'Anna School of Advanced Studies); Piva, Mariacristina (Università Cattolica del Sacro Cuore); Virgillito, Maria Enrica (Università Cattolica del Sacro Cuore); Vivarelli, Marco (Università Cattolica del Sacro Cuore) |
| 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:iza:izadps:dp12408&r=all |
| By: | Giacomo Domini; Marco Grazzi; Daniele Moschella; Tania Treibich |
| Abstract: | This paper investigates how investment in automation-intensive goods impacts on worker flows at the firm level and, within firms, across occupational categories. Resorting to an integrated dataset encompassing detailed information on firms, their imports, and employer-employee data for French manufacturing employers over 2002-2015, we identify 'automation spikes' using imports of intermediates embedding automation technologies and then test their impact on employment dynamics. We find that automation spikes are positively correlated with preceding and contemporaneous growth in employment, mainly due to lower separation rates of investing firms. These differential patterns of net and gross worker flows do not appear to change significantly across different types of workers (occupational categories, 'techies', routine-intensive vs. non routine-intensive jobs). |
| Keywords: | Automation; Skills; Technological Change; Gross Worker Flows.. |
| Date: | 2019–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2019/22&r=all |
| By: | Ljubica Nedelkoska; Frank Neffke |
| Abstract: | The notion of skills plays an increasingly important role in a variety of research fields. Since the foundational work on human capital theory, economists have approached skills through the lens of education, training and work experience, whereas early work in evolutionary economics and management stressed the analogy between skills of individuals and the organizational routines of firms. We survey how the concept of skills has evolved into notions such as skills mismatch, skill transferability and skill distance or skill relatedness in labor economics, management, and evolutionary approaches to economics and economic geography. We find that these disciplines converged in embracing increasingly sophisticated approaches to measuring skills. Economists have expanded their approach from quantifying skills in terms of years of education to measuring them more directly, using skill tests, self-reported skills and job tasks, or skills and job tasks reported by occupational experts. Others have turned to administrative and other large-scale data sets to infer skill similarities and complementarities from the careers of sometimes millions of workers. Finally, a growing literature on team human capital and skill complementarities has started thinking of skills as features of collectives, instead of only of individuals. At the same time, scholars in corporate strategy have studied the micro-determinants of team formation. Combined, the developments in both strands of research may pave the way to an understanding of how individual-level skills connect to firm-level routines. |
| Keywords: | Human capital, skills and tasks, skill relatedness, skill mismatch, skill transferability |
| JEL: | J24 J62 P25 L16 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1921&r=all |
| By: | Alejandro Micco |
| Abstract: | Digital technologies, robotics, and artificial intelligence substitute tasks performed by labor are bringing back old fears about the impact of technology on labor markets and international trade. The aim of this paper is to provide evidence about the causal effect of automation on the labor market and sectoral US imports. We use robots per workers, instrumented by robot penetration in Europe, to study employment in almost 800 occupations in 285 industries in the US during 2002-2016. We use Autor et al (2003) and Frey and Osborne (2017) methodologies to define occupations at risk of automation and to study their behavior after robots´ penetration. We find that employment in occupations at risk has been declining at an annual rate of 2.0-2.5%, relative to other occupations. This result is mainly driven by a substitution effect within industries defined at the 4-digit NAICS level. One standard deviation increase in robots per worker reduces employment growth by 1.25-1.45% in occupations at risk compared to the other professions in the same sector. Industries with a higher share of occupation at risk have a lower rate of employment growth during the period 2002-2016. Also, imports of commodities produced by these sectors have been falling, in particular from countries with lower penetration of automation technologies. This result suggests that automation is changing countries´ comparative advantage. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:udc:wpaper:wp486&r=all |
| By: | Matteo Deleidi; Mariana Mazzucato |
| Abstract: | The paper investigates the determinants of economic growth from both a theoretical and an empirical perspective. The paper combines the Sraffian supermultiplier model of growth with the Neo-Schumpeterian framework that emphasizes the entrepreneurial role of the state. We aim to detect the macroeconomic effect generated by alternative fiscal policies: generic ones and “mission-oriented” ones. Using a SVAR model for the US economy for the 1947–2018 period, we show that mission-oriented policies produce a larger positive effect on GDP (fiscal multiplier) and on private investment in R&D (crowd-in effect) than the effect produced by generic public expenditures. |
| Keywords: | Mission-oriented innovation policies, Sraffian supermultiplier, SVAR, fiscal multiplier, crowding-in effect. |
| JEL: | C32 E22 E62 O25 O30 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:rtr:wpaper:0248&r=all |
| By: | Artur Santoalha; Ron Boschma |
| Abstract: | Regional diversification is a process characterized by past and place dependence: new activities tend to emerge and develop in a region in technological or industrial fields closely related to existing local activities. Recently, the relatedness concept has also been applied successfully to studies on green diversification of regions, providing new insights to the transition literature that is primarily focused on disruptive change. What has received little attention is a systematic approach that assesses the role of political support for the ability of regions to diversify into new green activities. This paper makes a first attempt to test the impact of regional capabilities and political support for environmental policy at the national and regional scale on the ability of 95 regions in 7 European countries to diversify into new green technologies during the period 2000-2012. We find evidence that related capabilities rather than political support in a region is associated with green diversification of regions in Europe. However, political support tends to moderate the role of regional capabilities. |
| Keywords: | green technologies, regional diversification, sustainability transition, political support, relatedness |
| JEL: | O18 O44 Q55 R11 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1922&r=all |
| By: | Kounetas, Konstantinos; Stergiou, Eirini |
| Abstract: | European policies regarding global warming have been outspread the last few decades with many initiatives for industrial production process. In this paper we model eco-efficiency performance under a meta-frontier framework for 14 industries from the manufacturing sector from 27 European countries over the 1995-2011 period. The utilization of NOx, SOx, CO2, CH4, N2O, CO, NMVOC and NH3 as undesirable outputs and GVA as the desirable represent the impact of of economic activities on the environment. In the first stage, we estimate eco-efficiency using the conventional Directional Distance Function (DDF) as well as the non-radial DDF approach. In the second stage of analysis, we investigate the existence of conditional and unconditional convergence according to several methodologies. Our eco-efficiency estimates provide a distinct behavior for energy intensive European industries. Moreover, a decline occurs for the majority of them. In addition, our results using distributional dynamics approach and the recent approach of Philips and Sul (2007) supports the non-convergence hypothesis and the creation of distinct clubs. Finally, the establishment of a catch up index indicate an increase in a speed of convergence. |
| Keywords: | Eco-efficiency,Non-parametric frontier analysis, Convergence, Technological heterogeneity,European Industries. |
| JEL: | C22 C44 D2 D24 Q4 Q40 Q52 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94286&r=all |
| By: | Maïder SAINT-JEAN; Nabila ARFAOUI; Eric BROUILLAT; David VIRAPIN |
| Abstract: | This article investigates the technological knowledge pattern underlying the recent evolution in ocean energy technology (OET) trajectories, especially tidal and wave energy, ocean thermal energy, salinity gradient energy and offshore wind energy. Examination of the relational properties among the knowledge elements in the OET knowledge base, in particular, their substitutability and complementarity, allows a better understanding of the coherence of this knowledge base and the technological trajectories within the sector. We use patent data extracted from the Questel ORBIT database. The various technical options related to OETs are identified by Cooperative Patent Classification (CPC) codes and enable the construction of a dataset of OET patents granted between 2000 and 2015. We analyze the main trends emerging from the patent statistics and we construct a network of citations among OET patents and apply to it a main path algorithm. This allows a mapping of all possible streams of cumulative growth of technological knowledge and identification of the most important ones. We show that the knowledge base of OETs is split into two main families and technology patterns depending on whether the harnessing of ocean power and its conversion to renewable low-carbon electricity derive from physical or chemical science. OET trajectories are somewhat compartmentalized with few connections amongst them; however, there are links between some pivotal tidal and wave energy and offshore wind energy patents which have become the foundations to an OET knowledge base. By focusing specifically on the physics-based family of OETs, we can investigate the structural aspects of this knowledge base and analyze the aggregate level of complementarity and substitutability of its knowledge constituent. Our analysis partly confirms the increased coherence of the OET knowledge base over time but also highlights its fluctuating nature which in some ways mirrors the intermittent nature of ocean energy funding, further slowing consensus over designs which is key to commercialization. |
| Keywords: | Ocean energy technology, citation network analysis, knowledge base, complementarity, substitutability, dominant design |
| JEL: | O33 Q42 Q55 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:grt:wpegrt:2019-09&r=all |
| By: | Martina Bisello (Eurofound); Eleonora Peruffo (Eurofound); Enrique Fernandez-Macías (European Commission - JRC); Riccardo Rinaldi (University of Siena) |
| Abstract: | This paper investigates changes in the task content, methods and tools of European jobs from 1995 to 2015. Drawing on the taxonomy of tasks proposed by Bisello and Fernández-Macías (2016), this work tries to better understand whether changes in the average intensity of tasks performance are the result of changes in the shares of employment across jobs, or changes in the task content within-jobs, or both. The main findings from a combined analysis of the European Working Conditions Survey (EWCS) and European Jobs monitor data (EJM) suggest that jobs with more social task content expanded relative to the rest, but this is in contrast with a decline in the amount of social tasks people actually do in those (and other) jobs over the same period. A similar contradictory trend can be observed in terms of routine tasks, with compositional and intrinsic changes going in opposite directions: an actual increase in the total levels of routine at work is recorded, notwithstanding marginal compositional declines. The implications of these findings in the context of the current debate on the impact of technological change on employment are discussed. |
| Keywords: | Tasks, Technical Change, Structural Change, Labour Markets, Europe, Occupations |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:laedte:201902&r=all |
| By: | Tom Broekel |
| Abstract: | The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies? size, technologies scoring high on structural diversity are also shown to concentrate in space. |
| Keywords: | Complexity, technology, patents, technological complexity, network, diversity |
| JEL: | O11 O31 N70 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1918&r=all |
| By: | Bolhuis, Marijn |
| Abstract: | Developing economies tend to export more skill-intensive products as they become more productive. This paper provides a new tractable, quantitative framework to examine the role of inter-industry productivity spillovers in this development process. I start by documenting that a country’s comparative advantage tends to increase in industries that employ occupations that are used most intensively in current exports. In the model, productivity growth is driven by occupation-specific dynamic scale economies, which generate productivity spillovers between occupationally similar sectors. By exploiting cross-sector heterogeneity in foreign demand shocks, I find that dynamic scale economies are substantial in high-skilled production but negligible in low-skilled production. As a result, inter-industry productivity spillovers are larger in richer countries, and access to foreign markets allows developing countries to shift labor into sectors that contribute more to aggregate productivity growth. The model can account for a substantial share of the variation in aggregate and industry-level labor productivity growth across developing economies. Counterfactual exercises suggest that inter-industry spillovers play a quantitatively substantial role in accounting for slow cross-country convergence. Moreover, spillovers increase the gains from trade, especially in developing economies with a comparative advantage in manufacturing. |
| Keywords: | Productivity; Convergence; Spillovers; Dynamic scale economies; Comparative advantage; Exports |
| JEL: | F1 F4 O1 O3 O4 |
| Date: | 2019–06–16 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94730&r=all |
| By: | Severgnini, Battista (Department of Economics, Copenhagen Business School); Boerner, Lars |
| Abstract: | This paper studies the impact of the early adoption of one of the most important high-technology machines in history, the public mechanical clock, on long-run growth in Europe. We avoid endogeneity by considering the relationship between the adoption of clocks with an instrument based on the appearance of repeated solar eclipses. This is motivated by the predecessor technologies of mechanical clocks, astronomic instruments that measured the course of heavenly bodies. We find a significant increase in growth rates between 1500 and 1700 in the range of 30 percentage points in early adopter cities and areas. Finally, additional quantitative analysis suggests a positive relationship between mechanical clocks and contemporary long-term orientation nowadays. |
| Keywords: | technological adoption; cities; mechanical clocks; information technology; long-term orientation |
| JEL: | N13 N93 O33 |
| Date: | 2019–03–28 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cbsnow:2019_004&r=all |