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on Technology and Industrial Dynamics |
| By: | Philippe Aghion (Collège de France and London School of Economics); Céline Antonin (Sciences Po-OFCE); Simon Bunel (INSEE and Paris School of Economics); Xavier Jaravel (London School of Economics) |
| Abstract: | We use comprehensive micro data in the French manufacturing sector between 1994 and 2015 to document the effects of automation technologies on employment, wages, prices and profits. Causal effects are estimated with event studies and a shift-share IV design leveraging pre-determined supply linkages and productivity shocks across foreign suppliers of industrial equipment. At all levels of analysis — plant, firm, and industry — the estimated impact of automation on employment is positive, even for unskilled industrial workers. We also find that automation leads to higher profits, lower consumer prices, and higher sales. The estimated elasticity of employment to automation is 0.28, compared with elasticities of 0.78 for profits, -0.05 for prices, and 0.37 for sales. Consistent with the importance of business-stealing across countries, the industry-level employment response to automation is positive and significant only in industries that face international competition. These estimates can be accounted for in a simple monopolistic competition model: firms that automate more increase their profits but pass through some of the productivity gains to consumers, inducing higher scale and higher employment. The results indicate that automation can increase labor demand and can generate productivity gains that are broadly shared across workers, consumers and firm owners. In a globalized world, attempts to curb domestic automation in order to protect domestic employment may be self-defeating due to foreign competition. |
| Keywords: | Automation, employment, plant-level, firm-level, labor market, product market, manufacturing, France. |
| JEL: | J23 J24 L11 O3 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:fce:doctra:2001&r=all |
| By: | Erhan Artuc; Paulo Bastos; Bob Rijkers |
| Abstract: | This paper examines the effects of robotization on trade patterns, wages and welfare. It developsa Ricardian model with two-stage production and trade in intermediate and final goods in which robots can take over some tasks previously performed by humans in a subset of industries. An increase in robot adoption in the North reduces the cost of production and thereby impacts trade in final and intermediate goods with the South. The empirical analysis uses ordinary least squaresand instrumental-variable regressions exploiting variation in exposure to robots across countriesand sectors. Both reveal that greater robot intensity in own production leads to: (i) a rise inimports sourced from less developed countries in the same industry; and (ii) an even stronger increase in exports to those countries. Counterfactual simulations indicate that Northern roboti-zation raises domestic welfare, but initially depresses wages. However, this adverse effect is likely to be reversed by further reductions in robot prices. Northern robotization may lead to higherwages and welfare in the South. |
| Keywords: | Automation, robots, tasks, jobs, wages, trade, intermediate inputs, global valuechains, gains from trade |
| JEL: | F1 J23 J24 O3 O4 |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp01182020&r=all |
| By: | Sofia Samoili (European Commission - JRC); Riccardo Righi (European Commission - JRC); Melisande Cardona (European Commission - JRC); Montserrat Lopez-Cobo (European Commission - JRC); Miguel Vazquez-Prada Baillet (European Commission - JRC); Giuditta De-Prato (European Commission - JRC) |
| Abstract: | This report analyses and compares countries and regions in the evolving international industrial and research landscape of Artificial Intelligence (AI). The evidence presented is based on a unique database covering the years 2009-2018. The database has been specifically built from a multitude of sources to provide scientific evidence and monitor the AI landscape worldwide. Companies, universities, research institutes and governmental authorities with an active role in AI are identified and analysed in an aggregated fashion. The report presents a wide variety of indicators, allowing us to expand our knowledge on issues such as: the size of the AI ecosystem globally and at country level; which are the main global competitors of the EU; what is the level of industrial involvement per country; what are the firms’ demographics, profiling of economic agents according to their strengths in innovation and take-up of AI, including their patenting performance; and the degree of internal and external collaborations between EU and non-EU firms and research institutions. The analysis of the AI activities developed by agents in the studied territories provides interesting insights on their areas of specialisation, highlighting the strengths of the EU and its Member States in the global landscape. Each section offers a focus on EU Member States. |
| Keywords: | artificial intelligence, techno-economic analysis, digital transformation, AI landscape, AI thematic area, network of collaborations, AI industry |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc120106&r=all |
| By: | Konan Alain N'ghauran (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique); Corinne Autant-Bernard (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Despite the growing body of literature evaluating cluster policies, it still remains difficult to establish conclusively their structural effects on regional innovation networks. Focusing on the French cluster policy during the period 2005-2010, this study aims at evaluating how cluster policies influence the structure of local innovation networks following network topologies that may be beneficial for regional innovation. Based on a panel data of four periods and 94 NUTS3 French regions, we estimate spatial Durbin models, allowing us to identify direct, indirect and total effects of cluster policies. The results suggest that cluster policies can result in both positive and negative total effects on the structure of local innovation networks depending on regions' technological specialisation. Beyond the heterogeneous effects, the results also highlight that cluster policies may lead to a regional competition for the strengthening of innovation networks. This finding echoed previous research pointing out the possible 'beggar-thy-neighbour' effects of cluster policies. |
| Keywords: | Cluster,Regional innovation,Innovation network,Policy evaluation |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-02482565&r=all |
| By: | Toshihiro Okubo (Faculty of Economics, Keio University); Eric Strobl (Department of Economics, Bern University) |
| Abstract: | This paper investigates the damage impact of the 1959 Ise Bay Typhoon-the most destructive storm in Japanese history-on firm performance in Nagoya City. To this end, we combine firm-level data with a locally derived damage index measured in terms of the duration of storm surge-induced flooding. We find heterogeneous impacts of flood damage across firms and sectors. More specifically, older manufacturing firms tend to survive and, conditional on survival, longer time inundation moderated their employment and sales growth, but also promoted capital growth, suggesting investment in new machinery and facilities. In contrast, employment growth increased in the construction sector to satisfy the construction demand for rebuilding after the supertyphoon. |
| Keywords: | Typhoon, Flood, Firm survival, Firm growth, Nagoya city |
| JEL: | Q54 R10 R12 R14 D22 L25 |
| Date: | 2020–02–25 |
| URL: | http://d.repec.org/n?u=RePEc:keo:dpaper:2020-005&r=all |
| By: | Blandinieres, Florence; Steinbrenner, Daniela; Weiß, Bernd |
| Abstract: | A growing interest in R&D tax incentives as a way to sustain research and innovation efforts has given rise to a large number of evaluations. The absence of consensus in the literature about their impact on R&D is intertwined with the variety of underpinning R&D tax incentives designs. Our meta-analysis aims at explaining this heterogeneity by the designs characteristics of R&D tax incentives. We find that the type of design has a distinct impact on R&D demand in the short run. We argue that these distinct effects are the results of managing a trade-off between providing strong incentives for R&D and simplicity to claim R&D deduction. In this respect, incremental and volume-based designs find a balance between both dimensions while hybrid designs lack clarity and predictability in the short run. Their respective effect can be moderated by additional features (i.e. generosity, targeting rules) even if the latter increases complexity and decreases predictability. We conclude by highlighting the importance of having a stable, clear, and simple framework to enhance the effect of R&D tax incentives. |
| Keywords: | meta-analysis,research and innovation policies,tax incentives |
| JEL: | O32 H25 O38 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:20010&r=all |
| By: | Fackler, Daniel; Hölscher, Lisa; Schnabel, Claus; Weyh, Antje |
| Abstract: | Using representative linked employer-employee data for Germany, this paper analyzes short- and long-run differences in labor market performance of workers joining start-ups instead of incumbent firms. Applying entropy balancing and following individuals over ten years, we find huge and long-lasting drawbacks from entering a start-up in terms of wages, yearly income, and (un)employment. These disadvantages hold for all groups of workers and types of start-ups analyzed. Although our analysis of different subsequent career paths highlights important heterogeneities, it does not reveal any strategy through which workers joining start-ups can catch up with the income of similar workers entering incumbent firms. |
| Keywords: | startups,young firms,wages,linked employer-employee data |
| JEL: | J31 J63 L26 M51 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwqwdp:032020&r=all |
| By: | Patricia Jiménez Martínez (Comisión Nacional de los Mercados y la Competencia); Juan A. Máñez Castillejo (Universitat de València and ERICES); María E. Rochina Barrachina (Universitat de València and ERICES); Juan A. Sanchis Llopis (Universitat de València and ERICES) |
| Abstract: | This paper assesses the e ciency in resource allocation across rms within industries in Spain since early 90's until 2013. A static and a dynamic decomposition of total factor productivity are performed in order to study the degree of misallocation in each manufacturing sector and its evolution over time. We nd that within industries allocative e ciency increased moderately and productivity grew slightly (almost stagnated) from 1992 to 2007. The great crisis was characterized by a sharp drop in productivity and a general rise in within industry misallocation of resources (but it seems that only capital misallocation worsened, while employment misallocation diminished). From 2011 to 2013, productivity and allocative e ciency started to recover, but the productivity levels previous to the crisis were still not achieved at the end of the period. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:eec:wpaper:1919&r=all |
| By: | Olivera Kostoska; Viktor Stojkoski; Ljupco Kocarev |
| Abstract: | The expansion of global production networks has raised many important questions about the interdependence among countries and how future changes in the world economy are likely to affect the countries' positioning in global value chains. We are approaching the structure and lengths of value chains from a completely different perspective than has been available so far. By assigning a random endogenous variable to a network linkage representing the number of intermediate sales/purchases before absorption (final use or value added), the discrete-time absorbing Markov chains proposed here shed new light on the world input/output networks. The variance of this variable can help assess the risk when shaping the chain length and optimize the level of production. Contrary to what might be expected simply on the basis of comparative advantage, the results reveal that both the input and output chains exhibit the same quasi-stationary product distribution. Put differently, the expected proportion of time spent in a state before absorption is invariant to changes of the network type. Finally, the several global metrics proposed here, including the probability distribution of global value added/final output, provide guidance for policy makers when estimating the resilience of world trading system and forecasting the macroeconomic developments. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.05204&r=all |
| By: | John C. Haltiwanger; James R. Spletzer |
| Abstract: | We find that most of the rising between firm earnings inequality that dominates the overall increase in inequality in the U.S. is accounted for by industry effects. These industry effects stem from rising inter-industry earnings differentials and not from changing distribution of employment across industries. We also find the rising inter-industry earnings differentials are almost completely accounted for by occupation effects. These results link together the key findings from separate components of the recent literature: one focuses on firm effects and the other on occupation effects. The link via industry effects challenges conventional wisdom. |
| JEL: | E24 J24 J31 L22 |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26786&r=all |
| By: | Sophie Osotimehin (University of Quebec at Montreal); Latchezar Popov (Texas Tech University) |
| Abstract: | We analytically characterize the aggregate productivity loss from allocative distortions in a setting that accounts for the sectoral linkages of production. We show that the effects of distortions and the role of sectoral linkages depend crucially on how substitutable inputs are. We find that the productivity loss is smaller if input substitutability is low. Moreover, with low input substitutability, sectoral linkages do not systematically amplify the effects of distortions. In addition, the impact of the sectors that supply intermediate inputs becomes smaller. We quantify these effects in the context of the distortions caused by market power, using industry-level data for 35 countries. With our benchmark calibration, which accounts for low input substitutability, the median aggregate productivity loss from industry-level markups is 1.3%. To assume instead unit elasticities of substitution (i.e., to use a Cobb-Douglas production function) would lead to overestimating the productivity loss by a factor of 1.8. Sectoral linkages do amplify the cost of markups, but the amplification factor is considerably weaker than with unit elasticities. |
| Keywords: | Aggregate productivity; Input-output; Production network; Misallocation; CES production function; Market power |
| JEL: | D57 D61 O41 O47 |
| Date: | 2020–02–18 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedmoi:87579&r=all |
| By: | Hiromitsu Goto; Wataru Souma; Mari Jibu; Yuichi Ikeda |
| Abstract: | Generally, open innovation is a lucrative research topic within industries relying on innovation, such as the pharmaceutical industry, which are also known as knowledge-intensive industries. However, the dynamics of drug pipelines within a small-medium enterprise level in the global economy remains concerning. To reveal the actual situation of pharmaceutical innovation, we investigate the feature of knowledge flows between the licensor and licensee in the drug pipeline based on a multilayer network constructed with the drug pipeline, global supply chain, and ownership data. Thus, our results demonstrate proven similarities between the knowledge flows in the drug pipeline among the supply chains, which generally agrees with the situation of pharmaceutical innovation collaborated with other industries, such as the artificial intelligence industry. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.04620&r=all |