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on Technology and Industrial Dynamics |
| By: | Gupta, Apoorva; Stiebale, Joel |
| Abstract: | We study the effect of stronger patent protection on innovation activities of firms and firm-product level markups. Relying on cross-industry differences in the use of patents, we exploit firm-level variation in exposure to India's patent reform. For firms more exposed to stronger patent protection, we find an increase in patenting and R&D expenditure post-reform. Additionally, we estimate an increase in firm-product level markups after the reform, driven primarily by lower marginal costs rather than higher prices. Our results indicate that process innovations and output expansion contributed to these cost-savings, and incomplete pass-through accounts for a substantial part of rising markups. |
| Keywords: | Intellectual property rights, patent protection, innovation, R&D, markups, patents |
| JEL: | L10 O30 O31 O00 D22 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:dicedp:295746&r= |
| By: | Federico Moscatelli; Christian Chacua; Shreyas Gadgin Matha; Matte Hartog; Eduardo Hernandez Rodriguez; Julio Raffo; Muhammed A. Yildirim |
| Abstract: | Recent years have witnessed a resurgence of industrial policies globally. Through various industrial policy instruments, governments make critical scientific and technological choices that shape innovation paths and resource allocations. Our paper explores innovation capabilities as essential drivers of competitive outcomes, spanning science, technology, and production domains. Based on the economic complexity literature, we propose a methodological framework to measure the innovation capabilities empirically, leveraging data on scientific publications, patents, and trade. Our findings highlight the multidimensional nature of innovation capabilities and underscore the importance of understanding both the specialization and quality of these capabilities. Our results are in line with the complexity literature, as we also find: (i) positive correlations between the innovation complexity and economic growth; and, (ii) the predictive power of existing innovation capabilities for fostering new ones. Based on these findings, we propose novel indicators informing innovation policymaking on the innovation potential across science, technology, and production fields of an ecosystem. We suggest that innovation policymaking needs to be informed by deeper insights into innovation capabilities that are crucial for long-term growth and competitiveness improvement. |
| Keywords: | Innovation capabilities, Complexity metrics, Innovation ecosystems, Science and technology policy, Industrial policy, Economic development, Smart specialization |
| JEL: | O25 O31 O33 O30 O11 O14 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:81&r= |
| By: | Antea Barišić; Mahdi Ghodsi (The Vienna Institute for International Economic Studies, wiiw); Michael Landesmann (The Vienna Institute for International Economic Studies, wiiw); Alireza Sabouniha (The Vienna Institute for International Economic Studies, wiiw); Robert Stehrer (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | In this note, we study the relationship between the use of new technologies (e.g. robots and various ICT assets), labour demand and migration patterns. The adoption of new technologies might change the demand for labour in various ways, which in turn will have an impact on skill composition and wage levels of different types of workers. We report the main results from a study that first analyses the impact of robot adoption on wages by sector and skills. Second, we study the impact of robot adoption in manufacturing industries on the attraction of migrants while controlling for other factors in the labour demand function. This is followed by an analysis of push and pull factors of bilateral migration that focuses on the impact of relative automation gaps across countries. Finally, using the OeNB Euro Survey, we examine determinants of the intention to migrate and the role of income differentials between the countries of origin and destination. |
| Keywords: | Migration, migrant jobs, wages, employment, novel technologies, adoption of robots, digitalisation, European labour markets, Central Eastern European countries |
| JEL: | F22 F66 J61 J24 J20 O33 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:wii:pnotes:pn:77&r= |
| By: | Ricardo Hausmann; Muhammed A. Yildirim; Christian Chacua; Matte Hartog; Shreyas Gadgin Matha |
| Abstract: | Recent geopolitical challenges have revived the implementation of industrial and innovation policies. Ongoing discussions focus on supporting cutting-edge industries and strategic technologies but hardly pay attention to their impact on economic growth. In light of this, we discuss the design of innovation policies to address current development challenges while considering the complex nature of productive activities. Our approach conceives economic development and technological progress as a process of accumulation and diversification of knowledge. This process is limited by the tacit nature of knowledge and by countries' binding constraints to growth. Consequently, effective innovation policies should be place-based and multidimensional, leveraging countries' existing capabilities and addressing countries’ current problems. This contrasts policies that lead to economic efficiencies, such as copying other countries' solutions to problems that countries do not currently have. |
| Keywords: | Innovation policy, Industrial policy, Economic complexity, Know-how |
| JEL: | O25 O30 O38 F60 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:79&r= |
| By: | Ricardo Hausmann; Muhammed A. Yildirim; Christian Chacua; Matte Hartog; Shreyas Gadgin Matha |
| Abstract: | Technological know-how in a country shapes its growth potential and competitiveness. Scientific publications, patents, and international trade data offer complementary insights into how ideas from science, technology, and production evolve, combine, and are transformed into capabilities. Analyzing their trajectories enables a more comprehensive and multifaceted understanding of the whole innovation process, from generating ideas to internationally commercializing products. We analyze the production patterns in these three domains, documenting the differences between advanced and emerging market economies. We find that future income, patenting, and publishing growth correlate with the economic complexity indices calculated from these domains. Capabilities embedded in the country also shape future diversification opportunities and make the innovation process path dependent. Lastly, we also show that diversification opportunities can be inferred across innovation domains. |
| Keywords: | Economic complexity, Innovation complexity, Scientific complexity |
| JEL: | O25 O30 O38 F60 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:80&r= |
| By: | Milad Abbasiharofteh; Tom Broekel; Lars Mewes; |
| Abstract: | This paper examines how geographical proximity affected interregional co-patenting links in various technologies in the USA from 1836 to 2010. We classify technologies by their complexity and test whether that moderates the impact of distance on collaboration. Contrary to the ‘death of distance’ hypothesis, distance still matters for knowledge creation and exchange. Moreover, we show that the role of complexity has changed over time. However, this pattern reversed by the late 20th century, with collaborations in complex technologies becoming more resilient to distance than those in simpler technologies. However, this pattern reversed by the late 20th century, with collaborations in complex technologies becoming more resilient to distance than those in simpler technologies. |
| Keywords: | network evolution, interregional collaboration, geographical proximity, technological complexity |
| JEL: | O33 R12 N70 L14 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2414&r= |
| By: | Pierluigi Angelino; Dirk Czarnitzki; Astrid Volckaert |
| Abstract: | The Flemish government launched its Spearhead Cluster (SHC) policy in 2017. The aim is to boost strategic sectors by setting up cluster initiatives which coordinate collaborative R&D initiatives. In this paper, we analyze whether becoming a member of such a cluster initiative has an impact on the Total Factor Productivity (TFP) of the firm. We exploit firm-level data between 2013 and 2020 to estimate TFP and apply a difference-in-differences approach to assess the programs’ treatment effects. We find that becoming a member of a cluster has an average positive impact on firmlevel TFP of between 1 to 4.4 percent, depending on the econometric specification. These results are the first to provide an insight into the impact of the Flemish SHC policy on productivity. |
| Keywords: | cluster associations, cluster policy, innovation policy, total factor productivity, conditional difference-in-difference |
| Date: | 2024–05–22 |
| URL: | http://d.repec.org/n?u=RePEc:ete:msiper:741800&r= |
| By: | Christian Peukert; Florian Abeillon; Jérémie Haese; Franziska Kaiser; Alexander Staub |
| Abstract: | Human-created works represent critical data inputs to artificial intelligence (AI). Strategic behaviour can play a major role for AI training datasets, be it in limiting access to existing works or in deciding which types of new works to create or whether to create new works at all. We examine creators’ behavioral change when their works become training data for AI. Specifically, we focus on contributors on Unsplash, a popular stock image platform with about 6 million high-quality photos and illustrations. In the summer of 2020, Unsplash launched an AI research program by releasing a dataset of 25, 000 images for commercial use. We study contributors’ reactions, comparing contributors whose works were included in this dataset to contributors whose works were not included. Our results suggest that treated contributors left the platform at a higher-than-usual rate and substantially slowed down the rate of new uploads. Professional and more successful photographers react stronger than amateurs and less successful photographers. We also show that affected users changed the variety and novelty of contributions to the platform, with long-run implications for the stock of works potentially available for AI training. Taken together, our findings highlight the trade-off between interests of rightsholders and promoting innovation at the technological frontier. We discuss implications for copyright and AI policy. |
| Keywords: | generative artificial intelligence, training data, licensing, copyright, natural experiment |
| JEL: | K11 L82 L86 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_11099&r= |
| By: | d'Andria, Diego |
| Abstract: | We study the relationship between tax progressivity and the size of the R&D workforce, using a panel of European countries in 2000-2019. We review the theoretical literature which provides opposing predictions about such a relationship. We then demonstrate that such relationship exists as a "within" effect, it is negative, meaning that a larger tax progressivity is associated with smaller shares of employment in R&D activities, and it remains statistically significant after performing a number of robustness tests. Differently to previous studies based on patenting inventors, we find no effect due to top tax rates on the size of R&D employment. |
| Keywords: | Tax progressivity; R&D; Labour force structure |
| JEL: | H24 J21 J24 O3 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120937&r= |
| By: | Pierre Azoulay; Joshua L. Krieger; Abhishek Nagaraj |
| Abstract: | Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated by their innovations—and complementary assets—whether effective entry requires access to specialized infrastructure and capabilities to which incumbent firms can ration access. While the rapid improvements in AI foundation models promise transformative impacts across broad sectors of the economy, we argue that tight control over complementary assets will likely result in a concentrated market structure, as in past episodes of technological upheaval. We suggest the likely paths through which incumbent firms may restrict entry, confining newcomers to subordinate roles and stifling broad sectoral innovation. We conclude with speculations regarding how this oligopolistic future might be averted. Policy interventions aimed at fractionalizing or facilitating shared access to complementary assets might help preserve competition and incentives for extending the generative AI frontier. Ironically, the best hopes for a vibrant open source AI ecosystem might rest on the presence of a “rogue” technology giant, who might choose openness and engagement with smaller firms as a strategic weapon wielded against other incumbents. |
| JEL: | L17 L86 O32 O38 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32474&r= |
| By: | Khezri, Mohsen; Mamkhezri, Jamal; Heshmati, Almas |
| Abstract: | Purpose: This study endeavors to elucidate the divergent conclusions encountered in empirical research regarding the interplay of Economic Growth (EG) and Energy Consumption (EC). Design/methodology/approach: For this purpose, we employ the Panel Smooth Threshold Regression (PSTR) model to intricately examine the non-linear impacts of independent variables on EC and EG within a dataset encompassing 46 countries over the period from 1996 to 2021. Findings: The outcomes of our investigation can be summarized as follows: First, the findings underscore the positive impact of the logarithm of net capital formation on EG. This impact is particularly pronounced at low levels of Research and Development (R&D), gradually waning beyond a certain threshold. Second, the ratio of capital to labor exhibits a negative influence on EC at lower R&D levels. Notably, these detrimental impacts become more pronounced as R&D levels increase. Third, trade openness contributes positively to EG, particularly evident at low R&D levels. However, with increasing R&D levels, the incremental benefits from trade diminish. Finally, our findings lend support to the feedback hypothesis. Nevertheless, the impact of R&D expenditures in countries moderates these positive effects. Practical implications: Policymakers should strategically balance resource allocation between capital formation and research endeavors, considering diminishing returns at elevated levels of R&D spending, to ensure sustained EG. |
| Keywords: | economic growth (EG); energy consumption (EC); panel smooth threshold regression (PSTR) model; R&D spending |
| JEL: | F43 O32 O40 O47 Q41 |
| Date: | 2024–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:122698&r= |
| By: | Eliasson, Kent (Swedish Agency for Growth Policy Analysis); Hansson, Pär (Swedish Agency for Growth Policy Analysis); Lindvert, Markus (Swedish Agency for Growth Policy Analysis) |
| Abstract: | In the paper, we break down business sector R&D at an appropriate regional level (functional analysis regions, FA-regions) in Sweden. We describe the variation and development at the regional level. In an econometric analysis, we examine what affects the location and size of enterprise groups’ R&D activities in different FA-regions. We find that enterprise groups concentrate their R&D to the same regions, which are also regions with significant academic R&D (external agglomeration). Moreover, colocation of R&D and manufacturing within an enterprise group in a region (internal agglomeration) appears to be a significant location factor. Last but not least, the local availability of qualified R&D labor is another important localization factor for business sector R&D. Finally, when we compare the results from the econometric analysis with what enterprise groups themselves states as important motives for location, we find that they match quite well. |
| Keywords: | business sector R&D; regional location; external agglomeration; colocation of R&D and production; abundance of qualified labor |
| JEL: | J24 O32 R11 R12 |
| Date: | 2024–05–28 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:oruesi:2024_004&r= |
| By: | Alexander Cuntz; Frank Mueller-Langer; Alessio Muscarnera; Prince C. Oguguo; Marc Scheufen |
| Abstract: | TWe examine the implications of lowering barriers to online access to scientific publications for science and innovation in developing countries. We investigate whether and how free or low-cost access to scientific publications through the UN-led Research For Life (R4L) initiative leads to more scientific publications and clinical trials of authors affiliated with research institutions in developing countries. We find that free or reduced-fee access to the health science literature through Hinari (WHO-led subprogramme) increases the scientific publication output and clinical trials output of institutions in developing countries. In contrast, once we control for selection bias, we do not find empirical support for a positive Hinari effect on knowledge spillovers and local institutions’ research input into global patenting, as measured by paper citations in patent documents. Main findings can be generalized to other R4L subprogrammes and are likely to also apply to the WIPO-led Access to Research for Development and Innovation (ARDI) programme. |
| Keywords: | Scientific publications, Science, Innovation |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:78&r= |
| By: | Leone, Fabrizio |
| Abstract: | The diffusion of automation technology raises questions about the future of work, leading to calls for regulation. The ongoing discussions center on the decisions of technology adopters. In this paper, I study how supply-side adjustments shape the effects of policy interventions. I focus on the global market of industrial robots, a leading type of automation technology, where a few multinational enterprises (MNEs) dominate sales. To evaluate how these MNEs respond to policy changes, I collect new data on their characteristics and global sales networks. I then develop and estimate a multi-country general equilibrium model featuring oligopolistic multinational robot sellers. Using this model, I find that MNEs’ market entry and pricing responses transmit internationally and amplify the aggregate and distributional effects of policies targeting robots. |
| Keywords: | Multinational Enterprises, Market Power, Automation |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:cpm:docweb:2403&r= |
| By: | Daron Acemoglu; Simon Johnson |
| Abstract: | David Ricardo initially believed machinery would help workers but revised his opinion, likely based on the impact of automation in the textile industry. Despite cotton textiles becoming one of the largest sectors in the British economy, real wages for cotton weavers did not rise for decades. As E.P. Thompson emphasized, automation forced workers into unhealthy factories with close surveillance and little autonomy. Automation can increase wages, but only when accompanied by new tasks that raise the marginal productivity of labor and/or when there is sufficient additional hiring in complementary sectors. Wages are unlikely to rise when workers cannot push for their share of productivity growth. Today, artificial intelligence may boost average productivity, but it also may replace many workers while degrading job quality for those who remain employed. As in Ricardo’s time, the impact of automation on workers today is more complex than an automatic linkage from higher productivity to better wages. |
| JEL: | B12 J23 O14 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32416&r= |