nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒10‒19
twelve papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. The role of domestic-firm knowledge in foreign R&D collaborations: Evidence from co-patenting in Indian firms By Mathew, Nanditha; Napolitano, Lorenzo; Rizzo, Ugo
  2. The Ties That Bind Us: Social Networks and Productivity in the Factory By Afridi, Farzana; Dhillon, Amrita; Sharma, Swati
  3. Intangible capital indicators based on web scraping of social media By Breithaupt, Patrick; Kesler, Reinhold; Niebel, Thomas; Rammer, Christian
  4. Artificial Intelligence and High-Skilled Work: Evidence from Analysts By Jillian Grennan; Roni Michaely
  5. Environmental regulation and productivity growth: main policy challenges By Roberta De Santis; Piero Esposito; Cecilia Jona-Lasinio
  6. The effect of energy prices and environmental policy stringency on manufacturing employment in OECD countries: Sector- and firm-level evidence By Antoine Dechezleprêtre; Daniel Nachtigall; Balazs Stadler
  7. “In knowledge we trust: learning-by-interacting and the productivity of inventors” By Matteo Tubiana; Ernest Miguelez; Rosina Morneo
  8. Experience-based know-how, learning and innovation in German SMEs: An explorative analysis of the role of know-how in different modes of innovation By Alhusen, Harm
  9. Automation and reallocation: The lasting legacy of COVID-19 in Canada By Blit, Joel
  10. Impediments to the Schumpeterian Process in the Replacement of Large Firms By Mara Faccio; John J. McConnell
  11. Tapping into Talent: Coupling Education and Innovation Policies for Economic Growth By Ufuk Akcigit; Jeremy G. Pearce; Marta Prato
  12. Participation in global value chains and varieties of development patterns By Bruno Carballa Smichowski; Cédric Durand; Steven Knauss

  1. By: Mathew, Nanditha (UNU-MERIT); Napolitano, Lorenzo (Joint Research Center (JRC), European Commission); Rizzo, Ugo (Department of Mathematics and Computer Science, University of Ferrara)
    Abstract: In this paper we analyze the impact of foreign R&D collaborations on the performance of domestic firms and how the relationship is augmented by the pre-existing capabilities of the domestic firms. Using data on Indian firms, we study patterns of co-invention of Indian firms with foreign partners. The results from a causal mediation analysis confirm the crucial role played by domestic firms' absorptive capacity in enhancing the benefits from a foreign collaboration. The evidence we present in this work highlights the microeconomics behind the process of technological capability accumulation and catching up in developing countries.
    Keywords: Co-patenting, Foreign Collaboration, Absorptive Capacity, Capability accumulation, Corporate Performance
    JEL: D24 L20 O12 O32 O33 O34
    Date: 2020–10–05
  2. By: Afridi, Farzana (Indian Statistical Institute); Dhillon, Amrita (King's College London); Sharma, Swati (Indian Statistical Institute)
    Abstract: We use high frequency worker level productivity data from garment manufacturing units in India to study the effects of caste-based social networks on individual and group productivity when workers are complements in the production function but wages are paid at the individual level. Using exogenous variation in production line composition for almost 35,000 worker-days, we find that a 1 percentage point increase in the share of own caste workers in the line increases daily individual productivity by about 10 percentage points. The lowest performing worker increases her effort by more than 15 percentage points when the production line has a more homogeneous caste composition. Production externalities that impose financial costs due to worker's poor performance on co-workers within her social network can explain our findings. Our results suggest that even in the absence of explicit group-based financial incentives, social networks can be leveraged to improve both worker and group productivity.
    Keywords: caste, social networks, labor productivity, assembly lines, India
    JEL: Y40 Z13 J15 J24
    Date: 2020–09
  3. By: Breithaupt, Patrick; Kesler, Reinhold; Niebel, Thomas; Rammer, Christian
    Abstract: Knowledge-based capital is a key factor for productivity growth. Over the past 15 years, it has been increasingly recognised that knowledge-based capital comprises much more than technological knowledge and that these other components are essential for understanding productivity developments and competitiveness of both firms and economies. We develop selected indicators for knowledge-based capital, often denoted as intangible capital, on the basis of publicly available data from online platforms. These indicators based on data from Facebook and the employer branding and review platform Kununu are compared by OLS regressions with firm-level survey data from the Mannheim Innovation Panel (MIP). All regressions show a positive and significant relationship between survey-based firm-level expenditures for marketing and on-the-job training and the respective information stemming from the online platforms. We therefore explore the possibility of predicting brand equity and firm-specific human capital with machine learning methods.
    Keywords: Web Scraping,Knowledge-Based Capital,Intangibles
    JEL: C81 E22 O30
    Date: 2020
  4. By: Jillian Grennan (Duke University - Fuqua School of Business; Duke Innovation & Entrepreneurship Initiative); Roni Michaely (University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute)
    Abstract: Policymakers fear artificial intelligence (AI) will disrupt labor markets, especially for high-skilled workers. We investigate this concern using novel, task-specific data for security analysts. Exploiting variation in AI's power across stocks, we show analysts with portfolios that are more exposed to AI are more likely to reallocate efforts to soft skills, shift coverage towards low AI stocks, and even leave the profession. Analyst departures disproportionately occur among highly accurate analysts, leaving for non-research jobs. Reallocating efforts toward tasks that rely on social skills improve consensus forecasts. However, increased exposure to AI reduces the novelty in analysts' research which reduces compensation.
    Keywords: artificial intelligence, big data, technology, automation, sell-side analysts, job displacement, labor and finance, social skills, non-cognitive skills, tasks, skill premium, skill-biased technological change, compensation
    JEL: G17 G24 J23 J24 J31 O33
    Date: 2020–08
  5. By: Roberta De Santis; Piero Esposito; Cecilia Jona-Lasinio
    Abstract: In this paper, we investigate the environmental regulation-productivity nexus for 14 OECD countries over the years 1990-2015 and discuss its main policy challenges. Our findings support the hypothesis that environmental policies generate positive productivity returns through innovation as suggested by Porter and Van Der Linde (1995). We find that environmental policies have a productivity growth-promoting effect. Both market and non-marked based policies exert a positive but differentiated impact on labour and multifactor productivity growth. Environmental policy measures generate also potentially mixed redistributive impacts. As for specific polices, green taxes display the largest effect on multifactor productivity although with potentially negative redistributive impact. We also find that environmental regulation exerts indirect positive effect on productivity growth fostering capital accumulation especially in high ICT intensive countries.
    Keywords: Environmental regulation, productivity, innovation, Porter hypothesis
    Date: 2020–08
  6. By: Antoine Dechezleprêtre; Daniel Nachtigall; Balazs Stadler
    Abstract: This study empirically assesses the impact of energy prices and environmental policy stringency (EPS) on manufacturing employment in OECD countries over the period 2000- 2014. At the sector level, increases in energy prices and in EPS have a negative and statistically significant impact on total employment in the manufacturing sector. Energy-intensive sectors are most affected, while the impact is not statistically significant for less energy-intensive sectors. Even in highly energy-intensive sectors, however, the size of the effect is relatively small. Moreover, higher energy prices increase the probability of firm exit, but they have a statistically significant and small positive effect on the employment level of surviving firms. Accelerated firm exit allows surviving firms to expand, boosting firm-level employment. Therefore, the analysis demonstrates that there exist transition costs in the short run to imposing stricter environmental policies, as some workers are forced to move away from affected firms and sectors, even if many of these job losses are unlikely to be permanent as laid-off workers may ultimately find other jobs, notably in the services sector.
    JEL: Q52 Q54 Q58
    Date: 2020–10–08
  7. By: Matteo Tubiana (University of Bergamo); Ernest Miguelez (GREThA UMR CNRS 5113 - Université de Bordeaux); Rosina Morneo (AQR-IREA, University of Barcelona)
    Abstract: Innovation rarely happens through the actions of a single person. Innovators source their ideas while interacting with their peers, at different levels and with different intensities. In this paper, we exploit a dataset of disambiguated inventors in European cities to assess the influence of their interactions with co-workers, organizations’ colleagues, and geographically co-located peers, to understand if the different levels of interaction influence their productivity. Following inventors’ productivity over time and adding a large number of fixed effects to control for unobserved heterogeneity, we uncover critical facts, such as the importance of city knowledge stocks for inventors’ productivity, with firm knowledge stocks and network knowledge stocks being of smaller importance. However, when the complexity and quality of knowledge is accounted for, the picture changes upside down and closer interactions (individuals’ co-workers and firms’ colleagues) become way more important.
    Keywords: Inventors, Productivity, Stock of knowledge, Interactions. JEL classification: O18, O31, O33, O52, R12.
    Date: 2020–09
  8. By: Alhusen, Harm
    Abstract: The 'doing-using-interacting mode' of innovation (DUI) is considered an important component of innovative activity. It describes informal innovative activities and complements the 'science-technology-innovation mode' (STI) which is based on research and development. A common demarcation criterion between both modes of innovation is the relevance of experiencebased knowledge, know-how and know-who for the DUI mode of innovation whereas the STI mode of innovation is said to rely on codified knowledge, know-what and know-why. Based upon 81 in-depth interviews with German SMEs and regional innovation consultants, this work focuses on the role of experience-based know-how for SMEs innovations within different modes of innovation. Experience-based know-how is found to be important for all modes of innovation, regardless of an SMEs mode of innovation. Results from qualitative interviews show that firms view experience-based know-how as important for at least one of the following domains: product innovation, business process innovation & organizational routines and customer knowledge. However, the acquisition, transfer and transformation of experience-based know-how can strongly differ, depending on the respective mode of innovation. As a recommendation, the idea that know-how is a suitable demarcation criterion for modes of innovation should be revised in future research.
    Keywords: DUI,STI,tacit knowledge,experience-based knowledge,learning processes,modes of innovation
    JEL: O3 O30 O31 R10
    Date: 2020
  9. By: Blit, Joel
    Abstract: Recent evidence suggests that recessions play a crucial role in promoting automation and the reallocation of productive resources. Consistent with this, I show that in the three previous Canadian recessions, routine jobs were disproportionately lost. COVID-19 is likely to have a similar impact, but bigger because superimposed onto the usual recessionary transformational forces are health-specific incentives to automate. Using O*NET data, I construct an index of COVID-19 health risk and of routine task intensity to measure health incentives to automate and the feasibility of doing so. Across occupations, income groups, industries, and regions, the two indices are strongly negatively correlated, suggesting that automation will not be overly focused and that it may penetrate into hitherto relatively unaffected sectors like health and education. Nevertheless, office and health support workers are likely to be disproportionately affected, as will the retail and hospitality industries. The impacts will also be primarily felt by families toward the bottom of the income distribution and in smaller cities.
    Keywords: COVID-19,recessions,productivity,innovation,automation
    JEL: O33 O40 E32 J24
    Date: 2020
  10. By: Mara Faccio; John J. McConnell
    Abstract: Using newly-assembled data encompassing up to 75 countries and starting circa 1910, we find that the Schumpeterian process of creative destruction aptly describes the replacement of large firms by other firms, but exceptions to the norm of replacement are not rare and replacement is often not by new firms. Initial firm size and political connections represent the main obstacles to the Schumpeterian process while board interlocks and a corporate culture of innovation play modest roles. Consistent with a theory of political capture, when accompanied by regulations that restrict entry, political connections play a formidable role in abetting large firms remaining large.
    JEL: G3 G38 O16 P16
    Date: 2020–09
  11. By: Ufuk Akcigit; Jeremy G. Pearce; Marta Prato
    Abstract: How do innovation and education policy affect individual career choice and aggregate productivity? This paper analyzes the various layers that connect R&D subsidies and higher education policy to productivity growth. We put the development of scarce talent and career choice at the center of a new endogenous growth framework with individual-level heterogeneity in talent, frictions, and preferences. We link the model to micro-level data from Denmark and uncover a host of facts about the links between talent, higher education, and innovation. We use these facts to calibrate the model and study counterfactual policy exercises. We find that R&D subsidies, while less effective than standard models, can be strengthened when combined with higher education policy that alleviates financial frictions for talented youth. Education and innovation policies not only alleviate different frictions, but also impact innovation at different time horizons. Education policy is also more effective in societies with high income inequality.
    JEL: J24 O31 O38 O47
    Date: 2020–09
  12. By: Bruno Carballa Smichowski; Cédric Durand (CEPN - Centre d'Economie de l'Université Paris Nord - UP13 - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique); Steven Knauss
    Abstract: This paper relates participation in global value chains (GVCs) to development patterns at the country level. It accounts for the diversity and interdependence of development through a crosscountry analysis for 51 countries between 1995 and 2008. We identify three patterns of socioeconomic development related to various degrees and modes of GVC participation: a social upgrading mirage, the reproduction of the core and unequal growth. This result is achieved thanks to the introduction of two new elements to the literature: first, the introduction of new macroeconomic indicators of GVC participation and economic gains that are explicitly based in a theoretically consistent definition of GVCs; second, the identification of a variety of interdependent development patterns related to GVC participation through the use of principal component analysis and cluster analysis.
    Keywords: Global value chains,Development,PCA JEL classification: F63
    Date: 2020–09–20

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