nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒06‒08
fourteen papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Public policies and the art of catching up: matching the historical evidence with a multi-country agent-based model By Giovanni Dosi; Andrea Roventini; Emanuele Russo
  2. Related variety, recombinant knowledge and regional innovation. Evidence for Sweden, 1991-2010 By Mikhail Martynovich; Josef Taalbi
  3. Firm productivity dynamics and distribution: Evidence for Chile using micro data from administrative tax records By Elías Albagli; Mario Canales; Claudia de la Huerta; Matías Tapia; Juan Marcos Wlasiuk
  4. Innovation catalysts - How multinationals reshape the global geography of innovation By Riccardo Crescenzi; Arnaud Dyèvre; Frank Neffke
  5. The impact of financial constraints on tradable and non-tradable R&D investments in Portugal By Magalhaes, Manuela
  6. Knowledge Transfers from Federally Supported R&D By Link, Albert
  7. Does Goliath Help David? Anchor Firms and Startup Clusters By Rahul R. Gupta
  8. Evaluating the impact of public policies on large firms: a synthetic control approach to science-industry transfer policies By Autant-Bernard, C.; Fotso, R.; Massard, N.
  9. Automation, workers’ skills and job satisfaction By Henrik Schwabe; Fulvio Castellacci
  10. Does Electricity Drive Structural Transformation? Evidence from the United States By Gaggl, Paul; Gray, Rowena; Marinescu, Ioana E.; Morin, Miguel
  11. Optimal Patent Policy for Pharmaceutical Industry By Izhak, Olena; Saxell, Tanja; Takalo, Tuomas
  12. The Importance of Tacit Knowledge: Dynamic Inventor Activity in the Commercialization Phase By Maurseth, Per Botolf; Svensson, Roger
  13. Intellectual property reform in the laboratory By Benslimane, I.; Crosetto, P.; Magni-Berton, R.; Varaine, S.
  14. The Influence of Hidden Researcher Decisions in Applied Microeconomics By Huntington-Klein, Nick; Arenas, Andreu; Beam, Emily A.; Bertoni, Marco; Bloem, Jeffrey R.; Burli, Pralhad; Chen, Naibin; Greico, Paul; Ekpe, Godwin; Pugatch, Todd; Saavedra, Martin; Stopnitzky, Yaniv

  1. By: Giovanni Dosi (Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna, Pisa (Italy)); Andrea Roventini (OFCE Sciences Po, Sophia-Antipolis (France), Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna, Pisa (Italy)); Emanuele Russo (Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna, Pisa (Italy))
    Abstract: In this paper, we study the effects of industrial policies on international convergence using a multi-country agent-based model which builds upon Dosi et al. (2019b). The model features a group of microfounded economies, with evolving industries, populated by heterogeneous firms that compete in international markets. In each country, technological change is driven by firms’ activities of search and innovation, while aggregate demand formation and distribution follows Keynesian dynamics. Interactions among countries take place via trade flows and international technological imitation. We employ the model to assess the different strategies that laggard countries can adopt to catch up with leaders: market-friendly policies; industrial policies targeting the development of firms’ capabilities and R&D investments, as well as trade restrictions for infant industry protection; protectionist policies focusing on tariffs only. We find that markets cannot do the magic: in absence of government interventions, laggards will continue to fall behind. On the contrary, industrial policies can successfully drive international convergence among leaders and laggards, while protectionism alone is not necessary to support catching up and countries get stuck in a sort of middle-income trap. Finally, in a global trade war, where developed economies impose retaliatory tariffs, both laggards and leaders are worse off and world productivity growth slows down.
    Keywords: Endogenous growth, catching up, technology-gaps, industrial policies, agent-based models.
    JEL: F41 F43 O4 O3
    Date: 2020–06
  2. By: Mikhail Martynovich; Josef Taalbi
    Abstract: This study investigates how related variety in the regional employment mix affects the innovation output of a region. Departing from the idea of recombinant innovation, previous research has argued that related variety enhances regional innovation as inter-industry knowledge spillovers occur more easily between different but cognitively similar industries. This study combines a novel dataset and related variety measures based on network theory, which allows a more nuanced perspective on the relationship between related variety and regional innovation. The principal novelty of the paper lies in employing new data on product innovations commercialised by Swedish manufacturing firms between 1970 and 2013. In this respect, it allows a direct measure of regional innovation output as compared to patent measures, usually employed in similar studies. The second contribution of this paper is that we employ network-topology based measures of related variety that allow us to measure relatedness as the recombination rather than direct flow of knowledge. We argue that this measure comes closer to the notion of innovation as spurred by recombination and show that this measure is a superior predictor of innovation activity.
    Keywords: related variety, relatedness, innovation, network analysis
    JEL: L16 O31 R11 R12
    Date: 2020–03
  3. By: Elías Albagli; Mario Canales; Claudia de la Huerta; Matías Tapia; Juan Marcos Wlasiuk
    Abstract: Using administrative tax records for all formal Chilean firms, we compute and characterize the evolution and distribution of total factor productivity at the firm level. With data on labor, capital, and value-added, we compute TFPR measures for individual firms between 2006 and 2015, allowing for differences in factor intensities across economic sectors. Our results show that factor reallocation plays a relevant role in explaining the evolution of aggregate TFP in Chile over the last decade. Firms with higher TFPR hire more workers, have stronger capital growth, and have a larger probability of survival. However, the extent of reallocation does not prevent a large, persistent dispersion in TFPR among firms. The magnitude of this dispersion suggests that further reallocation could bring up first-order gains in aggregate productivity and output. Our results also suggest that misallocation comes mainly from distortions on the firms´ overall scale, rather than from distortions on the relative use of capital and labor.
    Date: 2019–05
  4. By: Riccardo Crescenzi; Arnaud Dyèvre; Frank Neffke
    Abstract: We study whether and when Research and Development (R&D) activities by foreign multinationals help in the formation and development of new innovation clusters. Combining information on nearly four decades worth of patents with socio-economic data for regions that cover virtually the entire globe, we use matched difference-in-differences estimation to show that R&D activities by foreign multinationals have a positive causal effect on local innovation rates. This effect is sizeable: foreign research activities help a region climb 14 percentiles in the global innovation ranks within five years. This effect materializes through a combination of knowledge spillovers to domestic firms and the attraction of new foreign firms to the region. However, not all multinationals generate equal benefits. In spite of their advanced technological capabilities, technology leaders generate fewer spillovers than technologically less advanced multinationals. A closer inspection reveals that technology leaders also engage in fewer technological alliances and exchange fewer workers in local labor markets abroad than less advanced firms. Moreover, technology leaders tend to set up their foreign R&D activities in regions with relatively low absorptive capacity. We attribute these differences to that fact that the trade-off between costs and benefits of local spillovers a multinational faces depends on the multinational’s technological sophistication. This illustrates the importance of understanding corporate strategy when analyzing innovation clusters.
    Keywords: innovation, regions, foreign direct investment, patenting, cluster emergence
    JEL: O32 O33 R11 R12
    Date: 2020–03
  5. By: Magalhaes, Manuela
    Abstract: We develop a directed technical change model with two sectors, tradable and non-tradable, and dynamic firms’ decisions to invest in R&D in the presence of financial constraints. The model establishes a linkage between R&D decisions, product and process innovations, future productivity, profits, and credit constraints. The model is estimated using Portuguese firms’ data of the tradable and non-tradable sectors. We find that the previous R&D investments raises the innovating probabilities, the innovating probabilities are higher in the tradable sector, and the startup costs of innovation tend to be higher than the maintenance costs. The results also show complementary between the R&D benefits and the firm’s financial strength, diminishing marginal returns to capital on innovation benefits, and high heterogeneity of the innovation costs across industries. Finally, when the firms’ financial strength and the trade-off between tradable and non-tradable goods are considered, the R&D benefits in the non-tradable sector do not compensate its cost given the higher productivity and innovation probabilities of the tradable sector. As a result, the R&D investments in the tradable sector illustrates a misallocation of financial resources.
    Keywords: : Credit constraints, firm-level data, productivity, R&D, tradable and non-tradable goods.
    JEL: O31 O32
    Date: 2020–04–04
  6. By: Link, Albert (University of North Carolina at Greensboro, Department of Economics)
    Abstract: The purpose of this paper is to identify covariates with publication activity, a form of knowledge transfer, from SBIR publicly funded research. The paper offers an argument about the policy relevance of studying knowledge transfers from publicly funded research that occurs in private sector firms. Relevant explanatory variables are the length of the funded research project, university involvement in the project, the firm's history of SBIR funding, and the academic background of firms' founders.
    Keywords: Technology transfer; Public sector R&D; Entrepreneurship; Program evaluation; SBIR program;
    JEL: H54 L26 O31 O32 O38
    Date: 2020–05–21
  7. By: Rahul R. Gupta
    Abstract: This paper investigates the effects of a large firm’s geographical expansion (anchor firm) on local worker transitions into young firms through wage effects in industries economically proximate to the anchor firm. Using hand-collected data matched to administrative Census microdata, I exploit anchor firms’ site selection processes to employ a difference-in-differences approach to compare workers in winning counties to those in counterfactual counties. The arrival of an anchor firm induces worker reallocation towards young firms in industries linked through input-output channels by a magnitude of 120 new businesses that account for approximately 2,300 jobs. Consistent with the literature in personnel and organizational economics, incumbent firms experiencing the fastest wage growth due to these shocks shed mid-layer employees who select into young firms within the county and in their own industry of experience. These effects are strongest in the most specialized and knowledge-intensive industries. Attracting an anchor firm to a county appears to have limited spillover effects in overall employment that are mainly driven by reorganization of incumbent firms in the anchor’s input-output industries that face rising labor costs.
    Date: 2020–05
  8. By: Autant-Bernard, C.; Fotso, R.; Massard, N.
    Abstract: Large firms dominate R&D investment in most countries and receive the majority of public R&D funding. Due to methodological difficulties, however, evaluation of the effect of government-sponsored R&D programmes mainly focuses on small- and medium-sized enterprises. The scarcity of large firms and their heterogeneity hampers the ability to find proper counterfactuals for very large companies and makes it difficult to use proper inference methods to measure the impact of a specific policy. In order to address these methodological issues, we propose using the synthetic control method the synthetic control method, initially developed by Abadie et al. (2010) to evaluate programmes on a regional scale. We apply this method to evaluate the impact of a new French science-industry transfer initiative and compare the results with the random trend model and more standard counterfactual approaches. Based on data covering a long pre-treatment period (1998–2011) and ongoing treatment period (2012–2015), we reveal a convergence between the results obtained with the synthetic control method and the random trend model, and demonstrate that traditional counterfactual evaluation methods are not appropriate for large firms. Moreover, the synthetic control method has the advantage of providing an individual assessment of the policy impact on each firm. In the specific case of the French science-industry transfer initiative, it reveals that the impact on private R&D is highly heterogenous both on RD inputs and cooperation behaviours. Beyond this specific transfer policy, this study suggests that the synthetic control method opens new research perspectives in policy impact evaluation at the firm level.
    JEL: C23 D22 O38
    Date: 2020
  9. By: Henrik Schwabe (TIK, University of Oslo); Fulvio Castellacci (TIK, University of Oslo)
    Abstract: When industrial robots are adopted by firms in a local labor market, some workers are displaced and become unemployed. Other workers that are not directly affected by automation may however fear that these new technologies might replace their working tasks in the future. This fear of a possible future replacement is important because it negatively affects workers’ job satisfaction at present. This paper studies the extent to which automation affects workers’ job satisfaction, and whether this effect differs for high- versus low-skilled workers. The empirical analysis uses microdata for several thousand workers in Norway from the Working Life Barometer survey for the period 2016-2019, combined with information on the introduction of industrial robots in Norway from the International Federation of Robotics. Our identification strategy exploits variation in the pace of introduction of industrial robots in Norwegian regions and industries since 2007 to instrument workers’ fear of replacement. The results indicate that automation in industrial firms in recent years have induced 40% of the workers that are currently in employment to fear that their work might be replaced by a smart machine in the future. Such fear of future replacement does negatively affect workers’ job satisfaction at present. This negative effect is stronger for low-skilled workers, which are those carrying out routine-based tasks, and who are therefore more exposed to the risks of automation.
    Date: 2020–05
  10. By: Gaggl, Paul (University of North Carolina at Charlotte); Gray, Rowena (University of California, Merced); Marinescu, Ioana E. (University of Pennsylvania); Morin, Miguel (The Alan Turing Institute)
    Abstract: Electricity is a general purpose technology and the catalyst for the second industrial revolution. What was its impact on the structure of employment? We use U.S. Census data from 1910 to 1940 and measure electrification with the length of higher-voltage electricity lines. Instrumenting for electrification using hydro-electric potential, we find that the average expansion of high-voltage transmission lines between 1910 and 1940 increased the share of operatives in a county by 3.3 percentage points and decreased the share of farmers by 2.1 percentage points. Electrification can explain 50.5% of the total increase in operatives, and 18.1% of the total decrease in farmers between 1910 and 1940. At the industry level, electrification drove 15.7% of the decline in the share of agricultural employment and 28.4% of the increase in the share of manufacturing employment between 1910 and 1940. Electrification was thus a key driver of structural transformation in the U.S. economy.
    Keywords: technological change, electrification, structural change
    JEL: E25 E22 J24 J31 N32 N72 O33
    Date: 2020–05
  11. By: Izhak, Olena; Saxell, Tanja; Takalo, Tuomas
    Abstract: We show how characterizing optimal patent policy for the pharmaceutical industry only requires information about generic producers’ responses to changes in the effective duration and scope of new drug patents. To estimate these responses, we use data on Paragraph IV patent challenges, and two quasi-experimental approaches: one based on changes in patent laws and another on the allocation of patent applications to examiners. We find that extending effective patent duration increases generic entry via Paragraph IV patent challenges whereas broadening protection reduces it. Our results imply that pharmaceutical patents should be made shorter but broader.
    Keywords: patent policy, pharmaceuticals, generic entry, innovation, imitation, Business regulation and international economics, I18, K20, L13, O34, O31,
    Date: 2020
  12. By: Maurseth, Per Botolf (Department of Economics); Svensson, Roger (Research Institute of Industrial Economics (IFN))
    Abstract: Inventors generally know more about their inventions than what is written down in patent applications. Because they possess this tacit knowledge, inventors may need to play an active role when patents are commercialized. We build on Arora (1995) and model firm-inventor cooperation in the commercialization of a given invention. Tacit knowledge warrants inventor activity. However, imperfect IPRs may reduce inventors’ incentives to engage in the commercialization process. We analyze when first-best inventor activity is achieved in a two-stage contract. In the empirical part, we analyze when inventor activity is important for the successful commercialization of patents by using a detailed patent database. The database contains unique information on inventor activity, patent commercialization modes and the profitability of commercialization. In the empirical estimations, we find that inventor activity has a strong positive correlation with profitability when a patent is sold or licensed to another firm. When a patent is sold or licensed in the second phase, it is still inventor activity in the first phase that matters for profitability. Thus, our interpretation is that tacit knowledge and close cooperation between inventors and external firms are often crucial for the successful commercialization of patents.
    Keywords: Tacit knowledge; Inventor activity; Patents; Commercialization
    JEL: O31 O33 O34
    Date: 2020–05–28
  13. By: Benslimane, I.; Crosetto, P.; Magni-Berton, R.; Varaine, S.
    Abstract: This study attempts to experimentally capture the effects of democratic reform of intellectual property (IP) and measure how a vote "against IP" can disappoint the most talented innovators and reduce their creativity. Contrary to expectations, the results show that such a vote increases overall creativity. Actually, the most talented innovators do not vote in favor of IP. Rather, those who vote in favor of IP are those who benefit relatively more from royalties. Surprisingly, no correlation is found between these two populations: the IP in our experiment seems not to reward the best players, but the players choosing an ’autarkic’ strategy of relying on their own creationsand forego cross-fertilization with other players. These are not particularly brilliant players thatopt for a rent-seeking strategy that maximises gainsfromthe IP systemitself. There are plausible arguments to argue that this result is at least partly valid in the real world, especially for complexand highly sequential innovations where it has been proven that patent trolls and anti-competitivestrategies are important. These findings lead us not to recommend IP constitutional protections,because there are no major "tyranny from the majority" concerns.
    JEL: O34 D90 D72
    Date: 2020
  14. By: Huntington-Klein, Nick (California State University); Arenas, Andreu (University of Barcelona); Beam, Emily A. (University of Vermont); Bertoni, Marco (University of Padova); Bloem, Jeffrey R. (University of Minnesota); Burli, Pralhad (Idaho National Laboratory); Chen, Naibin (Pennsylvania State University); Greico, Paul (Pennsylvania State University); Ekpe, Godwin (Northern Illinois University); Pugatch, Todd (Oregon State University); Saavedra, Martin (Oberlin College); Stopnitzky, Yaniv (University of San Francisco)
    Abstract: Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many-analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3-4 times the typical reported standard error.
    Keywords: replication, metascience, research
    JEL: C81 C10 B41
    Date: 2020–05

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