nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2019‒12‒23
nine papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Public R&D and green knowledge diffusion:\r\nEvidence from patent citation data By Gianluca ORSATTI
  2. Greentech homophily and path dependence in a large patent citation network By Nomaler, Onder; Verspagen, Bart
  3. Productivity Dynamics in French Woodworking Industries. By Enrico De Monte; Anne-Laure Levet
  4. The Impacts of Patent and R&D Expenditures on the High-Tech Exports of Newly Industrialised Countries: A Panel Cointegration Analysis By Robert Ackrill; Rahmi Cetin
  5. Labor Market Effects of Technology Shocks Biased toward the Traded Sector By Luisito Bertinelli; Olivier Cardi; Romain Restout
  6. Understanding Heterogeneity in the Performance Feedback – Organizational Responsiveness Relationship: A Meta-Analysis By Verver, Hugo; van Zelst, Marino; Lucas, Gerardus Johannes Maria; Meeus, Marius
  7. Competition policy and Industrial property: relationship through panel data approach 2007 – 2015 By Herrera Saavedra, Juan Pablo; Lozano Maturana, Ginette; Campo Robledo, Jacobo; Parra Ochoa, Catalina
  8. Is This Time Different? What History Says About Machines’ Impact on Jobs By Anek Belbase; Alice Zulkarnain
  9. Spillovers and Exports: A Meta-Analysis By Jianhua Duan; Kuntal K. Das; Laura Meriluoto; W. Robert Reed

  1. By: Gianluca ORSATTI
    Abstract: The present paper investigates the relationship between public R&D and the diffusion of green knowledge. To do so, we exploit information contained in green patents filed at the European Patent Office from 1980 to 1984. The diffusion of green knowledge is measured by meaning of patent citations. The level of public R&D is instrumented through the policy reaction to the 1986 Chernobyl nuclear accident – that affected the level of public R&D in the energy generation domain – in a difference in differences setting. Results show that a 10% increase in public R&D increases by around 0.7% the number of citations to green patents. Moreover, increasing public R&D fosters the diffusion of green knowledge across traditional (non-green) domains and increases the average technological distance of inventions citing green patents. This evidence suggests that public R&D is a driver of green knowledge diffusion, accelerates the hybridization of traditional innovation processes and fosters technological diversification.
    Keywords: Public R&D, Green innovation, Knowledge diffusion, Patent citations, Environmental policy, Green R&D
    JEL: O30 O32 O33 O38 Q55
    Date: 2019
  2. By: Nomaler, Onder (UNU-MERIT); Verspagen, Bart (UNU-MERIT, and SBE, Maastricht University)
    Abstract: We propose a method to identify the main technological trends in a very large (i.e., universal) patent citation network comprising all patented technologies. Our method builds on existing literature that implements a similar procedure, but for much smaller networks, each covering a truncated sub-network comprising only the patents of a selected technology field. The increase of the scale of the network that we analyse allows us to analyse so-called macro fields of technology (distinct technology fields related by a coherent overall goal), such as environmentally friendly technologies (Greentech). Our method extracts a so-called network of main paths (NMP). We analyse the NMP in terms of the distribution of Greentech in this network. For this purpose, we construct a number of theoretical benchmark models of trajectory formation. In these models, the ideas of homophily (Green patents citing Green patents) and path dependency (the impact of upstream Green patents in the network) play a large role. We show that a model taking into account both homophily and path dependence predicts well the number of Green patents on technological trajectories, and the number of clusters of Green patents on technological trajectories.
    Keywords: patent citations, citation networks, main path, technological change, green technology, climate change mitigation
    JEL: Q55 Q54 O31 O33 O34
    Date: 2019–12–17
  3. By: Enrico De Monte; Anne-Laure Levet
    Abstract: This paper investigates productivity dynamics of firms active in French woodworking 4- digit industries. For this purpose we analyze firm-level data from the two fiscal data bases FICUS (1994 - 2008) and FARE (2008 - 2016). Based on firm-level productivity measures, recovered from the estimation of a value-added Cobb-Douglas production function, we mainly study the industries’ aggregate productivity growth related to entry and exit. Also, by constructing a transition matrix we investigate firms’ probability to survive, enter or exit given a specific ranking of their productivity. We find that all industries increased considerably their aggregate productivity between 1994 and 2016, where the by far largest part of this positive development is contributed by survivors productivity improvement. Entrants contribute negatively to aggregate productivity growths while the contribution of exitors varies in sign for different industries. Also, we find that firms reveal high persistence in their productivity ranking over time and that entry and exit is more probable for low productive and small firms.
    Keywords: production function estimation, aggregate productivity, productivity decomposition, technological change, firm entry and exit.
    JEL: C13 C14 D24 D30 O47
    Date: 2019
  4. By: Robert Ackrill; Rahmi Cetin
    Abstract: In this paper, we have sought to complement the extensive literature analysing firm level data on the links between innovation and exports, with an exploration of whether these variables are related at the country-level, for a group of eight NICs. We have been particularly interested with innovation in and export of high-tech products. At the outset, we identified seven hypotheses for testing. Our findings are that, for our panel of eight NICs over the period 1996-2014, patents and R&D expenditures both exert a significant positive effect on these countries’ exports of high-tech goods.
    Date: 2019–12
  5. By: Luisito Bertinelli; Olivier Cardi; Romain Restout
    Abstract: Motivated by recent evidence pointing at an increasing contribution of asymmetric shocks across sectors to economic fluctuations, we explore the sectoral composition effects of technology shocks biased toward the traded sector. Using a panel of seventeen OECD countries over the period 1970-2013, our VAR evidence reveals that a permanent increase in traded relative to non-traded TFP lowers the traded hours worked share by shifting labor toward the non-traded sector, and has an expansionary effect on the labor income share in both sectors. Our quantitative analysis shows that the open economy version of the neoclassical model can reproduce the reallocation and redistributive effects we document empirically once we allow for technological change biased toward labor together with additional specific elements. Calibrating the model to country-specific data, the model can account for the cross-country dispersion in the reallocation and redistributive effects we document empirically once we let factor-biased technological change vary across sectors and between countries. Finally, we document evidence which supports our hypothesis of factor-biased technological change as we find empirically that countries where capital-intensive industries contribute more to the increase in traded TFP are those where capital relative to labor efficiency increases.
    Keywords: Sectoral technology shocks, factor-augmenting efficiency, Open economy, Labor reallocation across sectors, CES production function, Labor income share
    JEL: E22 F11 F41 F43
    Date: 2019
  6. By: Verver, Hugo; van Zelst, Marino (Tilburg University); Lucas, Gerardus Johannes Maria (De Montfort University); Meeus, Marius
    Abstract: Organizational performance feedback theory (PFT), which is derived from the Behavioral Theory of the Firm, has emerged as a key perspective guiding studies investigating how performance relative to aspiration levels (i.e., performance feedback) influences organizational responsiveness. While the PFT literature refers to a core prediction - performance below aspirations induces more responsiveness than performance above aspirations does - empirical evidence reveals considerable conflicting findings. In line with contested issues in the current PFT literature, we propose a series of research questions and more refined predictions, which we elated to specific dimensions of performance feedback (valence, type of aspiration level and performance indicator), type of responsiveness (search versus change), and organizational characteristics (age, form of ownership, and industry). We test these refinements with various meta-analytic approaches, based on 263 effect sizes extracted from 156 studies. Our results demonstrate that the way in which performance feedback influences organizational responsiveness is sensitive to the factors we based our predictions on, with meta-analyzed effect sizes ranging from -0.106 to 0.055. Our findings help to systematically distinguish patterns in the heterogeneity associated with the performance feedback-responsiveness relationship. These results support our contention that more refined explanations, measures, and models of organizational performance feedback are needed.
    Date: 2019–04–29
  7. By: Herrera Saavedra, Juan Pablo; Lozano Maturana, Ginette; Campo Robledo, Jacobo; Parra Ochoa, Catalina
    Abstract: In the last century, the relation between competition and innovation has been a subject of particular interest, considering the important role that technological progress plays on economic growth and social welfare. Moreover, for several decades, the interest and discussion in regards to this matter has been the focus of heated debates among economists, jurists; and, most notably, among Competition and Industrial Property Authorities, since competition and innovation are the main axes in any modern approach to industrial policy. This paper examines the relation between competition and innovation, based on the estimation of panel data models for 75 countries between 2007 and 2015. The results show an inverted-U relation between innovation and competition. In other words, increases in competition generates innovation to a certain level (turning point) where the effect of competition on innovation is negative. This is consistent with Aghion et al. (2005) approach. The results are robust to different variables used as a proxy for innovation.
    Keywords: Industrial Property; Competition; Panel Data; GMM; inverted-U
    JEL: C33 L11 L22 M13
    Date: 2019–12
  8. By: Anek Belbase; Alice Zulkarnain
    Abstract: Throughout history, a familiar story has played out in societies undergoing rapid technological change. On one side, doomsday predictors have warned that laborsaving machines will make jobs obsolete and fuel social unrest. On the other side, utopians have preached a machine-powered era of abundance and leisure. Both sides have always thought that “this time is different” and that the world would never be the same. In a sense, both sides have been right (though not to the extremes predicted). Technological innovation has made workers more productive overall but has also displaced workers and periodically fed social unrest. Importantly, each wave of innovation and adoption has changed the nature of work and the relative value of workers’ skills in unique ways. Like prior generations trying to prepare for an uncertain future, current workers and policymakers are wondering how the rise of computers and robots – which can seemingly beat humans at any task from detecting tumors to driving – will change the nature of work. The stakes are particularly high for older workers, who increasingly need to work until their late 60s to afford to retire. This brief is the first of a three-part series investigating the impact of the current wave of automation on the job prospects of older workers. To place this automation wave in context, this brief reviews the literature on the effect of laborsaving technology over the past two centuries. The discussion proceeds as follows. The first section explains how technology expands the economic pie. The second section describes how machines change the level and type of labor that is in demand. The third section focuses on the painful transitions that some workers have faced because of machines, and the fourth section compares the changes taking place today to past waves to assess whether this time is, in fact, different. The final section concludes that changes today, while qualitatively different from the past, are comparable in scope. It seems reasonable to expect that – at least for a few more decades – machines will continue to make some skills more valuable than others without making human skills obsolete.
    Date: 2019–07
  9. By: Jianhua Duan; Kuntal K. Das (University of Canterbury); Laura Meriluoto (University of Canterbury); W. Robert Reed (University of Canterbury)
    Abstract: This study uses meta-analysis to analyze the empirical literature on spillovers and exports. It collects 3,291 estimated spillover effects from 99 studies. The estimated spillover effects in the literature span a large number of types and measures of both exports and spillovers. As a result, we transform estimates to partial correlation coefficients. We analyze these transformed effects using four different versions of Weighted Least Squares (WLS) estimators, incorporating both meta-analytic “Fixed Effects” and “Random Effects”. Our analysis produces three main findings. First, while we estimate a overall mean effect of spillovers on exports that is statistically significant, the size of the effect is economically negligible. Second, we find modest evidence for the existence of publication bias in the empirical literature. Publication bias can arise when researchers and journals have a preference to publish articles that find positive and significant results. While some of our tests indicate the presence of publication bias, in every case the size of the effect is small. Third, using both Bayesian Model Averaging and frequentist meta-regression analysis, we find that some data, estimation, and study characteristics are significant in some regressions. However, only a few of the characteristics are robust, and none are large in size.
    Keywords: Spillovers, Exports, Meta-analysis; Meta-Regression Analysis; Bayesian Model Averaging, Partial Correlation Coefficient
    JEL: D62 F10 F20 O30 C80
    Date: 2019–12–01

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