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on Technology and Industrial Dynamics |
| By: | Giovanni Dosi |
| Abstract: | This essay outlines the evolutionary research agenda thoroughly explored in its microeconomic aspects in the forthcoming Manual, The Foundations of Complex Evolving Economies. Part One: Innovation, Organization and Industrial Dynamics, Oxford University Press, 2023. But is there an ''evolutionary paradigm'', in the first place? And if yes, what is it? In brief, in such a paradigm, the economy is interpreted as a complex evolving system. In that, a wide set of techno-economic phenomena are understood as emergent properties - outcomes of far-from-equilibrium interactions among heterogeneous agents - characterized by endogenous preferences, most often ''boundedly rational'' - but always capable of learning, adapting, and innovating with respect to their understandings of the world in which they operate, the technologies they master, their organizational forms, and their behavioral repertoires. All that involves some crucial properties. First, if the entities are genuinely evolving, new elements, new technologies, new organizational forms, new patterns of interaction are bound to appear along the course of evolution. Second, evolution is a multi-scale phenomenon. This is a fundamental property of biological evolution, and even more so is the evolution of economies and whole societies, nested in different institutions - possibly evolving at different paces, and coupled with technological and organizational changes. Third, but relatedly, economies are complex interactive systems. Interaction generally implies emergence. There is no isomorphism between macroscopic phenomena, say, the dynamics of industries, markets, and whole economies, on the one hand, and the behaviours of individual entities, on the other. More is different (Anderson, 1972). Fourth, complexity is intimately linked with non-linearities, and thus multiple possible dynamical paths. History counts. And this, even more so, in socio-economic environments characterized by knowledge accumulation. Knowledge builds upon itself, thus involving what economists in their jargon call dynamic increasing returns. As summarized in this essays Part One of the Manual addresses in the foregoing perspective, (i) Innovation and technological evolution; (ii) The theory of the firm in evolving environments; (iii) The formalization of learning processes; (iv) the theory of production; (v) consumption patterns; (vi) economic interactions and the working of markets; and, (vii) The ensuing structures and evolution of industries. Further in this essay we sketch some fundamental topics of the macroeconomic and developmental research ahead, which we mean to explore in Part Two of the Manual, in progress. At the same time the reader is warned against multiple risks of ''normalization'' by which 'evolution' is reduced to sheer 'innovation', and the latter is handled by standard econometric instruments, which are inevitably bound to largely neglect, among other features, the emergence of novelty, coupled dynamics, profound heterogeneities at all levels, and various forms of complementarities. |
| Keywords: | Economic evolution; complex systems; technological and organizational innovation; heterogeneity; market processes; bounded rationality; organizational capabilities; routines and heuristics; theory of production; industrial structures. |
| Date: | 2022–09–21 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2022/24&r= |
| By: | Seung Hwan Kim; Jeong hwan Jeon; Anwar Aridi; Bogang Jun |
| Abstract: | This research aims to identify factors that affect the technological transition of firms toward industry 4.0 technologies (I4Ts) focusing on firm capabilities and policy impact using relatedness and complexity measures. For the analysis, a unique dataset of Korean manufacturing firms' patent and their financial and market information was used. Following the Principle of Relatedness, which is a recently shaped empirical principle in the field of economic complexity, economic geography, and regional studies, we build a technology space and then trace each firm's footprint on the space. Using the technology space of firms, we can identify firms that successfully develop a new industry 4.0 technology and examine whether their accumulated capabilities in their previous technology domains positively affect their technological diversification and which factors play a critical role in their transition towards industry 4.0. In addition, by combining data on whether the firms received government support for R&D activities, we further analyzed the role of government policy in supporting firms' knowledge activity in new industry 4.0 technologies. We found that firms with higher related technologies and more government support are more likely to enter new I4Ts. We expect our research to inform policymakers who aim to diversify firms' technological capabilities into I4Ts. |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2209.02239&r= |
| By: | Marco Guerzoni; Massimiliano Nuccio; Federico Tamagni |
| Abstract: | Innovation studies have largely recognized the role of knowledge in fostering innovation and growth of entrants. Previous literature has focused on entrepreneurial and managerial capabilities and education and knowledge incorporated in material and immaterial resources. We assume that new firms need to possess different pieces of knowledge, but beyond diversity, business performance relies also on knowledge distinctiveness. In other words, the complexity of a knowledge base is not simply the recombination of homogeneous pieces of knowledge but it also depends on the specific nature of each of them. This paper develops a new complexity indicator able to capture the complexity of the knowledge base by applying a topic modeling approach to the analysis of patent text. We explore the empirical relation between pre-entry complexity of knowledge, as measured by our complexity index, and post-entry growth performance of a sample of Italian firms entering the market in 2009-2011, which we then follow over the period 2012-2021. Baseline results show a significant and positive association between knowledge complexity and growth, even after controlling for firm characteristics and year, sector and region fixed-effects. Robustness analysis reveal this positive effect is stronger in the medium-long run while relatively weaker for innovative SMEs. |
| Keywords: | pre-entry knowledge base; complexity; text analysis; patents; firm growth; post-entry performance. |
| Date: | 2022–09–21 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2022/25&r= |
| By: | Matheus Eduardo Leusin |
| Abstract: | This paper investigates how the development of AI-related inventions by Multinational Enterprises (MNEs) affects their technological trajectories and innovative performance. I combine a matched-pair analysis with an extension of the Difference-in-Difference method to analyse these effects over a novel panel dataset of MNEs. This dataset links over 30 thousand MNEs to more than 10 million patents that these companies owned directly or indirectly (i.e., through their subsidiaries) in the period from 2011 to 2019. The results indicate that MNEs introducing AI-related inventions increase the relatedness of subsequent inventions by about 10 per cent compared to a control group. These results are robust when accounting for a self-selection bias. AI is thus being used to reinforce the existing technological trajectories, rather than to disrupt them. The results also suggest that the number of subsequent inventions is about 40 per cent higher for MNEs that introduce AI during the observation period compared to the control group, without significant effects on the intensity of R&D expenditures per invention. It is argued that this increase in innovative performance is linked not only to knowledge dynamics created by learning about AI but also by AI's technical potential to be used for learning. |
| Keywords: | Technological trajectory; Relatedness; Artificial Intelligence; Innovative performance |
| JEL: | D22 O14 O33 L25 |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:atv:wpaper:2201&r= |
| By: | Maciej Albinowski; Piotr Lewandowski |
| Abstract: | We study the age- and gender-specific labour market effects of two key modern technologies – Information and Communication Technologies (ICT), and robots – in 14 European countries between 2010-2018. To identify the causal effects of technology adoption, we utilize the variation of technology adoption between industries and apply the instrumental variables strategy proposed by Acemoglu and Restrepo (2020). We find that the adoption of ICT and robots increased the shares of young and prime-aged women in employment and wage bill of particular sectors, but reduced the shares of older women and prime-aged men. The negative effects were particularly pronounced for older women in cognitive occupations – who tend to have low ICT-related skills – and for young men in routine manual occupations who experienced substitution by robots. Between 2010 and 2018, the growth of ICT capital played a visibly larger role than robot adoption in explaining changes in labour market outcomes of demographic groups. |
| Keywords: | technological change, labour market outcomes, demographic groups, Europe |
| JEL: | J24 O33 J23 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:ibt:wpaper:wp042022&r= |
| By: | N. Aaron Pancost; Chen Yeh |
| Abstract: | In this note, we evaluate the sensitivity of commonly-used decompositions for aggregate productivity. Our analysis spans the universe of U.S. manufacturers from 1977 to 2012 and we find that, even holding the data and form of the production function fixed, results on aggregate productivity are extremely sensitive to how productivity at the firm level is measured. Even qualitative statements about the levels of aggregate productivity and the sign of the covariance between productivity and size are highly dependent on how production function parameters are estimated. Despite these difficulties, we uncover some consistent facts about productivity growth: (1) labor productivity is consistently higher and less error-prone than measures of multi-factor productivity; (2) most productivity growth comes from growth within firms, rather than from reallocation across firms; (3) what growth does come from reallocation appears to be driven by net entry, primarily from the exit of relatively less-productive firms. |
| Keywords: | aggregate productivity, growth, misallocation, entry, exit |
| JEL: | D24 E24 L60 |
| Date: | 2022–07 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:22-25&r= |
| By: | Jessica Birkholz |
| Abstract: | This study explores the regional innovation system characteristics that build the basis for the regional absorptive capacity of entrepreneurial knowledge. Regionalized patent data is combined with firm level and regional information for German regions over the period 1995 until 2015. Network analysis is applied to identify regional innovation system characteristics on three different layers: 1) cooperation between incumbent firms, 2) learning regimes, and 3) the technological knowledge base. Random forest analyses on basis of conditional inference classification trees are used to identify the most important characteristics for the regional absorption of entrepreneurial knowledge in general and on different efficiency levels. It is shown that characteristics on all three layers impact the regional absorption of entrepreneurial knowledge. Further, the direction and magnitude of the effect regional innovation system characteristics have on the regional knowledge absorption vary across different levels of absorption rates. It is concluded that for a successful implementation of policies to increase the impact of entrepreneurial knowledge on regional development, the regional innovation system needs to be monitored and adapted continuously. |
| Keywords: | Entrepreneurship, Regional absorptive capacity, Smart specialization |
| JEL: | L26 O33 D85 |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:atv:wpaper:2205&r= |
| By: | Haufler, Andreas (LMU Munich and CESifo); Schindler, Dirk (Erasmus University Rotterdam) |
| Abstract: | Many countries have introduced patent box regimes in recent years, offering a reduced tax rate to businesses for their IP-related income. In this paper, we analyze the effects of patent box regimes when countries can simultaneously use patent boxes and R&D subsidies to promote innovation. We show that when countries set their tax policies non-cooperatively, innovation is fostered, at the margin, only by the R&D subsidy, whereas the patent box tax rate is targeted at attracting international profit shifting. In equilibrium, patent box regimes emerge endogenously under policy competition, but never under policy coordination. We also compare the competition for mobile patents with the competition for mobile R&D units and show that enforcing a nexus principle is likely to reduce the aggressiveness of patent box regimes. |
| Keywords: | corporate taxation; profit shifting; patent boxes; R&D tax credits; tax competition; |
| JEL: | H25 H87 F23 |
| Date: | 2022–09–09 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:336&r= |
| By: | Jessica Birkholz; Jarina Kühn; Mariia Shkolnykova |
| Abstract: | This paper contributes to the discussion on exploration and exploitation by analyzing the innovation behavior of SMEs and large firms during the first year of the COVID-19 pandemic in Germany. It provides a novel way to measure the type of firm innovation behavior in a dynamically changing environment. After collecting news articles about innovation activities conducted by firms, we applied text mining techniques to identify the positioning of each firm on the continuum from exploitation to exploration. The results of our analyses indicate three main dynamics: 1) all studied firms tend to conduct more explorative innovation activities during the COVID-19 crisis, 2) large and "technology-intensive" firms are more prone to perform explorative innovation activities than SMEs and firms that are not "technology-intensive", and 3) technology intensity is associated with explorative innovation behavior during the crisis. Our results suggest that considering technology intensity and the size of firms is important for designing effective policies during crises. |
| Keywords: | COVID-19, Crisis, Innovation, SME, Text Mining, News Data, Exploration, Exploitation |
| JEL: | O31 O33 L25 |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:atv:wpaper:2203&r= |
| By: | Enghin Atalay; Sebastian Sotelo; Daniel I. Tannenbaum |
| Abstract: | We introduce new measurement tools to understand the sources of earnings differences across space. Based on the natural language employers use in job vacancy text, we develop granular measures of job tasks and of worker specialization. We find that jobs in larger commuting zones involve greater interpersonal interactions and have higher computer software requirements. Between 10 and 50 percent of task and technology variation between large and small commuting zones exists within occupations. Further, workers in larger markets are more specialized within occupations. Tasks, technologies, and worker specialization account for a substantial portion of the market size premium even within occupations. |
| JEL: | J20 J24 R12 R23 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30421&r= |
| By: | Jeon, Doh-Shin; Lefouili, Yassine; Madio, Leonardo |
| Abstract: | We study a platform’s incentives to delist IP-infringing products and the effects of holding the platform liable for the presence of such products on innovation and consumer welfare. For a given number of buyers on the platform, platform liability increases innovation by reducing the competitive pressure that innovative products face from IP-infringing products. However, platform liability can have unintended consequences, which can overturn this intended effect on innovation. Moreover, there can be a misalignment of interests between innovators and buyers as platform liability reduces consumer surplus for a given number of innovators. We also analyze how different types of cross-group network effects affect the impact of platform liability on innovation and consumer welfare. |
| Keywords: | Platform, Liability, Intellectual Property, Innovation. |
| JEL: | K40 K42 K13 L13 L86 |
| Date: | 2022–09–19 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:127344&r= |
| By: | Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio |
| Abstract: | In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–09–11 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:114526&r= |
| By: | Laurent BERGÉ; Thorsten DOHERR; Katrin HUSSINGER |
| Abstract: | How do intellectual property rights influence academic science? We investigate the consequences of the introduction of software patents in the U.S. on the publications of university researchers in the field of computer science. Difference-in-difference estimations reveal that software scientists at U.S. universities produced fewer publications (both in terms of quantity and quality) than their European counterparts after patent rights for software inventions were introduced. We then introduce a theoretical model that accounts for substitution and complementarity between patenting and publishing as well as for the direction of research. In line with the model’s prediction, further results show that the decrease in publications is largest for scientists at the bottom of the ability distribution. Further, we evidence a change in the direction of research following the reform towards more applied research. |
| Keywords: | patent rights, publications, economics of science, difference-in-difference estimation, model of science production |
| JEL: | I23 O31 O34 O38 L38 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:grt:bdxewp:2022-11&r= |
| By: | Dario Diodato; Ricardo Hausmann (Center for International Development at Harvard University); Ulrich Schetter (Center for International Development at Harvard University) |
| Abstract: | We revisit the well-known fact that richer countries tend to produce a larger variety of goods and analyze economic development through (export) diversification. We show that countries are more likely to enter ‘nearby’ industries, i.e., industries that require fewer new occupations. To rationalize this finding, we develop a small open economy (SOE) model of economic development at the extensive industry margin. In our model, industries differ in their input requirements of non-tradeable occupations or tasks. The SOE grows if profit maximizing firms decide to enter new, more advanced industries, which requires training workers in all occupations that are new to the economy. As a consequence, the SOE is more likely to enter nearby industries in line with our motivating fact. We provide indirect evidence in support of our main mechanism and then discuss implications: We show that there may be multiple equilibria along the development path, with some equilibria leading on a pathway to prosperity while others resulting in an income trap, and discuss implications for industrial policy. We finally show that the rise of China has a non-monotonic effect on the growth prospects of other developing countries, and provide suggestive evidence for this theoretical prediction. |
| Keywords: | economic complexity, economic convergence, export diversification, industrial policy, multiple equilibria, poverty trap, product space, structural change |
| JEL: | F43 O11 O14 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:cid:wpfacu:416&r= |
| By: | Sancho-Bosch, Diego; Guerrero, Alex J.; Heijs, Joost |
| Abstract: | This study analyses the differentiated effects of the public support for private R&D and innovation considering the financial situation of the firm. Two main questions are analyzed. Firstly, do the firms that have less access to funds for RDI –and therefore could depend more on the public support- get more frequently support? And, secondly, do such firms show a higher level of financial additionality than the firms with less financial restrictions? Despite of the fact that market failures imply basically that firms underinvest in R&D and often lack access to financial markets, only a few papers were detected that analyze the above-mentioned questions and present contradictory non-conclusive results. All of them used only one or two –often dummy- variables as indicator to measure the financial restrictions. Moreover, only four studies analyzed the intermediating role of the financial restriction on the policy impact in terms of the financial additionality and five measures its effect on the degree of participation. The main novelty of this paper is the simultaneous use of a broad set 17 different indicators (reflecting quantitative data on the firm’s liabilities or indebtedness, assets, and liquidity) directly derived from the firms’ balance sheet. These were clustered by a factor analysis in 7 synthetic indicators, which are used in an innovation policy evaluation framework based on the Propensity Score Matching Method. The main findings show that in Spain financial constraints negatively affect the access to public funds. There are significant differences between the level and cost of debt for both probability and financial additionality. Solvency indicators report that solvent firms are negatively discriminated for the likelihood of participation, however we find different effects for the impact depending on the public support that firms receive and their size. |
| Keywords: | Public policy, innovation, financial constraints, evaluation, financial additionality |
| JEL: | G32 H25 M48 O38 |
| Date: | 2022–06–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:114659&r= |