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on Technology and Industrial Dynamics |
| By: | Christoph Grimpe; Fuad Hasanov; Wolfgang Sofka; Geoffrey Borchardt; Philip Schulz |
| Abstract: | A well-functioning market for technology, or ideas, is an important determinant for the type, scope, and distribution of innovation activities. We use a panel of 20 industries across 24 European countries to study the key determinants driving the market for technology. We explore whether the expenditures on external knowledge depends on the sectoral pattern of innovation and an industry’s distance to the global technological frontier. Disseminating knowledge and technology within the industry, bringing it closer to the global technological frontier, tends to reduce the expenditures for external knowledge except in supplier-dominated industries. We also find important complementarity effects in the market for external knowledge. Industries with high R&D spending, with increasingly large firms, and with large investments in machinery and software foster growth of the market for technology. Our findings suggest tailoring innovation policies to help expand both the size of the market for technology and the use of these markets in specific industries. |
| Keywords: | Markets for technology; patterns of innovation; industry studies; R&D; external knowledge; industrial policy |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/020 |
| By: | Eric BOND; HOANG Trang; MA Yan; MAKIOKA Ryo |
| Abstract: | The paper studies the effect of R&D investments by parent multinational corporations (MNC) and their affiliates on the decisions of those affiliates to purchase intermediate inputs across different locations. We first develop a theoretical model of R&D and sourcing decisions to provide potential mechanisms and to guide our empirical analysis. Our fixed-effects regression results imply that, first, higher affiliate R&D expenditures are associated with a higher share of the affiliate’s purchases from local firms. Second, higher R&D expenditures by affiliates in other countries (i.e., those under the same parent firm but located in a different foreign country) are associated with a higher share of affiliate purchases from those countries. Third, we find that the affiliate’s R&D expenditures are negatively correlated with the purchase share from the parent home country and from the parent firm. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25007 |
| By: | FUKUGAWA Nobuya; CHANG Kuo-I |
| Abstract: | The establishment and expansion of science parks have been pivotal to Taiwan's economic development. This study integrates administrative, financial, and patent data to evaluate the causal impact of Taiwan’s three major science parks—Hsinchu, Central, and Southern—on tenant firms across three types of additionality: input, behavioral, and output. Specifically, it investigates whether relocating to science parks significantly enhances R&D investment, PhD employment, total factor productivity, and patent quality. To address challenges like staggered firm entry and selection bias, the study employs augmented inverse probability weighting combined with a difference-in-differences model for panel data with staggered treatments, ensuring robust causal inference. The findings reveal significantly positive effects across all three types of additionality, extending beyond the Hsinchu Science-based Industrial Park. By integrating multiple value-adding channels and expanding the analysis to all three major science parks, this research provides a comprehensive evaluation and extends the scope of previous studies. Additionally, it highlights heterogeneity in effects by firm size and industry, underscoring the need for tailored policies to maximize the benefits of science parks. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25005 |
| By: | Ruiz, Walter; Spinola, Danilo; Villalba, Maria Luisa |
| Abstract: | This paper develops an Agent-Based Model (ABM) to study the impact of Science, Technology, and Innovation (STI) policies on innovation systems. The model, which we call the Adaptive Innovation System Model (AdaptISM), simulates the technological innovation capabilities required for knowledge and technology generation, diffusion, and utilisation, integrating decision rules that capture the emergent behaviours of agents interacting with innovation opportunities. The model is empirically validated using data from the coffee and avocado agricultural production chains (APCs) in Antioquia, Colombia, which are two sectors of regional economic and local importance. The validation process allows the evaluation of individual and combined STI policy modes, identifying which policy strategies most effectively enhance innovation performance and economic outcomes. By enabling the exploration of “what-if” scenarios, the ABM provides a tool to assess STI policy contributions systematically and offers practical insights into resource allocation in local innovation systems. This approach addresses a critical challenge in innovation policy design: understanding how STI policies influence system performance. The findings highlight the utility of combining policy approaches to improve innovation and economic growth, offering a replicable framework for policymakers and researchers seeking to optimise the performance of innovation systems. |
| Keywords: | STI policy; innovation systems; agricultural production chains; Agent-based modelling |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:akf:cafewp:32 |
| By: | Matthew R. Denes; Spyridon Lagaras; Margarita Tsoutsoura |
| Abstract: | Platform intermediation of goods and services has considerably transformed the U.S. economy. We use administrative data on U.S. tax returns to study the role of the gig economy on entrepreneurship. We find that gig workers are more likely to become entrepreneurs, particularly those who are lower income, younger, and benefit from flexibility. We track all newly created firms and show that gig workers start firms in similar industries as their gig experience, which are less likely to survive and demonstrate higher performance. Overall, our findings suggest on-the-job learning promotes entrepreneurial entry and shifts the types of firms started by entrepreneurs. |
| JEL: | G30 J21 J22 J24 L26 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33347 |
| By: | Fuinhas, José Alberto; Javed, Asif; Sciulli, Dario; Valentini, Edilio |
| Abstract: | Governments across the globe are implementing stricter environmental policies to combat climate change and promote sustainability. This study contributes to the growing literature exploring the influence of environmental policy on skill-biased employment across various occupations. Specifically, we examine the causal effect of the revised version of Environmental Policy Stringency Index (EPS) and its components on skill-biased employment, focusing on occupations such as managers, professionals, technicians, and manual workers across 21 European economies from 2008 to 2020. Using the Method of Moments Quantile Regression (MMQR), the findings reveal that stringent environmental policies affect employment shares across different occupational categories. Skilled workers tend to benefit more from such policies, with a notable increase in the employment of professionals across all policy measures and a more differentiated impact among technicians and managers. In contrast, manual workers are generally adversely affected by environmental policies. These asymmetric effects on occupations exacerbate labour market inequalities, including disparities in employment levels and potential earnings. This research highlights the importance of designing tailored policies to mitigate adverse labour market outcomes while facilitating a transition to sustainable economic practices. |
| Keywords: | Climate Change, Environmental Economics and Policy, Labor and Human Capital, Sustainability |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:349167 |
| By: | Prashant Garg; Thiemo Fetzer |
| Abstract: | We analyze over 44, 000 NBER and CEPR working papers from 1980 to 2023 using a custom language model to construct knowledge graphs that map economic concepts and their relationships. We distinguish between general claims and those documented via causal inference methods (e.g., DiD, IV, RDD, RCTs). We document a substantial rise in the share of causal claims-from roughly 4% in 1990 to nearly 28% in 2020-reflecting the growing influence of the "credibility revolution." We find that causal narrative complexity (e.g., the depth of causal chains) strongly predicts both publication in top-5 journals and higher citation counts, whereas non-causal complexity tends to be uncorrelated or negatively associated with these outcomes. Novelty is also pivotal for top-5 publication, but only when grounded in credible causal methods: introducing genuinely new causal edges or paths markedly increases both the likelihood of acceptance at leading outlets and long-run citations, while non-causal novelty exhibits weak or even negative effects. Papers engaging with central, widely recognized concepts tend to attract more citations, highlighting a divergence between factors driving publication success and long-term academic impact. Finally, bridging underexplored concept pairs is rewarded primarily when grounded in causal methods, yet such gap filling exhibits no consistent link with future citations. Overall, our findings suggest that methodological rigor and causal innovation are key drivers of academic recognition, but sustained impact may require balancing novel contributions with conceptual integration into established economic discourse. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.06873 |
| By: | Diego A. Comin; Xavier Cirera; Marcio Cruz |
| Abstract: | This paper examines technology sophistication in establishments. To comprehensively measure technology sophistication, we create a grid that covers key business functions and the technologies used to conduct them. Analyzing data from over 21, 000 establishments in 15 countries, we find that the most widely used technology is usually not the most sophisticated available in the business function. There is significant variation in technology sophistication across and within countries, explaining 31% of productivity dispersion and over half of the agricultural productivity gap. The sophistication of widely used technologies is more relevant for productivity than the most advanced technologies. More sophisticated technologies are appropriate for both developed and developing countries. |
| JEL: | O1 O3 O4 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33358 |
| By: | Vanya Georgieva |
| Abstract: | Industrial policy has gained popularity in recent years and across all regions and income levels. Consequently, it is increasingly important to understand how governments choose the sectors they target. This analysis explores the role of domestic production networks in sector targeting, while controlling for other sector and global value chain characteristics. Combining datasets on industrial policy (Global Trade Alert) and input-output linkages (ICIO, OECD) provides novel insight into the network features of industrial policy. In particular, a sector’s ‘centrality’—i.e., its degree of connectedness - within the domestic production network is an important and significant predictor of sector intervention. The results indicate that industrial policy is used differently across regions, income groups, time periods, and types of policy tools. Notably, emerging economies tend to target more central sectors, while advanced economies target less central ones, on average. However, there has been a global shift toward more central sectors over time. Lastly, subsidies are deployed on more central sectors, while tariffs are used on less central ones. |
| Keywords: | Industrial Policy; Trade Policy; Subsidies; Global Value Chains; Production Networks; Spillovers |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/023 |
| By: | Casey O. Barkan |
| Abstract: | It is widely assumed that increases in economic productivity necessarily lead to economic growth. In this paper, it is shown that this is not always the case. An idealized model of an economy is presented in which a new technology allows capital to be utilized autonomously without labor input. This is motivated by the possibility that advances in artificial intelligence (AI) will give rise to AI agents that act autonomously in the economy. The economic model involves a single profit-maximizing firm which is a monopolist in the product market and a monopsonist in the labor market. The new automation technology causes the firm to replace labor with capital in such a way that its profit increases while total production decreases. The model is not intended to capture the structure of a real economy, but rather to illustrate how basic economic mechanisms can give rise to counterintuitive and undesirable outcomes. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.15718 |