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on Technology and Industrial Dynamics |
| By: | Iorio, Roberto (CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy); D'Amore, Rosamaria (Link Campus University, Department of Human Sciences); Lubrano Lavadera, Giuseppe (Link Campus University, Department of Human Sciences) |
| Abstract: | Analyzing data from the 2020 Community Innovation Survey for Italy, we study the phenomenon of eco-innovation, that is the introduction of Innovations With Environmental Benefits (IWEBs). We aim to give an idea of the attitude of firms towards the changes deriving from climate change, of the magnitude of ecoinnovation phenomenon in Italy, of the benefits deriving from eco-innovations, of the reasons that induce firms to introduce them. We analyze whether and to what extent the importance attributed to environmental factors is effectively translated in the introduction of IWEBs, if and how the importance given to different motivations for introducing an IWEB is related to the number of benefits it generates. We also study if and how some characteristics of the firms, like sector, size, human capital, have a relationship with the probability to introduce an IWEB, both directly and influencing the motivations related to the eco-innovation. |
| Keywords: | Environmental economics; Eco-innovations; Determinants of innovation |
| JEL: | O31 Q55 Q58 |
| Date: | 2024–11–19 |
| URL: | https://d.repec.org/n?u=RePEc:sal:celpdp:0169 |
| By: | Cowx, Mary (Arizona State U); Lester, Rebecca (Stanford U); Nessa, Michelle (Michigan State U) |
| Abstract: | We study the tax payment and innovation consequences of limiting the tax deductibility of research and development (“R&D†) expenditures. Beginning in 2022, U.S. companies are required to capitalize and amortize R&D rather than immediately deduct these expenditures. We utilize variation in U.S. firms’ fiscal year ends to test the effects of the R&D tax change in a difference-in-differences framework. We first document that affected U.S. firms’ cash effective tax rates increase by 11.9 percentage points (62%), on average. We then test and find decreases in R&D investment among domestic-only, research-intensive, and constrained firms. In aggregate, these estimates translate to a reduction in R&D of $12.2 billion in the first year among the most research-intensive firms. Further, we observe decreased capital expenditures and share repurchases among affected companies, suggesting that firms also reduced other types of investment and shareholder payout to meet the increased cash tax liability. The paper provides policy relevant evidence about the significant real effects of limiting innovation tax incentives. |
| JEL: | H25 M41 M48 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:ecl:stabus:4192 |
| By: | Wenxiao WANG (Zhongnan University of Economics and Law); Shandre THANGAVELU (Sunway University, The University of Adelaide) |
| Abstract: | This study examines the relationship between city agglomeration and firm-level performance of global value chains (GVCs) in China. Using a novel dataset of night-time light data and survey data from Chinese manufacturing firms, the dynamic changes of urban agglomeration in China are studied, analysing their impact on firm-level productivity, GVC participation, and GVC upstreamness. The results highlight that the concentration of economic activity in urban areas can lead to productivity gains for firms, especially in the upstream stages of GVCs, which is characterised by higher value-added activities and better access to knowledge and technology. The study also finds that urban agglomeration promotes industrial specialisation and human capital spillovers, further improving the upstreamness of firms in GVCs. Firms in larger cities also tend to be more productive, participate more in GVCs, and are closer to the final demand of GVCs. |
| Keywords: | city agglomeration, global value chains, productivity, upstreamness, GVC participation |
| JEL: | F14 F23 |
| Date: | 2024–06–18 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-14 |
| By: | Campiglio, Emanuele; Spiganti, Alessandro; Wiskich, Anthony |
| Abstract: | Access to finance is a major barrier to clean innovation. We incorporate a financial sector in a directed technological change model, where research firms working on different technologies raise funding from financial intermediaries at potentially different costs. We show that, in addition to a rising carbon tax and a generous but short-lived clean research subsidy, optimal climate policies include a clean finance subsidy directly aimed at reducing the financing cost differential across technologies. The presence of an endogenous financing experience effect induces stronger mitigation efforts in the short-term to accelerate the convergence of heterogeneous financing costs. This is achieved primarily through a carbon price premium of 39% in 2025, relative to a case with no financing costs. |
| Keywords: | carbon tax; endogenous growth; green financial policy; innovation policy; low-carbon transition; optimal climate policy; sustainable finance |
| JEL: | H23 O31 Q55 Q58 G18 |
| Date: | 2024–11–30 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126063 |
| By: | Amadei, Claudia; Dosi, Cesare; Pintus, Francesco Jacopo |
| Abstract: | The decoupling of energy-related carbon emissions from economic growth has been mostly driven by reductions of the energy intensity of GDP, which can be attributed either to changes in countries’ economic structure or within-sector energy-efficiency improvements. One question is whether observed reductions in energy intensity may stem from shifts to less energy-intensive sectors without equivalent changes in consumption patterns, raising uncertainty on their true impact on global decarbonization. This paper aims to empirically investigate this mechanism in a panel of 15 OECD countries. First, using an Index Decomposition Analysis (IDA) including an offshoring factor, we show that structural changes in the production side have generally been unmatched with similar changes in consumption patterns. We then proxy a “demand-invariant structural change” in a Bayesian Structural Panel VAR model, by exploiting a novel measure given by the divergence between consumption-based and production-based carbon emissions. We find that shocks in this divergence measure are efficiently associated with demand-invariant structural changes and persistently and significantly reduce national energy intensity. Taken together, our results support the thought that caution should be taken when using production-based indicators to assess a country’s contribution to global carbon mitigation. |
| Keywords: | Climate Change, Environmental Economics and Policy, Sustainability |
| Date: | 2024–11–14 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:348101 |
| By: | Subash SASIDHARAN (Indian Institute of Technology Madras, Chennai, India); Shandre THANGAVELU (Sunway University, The University of Adelaide); Ketan REDDY (Indian Institute of Management Raipur, India) |
| Abstract: | In this study, we explore the impact of urban amenities and the global value chain (GVC) participation of Indian firms on their firm performance using firm-level data. The study uses micro-level data matching firms to urban amenities at the district level based on their district location. Using a panel data framework, we observe a positive relationship between urban amenities and the GVC participation of firms on their productivity performance. We also observe a positive impact of GVC participation on the productivity of firms, especially on their total factor productivity. In terms of channels, we observe the GVC impact through educational amenities on the productivity of the firms. This suggests education amenities increase the productive performance of GVC firms. We also observe that financial amenities tend to increase the productive performance of GVC firms. The results of the paper highlight the importance of urban amenities in affecting the productive performance of Indian firms in GVC activities. |
| Keywords: | Amenities Index; Global Value Chains: Manufacturing; TFP |
| JEL: | F14 F15 L6 |
| Date: | 2024–06–18 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-13 |
| By: | Wenxiao WANG (Zhongnan University of Economics and Law, China); Shandre Mugan THANGAVELU (Sunway University, Malaysia and the University of Adelaide, Australia) |
| Abstract: | : This paper uses detailed firm-level and transactional-level trade data to examine the causal relationship between digitalisation and servicification in Chinese manufacturing firms. Using the novel approach of text mining and analysis, this paper constructs two firmlevel measurements of digitalisation and servicification. Further, it explores the impact of digitalisation on services integration within manufacturing activities. We find digitalisation plays a crucial role in enhancing manufacturing servicification, enabling firms to produce and sell more service products. We also highlight that the two mechanisms through which digitalisation promotes servicification are digital technology and profitability. This paper contributes to the existing literature by developing the micro-level evidence of the digital transformation occurring within Chinese manufacturing firms and sheds light on the emerging services-led global value chain upgrading pattern. |
| Keywords: | digitalisation, servicification, manufacturing firms, text mining, text analysis |
| JEL: | F14 F23 |
| Date: | 2024–05–07 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-04 |
| By: | Thiemo Fetzer (University of Bonn & University of Warwick); Peter John Lambert (London School of Economics and Political Science); Bennet Feld (London School of Economics and Political Science); Prashant Garg (Imperial College Business School) |
| Abstract: | This paper leverages generative AI to build a network structure over 5, 000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step `build-prune' approach using an ensemble of prompt-tuned generative AI classifications. The 'build' step provides an initial distribution of edge-predictions, the `prune' step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade. |
| Keywords: | Supply-Chain Network Analysis, Large Language Models, On-shoring, Industrial Policy, Trade wars, Econometrics-of-LLMs |
| JEL: | F14 F23 L16 F52 O25 N74 C81 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:346 |