Pub Date : 2026-01-25DOI: 10.1016/j.strueco.2026.01.012
Qi Cui , ShiWen Yao , Chenyu Meng , Mahuaqing Zuo , Yu Liu
The concerns regarding the challenges of large-scale industrial robot applications to energy and environment systems have added uncertainty to this trend. This study utilized a dynamic computable general equilibrium (CGE) model to evaluate the economic and energy consequences of large-scale industrial robot applications in China’s manufacturing industry. This study found that industrial robot applications will substantially enhance the output value of China’s manufacturing sectors by raising their production efficiency. Meanwhile, the most of manufacturing sectors will experience a significant increase in electricity and primary energy consumption, leading to the increased carbon emissions in China. With the decomposition of electricity consumption, the direct electricity consumptions for all manufacturing sectors were positive, whereas the indirect ones were mostly negative. So, trade-offs between economic growth and carbon reduction exist in industrial robot applications. Therefore, a series of carbon reduction measures should be implemented alongside technological advancements to balance economic benefits and ecological costs.
{"title":"Energy and economic consequences of large-scale industrial robot applications in China’s manufacturing industry","authors":"Qi Cui , ShiWen Yao , Chenyu Meng , Mahuaqing Zuo , Yu Liu","doi":"10.1016/j.strueco.2026.01.012","DOIUrl":"10.1016/j.strueco.2026.01.012","url":null,"abstract":"<div><div>The concerns regarding the challenges of large-scale industrial robot applications to energy and environment systems have added uncertainty to this trend. This study utilized a dynamic computable general equilibrium (CGE) model to evaluate the economic and energy consequences of large-scale industrial robot applications in China’s manufacturing industry. This study found that industrial robot applications will substantially enhance the output value of China’s manufacturing sectors by raising their production efficiency. Meanwhile, the most of manufacturing sectors will experience a significant increase in electricity and primary energy consumption, leading to the increased carbon emissions in China. With the decomposition of electricity consumption, the direct electricity consumptions for all manufacturing sectors were positive, whereas the indirect ones were mostly negative. So, trade-offs between economic growth and carbon reduction exist in industrial robot applications. Therefore, a series of carbon reduction measures should be implemented alongside technological advancements to balance economic benefits and ecological costs.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 230-247"},"PeriodicalIF":5.5,"publicationDate":"2026-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-15DOI: 10.1016/j.strueco.2026.01.009
Tao Ma, Huaxin Zhong, Tiantian Wang, Junzhen Li, Hao Wang
Firm dynamics are a fundamental driver of regional productivity growth. This study examines how urban AI development shapes firm dynamics and regional productivity using Chinese city-level and firm registration data (2014–2023). We find AI stimulates both firm entry and exit while raising incumbent firm productivity. Mediation analysis shows that increased entry is the primary channel through which AI enhances regional productivity. Effects are stronger in eastern regions, core cities, and technology-intensive sectors. In some traditional industries, AI leads to significantly stronger exit than entry effects, and even reduces productivity in certain sectors. Spatial econometric results reveal AI attracts entry to specific locations (a “siphoning effect”) while reducing exit pressures elsewhere (a “buffering effect”). The research offers new evidence on how AI influences economic efficiency through firm reallocation, with implications for regional policy.
{"title":"Urban artificial intelligence, market turnover, and productivity","authors":"Tao Ma, Huaxin Zhong, Tiantian Wang, Junzhen Li, Hao Wang","doi":"10.1016/j.strueco.2026.01.009","DOIUrl":"10.1016/j.strueco.2026.01.009","url":null,"abstract":"<div><div>Firm dynamics are a fundamental driver of regional productivity growth. This study examines how urban AI development shapes firm dynamics and regional productivity using Chinese city-level and firm registration data (2014–2023). We find AI stimulates both firm entry and exit while raising incumbent firm productivity. Mediation analysis shows that increased entry is the primary channel through which AI enhances regional productivity. Effects are stronger in eastern regions, core cities, and technology-intensive sectors. In some traditional industries, AI leads to significantly stronger exit than entry effects, and even reduces productivity in certain sectors. Spatial econometric results reveal AI attracts entry to specific locations (a “siphoning effect”) while reducing exit pressures elsewhere (a “buffering effect”). The research offers new evidence on how AI influences economic efficiency through firm reallocation, with implications for regional policy.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 218-229"},"PeriodicalIF":5.5,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-11DOI: 10.1016/j.strueco.2026.01.007
Timothy A. Kohler , Adam Green , Scott G. Ortman
We use archaeological data on house sizes to generate estimates for economic inequality and economic growth from the Early Holocene to about the first millennium AD. At worldwide scales these variables are positively but loosely related; patterns are more divergent at regional levels. Cross-sectional regression shows that the formation of central-place hierarchies and development of landesque capital (indicating land-limited production) were positively linked to both economic growth and inequality; development of bronze smelting, animal management, and farming were also positively linked to growth. Iron smelting was linked to reduced inequality whereas presence of copper smelting and animals for portage were linked to reduced growth. We track the dynamics of inequality and growth through time in SW Asia/SE Europe, Britain, and SE North America, and analyze the first two with general additive models. Examination of three well-known interaction zones (Bronze Age West Asia, the Classic Maya world, and first-millennium-AD Britain) shows surprisingly regular transformations of the relationship between economic growth and inequality on millennial time scales. Overall our findings emphasize a strong cumulative component to both economic growth (productivity) and economic inequality over the substantial portions of the pre-capitalist Holocene that we analyze.
{"title":"Kuznets at -7000: Is there a really long-term relationship between growth and inequality?","authors":"Timothy A. Kohler , Adam Green , Scott G. Ortman","doi":"10.1016/j.strueco.2026.01.007","DOIUrl":"10.1016/j.strueco.2026.01.007","url":null,"abstract":"<div><div>We use archaeological data on house sizes to generate estimates for economic inequality and economic growth from the Early Holocene to about the first millennium AD. At worldwide scales these variables are positively but loosely related; patterns are more divergent at regional levels. Cross-sectional regression shows that the formation of central-place hierarchies and development of landesque capital (indicating land-limited production) were positively linked to both economic growth and inequality; development of bronze smelting, animal management, and farming were also positively linked to growth. Iron smelting was linked to reduced inequality whereas presence of copper smelting and animals for portage were linked to reduced growth. We track the dynamics of inequality and growth through time in SW Asia/SE Europe, Britain, and SE North America, and analyze the first two with general additive models. Examination of three well-known interaction zones (Bronze Age West Asia, the Classic Maya world, and first-millennium-AD Britain) shows surprisingly regular transformations of the relationship between economic growth and inequality on millennial time scales. Overall our findings emphasize a strong cumulative component to both economic growth (productivity) and economic inequality over the substantial portions of the pre-capitalist Holocene that we analyze.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 207-217"},"PeriodicalIF":5.5,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper tests whether dual-purpose policy promotes digital–green technology convergence (DGTC) by expanding domain-specific technological stocks within a policy impetus–technological accumulation–technological convergence framework. We evaluate this mechanism in the context of China’s Low-Carbon City Pilot (LCCP). Using a city–year panel of 264 Chinese prefecture-level cities from 2008–2023, DGTC is measured with two classic patent-based indicators—co-classification and cross-domain direct citation. The mediating mechanism is captured as digital and green technology accumulation through patent stocks and counts of innovating entities in both domains. Heterogeneity is examined with respect to policy implementation conditions, focusing on city endowments and the digital–green ecosystem. The empirical results show that the LCCP significantly increases DGTC, with consistent effects across both indicators and robust to multiple checks. Mediation analyses indicate that the LCCP raises digital and green accumulation, with stronger effects on the digital side and similar but milder effects on the green side. Heterogeneity tests reveal stronger effects in eastern and mega/large cities, as well as in contexts where intellectual property protection is tighter, network infrastructure more advanced, and government or public attention to green goals higher. Taken together, the study reaffirms that policy is an important driver of technological convergence. Using a nationwide, long-span city-level dataset, it constructs and validates two co-primary city-level DGTC measures with novel scope and comprehensive urban coverage, providing actionable evidence for designing and implementing context-specific policy portfolios.
{"title":"Towards technology-convergent cities: How does the low-carbon economy contribute?","authors":"Henglong Zhang , Yeheng Zhang , Yongwei Yu , Liming Ge","doi":"10.1016/j.strueco.2026.01.005","DOIUrl":"10.1016/j.strueco.2026.01.005","url":null,"abstract":"<div><div>This paper tests whether dual-purpose policy promotes digital–green technology convergence (DGTC) by expanding domain-specific technological stocks within a policy impetus–technological accumulation–technological convergence framework. We evaluate this mechanism in the context of China’s Low-Carbon City Pilot (LCCP). Using a city–year panel of 264 Chinese prefecture-level cities from 2008–2023, DGTC is measured with two classic patent-based indicators—co-classification and cross-domain direct citation. The mediating mechanism is captured as digital and green technology accumulation through patent stocks and counts of innovating entities in both domains. Heterogeneity is examined with respect to policy implementation conditions, focusing on city endowments and the digital–green ecosystem. The empirical results show that the LCCP significantly increases DGTC, with consistent effects across both indicators and robust to multiple checks. Mediation analyses indicate that the LCCP raises digital and green accumulation, with stronger effects on the digital side and similar but milder effects on the green side. Heterogeneity tests reveal stronger effects in eastern and mega/large cities, as well as in contexts where intellectual property protection is tighter, network infrastructure more advanced, and government or public attention to green goals higher. Taken together, the study reaffirms that policy is an important driver of technological convergence. Using a nationwide, long-span city-level dataset, it constructs and validates two co-primary city-level DGTC measures with novel scope and comprehensive urban coverage, providing actionable evidence for designing and implementing context-specific policy portfolios.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 185-206"},"PeriodicalIF":5.5,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-08DOI: 10.1016/j.strueco.2026.01.006
Xiaolong He , Zhuangxiong Yu , Yufan Liang
This paper studies how public data platforms affect city-level capital–labor allocation. Using panel data for 280 prefecture-level cities from 2008–2022, we exploit their staggered rollout in a difference-in-differences design treating platform launches as content-side information shocks. We find that platform adoption reduces city-level factor misallocation by roughly 23 percent relative to the pre-reform mean. The results are robust across specifications and to addressing endogeneity concerns. Further, results from the mechanism analysis indicate that platform adoption reduces misallocation via market-competition channels, including greater firm entry, deeper venture capital investment, and larger international trade volumes. Moreover, the impact is stronger in cities with less administrative fragmentation, greater dialect diversity, or more rugged terrain. Finally, spatial-econometric models indicate positive spillovers to neighboring cities, suggesting cross-city diffusion of information and practices. Overall, the findings suggest that public data platform acts as a low-distortion policy tool to improve urban factor allocation.
{"title":"Public data, market competition and resource misallocation","authors":"Xiaolong He , Zhuangxiong Yu , Yufan Liang","doi":"10.1016/j.strueco.2026.01.006","DOIUrl":"10.1016/j.strueco.2026.01.006","url":null,"abstract":"<div><div>This paper studies how public data platforms affect city-level capital–labor allocation. Using panel data for 280 prefecture-level cities from 2008–2022, we exploit their staggered rollout in a difference-in-differences design treating platform launches as content-side information shocks. We find that platform adoption reduces city-level factor misallocation by roughly 23 percent relative to the pre-reform mean. The results are robust across specifications and to addressing endogeneity concerns. Further, results from the mechanism analysis indicate that platform adoption reduces misallocation via market-competition channels, including greater firm entry, deeper venture capital investment, and larger international trade volumes. Moreover, the impact is stronger in cities with less administrative fragmentation, greater dialect diversity, or more rugged terrain. Finally, spatial-econometric models indicate positive spillovers to neighboring cities, suggesting cross-city diffusion of information and practices. Overall, the findings suggest that public data platform acts as a low-distortion policy tool to improve urban factor allocation.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 110-122"},"PeriodicalIF":5.5,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.strueco.2026.01.004
Paul Carrillo-Maldonado, Zoe Cruz
This paper analyzes the effect of minimum wage on the macroeconomic performance of Ecuador. We use narrative identification to obtain the structural changes because of minimum wage. We estimate the impulse response function to understand the dynamic response of output, prices, and unemployment to exogenous changes in the minimum wage through local projections and structural vector autoregressive. The main results show a positive response of the gross domestic product in the short term when the minimum wage increases. Other variables such as inflation, unemployment rate, and real wage do not respond to this shock.
{"title":"Macroeconomic consequences of minimum wage in a developing country","authors":"Paul Carrillo-Maldonado, Zoe Cruz","doi":"10.1016/j.strueco.2026.01.004","DOIUrl":"10.1016/j.strueco.2026.01.004","url":null,"abstract":"<div><div>This paper analyzes the effect of minimum wage on the macroeconomic performance of Ecuador. We use narrative identification to obtain the structural changes because of minimum wage. We estimate the impulse response function to understand the dynamic response of output, prices, and unemployment to exogenous changes in the minimum wage through local projections and structural vector autoregressive. The main results show a positive response of the gross domestic product in the short term when the minimum wage increases. Other variables such as inflation, unemployment rate, and real wage do not respond to this shock.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 137-148"},"PeriodicalIF":5.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.strueco.2026.01.001
Meichen Zhang, Yuan Wang
Amid rising uncertainty in global climate governance and increasingly difficult inter-state coordination, leveraging domestic specialization to convert efficiency gains into emissions reductions offers a feasible pathway. In this study, we develop a time-series global multi-regional input-output (MRIO) database embedding Chinese provinces, enabling subnational value chain decomposition and logarithmic mean divisia index (LMDI)-based analysis of energy intensity dynamics. This framework captures the spatiotemporal evolution of China’s energy intensity, identifies key inflection points across policy phases, and disentangles underlying drivers. Empirical results indicate that between 2003 and 2017, China experienced a decline in energy intensity across both production and consumption sides, with reductions of 69% and 60%, respectively. These improvements peaked during the 11th Five-Year Plan, as fossil-fuel-reliant, resource-intensive provinces cut energy intensity well above the national average. Interprovincial industrial linkages are a key channel driving energy-efficiency gains. Optimizing domestic value-chain coordination provides a feasible, efficiency-based mitigation margin under existing national burden-sharing.
{"title":"Unlocking the potential for energy efficiency across china's subnational value chains","authors":"Meichen Zhang, Yuan Wang","doi":"10.1016/j.strueco.2026.01.001","DOIUrl":"10.1016/j.strueco.2026.01.001","url":null,"abstract":"<div><div>Amid rising uncertainty in global climate governance and increasingly difficult inter-state coordination, leveraging domestic specialization to convert efficiency gains into emissions reductions offers a feasible pathway. In this study, we develop a time-series global multi-regional input-output (MRIO) database embedding Chinese provinces, enabling subnational value chain decomposition and logarithmic mean divisia index (LMDI)-based analysis of energy intensity dynamics. This framework captures the spatiotemporal evolution of China’s energy intensity, identifies key inflection points across policy phases, and disentangles underlying drivers. Empirical results indicate that between 2003 and 2017, China experienced a decline in energy intensity across both production and consumption sides, with reductions of 69% and 60%, respectively. These improvements peaked during the 11th Five-Year Plan, as fossil-fuel-reliant, resource-intensive provinces cut energy intensity well above the national average. Interprovincial industrial linkages are a key channel driving energy-efficiency gains. Optimizing domestic value-chain coordination provides a feasible, efficiency-based mitigation margin under existing national burden-sharing.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 168-184"},"PeriodicalIF":5.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.strueco.2025.12.012
Reda Cherif , Fuad Hasanov , Lichen Wang
We shed new light on the determinants of growth by tackling the blunt and weak instrument problems in the empirical growth literature. As an instrument for each endogenous variable, we propose average values of the same variable in neighboring countries. This method has the advantage of producing variable-specific and time-varying—namely, “sharp”—and strong instruments. We also introduce “bias norms” to test the sensitivity of the estimates to the potential invalidity of our instruments. The estimations show that export sophistication is a relatively robust determinant of growth compared to other standard growth determinants such as years of schooling, trade openness, private credit to the economy, and institutions as measured by law and order. Other growth determinants such as human capital quality and technological level of production may be important to the extent they help improve export sophistication.
{"title":"Sharp instrument: A stab at identifying the causes of economic growth","authors":"Reda Cherif , Fuad Hasanov , Lichen Wang","doi":"10.1016/j.strueco.2025.12.012","DOIUrl":"10.1016/j.strueco.2025.12.012","url":null,"abstract":"<div><div>We shed new light on the determinants of growth by tackling the blunt and weak instrument problems in the empirical growth literature. As an instrument for each endogenous variable, we propose average values of the same variable in neighboring countries. This method has the advantage of producing variable-specific and time-varying—namely, “sharp”—and strong instruments. We also introduce “bias norms” to test the sensitivity of the estimates to the potential invalidity of our instruments. The estimations show that export sophistication is a relatively robust determinant of growth compared to other standard growth determinants such as years of schooling, trade openness, private credit to the economy, and institutions as measured by law and order. Other growth determinants such as human capital quality and technological level of production may be important to the extent they help improve export sophistication.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 149-167"},"PeriodicalIF":5.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.strueco.2026.01.003
Yifei Li , Yuegang Song , Chien-Chiang Lee
In the context of increasing global economic uncertainty, promoting the deep integration of artificial intelligence technology and the real economy has become a core concern for ensuring the safety of the manufacturing industry chain and advancing high-quality development. However, how industrial robot adoption (IRA) can empower global value chain (GVC) resilience, its mechanisms of action and boundaries of influence remain to be clarified as a major practical issue that requires urgent investigation. To examine this issue, this study uses the World Industrial Robot Database from the International Federation of Robotics, World Bank World Development Indicators and Organisation for Economic Cooperation and Development (OECD) input–output tables to construct a three-dimensional, country–industry–year panel covering nine manufacturing industries in 53 countries from 2000 to 2018. We quantify manufacturing GVCs’ resilience from safety and stability dimensions and systematically examine the influence of IRA. The findings reveal that IRA can significantly improve manufacturing GVCs’ overall resilience, which remains valid following a series of robustness and endogeneity tests. Further analysis reveals that this enabling effect is more prominent for labour- and technology-intensive industries, OECD countries and high import-dependent countries. Mechanism analysis confirms that IRA primarily enhances GVCs’ resilience through three channels of labour substitution, reduced trade costs and promoting technological innovation. In addition, our spatial econometric model results demonstrate that the impact of IRA not only benefits the country but also has a positive driving effect on neighbouring countries’ GVC resilience through significant positive spatial spillover effects. This study provides new insights into the evolution of manufacturing GVCs in the era of Industry 4.0 and offers valuable empirical evidence and decision-making guidance for countries to advance GVC upgrading.
{"title":"Industrial robot adoption and the resilience of manufacturing global value chains","authors":"Yifei Li , Yuegang Song , Chien-Chiang Lee","doi":"10.1016/j.strueco.2026.01.003","DOIUrl":"10.1016/j.strueco.2026.01.003","url":null,"abstract":"<div><div>In the context of increasing global economic uncertainty, promoting the deep integration of artificial intelligence technology and the real economy has become a core concern for ensuring the safety of the manufacturing industry chain and advancing high-quality development. However, how industrial robot adoption (IRA) can empower global value chain (GVC) resilience, its mechanisms of action and boundaries of influence remain to be clarified as a major practical issue that requires urgent investigation. To examine this issue, this study uses the World Industrial Robot Database from the International Federation of Robotics, World Bank World Development Indicators and Organisation for Economic Cooperation and Development (OECD) input–output tables to construct a three-dimensional, country–industry–year panel covering nine manufacturing industries in 53 countries from 2000 to 2018. We quantify manufacturing GVCs’ resilience from safety and stability dimensions and systematically examine the influence of IRA. The findings reveal that IRA can significantly improve manufacturing GVCs’ overall resilience, which remains valid following a series of robustness and endogeneity tests. Further analysis reveals that this enabling effect is more prominent for labour- and technology-intensive industries, OECD countries and high import-dependent countries. Mechanism analysis confirms that IRA primarily enhances GVCs’ resilience through three channels of labour substitution, reduced trade costs and promoting technological innovation. In addition, our spatial econometric model results demonstrate that the impact of IRA not only benefits the country but also has a positive driving effect on neighbouring countries’ GVC resilience through significant positive spatial spillover effects. This study provides new insights into the evolution of manufacturing GVCs in the era of Industry 4.0 and offers valuable empirical evidence and decision-making guidance for countries to advance GVC upgrading.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 93-109"},"PeriodicalIF":5.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.strueco.2026.01.002
Gabriel Lozano-Reina , Gregorio Sánchez-Marín , J. Samuel Baixauli-Soler
Next Generation EU (NGEU) funds represent a large-scale public investment aimed at mitigating the economic impact of COVID-19 and advancing industrial modernization across the European Union. This study analyzes their early effects in Spain through three objectives: (i) to provide an integrated overview of the design and industrial orientation of the Spain Can Plan, including the role of Industrial Policy Spain 2030 and PERTEs as mission-oriented instruments; (ii) to examine the macro-level implementation of NGEU funds across strategic policy levers, beneficiaries, and regions; and (iii) to assess how sectoral patterns and firm-level characteristics shape the absorption of support. Evidence from the ELISA and SABI databases shows pronounced territorial and sectoral asymmetries, with energy-related and capital-intensive activities receiving a high share of resources. At the firm level, funding allocation is closely linked to pre-existing structural capabilities, whilst post-COVID financial indicators point to improvements in profitability, productivity, and financial stability. The study concludes with policy recommendations to strengthen Spain’s industrial modernization and its strategic positioning in the global economy.
{"title":"Next Generation EU and industrial transformation: Evidence from Spain","authors":"Gabriel Lozano-Reina , Gregorio Sánchez-Marín , J. Samuel Baixauli-Soler","doi":"10.1016/j.strueco.2026.01.002","DOIUrl":"10.1016/j.strueco.2026.01.002","url":null,"abstract":"<div><div>Next Generation EU (NGEU) funds represent a large-scale public investment aimed at mitigating the economic impact of COVID-19 and advancing industrial modernization across the European Union. This study analyzes their early effects in Spain through three objectives: (i) to provide an integrated overview of the design and industrial orientation of the Spain Can Plan, including the role of Industrial Policy Spain 2030 and PERTEs as mission-oriented instruments; (ii) to examine the macro-level implementation of NGEU funds across strategic policy levers, beneficiaries, and regions; and (iii) to assess how sectoral patterns and firm-level characteristics shape the absorption of support. Evidence from the ELISA and SABI databases shows pronounced territorial and sectoral asymmetries, with energy-related and capital-intensive activities receiving a high share of resources. At the firm level, funding allocation is closely linked to pre-existing structural capabilities, whilst post-COVID financial indicators point to improvements in profitability, productivity, and financial stability. The study concludes with policy recommendations to strengthen Spain’s industrial modernization and its strategic positioning in the global economy.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 123-136"},"PeriodicalIF":5.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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