This paper examines how technological progress in either green or fossil energy affects the consumption of both energy types within a neoclassical growth model that explicitly separates energy inputs—unlike the original Saunders (1992) framework. By incorporating substitution elasticities between production factors, we investigate whether improvements in one sector genuinely displace fossil fuels or instead generate structural rebound effects that increase total energy use. Using alternative functional forms—Cobb–Douglas and nested CES—we show that when the elasticity of substitution exceeds one, technological progress in either green or fossil energy can amplify the use of one or even both energy types, potentially triggering backfire effects, whereas low substitution elasticities moderate this impact. These findings highlight that the environmental effectiveness of technological change depends critically on production structures and substitution possibilities, offering policy-relevant insights for managing systemic rebound mechanisms.
{"title":"Unraveling the interplay of substitution elasticities and the green energy rebound effect","authors":"Verónica Acurio Vásconez , Mónica Pereira Henriques","doi":"10.1016/j.strueco.2025.10.007","DOIUrl":"10.1016/j.strueco.2025.10.007","url":null,"abstract":"<div><div>This paper examines how technological progress in either green or fossil energy affects the consumption of both energy types within a neoclassical growth model that explicitly separates energy inputs—unlike the original Saunders (1992) framework. By incorporating substitution elasticities between production factors, we investigate whether improvements in one sector genuinely displace fossil fuels or instead generate structural rebound effects that increase total energy use. Using alternative functional forms—Cobb–Douglas and nested CES—we show that when the elasticity of substitution exceeds one, technological progress in either green or fossil energy can amplify the use of one or even both energy types, potentially triggering backfire effects, whereas low substitution elasticities moderate this impact. These findings highlight that the environmental effectiveness of technological change depends critically on production structures and substitution possibilities, offering policy-relevant insights for managing systemic rebound mechanisms.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 717-725"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360994","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 : 2025-12-01Epub Date: 2025-05-03DOI: 10.1016/j.strueco.2025.05.004
Yunhua Xiang , Rong Huang
This paper investigates the impact of social security contributions on firms’ human capital structure, utilizing data from listed companies in China between 2012 and 2019. The empirical results suggest that social security contributions have a significant positive impact on the human capital structure of enterprises, and this finding persists through a series of robustness tests. This enhancement effect can be explained by dynamic capability theory, which is primarily reflected in human resource development and technical resource optimization. The heterogeneity test indicates that the effect of social security contributions on the enhancement of the human capital structure is more pronounced in technology-intensive, non-state-owned, and small-scale firms. Furthermore, the advancement of the digital economy exerts a positive moderating effect, varying across different levels of human capital skills. The economic consequences analysis indicates that the enhancement of human capital structure due to social security contributions not only enhances corporate governance but also drives the improvement of regional industrial structure. To enhance social security contributions and optimize the human capital structure within firms, it is recommended that businesses focus on the impact of social security contributions and actively fulfill their responsibilities regarding these payments. Concurrently, the government should develop differentiated social security contribution policies and promote the growth of the digital economy across various regions to effectively support social security services and improve the labor capital structure.
{"title":"Social security contributions and firms’ human capital structure: Evidence from China","authors":"Yunhua Xiang , Rong Huang","doi":"10.1016/j.strueco.2025.05.004","DOIUrl":"10.1016/j.strueco.2025.05.004","url":null,"abstract":"<div><div>This paper investigates the impact of social security contributions on firms’ human capital structure, utilizing data from listed companies in China between 2012 and 2019. The empirical results suggest that social security contributions have a significant positive impact on the human capital structure of enterprises, and this finding persists through a series of robustness tests. This enhancement effect can be explained by dynamic capability theory, which is primarily reflected in human resource development and technical resource optimization. The heterogeneity test indicates that the effect of social security contributions on the enhancement of the human capital structure is more pronounced in technology-intensive, non-state-owned, and small-scale firms. Furthermore, the advancement of the digital economy exerts a positive moderating effect, varying across different levels of human capital skills. The economic consequences analysis indicates that the enhancement of human capital structure due to social security contributions not only enhances corporate governance but also drives the improvement of regional industrial structure. To enhance social security contributions and optimize the human capital structure within firms, it is recommended that businesses focus on the impact of social security contributions and actively fulfill their responsibilities regarding these payments. Concurrently, the government should develop differentiated social security contribution policies and promote the growth of the digital economy across various regions to effectively support social security services and improve the labor capital structure.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 82-93"},"PeriodicalIF":5.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935613","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 : 2025-12-01Epub Date: 2025-09-09DOI: 10.1016/j.strueco.2025.08.001
Julia Jabłońska , Jakub Mućk
We investigate the main drivers of automation in Poland. Using a unique occupation–firm level dataset with direct measures of automation, we subsequently document a series of stylized facts on firms’ past and planned adoption of automation technologies. The adoption extends well beyond the manufacturing — reaching industries from agriculture and retail to professional and business services, with intensity highest in sectors that previously attracted FDI and slightly less pronounced in R&D-oriented industries. Despite substantial industry- and occupation-level differences, much of the variation in automation can be attributed to firm-level heterogeneity within industries. More productive firms tend to exhibit not only higher current levels of automation, but also greater potential for further adoption — resulting, on average, in a larger gap between where they are now and what remains feasible. Large firms are more likely to automate, as fixed costs associated with automation are more easily absorbed by larger enterprises. We also find some evidence supporting a learning-by-exporting mechanism: a higher propensity to automate is observed among exporting firms. However, the link between exporting status and automation is quite heterogeneous and depends crucially on the nature of trade linkages. In general, exporters specialized in producing intermediates at early stages of GVC (forward linkages) lag behind their counterparts that are closer to final demand (backward participation). Finally, our results suggest a significant appetite for further automation because more advanced adopters appear more likely to continue automating their production.
{"title":"Appetite for Destruction. A firm-level portrait of automation in Poland","authors":"Julia Jabłońska , Jakub Mućk","doi":"10.1016/j.strueco.2025.08.001","DOIUrl":"10.1016/j.strueco.2025.08.001","url":null,"abstract":"<div><div>We investigate the main drivers of automation in Poland. Using a unique occupation–firm level dataset with direct measures of automation, we subsequently document a series of stylized facts on firms’ past and planned adoption of automation technologies. The adoption extends well beyond the manufacturing — reaching industries from agriculture and retail to professional and business services, with intensity highest in sectors that previously attracted FDI and slightly less pronounced in R&D-oriented industries. Despite substantial industry- and occupation-level differences, much of the variation in automation can be attributed to firm-level heterogeneity within industries. More productive firms tend to exhibit not only higher current levels of automation, but also greater potential for further adoption — resulting, on average, in a larger gap between where they are now and what remains feasible. Large firms are more likely to automate, as fixed costs associated with automation are more easily absorbed by larger enterprises. We also find some evidence supporting a learning-by-exporting mechanism: a higher propensity to automate is observed among exporting firms. However, the link between exporting status and automation is quite heterogeneous and depends crucially on the nature of trade linkages. In general, exporters specialized in producing intermediates at early stages of GVC (forward linkages) lag behind their counterparts that are closer to final demand (backward participation). Finally, our results suggest a significant appetite for further automation because more advanced adopters appear more likely to continue automating their production.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 391-402"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048198","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 : 2025-12-01Epub Date: 2025-05-07DOI: 10.1016/j.strueco.2025.04.007
Alessandro Agnesi , Alberto Russo
This paper examines how inflation affects income redistribution within the economy – considering household heterogeneity in terms of income sources, debt levels and consumption preferences – by employing an agent-based stock-flow consistent (AB-SFC) macroeconomic model. In particular, we investigate the consequences of an increase in firms’ intermediate costs on income inequality and key macroeconomic and financial variables. Four channels through which an increase in price affects functional and inter-personal distribution are explored: (i) the inflation inequality channel, (ii) the profit–wage channel, (iii) the macroeconomic activity channel, and (iv) the indebtedness channel. Rising inflation dampens overall economic performance, resulting in increased unemployment, higher prices, and higher income inequality. Our analysis also indicates that rising household debt, driven by the indebtedness channel and resulting from efforts to maintain consumption, poses risks to financial stability. Furthermore, we find that, in the context of market concentration, the markup of systemically significant sectors serves as a primary conduit for redistribution in response to inflationary pressures. This ultimately influences the extent of unemployment, the persistence of inflationary trends, and the magnitude of redistribution.
{"title":"Redistribution through inflation: A multi-sector approach to income dynamics","authors":"Alessandro Agnesi , Alberto Russo","doi":"10.1016/j.strueco.2025.04.007","DOIUrl":"10.1016/j.strueco.2025.04.007","url":null,"abstract":"<div><div>This paper examines how inflation affects income redistribution within the economy – considering household heterogeneity in terms of income sources, debt levels and consumption preferences – by employing an agent-based stock-flow consistent (AB-SFC) macroeconomic model. In particular, we investigate the consequences of an increase in firms’ intermediate costs on income inequality and key macroeconomic and financial variables. Four channels through which an increase in price affects functional and inter-personal distribution are explored: (i) the inflation inequality channel, (ii) the profit–wage channel, (iii) the macroeconomic activity channel, and (iv) the indebtedness channel. Rising inflation dampens overall economic performance, resulting in increased unemployment, higher prices, and higher income inequality. Our analysis also indicates that rising household debt, driven by the indebtedness channel and resulting from efforts to maintain consumption, poses risks to financial stability. Furthermore, we find that, in the context of market concentration, the markup of systemically significant sectors serves as a primary conduit for redistribution in response to inflationary pressures. This ultimately influences the extent of unemployment, the persistence of inflationary trends, and the magnitude of redistribution.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 69-81"},"PeriodicalIF":5.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931792","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}
Integrating intelligent technologies into corporate processes represents a transformative response to sustainable and responsible business practices. Despite its growing significance, the effects and mechanisms through which intelligent transformation impacts corporate environmental, social, and governance (ESG) performance remain insufficiently explored. Drawing on resource orchestration and dynamic capabilities theory, this study develops a theoretical framework to analyze how intelligent transformation empowers ESG improvement. Using a comprehensive dataset of Chinese A-share listed companies from 2009 to 2023, the empirical results confirm that intelligent transformation significantly enhances ESG performance. This improvement is realized through three key channels: enhancing information disclosure quality, fostering green innovation, and mitigating supply chain concentration. Furthermore, the effects are more pronounced among state-owned enterprises, technology- and capital-intensive corporations, corporations located in the eastern area of China, and those operating in highly marketized regions. A value chain analysis further reveals that intelligent transformation in research design, manufacturing, and marketing consistently drives ESG enhancements. These findings enrich the literature on intelligent transformation and provide actionable insights for corporations seeking to optimize their sustainability practices in an intelligence era.
{"title":"Driving environmental, social, and governance excellence: The direct and indirect effects of intelligent transformation","authors":"Yuhang Chen , Yilin Zhong , Feng Xu , Qinghua Zhang","doi":"10.1016/j.strueco.2025.08.008","DOIUrl":"10.1016/j.strueco.2025.08.008","url":null,"abstract":"<div><div>Integrating intelligent technologies into corporate processes represents a transformative response to sustainable and responsible business practices. Despite its growing significance, the effects and mechanisms through which intelligent transformation impacts corporate environmental, social, and governance (ESG) performance remain insufficiently explored. Drawing on resource orchestration and dynamic capabilities theory, this study develops a theoretical framework to analyze how intelligent transformation empowers ESG improvement. Using a comprehensive dataset of Chinese A-share listed companies from 2009 to 2023, the empirical results confirm that intelligent transformation significantly enhances ESG performance. This improvement is realized through three key channels: enhancing information disclosure quality, fostering green innovation, and mitigating supply chain concentration. Furthermore, the effects are more pronounced among state-owned enterprises, technology- and capital-intensive corporations, corporations located in the eastern area of China, and those operating in highly marketized regions. A value chain analysis further reveals that intelligent transformation in research design, manufacturing, and marketing consistently drives ESG enhancements. These findings enrich the literature on intelligent transformation and provide actionable insights for corporations seeking to optimize their sustainability practices in an intelligence era.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 313-331"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932000","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 : 2025-12-01Epub Date: 2025-05-03DOI: 10.1016/j.strueco.2025.05.001
Fahd Boundi-Chraki , Ignacio Perrotini-Hernández
Based on the general law of capitalist accumulation and its theoretical mechanisms, this paper aims to examine the relationship between automation and employment across several sectors in 42 countries from 2000 to 2014. Using data from the World Input-Output Database (WIOD), vertically integrated labour productivity and vertically integrated capital-output ratio are computed as indices to measure the impact of technological change and mechanisation on sectoral employment dynamics. To address potential endogeneity, cross-sectional dependence, and slope heterogeneity in data, the dynamic panel Generalised Method of Moments (GMM) combined with the Common Correlated Effect (CCE) is applied. The sample is divided into advanced and emerging economies to identify disparities related to the developmental degree of the countries under investigation, while industries are distinguished to determine which are more vulnerable to automation. The empirical findings support the hypothesis of labour-saving technological progress and mechanisation, consistent with classical political economy and Marxian theories.
{"title":"Re-examining the automation-employment nexus from a classical political economy approach","authors":"Fahd Boundi-Chraki , Ignacio Perrotini-Hernández","doi":"10.1016/j.strueco.2025.05.001","DOIUrl":"10.1016/j.strueco.2025.05.001","url":null,"abstract":"<div><div>Based on the general law of capitalist accumulation and its theoretical mechanisms, this paper aims to examine the relationship between automation and employment across several sectors in 42 countries from 2000 to 2014. Using data from the World Input-Output Database (WIOD), vertically integrated labour productivity and vertically integrated capital-output ratio are computed as indices to measure the impact of technological change and mechanisation on sectoral employment dynamics. To address potential endogeneity, cross-sectional dependence, and slope heterogeneity in data, the dynamic panel Generalised Method of Moments (GMM) combined with the Common Correlated Effect (CCE) is applied. The sample is divided into advanced and emerging economies to identify disparities related to the developmental degree of the countries under investigation, while industries are distinguished to determine which are more vulnerable to automation. The empirical findings support the hypothesis of labour-saving technological progress and mechanisation, consistent with classical political economy and Marxian theories.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 32-51"},"PeriodicalIF":5.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931793","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 : 2025-12-01Epub Date: 2025-11-08DOI: 10.1016/j.strueco.2025.11.001
Samantha Coccia , Mauro Gallegati , Alberto Russo
This paper examines the impact of macro prudential policies on financial stability and inequality, focusing on the effects of debt service-to-income (DTI) ratio reductions and on its coordination with a conventional monetary policy. Using a macroeconomic simulation model, we find that reducing DTI threshold bring about a decrease in both households indebtedness and non-performing loans (NPLs), while causing economic contraction, and worsening inequality by restricting access to credit for lower-income households. Our findings suggest that while macro prudential policy (lower DTI) alone is able to grant more financial stability at the cost of greater inequality, a combination with expansionary monetary policies can reduce these disparities while ensuring financial stability.
{"title":"Macroprudential and monetary policies to deal with inequality","authors":"Samantha Coccia , Mauro Gallegati , Alberto Russo","doi":"10.1016/j.strueco.2025.11.001","DOIUrl":"10.1016/j.strueco.2025.11.001","url":null,"abstract":"<div><div>This paper examines the impact of macro prudential policies on financial stability and inequality, focusing on the effects of debt service-to-income (DTI) ratio reductions and on its coordination with a conventional monetary policy. Using a macroeconomic simulation model, we find that reducing DTI threshold bring about a decrease in both households indebtedness and non-performing loans (NPLs), while causing economic contraction, and worsening inequality by restricting access to credit for lower-income households. Our findings suggest that while macro prudential policy (lower DTI) alone is able to grant more financial stability at the cost of greater inequality, a combination with expansionary monetary policies can reduce these disparities while ensuring financial stability.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 895-912"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525643","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 : 2025-12-01Epub Date: 2025-05-07DOI: 10.1016/j.strueco.2025.05.007
Huai Deng , Xianhua Wu , Hui Xu , You Wu , Xin-Zhong Liang
With global warming and the increasing frequency of extreme high-temperature events exhibiting “fat-tail” characteristics, traditional climate-socio-economic models such as Integrated Assessment Models (IAMs) cannot well reflect the related tail trend and economic damages caused by high-temperature risks. We present a dynamic stochastic equation model (referred to as CEM) that incorporates risk factors for a more accurate assessment. Our study reveals: (1) By 2100, the probability of extreme temperature events is expected to increase by about 3.45 times, leading to severe economic damages and confirming a “fat-tail” trend. (2) Extreme high temperatures may cause economic damages that are challenging to quantify, posing difficulties for conventional warming pathways to estimate these impacts accurately. (3) The average increase of temperature tail probability due to an additional carbon emission of 1 ppm is approximately 0.15 × 10–4. The key innovation of this paper lies in its quantitative analysis of the economic damage caused by extreme high-temperatures events and its exploration of the “fat-tail” features of climate change. Our findings offer methodological and empirical insights to support the development of more robust climate policies to address these extreme risks.
{"title":"Quantifying aggregated economic damages from “fat-tail” extremes high-temperature events in climate change","authors":"Huai Deng , Xianhua Wu , Hui Xu , You Wu , Xin-Zhong Liang","doi":"10.1016/j.strueco.2025.05.007","DOIUrl":"10.1016/j.strueco.2025.05.007","url":null,"abstract":"<div><div>With global warming and the increasing frequency of extreme high-temperature events exhibiting “fat-tail” characteristics, traditional climate-socio-economic models such as Integrated Assessment Models (IAMs) cannot well reflect the related tail trend and economic damages caused by high-temperature risks. We present a dynamic stochastic equation model (referred to as CEM) that incorporates risk factors for a more accurate assessment. Our study reveals: (1) By 2100, the probability of extreme temperature events is expected to increase by about 3.45 times, leading to severe economic damages and confirming a “fat-tail” trend. (2) Extreme high temperatures may cause economic damages that are challenging to quantify, posing difficulties for conventional warming pathways to estimate these impacts accurately. (3) The average increase of temperature tail probability due to an additional carbon emission of 1 ppm is approximately 0.15 × 10<sup>–4</sup>. The key innovation of this paper lies in its quantitative analysis of the economic damage caused by extreme high-temperatures events and its exploration of the “fat-tail” features of climate change. Our findings offer methodological and empirical insights to support the development of more robust climate policies to address these extreme risks.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 108-121"},"PeriodicalIF":5.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072529","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 : 2025-12-01Epub Date: 2025-10-27DOI: 10.1016/j.strueco.2025.10.015
Yichen Yang , Yu Zhao , Wen Liu
Since the 1990s, the number and depth of regional trade agreements (RTAs) have grown rapidly, forming a network structure and playing an important role in global value chain (GVC) cooperation. This paper theoretically and empirically investigates the effect of RTA network centrality on GVC positions. We use social network analysis to construct network centrality indicators from three dimensions—individual, local, and global—based on network characteristics, which capture countries’ advantageous positions, and use upstreamness to measure GVC positions. We find that RTA network centrality can enhance GVC positions. Such effects are more pronounced in “WTO-extra” provisions and lower-middle-income countries. Total factor productivity and human capital levels are essential mechanisms. Moreover, we confirm that the RTA network improves GVC positions by promoting regionalization rather than globalized international fragmentation. In the face of increasing international competition, we reveal that regional economic integration is beneficial for improving GVC welfare.
{"title":"Climbing up global value chains: Is the regional trade agreement network stepping stones or stumbling blocks?","authors":"Yichen Yang , Yu Zhao , Wen Liu","doi":"10.1016/j.strueco.2025.10.015","DOIUrl":"10.1016/j.strueco.2025.10.015","url":null,"abstract":"<div><div>Since the 1990s, the number and depth of regional trade agreements (RTAs) have grown rapidly, forming a network structure and playing an important role in global value chain (GVC) cooperation. This paper theoretically and empirically investigates the effect of RTA network centrality on GVC positions. We use social network analysis to construct network centrality indicators from three dimensions—individual, local, and global—based on network characteristics, which capture countries’ advantageous positions, and use upstreamness to measure GVC positions. We find that RTA network centrality can enhance GVC positions. Such effects are more pronounced in “WTO-extra” provisions and lower-middle-income countries. Total factor productivity and human capital levels are essential mechanisms. Moreover, we confirm that the RTA network improves GVC positions by promoting regionalization rather than globalized international fragmentation. In the face of increasing international competition, we reveal that regional economic integration is beneficial for improving GVC welfare.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 849-867"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424484","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 : 2025-12-01Epub Date: 2025-10-21DOI: 10.1016/j.strueco.2025.10.012
Yue Lu , Minghui Ma , Yaning Wei , Yue Zhang
Utilizing firm-level data from 2000 to 2012, sourced from the Annual Survey of Industrial Firms, China’s Environmental Statistics Database, the International Federation of Robotics, and China Customs Trade Statistics, we estimate the effects and mechanisms of artificial intelligence (AI) on firms’ sulfur dioxide (SO2) emissions. Our analysis reveals that AI significantly reduces firms’ SO2 emissions, and this result remains robust to extensive checks and an instrumental variable approach addressing endogeneity. Furthermore, AI decreases firms’ SO2 emissions through three channels: enhancing energy efficiency, optimizing supply chain management, and strengthening pollution abatement capacity. Additionally, heterogeneity analysis indicates a more pronounced reduction in SO2 emissions for capital-intensive and emission-intensive industries, as well as for firms that are more productive, larger, older, and located in eastern regions. Finally, our analysis yields the valuable insight that firms located more upstream in the global value chain accrue more substantial environmental benefits from AI adoption, thereby helping to mitigate the global issue arising from environmental bias in trade policies. Overall, the study underscores AI’s potential to reduce firms’ SO2 emissions and contributes to the literature on the environmental impacts of digital technology.
{"title":"Artificial intelligence, global value chain position and manufacturing firm emissions","authors":"Yue Lu , Minghui Ma , Yaning Wei , Yue Zhang","doi":"10.1016/j.strueco.2025.10.012","DOIUrl":"10.1016/j.strueco.2025.10.012","url":null,"abstract":"<div><div>Utilizing firm-level data from 2000 to 2012, sourced from the Annual Survey of Industrial Firms, China’s Environmental Statistics Database, the International Federation of Robotics, and China Customs Trade Statistics, we estimate the effects and mechanisms of artificial intelligence (AI) on firms’ sulfur dioxide (SO<sub>2</sub>) emissions. Our analysis reveals that AI significantly reduces firms’ SO<sub>2</sub> emissions, and this result remains robust to extensive checks and an instrumental variable approach addressing endogeneity. Furthermore, AI decreases firms’ SO<sub>2</sub> emissions through three channels: enhancing energy efficiency, optimizing supply chain management, and strengthening pollution abatement capacity. Additionally, heterogeneity analysis indicates a more pronounced reduction in SO<sub>2</sub> emissions for capital-intensive and emission-intensive industries, as well as for firms that are more productive, larger, older, and located in eastern regions. Finally, our analysis yields the valuable insight that firms located more upstream in the global value chain accrue more substantial environmental benefits from AI adoption, thereby helping to mitigate the global issue arising from environmental bias in trade policies. Overall, the study underscores AI’s potential to reduce firms’ SO<sub>2</sub> emissions and contributes to the literature on the environmental impacts of digital technology.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 815-827"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424482","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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