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Artificial intelligence, global value chain position and manufacturing firm emissions 人工智能、全球价值链地位和制造企业排放
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-21 DOI: 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.
本文利用2000年至2012年工业企业年度调查、中国环境统计数据库、国际机器人联合会和中国海关贸易统计的企业层面数据,估计了人工智能(AI)对企业二氧化硫(SO2)排放的影响和机制。我们的分析表明,人工智能显著减少了企业的二氧化硫排放,这一结果对于广泛的检查和解决内生性的工具变量方法仍然是稳健的。此外,人工智能通过提高能源效率、优化供应链管理和加强污染减排能力三个渠道减少了企业的二氧化硫排放。此外,异质性分析表明,资本密集型和排放密集型行业,以及生产力更高、规模更大、历史更悠久、位于东部地区的企业,二氧化硫排放量的减少更为显著。最后,我们的分析得出了有价值的见解,即位于全球价值链上游的公司从采用人工智能中获得了更大的环境效益,从而有助于减轻贸易政策中环境偏见引起的全球问题。总体而言,该研究强调了人工智能减少企业二氧化硫排放的潜力,并为数字技术对环境影响的文献做出了贡献。
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引用次数: 0
Closing the productivity–wage gap in the European Union: The role of the labor share 缩小欧盟的生产率与工资差距:劳动收入份额的作用
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-21 DOI: 10.1016/j.strueco.2025.10.005
Alessandro Bellocchi , Francesco Saraceno , Giuseppe Travaglini
This paper examines the determinants of the productivity–wage gap in the European Union between 2002 and 2018, with a focus on the role of the labor share. Drawing on a nested CES production framework and industry-level data for 17 EU countries, we find that higher tangible capital intensity, particularly in non-ICT assets, together with capital-biased technological progress, have reduced the labor share of low- and medium-skilled workers. Institutional changes, including weaker collective bargaining coverage, the erosion of employment protection and the rising use of temporary contracts, have further accelerated this decline. Our results reveal marked heterogeneity across asset types, industries and skill groups, highlighting the need for targeted policies to mitigate the distributional consequences of capital deepening and technological change.
本文研究了2002年至2018年欧盟生产率与工资差距的决定因素,重点研究了劳动收入占比的作用。利用嵌套的CES生产框架和17个欧盟国家的行业层面数据,我们发现更高的有形资本密集度,特别是在非ict资产中,加上资本偏向的技术进步,降低了中低技能工人的劳动份额。制度变化,包括集体谈判覆盖面的减弱、就业保护的削弱以及临时合同使用的增加,进一步加速了这种下降。我们的研究结果揭示了资产类型、行业和技能群体之间的显著异质性,强调需要有针对性的政策来减轻资本深化和技术变革的分配后果。
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引用次数: 0
Cross-border data flows and AI adoption: Agent-based model simulations 跨境数据流和人工智能采用:基于代理的模型仿真
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-21 DOI: 10.1016/j.strueco.2025.10.009
Franziska Klügl , Hildegunn Kyvik Nordås
This paper develops a dynamic Agent Based Model to study the role of cross-border data flows for the joint uptake of artificial intelligence enabled software in manufacturing and engineering. The model features two technology-related business models: engineering as a face-to-face consultancy service, and engineering as a software licensing service. Engineering agents harvest data from their software clients in the home country and abroad and use the data for quality assurance and software updates. We compare scenarios along two dimensions: (i) harvesting data from own clients only versus from open data repositories, (ii) the strength of competition measured by the probability that a contract will be extended by another period. We find that restrictions on cross-border data flows slow down the speed of adoption considerably, particularly in small countries. The simulations generate an S-shaped technology uptake path for manufacturers and a U-shaped relationship between competition and technology uptake in engineering. Interestingly, cross-border data flows flatten the U.
本文开发了一个动态的基于Agent的模型来研究跨界数据流在制造和工程中联合采用人工智能软件中的作用。该模式以两种与技术相关的商业模式为特色:作为面对面咨询服务的工程,以及作为软件许可服务的工程。工程代理从国内外的软件客户那里收集数据,并将这些数据用于质量保证和软件更新。我们从两个方面比较了各种情况:(i)只从自己的客户那里收集数据,而不是从开放的数据存储库中收集数据;(ii)通过合同将被延长一段时间的可能性来衡量的竞争强度。我们发现,对跨境数据流动的限制大大减缓了采用的速度,特别是在小国。仿真结果表明,制造业的技术吸收路径为s型,竞争与工程技术吸收之间呈u型关系。有趣的是,跨境数据流使美国经济趋于平缓。
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引用次数: 0
The synergistic impact of the EU's provision of low-carbon technical assistance under the carbon border adjustment mechanism: A GTAP model-based study 碳边界调整机制下欧盟提供低碳技术援助的协同效应:基于GTAP模型的研究
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-20 DOI: 10.1016/j.strueco.2025.10.011
Yiting Wang , Ji Guo , Xianhua Wu , You Wu
To mitigate carbon leakage risks and safeguard the competitiveness of the EU domestic industries, the European Commission instituted the Carbon Border Adjustment Mechanism (CBAM). However, as a unilateral environmental policy, the CBAM may face retaliatory measures from the EU’s trading partners, raising concerns about potential negative impacts on the EU. It is important to consider whether providing low-carbon technology support and preferential carbon tariffs to developing countries could mitigate the negative repercussions for the EU. To investigate these issues, this study employs the Global Trade Analysis Project (GTAP) Computable General Equilibrium Model to examine the impacts on the EU’s economy under the different scenarios. The simulation results demonstrate that retaliatory measures implemented by developed and developing countries against the EU would impose a negative impact on the EU's economy. However, providing low-carbon technological support and preferential carbon tariffs to developing countries would mitigate such adverse effects on the EU’s economy.
为了降低碳泄漏风险,保障欧盟国内产业的竞争力,欧盟委员会建立了碳边界调整机制(CBAM)。然而,作为一项单方面的环境政策,CBAM可能会面临欧盟贸易伙伴的报复性措施,这引发了对欧盟潜在负面影响的担忧。重要的是要考虑向发展中国家提供低碳技术支持和优惠碳关税是否可以减轻对欧盟的负面影响。为了探讨这些问题,本研究采用全球贸易分析项目(GTAP)可计算一般均衡模型来研究不同情景下对欧盟经济的影响。仿真结果表明,发达国家和发展中国家对欧盟实施的报复性措施会对欧盟经济产生负面影响。然而,向发展中国家提供低碳技术支持和优惠碳关税将减轻对欧盟经济的不利影响。
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引用次数: 0
Global carbon emission implications of China’s demographic ageing 中国人口老龄化对全球碳排放的影响
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-20 DOI: 10.1016/j.strueco.2025.10.008
Yafei Wang , Siyang Wu , Lixiao Xu
China’s rapidly ageing exerts increasingly complex impacts on global carbon emissions. While most studies primarily examined domestic carbon of elderly, its global implications remain understudies. This study develops a novel provincial-global multi-regional input–output (MRIO) model, integrating Chinese Household Expenditure Surveys, to quantify carbon footprints of older adults. The results reveal that although the elderly show relatively lower per capita emissions (2.63 t per capita in 2020), their rising demographic share (from 8.8% in 2005 to 12.5% in 2020) and annual growth rate of emissions (11.77%) represent ageing as a significant driver of global emissions. Key sources, including food and residence, while emissions embodied in international trade, particularly from Brazil, Australia, and Russia, are increasingly prominent. At the sectoral level, power generation and agriculture dominate both domestic and imported emissions. The findings highlight the urgency of incorporating demographic ageing into carbon mitigation strategies and addressing foreign emissions embedded in elderly consumption.
中国快速老龄化对全球碳排放的影响越来越复杂。虽然大多数研究主要是针对国内老年人的碳排放,但其对全球的影响仍有待研究。本研究通过整合中国家庭支出调查,建立了一个新的省-全球多区域投入产出(MRIO)模型来量化老年人的碳足迹。结果表明,尽管老年人的人均排放量相对较低(2020年为2.63吨),但其人口比例(从2005年的8.8%增加到2020年的12.5%)和年排放量增长率(11.77%)的上升表明老龄化是全球排放的重要驱动因素。主要来源,包括食品和住宅,而国际贸易,特别是来自巴西、澳大利亚和俄罗斯的排放,日益突出。在部门一级,发电和农业在国内和进口排放中占主导地位。研究结果强调了将人口老龄化纳入碳减排战略和解决老年人消费中隐含的外国排放的紧迫性。
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引用次数: 0
The acceleration and attenuation: Internet infrastructure and employment adjustment patterns 加速与衰减:互联网基础设施与就业调整模式
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-20 DOI: 10.1016/j.strueco.2025.10.003
Li Yu , Siyuan Zhao , Chen Liu , Fenglan Chen
How does the arrival of broadband Internet affect firms’ employment adjustment patterns? Understanding this relationship is crucial, particularly given the challenges of employment recovery following major economic shocks such as the global financial crisis and the COVID-19 pandemic. We examine this question using China’s broadband infrastructure expansion in the early 2000s. Using establishment-level data, we find that Internet access increases employment adjustment rates, reduces the probability of inaction, and increases the likelihood of smooth adjustments. Internet access also alters the distribution of adjustment types: firms transition more quickly from spike to smooth adjustments, while maintaining smooth adjustment periods longer before reverting to inaction. By alleviating search frictions, lowering fixed hiring costs, and reducing firm-level uncertainty, these shifts in adjustment patterns improve firms’ responsiveness to economic shocks: cities with better Internet infrastructure show stronger employment responses to positive demand shocks from WTO and faster recovery from the 2008-09 crisis. The changes in distribution of adjustment types not only promote employment growth but also generate significant efficiency gains: micro-level improvements explain 44 percent of the reduction in firm-level labor misallocation, while cities with better digital infrastructure exhibit lower dispersion in labor’s marginal product, though the magnitude depends on local labor mobility institutions.
宽带互联网的到来如何影响企业的就业调整模式?理解这种关系至关重要,特别是考虑到全球金融危机和COVID-19大流行等重大经济冲击后就业复苏的挑战。我们用本世纪初中国宽带基础设施的扩张来研究这个问题。利用企业层面的数据,我们发现互联网接入提高了就业调整率,降低了不作为的可能性,并增加了顺利调整的可能性。互联网的接入也改变了调整类型的分布:企业更快地从峰值调整过渡到平稳调整,同时在恢复无所作为之前保持平稳调整周期的时间更长。通过缓解搜索摩擦、降低固定雇佣成本和降低企业层面的不确定性,这些调整模式的转变提高了企业对经济冲击的响应能力:拥有更好互联网基础设施的城市对WTO的积极需求冲击表现出更强的就业反应,并从2008-09年危机中复苏得更快。调整类型分布的变化不仅促进了就业增长,而且还产生了显著的效率提升:微观层面的改善解释了44%的企业层面劳动力错配减少,而拥有更好数字基础设施的城市在劳动力边际产品上表现出更低的分散,尽管其程度取决于当地的劳动力流动制度。
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引用次数: 0
The digital effects on structural change: data as a new driver of China’s economic growth 数字对结构变化的影响:数据成为中国经济增长的新动力
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-18 DOI: 10.1016/j.strueco.2025.10.010
Yu Zhao , Maoyu Gong , Ning Zhang
This paper investigates how the data factor of production (DFP) reshapes economic structure and productivity dynamics under environmental constraints. We propose a directional input distance function model within a meta-frontier framework to characterize DFP-embedded production technology. The model highlights the asymmetric relationship between DFPs and traditional inputs, specifying that while DFPs enhance productivity, they are not essential for generating positive output. Applying this parameterized model to a panel dataset of 285 Chinese cities from 2013 to 2022, we find a significant acceleration in productivity after the central government’s formal institutionalization of data as a factor of production. The direct contribution of DFPs accounts for approximately 40 % of this growth. A regional heterogeneity analysis reveals that while all regions share this common growth trend, their underlying drivers differ: the eastern region relies on technological innovation, whereas the central and western regions depend on efficiency catch-up. In addition, our estimates of substitution elasticities reveal the heterogeneous role of DFPs, which are found to be dependent on human capital (complementarity) while serving as a weak substitute for capital and energy. These findings underscore the critical role of digital infrastructure and targeted policies in facilitating the green economic transformation.
本文研究了环境约束下数据生产要素(DFP)如何重塑经济结构和生产力动态。我们提出了一个元前沿框架内的定向输入距离函数模型来描述dfp嵌入式生产技术。该模型强调了dfp与传统投入之间的不对称关系,指出虽然dfp提高了生产率,但它们并不是产生正产出所必需的。将这一参数化模型应用于2013 - 2022年中国285个城市的面板数据集,我们发现在中央政府将数据作为生产要素正式制度化后,生产率显著加快。dfp的直接贡献约占这一增长的40%。区域异质性分析表明,虽然所有地区都有这一共同的增长趋势,但其潜在驱动因素不同:东部地区依赖技术创新,而中西部地区依赖效率追赶。此外,我们对替代弹性的估计揭示了dfp的异质性作用,发现dfp依赖于人力资本(互补性),同时作为资本和能源的弱替代品。这些发现强调了数字基础设施和有针对性的政策在促进绿色经济转型中的关键作用。
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引用次数: 0
A post-Keynesian-structuralist empirical approach to inflationary pressures in Türkiye 后凯恩斯主义-结构主义的经验主义方法研究日本通胀压力
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-17 DOI: 10.1016/j.strueco.2025.10.004
Betül Mutlugün
Inflation in Türkiye surged to nearly 85% in 2022, the highest level in two decades. This study analyzes inflation dynamics through a Post-Keynesian Structuralist framework using a Structural Vector Autoregression model with data from October 2004 to September 2024. The findings reveal that: (i) exchange rate shocks are the primary driver of inflation, with global oil prices also playing a significant role; (ii) unit labor costs contribute minimally as a propagation mechanism due to weakened collective bargaining and the growing productivity-pay gap; (iii) demand-side factors, such as capacity utilization, have limited influence on inflation; and (iv) monetary policy primarily operates through the exchange rate channel, where policy rate hikes lead to currency appreciation but fail to significantly curb aggregate demand. These results underscore the challenges faced by Türkiye’s monetary authorities in addressing inflation driven largely by external shocks and structural economic vulnerabilities.
2022年,俄罗斯的通货膨胀率飙升至近85%,是20年来的最高水平。本文采用2004年10月至2024年9月的数据,采用结构向量自回归模型,通过后凯恩斯结构主义框架分析通货膨胀动态。研究结果表明:(1)汇率冲击是通货膨胀的主要驱动因素,全球油价也起着重要作用;(ii)由于集体谈判的削弱和生产率与工资差距的扩大,单位劳动力成本作为一种传播机制的贡献最小;需求方面的因素,如产能利用率,对通货膨胀的影响有限;(4)货币政策主要通过汇率渠道运作,政策加息导致货币升值,但不能显著抑制总需求。这些结果凸显了日本货币当局在应对主要由外部冲击和结构性经济脆弱性驱动的通胀方面所面临的挑战。
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引用次数: 0
The changing drivers of inflation – the case of food: Macroeconomics, speculation, climate change and war 不断变化的通胀驱动因素——以食品为例:宏观经济、投机、气候变化和战争
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-17 DOI: 10.1016/j.strueco.2025.10.006
Bernardina Algieri , Lukas Kornher , Joachim von Braun
The inflation surge in recent years has produced profound social, economic, and political consequences. Food price changes, being part of inflation, affect low-income segments particularly strongly. This is important to consider because macro-economic and central banks’ attention is mainly on core inflation, which excludes food. What makes this period so unusual is the breadth of price pressures that involve both developing and rich countries, meaning that inflation has been getting more synchronized across borders. This study examines the driving factors behind global food price hikes and their rates of change. Our analysis reveals that a complex mix of causes has led to the soaring food prices in 2021–2022. The spread of COVID-19 produced disruptions in the world’s supply chains, pushing the cost of producing and transporting food upward. The increase in fertilizer and energy prices has further exacerbated production costs for agricultural products. Adverse climatic phenomena (La Niña), generating droughts in parts of Africa, Asia, and the Americas, caused damage to harvests and fueled inflation. The war in Ukraine and the trade blockade of grain exports made things worse. Additional culprits were speculative activities in financial markets that were already underway before the Russia-Ukraine war. Soaring inflation increases inequality and makes vulnerable countries hungrier and poorer. At the same time, since global factors contribute to food price movements, implying that a crucial component of price inflation is exogenous to individual countries, the effectiveness of national monetary and fiscal policies could be limited. Instead, enhanced cooperation among nations with coordinated policy responses could be important to avoid the exacerbation of prices.
近年来通货膨胀的激增已经产生了深刻的社会、经济和政治后果。食品价格变化作为通货膨胀的一部分,对低收入阶层的影响尤为强烈。考虑这一点很重要,因为宏观经济和央行的注意力主要集中在核心通胀上,不包括食品。这一时期的不同寻常之处在于,发展中国家和富裕国家都面临着广泛的价格压力,这意味着各国的通胀变得更加同步。本研究探讨了全球食品价格上涨背后的驱动因素及其变化率。我们的分析显示,导致2021-2022年食品价格飙升的原因非常复杂。2019冠状病毒病的传播扰乱了全球供应链,推高了粮食生产和运输成本。化肥和能源价格的上涨进一步加剧了农产品的生产成本。不利的气候现象(网址Niña)在非洲、亚洲和美洲部分地区造成干旱,对收成造成损害,并加剧了通货膨胀。乌克兰的战争和粮食出口的贸易封锁使情况变得更糟。另一个罪魁祸首是金融市场上的投机活动,这些活动在俄乌战争之前就已经开始了。飞涨的通货膨胀加剧了不平等,使脆弱的国家更加饥饿和贫穷。与此同时,由于全球因素促成粮食价格变动,这意味着价格通货膨胀的一个关键组成部分是个别国家的外生因素,因此国家货币和财政政策的效力可能有限。相反,加强各国之间的合作,采取协调一致的政策应对措施,对于避免价格恶化可能很重要。
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引用次数: 0
Is productive service intermediate input a good instrument for enhancing the Global Value Chain participation? 生产性服务中间投入是提高全球价值链参与的好工具吗?
IF 5.5 2区 经济学 Q1 ECONOMICS Pub Date : 2025-10-08 DOI: 10.1016/j.strueco.2025.10.002
Sin-Som (Sergio) Tsiong, Hongsong Liu
Globalization has closely interconnected the production systems of various countries, and gaining a superiority in the Global Value Chain (GVC) has become a strategic imperative for many countries. Warrant attention, the service-based economy has been playing a pivotal role in optimizing and upgrading the GVC. Consequently, based on a sample that consists of 77 countries from 1995 to 2020, this article investigates the promoting effect of productive service intermediate input (PSII) on GVC participation. The findings are consistent with our expectations and are supported by a series of robustness checks and endogeneity handling. Heterogeneity analyses provide partial support for a geographic pattern linking PSII to GVC participation. Mediation analyses confirm that PSII enhances GVC participation through manufacturing servitization, financing constraint alleviation, and efficiency improvements. Finally, moderation analysis indicates that PSII exhibits a “substitution” effect vis-à-vis innovation capacity, implying a more feasible pathway for less developed countries to industrial upgrading.
全球化使各国的生产系统紧密相连,在全球价值链中取得优势已成为许多国家的战略要求。值得注意的是,服务型经济在全球价值链优化升级中发挥着举足轻重的作用。因此,本文以1995 - 2020年77个国家为样本,考察了生产性服务中间投入对全球价值链参与的促进作用。研究结果与我们的预期一致,并得到了一系列稳健性检查和内生性处理的支持。异质性分析为PSII与全球价值链参与之间的地理格局提供了部分支持。中介分析证实,PSII通过制造业服务化、融资约束缓解和效率提升提高了全球价值链参与。最后,适度分析表明PSII对-à-vis创新能力具有“替代”效应,为欠发达国家产业升级提供了一条更可行的路径。
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引用次数: 0
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Structural Change and Economic Dynamics
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