Structural Change and Economic Dynamics最新文献

英文中文

Exporting violence? Migration and violent conflict in Africa 出口暴力吗?非洲的移民和暴力冲突

IF 5.5 2区经济学 Q1 ECONOMICS

Structural Change and Economic Dynamics

Pub Date : 2025-10-28 DOI: 10.1016/j.strueco.2025.10.013

Nixon S. Chekenya , Canicio Dzingirai

Climate change and demographic pressures are reshaping Africa’s security landscape. Extreme weather shocks disrupt livelihoods and often induce people to move, while many states face persistent violent conflict. Migration represents a potential connection between these two challenges, yet isolating its causal effect on conflict remains difficult due to endogeneity and measurement concerns. In this paper, we examine whether net international migration increases the incidence of violent conflict in Africa and assess if there are heterogenous effects across regions within Africa. We compile panel data for 54 African countries from 1997 to 2024, measuring net migration as the difference between inflows and outflows, and conflict incidence using geocoded event data. To address endogeneity, we instrument migration with historical rainfall variability (from 1901 to 1950), which shaped long-run settlement and mobility patterns but predates modern political institutions. Using a control function IV Poisson model suitable for equi-dispersed count data, we find that migration significantly increases conflict incidence, with effects concentrated in countries and regions in Africa with weak governance and economic stress. These results highlight the need for anticipatory governance strategies which address both mobility and fragility in contexts vulnerable to climate change and demographic pressure.

气候变化和人口压力正在重塑非洲的安全格局。极端天气冲击破坏了人们的生计，往往促使人们迁移，而许多国家则面临持续的暴力冲突。移民代表了这两个挑战之间的潜在联系，但由于内生性和衡量方面的考虑，孤立其对冲突的因果影响仍然很困难。在本文中，我们研究了净国际移民是否增加了非洲暴力冲突的发生率，并评估了非洲各地区之间是否存在异质性影响。我们编制了54个非洲国家从1997年到2024年的面板数据，衡量净移民流入和流出之间的差异，以及使用地理编码事件数据的冲突发生率。为了解决内生性问题，我们用历史降雨变化（1901年至1950年）来衡量移民，这形成了长期的定居和流动模式，但早于现代政治制度。利用适合等分散计数数据的控制函数IV泊松模型，我们发现移民显著增加了冲突发生率，且影响集中在治理薄弱和经济压力大的非洲国家和地区。这些结果突出表明，在易受气候变化和人口压力影响的情况下，需要制定前瞻性治理战略，解决流动性和脆弱性问题。

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引用次数: 0

Climbing up global value chains: Is the regional trade agreement network stepping stones or stumbling blocks? 攀上全球价值链：区域贸易协定网络是垫脚石还是绊脚石？

IF 5.5 2区经济学 Q1 ECONOMICS

Structural Change and Economic Dynamics

Pub Date : 2025-10-27 DOI: 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.

20世纪90年代以来，区域贸易协定数量和深度快速增长，形成了网络结构，在全球价值链合作中发挥了重要作用。本文从理论和实证两方面探讨了区域交通运输网络中心性对全球价值链区位的影响。基于网络特征，利用社会网络分析从个体、地方和全球三个维度构建网络中心性指标，捕捉各国的优势位置，并利用上游性衡量全球价值链位置。研究发现，RTA网络的中心性可以提升GVC的地位。这种影响在“wto额外”条款和中低收入国家更为明显。全要素生产率和人力资本水平是重要的机制。此外，我们确认区域贸易协定网络通过促进区域化而不是全球化的国际碎片化来提高全球价值链的地位。面对日益激烈的国际竞争，我们发现区域经济一体化有利于提高全球价值链的福利。

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引用次数: 0

Unraveling the interplay of substitution elasticities and the green energy rebound effect 替代弹性与绿色能源反弹效应的相互作用

IF 5.5 2区经济学 Q1 ECONOMICS

Structural Change and Economic Dynamics

Pub Date : 2025-10-22 DOI: 10.1016/j.strueco.2025.10.007

Verónica Acurio Vásconez , Mónica Pereira Henriques

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.

本文考察了绿色能源和化石能源的技术进步如何在新古典增长模型中影响这两种能源的消费，该模型明确地将能源投入分开——与最初的桑德斯（1992）框架不同。通过纳入生产要素之间的替代弹性，我们研究了一个部门的改进是否真正取代了化石燃料，还是反而产生了增加总能源使用的结构性反弹效应。利用可替代的功能形式——柯布-道格拉斯和嵌套ces——我们表明，当替代弹性超过1时，无论是绿色能源还是化石能源的技术进步都会扩大一种甚至两种能源的使用，从而可能引发适得其反的效应，而低替代弹性则会缓和这种影响。这些发现突出表明，技术变革的环境有效性主要取决于生产结构和替代可能性，为管理系统性反弹机制提供了与政策相关的见解。

引用次数: 0

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

Structural Change and Economic Dynamics

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

Structural Change and Economic Dynamics

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。

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

Structural Change and Economic Dynamics

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。

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

Structural Change and Economic Dynamics

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

Structural Change and Economic Dynamics

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。

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

Structural Change and Economic Dynamics

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

Structural Change and Economic Dynamics

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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