This paper examines how organizational dispersion affects the economic performance of business units in multi-unit firms. When expanding operations, firms must balance the advantages of close oversight and control with the need to place units in locations that provide strategic resources or better access to markets. While managers are expected to weigh these trade-offs carefully, they may underestimate the challenges of managing and coordinating dispersed units, which can lead to inefficiencies that negatively impact performance. Using a large sample of 40,946 European business groups controlling approximately 107,000 subsidiaries, we analyze the factors that influence subsidiary performance in the context of organizational dispersion. Our findings suggest that organizational dispersion, measured as spatial distance between the headquarter and its business units, has a negative impact on subsidiary performance. Finally, we explore some potential mechanisms behind these effects.
{"title":"Organizational dispersion and economic performance in multi-unit firms","authors":"Giulio Cainelli , Valentina Giannini , Donato Iacobucci","doi":"10.1016/j.strueco.2025.11.010","DOIUrl":"10.1016/j.strueco.2025.11.010","url":null,"abstract":"<div><div>This paper examines how organizational dispersion affects the economic performance of business units in multi-unit firms. When expanding operations, firms must balance the advantages of close oversight and control with the need to place units in locations that provide strategic resources or better access to markets. While managers are expected to weigh these trade-offs carefully, they may underestimate the challenges of managing and coordinating dispersed units, which can lead to inefficiencies that negatively impact performance. Using a large sample of 40,946 European business groups controlling approximately 107,000 subsidiaries, we analyze the factors that influence subsidiary performance in the context of organizational dispersion. Our findings suggest that organizational dispersion, measured as spatial distance between the headquarter and its business units, has a negative impact on subsidiary performance. Finally, we explore some potential mechanisms behind these effects.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 44-65"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691788","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 : 2026-02-01Epub Date: 2025-11-18DOI: 10.1016/j.strueco.2025.11.004
Jing Yang , Danning Lu , Jianxun Shi
The contribution of high-growth firms to economic growth is gradually expanding, but its actual and subsequent effects on economy need to be further explored. This paper provides evidence for the study of the agglomeration externalities involving high-growth firms by analyzing their influence on non-high-growth firms’ productivity growth and input allocation within the same industry and region, as well as their spillover effects via both backward and forward linkages. The analysis shows robust proof of positive spillovers of high-growth firms on the labor productivity and inputs allocation of non-high-growth firms within the identical region and industry using manufacturing firm-level data on China between 2003 and 2013. The detailed mechanisms of agglomeration externalities associated with high-growth firms are further analyzed through three important channels, mainly including labor pooling, input sharing and knowledge spillover effects by the high-growth externalities.
{"title":"Agglomeration externalities of high-growth firms: the case of the manufacturing sector in China","authors":"Jing Yang , Danning Lu , Jianxun Shi","doi":"10.1016/j.strueco.2025.11.004","DOIUrl":"10.1016/j.strueco.2025.11.004","url":null,"abstract":"<div><div>The contribution of high-growth firms to economic growth is gradually expanding, but its actual and subsequent effects on economy need to be further explored. This paper provides evidence for the study of the agglomeration externalities involving high-growth firms by analyzing their influence on non-high-growth firms’ productivity growth and input allocation within the same industry and region, as well as their spillover effects via both backward and forward linkages. The analysis shows robust proof of positive spillovers of high-growth firms on the labor productivity and inputs allocation of non-high-growth firms within the identical region and industry using manufacturing firm-level data on China between 2003 and 2013. The detailed mechanisms of agglomeration externalities associated with high-growth firms are further analyzed through three important channels, mainly including labor pooling, input sharing and knowledge spillover effects by the high-growth externalities.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 1-19"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145584453","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 : 2026-02-01Epub Date: 2025-12-08DOI: 10.1016/j.strueco.2025.12.005
Sinuo Wang, Chu Wei
This study examines the productivity effects of China's Specialized, Refined, Differential, and Innovative (SRDI) industrial policy, a nationwide certification program for small and medium-sized enterprises. Using comprehensive financial data from Chinese A-share listed firms (2017–2023) and a staggered difference-in-differences design, we document three main findings. First, SRDI certification causes a 2.8 % increase in total factor productivity, robust to multiple identification strategies. Second, the productivity gains are driven by enhanced innovation activities and improved managerial efficiency. Third, heterogeneous treatment effects are more pronounced for firms in regions with favorable business environments and those operating in high-end manufacturing industries. These findings contribute to a more comprehensive understanding of the certification program, provide a replicable mode of industrial policy design, and advocate precision policy implementation.
{"title":"How certification programs boost SME productivity: Evidence from China’s targeted industrial policy","authors":"Sinuo Wang, Chu Wei","doi":"10.1016/j.strueco.2025.12.005","DOIUrl":"10.1016/j.strueco.2025.12.005","url":null,"abstract":"<div><div>This study examines the productivity effects of China's <em>Specialized, Refined, Differential, and Innovative</em> (SRDI) industrial policy, a nationwide certification program for small and medium-sized enterprises. Using comprehensive financial data from Chinese A-share listed firms (2017–2023) and a staggered difference-in-differences design, we document three main findings. First, SRDI certification causes a 2.8 % increase in total factor productivity, robust to multiple identification strategies. Second, the productivity gains are driven by enhanced innovation activities and improved managerial efficiency. Third, heterogeneous treatment effects are more pronounced for firms in regions with favorable business environments and those operating in high-end manufacturing industries. These findings contribute to a more comprehensive understanding of the certification program, provide a replicable mode of industrial policy design, and advocate precision policy implementation.</div><div>Classification: O25, D22, O38, H25, L25</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 152-170"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737276","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 : 2026-02-01Epub Date: 2025-12-09DOI: 10.1016/j.strueco.2025.12.007
Su Wang , Anqi Yu , Yueji Xin
As one of the largest sulfur dioxide (SO₂) emitters in the world, China has long been under pressure to reduce its SO₂ emission. The total amount of SO₂ emissions in China grew continuously between 2000 and 2006 and has been decreasing since. The total SO₂ emission of the manufacturing industry has remained stable, while Gross Domestic Product and manufacturing gross output have maintained sustained growth. In this study, we explored the factors underlying these opposite trends by decomposing total SO₂ emission changes of the manufacturing industry to the micro firm level. Results show that: (1) the scale effect is unambiguously positive; (2) the composition effect varies with the decomposition dimension; (3) the substitution effect, which reflects value-added share change, varies with both decomposition dimension and study period; and (4) the technique effect (the combined effect of energy intensity and pollution energy consumption share changes) is consistently negative. In view of future uncertainties, it is only by consolidating the technique effect that total SO₂ emission can be reduced effectively. These results on the channels affecting SO₂ emission can be used as a reference in the design of policies to effectively reduce SO₂ emissions from the manufacturing industry.
{"title":"Structural decomposition analysis of the SO2 emissions of China’s manufacture across the sector, sub-sector, and firm levels","authors":"Su Wang , Anqi Yu , Yueji Xin","doi":"10.1016/j.strueco.2025.12.007","DOIUrl":"10.1016/j.strueco.2025.12.007","url":null,"abstract":"<div><div>As one of the largest sulfur dioxide (SO₂) emitters in the world, China has long been under pressure to reduce its SO₂ emission. The total amount of SO₂ emissions in China grew continuously between 2000 and 2006 and has been decreasing since. The total SO₂ emission of the manufacturing industry has remained stable, while Gross Domestic Product and manufacturing gross output have maintained sustained growth. In this study, we explored the factors underlying these opposite trends by decomposing total SO₂ emission changes of the manufacturing industry to the micro firm level. Results show that: (1) the scale effect is unambiguously positive; (2) the composition effect varies with the decomposition dimension; (3) the substitution effect, which reflects value-added share change, varies with both decomposition dimension and study period; and (4) the technique effect (the combined effect of energy intensity and pollution energy consumption share changes) is consistently negative. In view of future uncertainties, it is only by consolidating the technique effect that total SO₂ emission can be reduced effectively. These results on the channels affecting SO₂ emission can be used as a reference in the design of policies to effectively reduce SO₂ emissions from the manufacturing industry.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 183-194"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790696","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 : 2026-02-01Epub Date: 2025-11-27DOI: 10.1016/j.strueco.2025.11.006
Francisco H.G. Ferreira , Domenico Moramarco , Vito Peragine
According to the Kuznets hypothesis, inequality first tends to increase and then decrease as a country develops. Whether borne out empirically, this inverted-U Kuznets curve, as a stylized ‘fact’, has shaped the discourse on economic development and income inequality for decades. In this paper we investigate whether a similar relationship holds between national income per capita and inequality of opportunity: the inequality associated with inherited individual circumstances such as gender, ethnicity, and family background. As, empirically, inequality of opportunity is positively correlated with income inequality (a relationship known as the ‘Great Gatsby’ curve), the relationship between inequality of opportunity and ‘development’ is expected to display the same inverted-U shape. We suggest that the existence of a Kuznets inequality of opportunity curve can be the result of a ‘triangular’ relationship between development, income inequality, and inequality of opportunity. We then draw on the newly published Global Estimates of Opportunity and Mobility database to shed new light on this ‘triangular’ relationship, primarily in a cross-sectional context.
{"title":"Economic development and inequality of opportunity: Kuznets meets the Great Gatsby?","authors":"Francisco H.G. Ferreira , Domenico Moramarco , Vito Peragine","doi":"10.1016/j.strueco.2025.11.006","DOIUrl":"10.1016/j.strueco.2025.11.006","url":null,"abstract":"<div><div>According to the Kuznets hypothesis, inequality first tends to increase and then decrease as a country develops. Whether borne out empirically, this inverted-U Kuznets curve, as a stylized ‘fact’, has shaped the discourse on economic development and income inequality for decades. In this paper we investigate whether a similar relationship holds between national income per capita and inequality of opportunity: the inequality associated with inherited individual circumstances such as gender, ethnicity, and family background. As, empirically, inequality of opportunity is positively correlated with income inequality (a relationship known as the ‘Great Gatsby’ curve), the relationship between inequality of opportunity and ‘development’ is expected to display the same inverted-U shape. We suggest that the existence of a Kuznets inequality of opportunity curve can be the result of a ‘triangular’ relationship between development, income inequality, and inequality of opportunity. We then draw on the newly published Global Estimates of Opportunity and Mobility database to shed new light on this ‘triangular’ relationship, primarily in a cross-sectional context.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 94-114"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691683","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 : 2026-02-01Epub Date: 2025-11-27DOI: 10.1016/j.strueco.2025.11.008
Ruixue Wang , Jiancheng Chen , Ze Han , Chao An , Wanting Bai , Xiangzheng Deng
This paper extends the analytical framework for measuring total factor productivity (TFP) in grain production by incorporating the environmental constraints related to pollution emissions. Employing a growth accounting approach, we decompose environmentally adjusted grain output growth into the contributions of labor, productive capital, and natural resource capital. This comprehensive indicator system provides a more nuanced understanding of the drivers of grain output growth while evaluating its long-term sustainability. Using panel data from 31 Chinese provinces from 2000 to 2021, the analysis integrates pollution emissions associated with grain production. The findings reveal a gradual decline in the dependence on agricultural chemicals, indicating a structural shift from traditional factor inputs toward green total factor productivity (GTFP) as the main engine of growth. Industry structural, human capital, and income level are shown to influence to the GTFP growth, suggesting that social and institutional factors play a key role in shaping GTFP trajectories. Significant regional heterogeneity is observed in both the contributions of production factors and their decomposition characteristics. In eastern regions such as Beijing, Tianjin, and Shanghai, the annual average growth in grain output is primarily driven by GTFP improvements. Labor input contributes significantly to more developed regions including Beijing, Shanghai, Zhejiang, Fujian, and Chongqing. Conversely, productive capital input plays a greater role in the central, western, and northeastern regions, with natural resource capital makes relatively higher contributions in the northeastern provinces.
{"title":"Assessing structural changes in factor contributions to green productivity growth in China's grain sector","authors":"Ruixue Wang , Jiancheng Chen , Ze Han , Chao An , Wanting Bai , Xiangzheng Deng","doi":"10.1016/j.strueco.2025.11.008","DOIUrl":"10.1016/j.strueco.2025.11.008","url":null,"abstract":"<div><div>This paper extends the analytical framework for measuring total factor productivity (TFP) in grain production by incorporating the environmental constraints related to pollution emissions. Employing a growth accounting approach, we decompose environmentally adjusted grain output growth into the contributions of labor, productive capital, and natural resource capital. This comprehensive indicator system provides a more nuanced understanding of the drivers of grain output growth while evaluating its long-term sustainability. Using panel data from 31 Chinese provinces from 2000 to 2021, the analysis integrates pollution emissions associated with grain production. The findings reveal a gradual decline in the dependence on agricultural chemicals, indicating a structural shift from traditional factor inputs toward green total factor productivity (GTFP) as the main engine of growth. Industry structural, human capital, and income level are shown to influence to the GTFP growth, suggesting that social and institutional factors play a key role in shaping GTFP trajectories. Significant regional heterogeneity is observed in both the contributions of production factors and their decomposition characteristics. In eastern regions such as Beijing, Tianjin, and Shanghai, the annual average growth in grain output is primarily driven by GTFP improvements. Labor input contributes significantly to more developed regions including Beijing, Shanghai, Zhejiang, Fujian, and Chongqing. Conversely, productive capital input plays a greater role in the central, western, and northeastern regions, with natural resource capital makes relatively higher contributions in the northeastern provinces.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 80-93"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145691790","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 : 2026-02-01Epub Date: 2025-11-19DOI: 10.1016/j.strueco.2025.11.005
Arthur Ribeiro Queiroz , Elton Eduardo Freitas , João Prates Romero
The objective of this paper is to assess the heterogeneity of employment multipliers between regions and sectors of distinct complexity levels, segmenting regions into four complexity levels and the economy into two sectors: complex and non-complex. Formal labor market data from 558 Brazilian micro-regions in three time points (2009, 2014 and 2019) were used in the investigation. Potential endogeneity was addressed by employing shift-share instrumental variables.. In less complex regions, the complex sector exhibits statistically weaker effects on both the non-complex sector and on itself, while the strongest positive impacts on employment arise from the non-complex sector’s self-multiplication, ranging from 0.92 to 1.8. In more complex regions, the complex sector presents the highest employment multiplier, generating between 1.06 and 1.43 jobs within itself and between 1.71 and 3.25 jobs in the non-complex sector.
{"title":"Economic complexity and local employment multipliers","authors":"Arthur Ribeiro Queiroz , Elton Eduardo Freitas , João Prates Romero","doi":"10.1016/j.strueco.2025.11.005","DOIUrl":"10.1016/j.strueco.2025.11.005","url":null,"abstract":"<div><div>The objective of this paper is to assess the heterogeneity of employment multipliers between regions and sectors of distinct complexity levels, segmenting regions into four complexity levels and the economy into two sectors: complex and non-complex. Formal labor market data from 558 Brazilian micro-regions in three time points (2009, 2014 and 2019) were used in the investigation. Potential endogeneity was addressed by employing shift-share instrumental variables.. In less complex regions, the complex sector exhibits statistically weaker effects on both the non-complex sector and on itself, while the strongest positive impacts on employment arise from the non-complex sector’s self-multiplication, ranging from 0.92 to 1.8. In more complex regions, the complex sector presents the highest employment multiplier, generating between 1.06 and 1.43 jobs within itself and between 1.71 and 3.25 jobs in the non-complex sector.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 20-43"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625374","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 : 2026-02-01Epub Date: 2025-12-22DOI: 10.1016/j.strueco.2025.12.011
Chen Lyu , Ke Wang , Xunpeng Shi , Bofeng Cai , Gang Yan
We provide the quantitative evaluation of the incentive structure of China National Emission Trading Scheme (CN ETS) by analyzing 2282 compliance firms and find that CN ETS provides economic incentives for emission abatement through trading profits but exhibits a Matthew effect, whereby firms with larger emission reductions achieve higher marginal profits. In the second compliance cycle, the market incentive effect improved, evidenced by an increase in trading profits per ton of emission reductions and a weaking of the Matthew effect. The benchmark allowance allocation has effectively encouraged low-emission-intensity coal-fired units while expediting the phase-out of high-emission intensity units. However, gas-fired units, despite their lowest emission intensity and high flexibility, receive weak incentives. Central state-owned enterprises and units with prior experience in China’s ETS pilots, exhibit lower trading participation. Enhancing allowances scarcity, implementing paid allowances, strengthening compliance enforcement and penalties, and increasing trading activity are suggested to improve the CN ETS.
{"title":"Effectiveness of market incentives in China’s National Emission Trading Scheme","authors":"Chen Lyu , Ke Wang , Xunpeng Shi , Bofeng Cai , Gang Yan","doi":"10.1016/j.strueco.2025.12.011","DOIUrl":"10.1016/j.strueco.2025.12.011","url":null,"abstract":"<div><div>We provide the quantitative evaluation of the incentive structure of China National Emission Trading Scheme (CN ETS) by analyzing 2282 compliance firms and find that CN ETS provides economic incentives for emission abatement through trading profits but exhibits a Matthew effect, whereby firms with larger emission reductions achieve higher marginal profits. In the second compliance cycle, the market incentive effect improved, evidenced by an increase in trading profits per ton of emission reductions and a weaking of the Matthew effect. The benchmark allowance allocation has effectively encouraged low-emission-intensity coal-fired units while expediting the phase-out of high-emission intensity units. However, gas-fired units, despite their lowest emission intensity and high flexibility, receive weak incentives. Central state-owned enterprises and units with prior experience in China’s ETS pilots, exhibit lower trading participation. Enhancing allowances scarcity, implementing paid allowances, strengthening compliance enforcement and penalties, and increasing trading activity are suggested to improve the CN ETS.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 251-261"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840056","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 : 2026-02-01Epub Date: 2025-12-17DOI: 10.1016/j.strueco.2025.12.003
Zsolt T. Kosztyán
This study examines the dynamic evolution of global trade networks from 1995 to 2020 using the Organization for Economic Co-operation and Development’s (OECD’s) intercountry input–output (ICIO) data. This research combines multilayer network theory methods with advanced statistical and econometric procedures, including dynamic multilayer network analysis methods, (bi)clustering, and causal analyses to evaluate the temporal nature of structural, sectorial and country-level indicators. The primary objective of this study is to identify causal patterns in multilayer trade network structures and reveal the roles of specific countries and industries as drivers of changes in global trade dynamics. Using the proposed methods, we define causal graphs between the structural indicators of the multilayer network. The resulting causal graph is organized into groups using modularity analysis, and the relationships are biclustered, thereby determining which structural factors/industries/countries affect other country groups/industries and revealing the dynamics of structural changes. We determine which factors change simultaneously and which factors and actors exhibit a delay between their changes. The analysis reveals significant shifts in structural indicators, highlighting the evolving roles of major players like China and the US. The findings indicate that the structural indicators of trade networks/industries/countries often move in unison, with changes in one country/industry potentially triggering rapid transformations across the entire network. This study also uncovers the cascading effects of economic disruptions on trade patterns, emphasizing the interconnectedness of countries and industries in the face of global economic changes. These insights are crucial for policymakers and business leaders, underscoring the need for adaptive strategies to enhance the level of resilience of countries and industries to persistent global economic fluctuations and crises.
{"title":"Exploring the forecasting and temporal causality patterns of multilayer trade networks reflecting global economic changes","authors":"Zsolt T. Kosztyán","doi":"10.1016/j.strueco.2025.12.003","DOIUrl":"10.1016/j.strueco.2025.12.003","url":null,"abstract":"<div><div>This study examines the dynamic evolution of global trade networks from 1995 to 2020 using the Organization for Economic Co-operation and Development’s (OECD’s) intercountry input–output (ICIO) data. This research combines multilayer network theory methods with advanced statistical and econometric procedures, including dynamic multilayer network analysis methods, (bi)clustering, and causal analyses to evaluate the temporal nature of structural, sectorial and country-level indicators. The primary objective of this study is to identify causal patterns in multilayer trade network structures and reveal the roles of specific countries and industries as drivers of changes in global trade dynamics. Using the proposed methods, we define causal graphs between the structural indicators of the multilayer network. The resulting causal graph is organized into groups using modularity analysis, and the relationships are biclustered, thereby determining which structural factors/industries/countries affect other country groups/industries and revealing the dynamics of structural changes. We determine which factors change simultaneously and which factors and actors exhibit a delay between their changes. The analysis reveals significant shifts in structural indicators, highlighting the evolving roles of major players like China and the US. The findings indicate that the structural indicators of trade networks/industries/countries often move in unison, with changes in one country/industry potentially triggering rapid transformations across the entire network. This study also uncovers the cascading effects of economic disruptions on trade patterns, emphasizing the interconnectedness of countries and industries in the face of global economic changes. These insights are crucial for policymakers and business leaders, underscoring the need for adaptive strategies to enhance the level of resilience of countries and industries to persistent global economic fluctuations and crises.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 209-236"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790694","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: 2025-10-17DOI: 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.
{"title":"A post-Keynesian-structuralist empirical approach to inflationary pressures in Türkiye","authors":"Betül Mutlugün","doi":"10.1016/j.strueco.2025.10.004","DOIUrl":"10.1016/j.strueco.2025.10.004","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"75 ","pages":"Pages 744-766"},"PeriodicalIF":5.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424429","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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