Pub Date : 2026-01-02DOI: 10.1016/j.strueco.2025.12.016
Manuela Cerimelo, Pablo de la Vega, Franco Vazquez, Natalia Porto
We study the wage gap between those who are in green jobs and those who are not (the wage greenium), in nine major Latin American countries that account for 81% of the region’s GDP: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, Peru and Uruguay. We contribute to the recent literature focused on developed countries that highlights a positive wage gap for those working in green jobs. We use the occupational approach to define green jobs and find that, in Latin America, they pay 15.8% more than non-green jobs. This result may be a desirable market feature, as workers might be encouraged to switch to greener occupations. In addition, we find that the wage greenium increases with the years of education, which suggests that workers with a medium or high educational level in green jobs are better off than their counterparts in non-green jobs.
{"title":"Greener jobs, higher wages? The Latin American wage greenium","authors":"Manuela Cerimelo, Pablo de la Vega, Franco Vazquez, Natalia Porto","doi":"10.1016/j.strueco.2025.12.016","DOIUrl":"10.1016/j.strueco.2025.12.016","url":null,"abstract":"<div><div>We study the wage gap between those who are in green jobs and those who are not (the wage greenium), in nine major Latin American countries that account for 81% of the region’s GDP: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, Peru and Uruguay. We contribute to the recent literature focused on developed countries that highlights a positive wage gap for those working in green jobs. We use the occupational approach to define green jobs and find that, in Latin America, they pay 15.8% more than non-green jobs. This result may be a desirable market feature, as workers might be encouraged to switch to greener occupations. In addition, we find that the wage greenium increases with the years of education, which suggests that workers with a medium or high educational level in green jobs are better off than their counterparts in non-green jobs.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 77-92"},"PeriodicalIF":5.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940383","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 : 2025-12-30DOI: 10.1016/j.strueco.2025.12.014
Fabio Lamperti , Davide Castellani
Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected.
{"title":"Automation and the risk of labor market exclusion across Europe","authors":"Fabio Lamperti , Davide Castellani","doi":"10.1016/j.strueco.2025.12.014","DOIUrl":"10.1016/j.strueco.2025.12.014","url":null,"abstract":"<div><div>Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 62-76"},"PeriodicalIF":5.5,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940382","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 : 2025-12-29DOI: 10.1016/j.strueco.2025.12.010
Luigi Riso, Gianmarco Vacca, Maria Zoia
In recent years, climate change has given cause for concern for the stability of the global economy, particularly financial stability. In this regard, its effects on the overall geopolitical set-up are also apparent. This work aims at disentangling the relationship among these three dimensions, via a streamlined set of econometric analyses. For Germany, France, Italy and Spain, the impact of extreme climate events on the geopolitical risk index is first investigated. The resulting climate-driven geopolitical risk is then related to each country’s financial stress index. The results that emerge from the empirical analysis highlight that the geopolitical risk induced by climate events plays a significant role in the financial stability of these countries. The impact of this type of risk turns out to depend on the specific territorial characteristics of the countries, as well as the peculiar policies and targeted measures to contain adverse climate events adopted by the various countries
{"title":"Climate-induced geopolitical risk and financial interdependence in Europe: A systemic transition perspective","authors":"Luigi Riso, Gianmarco Vacca, Maria Zoia","doi":"10.1016/j.strueco.2025.12.010","DOIUrl":"10.1016/j.strueco.2025.12.010","url":null,"abstract":"<div><div>In recent years, climate change has given cause for concern for the stability of the global economy, particularly financial stability. In this regard, its effects on the overall geopolitical set-up are also apparent. This work aims at disentangling the relationship among these three dimensions, via a streamlined set of econometric analyses. For Germany, France, Italy and Spain, the impact of extreme climate events on the geopolitical risk index is first investigated. The resulting climate-driven geopolitical risk is then related to each country’s financial stress index. The results that emerge from the empirical analysis highlight that the geopolitical risk induced by climate events plays a significant role in the financial stability of these countries. The impact of this type of risk turns out to depend on the specific territorial characteristics of the countries, as well as the peculiar policies and targeted measures to contain adverse climate events adopted by the various countries</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 23-42"},"PeriodicalIF":5.5,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886193","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 : 2025-12-27DOI: 10.1016/j.strueco.2025.12.013
Jing-hua Yin, Hai-Ying Song, Hui Zhu
Multiple frameworks have been used to explore the relationship between smart governance and sustainable development. However, three critical gaps persist: theoretical fragmentation, insufficient contextual analysis, and limited cross-country comparisons. Based on the triple-bottom-line theory and a dynamic coupling framework, this study systematically examines the staged evolutionary effects of smart governance on sustainable development and regional heterogeneity. Our hybrid research framework applies entropy-weighted comprehensive evaluation, feasible generalized least squares, and instrumental variable approaches to multi-source authoritative data from 159 countries spanning the period from 2003 to 2020. First, the results indicate that smart governance’s promoting effect increases with maturity. Second, the data reveal staged impacts. In the initial stage, hybrid governance drives economic growth, while in the middle stage, collaborative governance enhances institutional efficiency. In the long term, network governance reinforces climate action, while social equity remains inadequately addressed. Third, significant regional heterogeneity exists. Finally, mechanistically, smart governance operates through optimized business environments, improved institutional quality, and reduced climate vulnerability. However, its negative association with social trust highlights increased digital divide risks. This research provides dual perspectives on stage-specific adaptation and regional coordination for differentiated governance strategies.
{"title":"Smart governance for sustainable development: Stage-specific effects and regional heterogeneity in a global empirical framework","authors":"Jing-hua Yin, Hai-Ying Song, Hui Zhu","doi":"10.1016/j.strueco.2025.12.013","DOIUrl":"10.1016/j.strueco.2025.12.013","url":null,"abstract":"<div><div>Multiple frameworks have been used to explore the relationship between smart governance and sustainable development. However, three critical gaps persist: theoretical fragmentation, insufficient contextual analysis, and limited cross-country comparisons. Based on the triple-bottom-line theory and a dynamic coupling framework, this study systematically examines the staged evolutionary effects of smart governance on sustainable development and regional heterogeneity. Our hybrid research framework applies entropy-weighted comprehensive evaluation, feasible generalized least squares, and instrumental variable approaches to multi-source authoritative data from 159 countries spanning the period from 2003 to 2020. First, the results indicate that smart governance’s promoting effect increases with maturity. Second, the data reveal staged impacts. In the initial stage, hybrid governance drives economic growth, while in the middle stage, collaborative governance enhances institutional efficiency. In the long term, network governance reinforces climate action, while social equity remains inadequately addressed. Third, significant regional heterogeneity exists. Finally, mechanistically, smart governance operates through optimized business environments, improved institutional quality, and reduced climate vulnerability. However, its negative association with social trust highlights increased digital divide risks. This research provides dual perspectives on stage-specific adaptation and regional coordination for differentiated governance strategies.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 43-61"},"PeriodicalIF":5.5,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940380","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}
Including developing countries in the low-carbon transition is essential for meeting climate goals, yet their structural specificities are often ignored in transition models. This article presents a Structural Stock-Flow Consistent (SFC) model for open developing economies, dividing production into resource-based exports, non-tradable goods and services, and other tradable sectors. While SFC models highlight financial constraints, they rarely adopt a multi-sectoral perspective. Our model contributes by (1) providing a flexible framework that accommodates diverse country characteristics, balancing short-term demand with long-term structural strategies, and (2) demonstrating the limitations of carbon pricing alone in economies dependent on carbon-intensive sectors. By integrating structurally distinct sectors within a monetary framework, we reveal how financial constraints stemming from structural rigidities shape transition dynamics. Our results indicate that carbon pricing’s effectiveness depends on tax revenue recycling to avert recessions and support sustainable decarbonization. This requires fostering innovation and competitiveness in low-emission industries.
{"title":"Carbon tax recycling: Fostering reindustrialization in financialized developing economies","authors":"Guilherme Magacho , Antoine Godin , Danilo Spinola , Devrim Yilmaz","doi":"10.1016/j.strueco.2025.12.008","DOIUrl":"10.1016/j.strueco.2025.12.008","url":null,"abstract":"<div><div>Including developing countries in the low-carbon transition is essential for meeting climate goals, yet their structural specificities are often ignored in transition models. This article presents a Structural Stock-Flow Consistent (SFC) model for open developing economies, dividing production into resource-based exports, non-tradable goods and services, and other tradable sectors. While SFC models highlight financial constraints, they rarely adopt a multi-sectoral perspective. Our model contributes by (1) providing a flexible framework that accommodates diverse country characteristics, balancing short-term demand with long-term structural strategies, and (2) demonstrating the limitations of carbon pricing alone in economies dependent on carbon-intensive sectors. By integrating structurally distinct sectors within a monetary framework, we reveal how financial constraints stemming from structural rigidities shape transition dynamics. Our results indicate that carbon pricing’s effectiveness depends on tax revenue recycling to avert recessions and support sustainable decarbonization. This requires fostering innovation and competitiveness in low-emission industries.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"77 ","pages":"Pages 1-22"},"PeriodicalIF":5.5,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145852480","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 : 2025-12-22DOI: 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":"2025-12-22","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 : 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":"2025-12-17","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 : 2025-12-15DOI: 10.1016/j.strueco.2025.12.009
Jinyan Han , Qinhan Tian , Rongrong Chen , Jun Sun
In recent years, the construction industry and urbanization in developing countries, particularly China, have entered a phase characterized by slowing growth rates and an increasing emphasis on sustainable development. This study examines construction industry development using data from China and four developed countries (the United Kingdom, the United States, Japan, and South Korea) covering the period 1970–2022. Employing the Granger causality test, this study first identifies the causal links among construction industry, population urbanization and economic development. It then conducts an international comparative analysis, employs panel threshold regression and panel fixed-effects models with interaction terms to reveal the characteristics of the non-linear relationship between construction industry and urbanization in the third stage of urbanization. The results indicate that when the urbanization ratio approaches 80 % and GDP per capita reaches US$30,000, construction industry development will likely to stagnate for a considerable period. Economic crises are identified as factors contributing to this stagnation, particularly in countries within the third stage of urbanization. Nevertheless, recovery remains possible, depending on the construction industry's ability to adapt growth strategies to evolving urban needs. The conclusions, supported by the quantitative evidence, provide policy implications for China and other developing countries.
{"title":"An international comparison of the association between construction industry development and urbanization","authors":"Jinyan Han , Qinhan Tian , Rongrong Chen , Jun Sun","doi":"10.1016/j.strueco.2025.12.009","DOIUrl":"10.1016/j.strueco.2025.12.009","url":null,"abstract":"<div><div>In recent years, the construction industry and urbanization in developing countries, particularly China, have entered a phase characterized by slowing growth rates and an increasing emphasis on sustainable development. This study examines construction industry development using data from China and four developed countries (the United Kingdom, the United States, Japan, and South Korea) covering the period 1970–2022. Employing the Granger causality test, this study first identifies the causal links among construction industry, population urbanization and economic development. It then conducts an international comparative analysis, employs panel threshold regression and panel fixed-effects models with interaction terms to reveal the characteristics of the non-linear relationship between construction industry and urbanization in the third stage of urbanization. The results indicate that when the urbanization ratio approaches 80 % and GDP per capita reaches US$30,000, construction industry development will likely to stagnate for a considerable period. Economic crises are identified as factors contributing to this stagnation, particularly in countries within the third stage of urbanization. Nevertheless, recovery remains possible, depending on the construction industry's ability to adapt growth strategies to evolving urban needs. The conclusions, supported by the quantitative evidence, provide policy implications for China and other developing countries.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 195-208"},"PeriodicalIF":5.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790695","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 : 2025-12-15DOI: 10.1016/j.strueco.2025.12.006
Youlin Chen , Peiheng Yu , Lei Wang
Rapid urbanization has driven urban structure transformation and posed both opportunities and challenges for achieving high-quality economic growth. This study investigates the impact of urban polycentric structures (POLY) on green total factor productivity (GTFP) in China, innovatively highlights the mediating effect of scale borrowing and the moderating effect of urban development patterns. Results show that POLY has positive impacts on GTFP, and such promotion effect grows as GTFP increases. Scale borrowing plays a mediating role and different urban development patterns have various moderating effects. Specifically, urban expansion strengthens the positive moderating role of scale borrowing, whereas urban shrinkage weakens it. The threshold effect and heterogeneity analysis reveal that the positive impact of POLY on GTFP becomes more pronounced in cities with abundant land and population resources. In addition, POLY has positive spatial spillover effects, as its influence extends beyond individual cities and benefits neighboring areas. By integrating spatial structure, scale borrowing, and urban development patterns into one framework of economic growth, this study contributes to a novel understanding of high-quality economic development and sustainable urban structural transformation for policymakers.
{"title":"Exploring the relationship between urban polycentric structure and green total factor productivity in China: Insights from urban development patterns and scale borrowing","authors":"Youlin Chen , Peiheng Yu , Lei Wang","doi":"10.1016/j.strueco.2025.12.006","DOIUrl":"10.1016/j.strueco.2025.12.006","url":null,"abstract":"<div><div>Rapid urbanization has driven urban structure transformation and posed both opportunities and challenges for achieving high-quality economic growth. This study investigates the impact of urban polycentric structures (POLY) on green total factor productivity (GTFP) in China, innovatively highlights the mediating effect of scale borrowing and the moderating effect of urban development patterns. Results show that POLY has positive impacts on GTFP, and such promotion effect grows as GTFP increases. Scale borrowing plays a mediating role and different urban development patterns have various moderating effects. Specifically, urban expansion strengthens the positive moderating role of scale borrowing, whereas urban shrinkage weakens it. The threshold effect and heterogeneity analysis reveal that the positive impact of POLY on GTFP becomes more pronounced in cities with abundant land and population resources. In addition, POLY has positive spatial spillover effects, as its influence extends beyond individual cities and benefits neighboring areas. By integrating spatial structure, scale borrowing, and urban development patterns into one framework of economic growth, this study contributes to a novel understanding of high-quality economic development and sustainable urban structural transformation for policymakers.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 237-250"},"PeriodicalIF":5.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840057","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 : 2025-12-11DOI: 10.1016/j.strueco.2025.12.001
Robert Warren Anderson
This paper approaches the Great Depression, World War II and the post war boom with a novel dataset: business addresses from the phone book. Using more than 265,000 business year observations from Detroit I create a business count measure to proxy economic activity from 1920 to 1957. While this count is a small subset of all businesses, the over trend is consistent with broader economic movements. Individual industries of taverns, appliances, auto related industries, banks and housing have idiosyncratic fluctuations that reflect prior research. The overall correlation of the total business count with GDP along with distinctive individual industry movements suggests that counting entries from phone books can proxy for economic activity at a city and even industry level. Applying Artificial Intelligence to large scale digitization of phone books in potential future research will yield an annual look at city demographics and economic activity at the address level.
{"title":"Tracking Detroit business activity with the Yellow Pages 1920–1957","authors":"Robert Warren Anderson","doi":"10.1016/j.strueco.2025.12.001","DOIUrl":"10.1016/j.strueco.2025.12.001","url":null,"abstract":"<div><div>This paper approaches the Great Depression, World War II and the post war boom with a novel dataset: business addresses from the phone book. Using more than 265,000 business year observations from Detroit I create a business count measure to proxy economic activity from 1920 to 1957. While this count is a small subset of all businesses, the over trend is consistent with broader economic movements. Individual industries of taverns, appliances, auto related industries, banks and housing have idiosyncratic fluctuations that reflect prior research. The overall correlation of the total business count with GDP along with distinctive individual industry movements suggests that counting entries from phone books can proxy for economic activity at a city and even industry level. Applying Artificial Intelligence to large scale digitization of phone books in potential future research will yield an annual look at city demographics and economic activity at the address level.</div></div>","PeriodicalId":47829,"journal":{"name":"Structural Change and Economic Dynamics","volume":"76 ","pages":"Pages 171-182"},"PeriodicalIF":5.5,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737356","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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