Pub Date : 2026-01-01DOI: 10.1016/j.eap.2025.12.033
Xiaoyu Yin , Jia Li
Understanding how intellectual-property protection shapes employment is vital for policies that spur sustainable job growth. Most studies examine IP protection’s role in innovation, leaving its employment effects underexplored. Using data from Chinese listed firms between 2006 and 2019, this paper adopts a stacked difference-in-differences approach to evaluate the effect of the National Intellectual Property Model City Policy on firm-level employment. The results show that the policy significantly increases employment in pilot-city firms, and the impact is stronger for companies that already employ more R&D personnel (direct effect), channel additional capital into scaling up production (vertical innovation), or generate new products and services that open up fresh positions (horizontal innovation). Further analysis indicates that the policy reduces the proportion of low-skilled workers, signaling an upgrading of workforce skills. Heterogeneity analysis based on machine learning shows that firm size, educational infrastructure, and ecological environment further amplify the policy's employment effects. These findings suggest that strengthening intellectual property regimes and improving urban infrastructure can foster job growth and optimize policy outcomes.
{"title":"How strengthened intellectual property protection creates jobs? Empirical evidence from listed firms in China under a pilot policy","authors":"Xiaoyu Yin , Jia Li","doi":"10.1016/j.eap.2025.12.033","DOIUrl":"10.1016/j.eap.2025.12.033","url":null,"abstract":"<div><div>Understanding how intellectual-property protection shapes employment is vital for policies that spur sustainable job growth. Most studies examine IP protection’s role in innovation, leaving its employment effects underexplored. Using data from Chinese listed firms between 2006 and 2019, this paper adopts a stacked difference-in-differences approach to evaluate the effect of the National Intellectual Property Model City Policy on firm-level employment. The results show that the policy significantly increases employment in pilot-city firms, and the impact is stronger for companies that already employ more R&D personnel (direct effect), channel additional capital into scaling up production (vertical innovation), or generate new products and services that open up fresh positions (horizontal innovation). Further analysis indicates that the policy reduces the proportion of low-skilled workers, signaling an upgrading of workforce skills. Heterogeneity analysis based on machine learning shows that firm size, educational infrastructure, and ecological environment further amplify the policy's employment effects. These findings suggest that strengthening intellectual property regimes and improving urban infrastructure can foster job growth and optimize policy outcomes.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 641-662"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884538","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 : 2026-01-01DOI: 10.1016/j.eap.2026.01.011
Yarong Sun , Xinxiang Zhang , Lijun Hu , Fang He , Lei Chen
Promoting green economic efficiency has become a central objective of China's sustainable transition, requiring the coordinated deployment of multiple policy tools. This study investigates how environmental regulation and green finance jointly shape green development outcomes, and whether their combined application generates benefits beyond their individual effects. Building on a pressure-resource perspective, we develop a theoretical framework and conduct empirical tests using a balanced panel covering 287 prefecture-level cities from 2008 to 2022. The model assesses both separate and joint policy effects and further identifies the underlying transmission channels through emission constraints, innovation-driven growth, and financing support. The results show that although each policy independently improves green economic efficiency, their joint implementation further strengthens and enhances the effect, producing a synergy-enhancing outcome. Mechanism analysis further reveals that the synergy operates mainly through constraints on emissions, enhanced innovation dynamics, and targeted financing support. The positive effects are evident across varying levels of environmental pollution and energy dependence. However, in regions with a low level of industrial structure upgrading, the reinforcing effect of policy interaction weakens, suggesting that structural rigidities limit the potential gains from policy overlap.
{"title":"Evaluating the synergy of environmental regulation and green finance: A pressure-resource framework","authors":"Yarong Sun , Xinxiang Zhang , Lijun Hu , Fang He , Lei Chen","doi":"10.1016/j.eap.2026.01.011","DOIUrl":"10.1016/j.eap.2026.01.011","url":null,"abstract":"<div><div>Promoting green economic efficiency has become a central objective of China's sustainable transition, requiring the coordinated deployment of multiple policy tools. This study investigates how environmental regulation and green finance jointly shape green development outcomes, and whether their combined application generates benefits beyond their individual effects. Building on a pressure-resource perspective, we develop a theoretical framework and conduct empirical tests using a balanced panel covering 287 prefecture-level cities from 2008 to 2022. The model assesses both separate and joint policy effects and further identifies the underlying transmission channels through emission constraints, innovation-driven growth, and financing support. The results show that although each policy independently improves green economic efficiency, their joint implementation further strengthens and enhances the effect, producing a synergy-enhancing outcome. Mechanism analysis further reveals that the synergy operates mainly through constraints on emissions, enhanced innovation dynamics, and targeted financing support. The positive effects are evident across varying levels of environmental pollution and energy dependence. However, in regions with a low level of industrial structure upgrading, the reinforcing effect of policy interaction weakens, suggesting that structural rigidities limit the potential gains from policy overlap.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 1026-1044"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977721","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 : 2026-01-01DOI: 10.1016/j.eap.2026.01.010
Zheng Wang , Hongchao Liu
This study examines whether and how artificial intelligence engagement affects firms’ deviations from historically expected performance. Using data from non-financial A-share listed firms in China, this study constructs a firm-level indicator of AI engagement based on annual report text and empirically examines its impact on the historical performance expectation gap. The analysis further investigates the underlying transmission channels and the moderating role of the macro policy environment. The results show that higher AI engagement is associated with smaller deviations from historical performance expectations, suggesting that AI enhances firms’ ability to manage expectations and align outcomes with historical benchmarks. Mechanism analysis reveals that this effect operates indirectly through improvements in both supply chain stability and top management team consistency, highlighting the dual governance value of AI across internal and external dimensions. Moreover, the moderating effect analysis finds that the role of AI becomes more pronounced under accommodative monetary policy conditions, indicating that supportive policy environments amplify the effectiveness of AI-based governance. This study contributes to the literature by offering a micro-level governance perspective on the economic consequences of AI, and provides empirical insight into the dynamic interaction between technological integration, expectation management, and institutional conditions.
{"title":"Artificial intelligence and the historical performance expectation gap: Evidence from the moderating role of monetary easing","authors":"Zheng Wang , Hongchao Liu","doi":"10.1016/j.eap.2026.01.010","DOIUrl":"10.1016/j.eap.2026.01.010","url":null,"abstract":"<div><div>This study examines whether and how artificial intelligence engagement affects firms’ deviations from historically expected performance. Using data from non-financial A-share listed firms in China, this study constructs a firm-level indicator of AI engagement based on annual report text and empirically examines its impact on the historical performance expectation gap. The analysis further investigates the underlying transmission channels and the moderating role of the macro policy environment. The results show that higher AI engagement is associated with smaller deviations from historical performance expectations, suggesting that AI enhances firms’ ability to manage expectations and align outcomes with historical benchmarks. Mechanism analysis reveals that this effect operates indirectly through improvements in both supply chain stability and top management team consistency, highlighting the dual governance value of AI across internal and external dimensions. Moreover, the moderating effect analysis finds that the role of AI becomes more pronounced under accommodative monetary policy conditions, indicating that supportive policy environments amplify the effectiveness of AI-based governance. This study contributes to the literature by offering a micro-level governance perspective on the economic consequences of AI, and provides empirical insight into the dynamic interaction between technological integration, expectation management, and institutional conditions.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 1077-1092"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977723","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 : 2026-01-01DOI: 10.1016/j.eap.2025.12.026
Minmin Huang , Jin Hu , Mingjun Hu , Muhammad Irfan , Kaiya Wu
This study investigates the dynamic nexus between supply chain digitalization (SCD) and energy utilization efficiency (EUE) as a key pathway to improving energy resilience in urban China. Utilizing a Difference-in-Differences (DID) econometric approach on panel data from 276 cities spanning 2006 to 2021, our analysis reveals that SCD significantly enhances EUE through multiple channels: governmental support for innovation, advancements in green technological development, and stimulation of entrepreneurial ecosystems. The study finds that cities with robust technological infrastructures, diversified economic bases, and excellent business environment experience more pronounced efficiency gains, while regions with stringent environmental regulations show a “squeeze effect” that limits digitalization’s positive impact on energy performance. These findings underscore the need for adaptive, policy-driven frameworks that harmonize digital transformation with sustainable energy strategies, offering actionable insights for policymakers and stakeholders aiming to bolster energy resilience and secure energy supply chains.
{"title":"How technological and regulatory factors shape the impact of supply chain digitalization on energy utilization efficiency","authors":"Minmin Huang , Jin Hu , Mingjun Hu , Muhammad Irfan , Kaiya Wu","doi":"10.1016/j.eap.2025.12.026","DOIUrl":"10.1016/j.eap.2025.12.026","url":null,"abstract":"<div><div>This study investigates the dynamic nexus between supply chain digitalization (SCD) and energy utilization efficiency (EUE) as a key pathway to improving energy resilience in urban China. Utilizing a Difference-in-Differences (DID) econometric approach on panel data from 276 cities spanning 2006 to 2021, our analysis reveals that SCD significantly enhances EUE through multiple channels: governmental support for innovation, advancements in green technological development, and stimulation of entrepreneurial ecosystems. The study finds that cities with robust technological infrastructures, diversified economic bases, and excellent business environment experience more pronounced efficiency gains, while regions with stringent environmental regulations show a “squeeze effect” that limits digitalization’s positive impact on energy performance. These findings underscore the need for adaptive, policy-driven frameworks that harmonize digital transformation with sustainable energy strategies, offering actionable insights for policymakers and stakeholders aiming to bolster energy resilience and secure energy supply chains.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 663-680"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884545","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 : 2026-01-01DOI: 10.1016/j.eap.2026.01.009
Yijing Wang , Kang Xi
In the context of the global transition to a low-carbon economy, a key issue in balancing environmental regulation with the allocation of labour skills is how carbon market policies reshape the structure of labour demand through technological pathways. This study employs data from listed Chinese manufacturing companies from 2011 to 2023 and utilises a multi-period difference-in-differences (DID) approach to examine the impact of carbon market pilot policies. The findings indicate that these policies significantly promote firms’ skill premiums. Further mechanism analysis reveals that carbon emissions trading policies, by exerting regulatory pressure, incentivise firms to adopt robotics to enhance productivity. Consequently, firms' demand for high-skilled labour increases significantly, while the demand for low-skilled labour decreases. This study offers novel empirical evidence on the interaction between carbon market policies and labour market dynamics, providing policy insights to support the government in effectively responding to changes in the employment structure and promoting adaptive adjustments in the labour market during the green transition process.
{"title":"Carbon markets, industrial robots, and the labour skill premium","authors":"Yijing Wang , Kang Xi","doi":"10.1016/j.eap.2026.01.009","DOIUrl":"10.1016/j.eap.2026.01.009","url":null,"abstract":"<div><div>In the context of the global transition to a low-carbon economy, a key issue in balancing environmental regulation with the allocation of labour skills is how carbon market policies reshape the structure of labour demand through technological pathways. This study employs data from listed Chinese manufacturing companies from 2011 to 2023 and utilises a multi-period difference-in-differences (DID) approach to examine the impact of carbon market pilot policies. The findings indicate that these policies significantly promote firms’ skill premiums. Further mechanism analysis reveals that carbon emissions trading policies, by exerting regulatory pressure, incentivise firms to adopt robotics to enhance productivity. Consequently, firms' demand for high-skilled labour increases significantly, while the demand for low-skilled labour decreases. This study offers novel empirical evidence on the interaction between carbon market policies and labour market dynamics, providing policy insights to support the government in effectively responding to changes in the employment structure and promoting adaptive adjustments in the labour market during the green transition process.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 986-1004"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926029","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}
Geopolitical events, such as the Russia–Ukraine conflict, accelerate global energy trade reallocation and supply chain restructuring. Oil shocks spread through global production networks via trade flows reorganization and production consumption. However, existing studies have not clearly described the process by which shocks generate initial disturbances through trade channels and undergo nonlinear transmission through production channels. This study constructs the MRIONFCS (multi-regional input-output network integrated with non-failure cascading spreading model) framework to simulate the dynamic transmission of oil shocks triggered by the trade reallocation of Russian oil through trade-production dual channels. By quantifying the economic impacts of shocks across 26 sectors in 189 economies, the study finds that the combined effects of trade centralization and geopolitical divergence exacerbate the uneven distribution of shocks. Asia (e.g., India, China) is the primary beneficiary of positive shocks, achieving cross-sectoral gains through industrial chain coupling. Europe (e.g., Germany, Italy) becomes a concentrated zone of negative shocks, with some regions experiencing persistent negative impacts due to refinery technologies locked into Russian Urals crude oil and slow energy transitions. At the same time, geographically critical small and medium-sized countries play counterintuitive roles in shock diffusion. Strategic hub countries such as Tunisia exhibit significantly higher amplification effects on shocks compared to large economies like India, acting as amplifiers for nonlinear shock transmission. This study reveals that the synergy between industrial structures and geopolitical strategies leads to resilience disparities among countries facing shocks, providing policy guidance for global energy-industry collaborative governance.
{"title":"The global cascading impacts of oil shocks after geopolitical event based on a counterfactual simulation","authors":"Shuai Ren , Huajiao Li , Qianyong Tang , Yuqi Zhang","doi":"10.1016/j.eap.2025.12.038","DOIUrl":"10.1016/j.eap.2025.12.038","url":null,"abstract":"<div><div>Geopolitical events, such as the Russia–Ukraine conflict, accelerate global energy trade reallocation and supply chain restructuring. Oil shocks spread through global production networks via trade flows reorganization and production consumption. However, existing studies have not clearly described the process by which shocks generate initial disturbances through trade channels and undergo nonlinear transmission through production channels. This study constructs the MRIO<img>NFCS (multi-regional input-output network integrated with non-failure cascading spreading model) framework to simulate the dynamic transmission of oil shocks triggered by the trade reallocation of Russian oil through trade-production dual channels. By quantifying the economic impacts of shocks across 26 sectors in 189 economies, the study finds that the combined effects of trade centralization and geopolitical divergence exacerbate the uneven distribution of shocks. Asia (e.g., India, China) is the primary beneficiary of positive shocks, achieving cross-sectoral gains through industrial chain coupling. Europe (e.g., Germany, Italy) becomes a concentrated zone of negative shocks, with some regions experiencing persistent negative impacts due to refinery technologies locked into Russian Urals crude oil and slow energy transitions. At the same time, geographically critical small and medium-sized countries play counterintuitive roles in shock diffusion. Strategic hub countries such as Tunisia exhibit significantly higher amplification effects on shocks compared to large economies like India, acting as amplifiers for nonlinear shock transmission. This study reveals that the synergy between industrial structures and geopolitical strategies leads to resilience disparities among countries facing shocks, providing policy guidance for global energy-industry collaborative governance.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 772-787"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926028","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 : 2026-01-01DOI: 10.1016/j.eap.2026.01.004
Xin Gao, Can Guo, Aiqin Hu
Due to the increasingly close supply chain, trade, and investment linkages among enterprises, external shocks not only directly impact target firms but also exert significant indirect effects on affiliated enterprises along the supply chain. This paper takes the US Entity List sanctions against Chinese entities as a case study to empirically examine the impact of export controls on the stock price volatility of Chinese affiliated enterprises. The results indicate that US export controls significantly exacerbate stock price volatility among Chinese affiliated enterprises, exerting a notable adverse impact. This effect is more pronounced for smaller-scale, highly liquid, low R&D intensity, and non-foreign-invested affiliated enterprises. Mechanism analysis reveals that three factors play critical roles in transmitting this impact: the risk-taking capacity of affiliated enterprises, supply chain concentration, and investor confidence. Specifically, higher risk-taking capacity and diversified supply chain structures mitigate the adverse effects, while lower risk-taking capacity and concentrated supply chains intensify them; investor confidence functions as a transmission channel amplifying the negative impacts. Further analysis using a Difference-in-Differences-in-Differences (DDD) model shows that amid intensified export controls, the stock price volatility of affiliated enterprises in the high-tech sector is more severe. For high-tech enterprises, government subsidies effectively mitigate these adverse effects; however, higher risk-taking capacity intensifies the negative impacts (whereas lower risk-taking capacity mitigates them), and the intensifying effect of supply chain concentration as well as the transmission effect of investor confidence become statistically insignificant. By integrating export controls and the stock price dynamics of affiliated enterprises into a unified analytical framework, this paper provides important micro-level evidence and policy implications for Chinese enterprises to effectively respond to the indirect impacts of external shocks, thereby facilitating capital market stability and high-quality economic development.
{"title":"Export controls and stock price fluctuations of affiliated companies: Empirical evidence from the US entity list against China","authors":"Xin Gao, Can Guo, Aiqin Hu","doi":"10.1016/j.eap.2026.01.004","DOIUrl":"10.1016/j.eap.2026.01.004","url":null,"abstract":"<div><div>Due to the increasingly close supply chain, trade, and investment linkages among enterprises, external shocks not only directly impact target firms but also exert significant indirect effects on affiliated enterprises along the supply chain. This paper takes the US Entity List sanctions against Chinese entities as a case study to empirically examine the impact of export controls on the stock price volatility of Chinese affiliated enterprises. The results indicate that US export controls significantly exacerbate stock price volatility among Chinese affiliated enterprises, exerting a notable adverse impact. This effect is more pronounced for smaller-scale, highly liquid, low R&D intensity, and non-foreign-invested affiliated enterprises. Mechanism analysis reveals that three factors play critical roles in transmitting this impact: the risk-taking capacity of affiliated enterprises, supply chain concentration, and investor confidence. Specifically, higher risk-taking capacity and diversified supply chain structures mitigate the adverse effects, while lower risk-taking capacity and concentrated supply chains intensify them; investor confidence functions as a transmission channel amplifying the negative impacts. Further analysis using a Difference-in-Differences-in-Differences (DDD) model shows that amid intensified export controls, the stock price volatility of affiliated enterprises in the high-tech sector is more severe. For high-tech enterprises, government subsidies effectively mitigate these adverse effects; however, higher risk-taking capacity intensifies the negative impacts (whereas lower risk-taking capacity mitigates them), and the intensifying effect of supply chain concentration as well as the transmission effect of investor confidence become statistically insignificant. By integrating export controls and the stock price dynamics of affiliated enterprises into a unified analytical framework, this paper provides important micro-level evidence and policy implications for Chinese enterprises to effectively respond to the indirect impacts of external shocks, thereby facilitating capital market stability and high-quality economic development.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 965-985"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925886","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 : 2026-01-01DOI: 10.1016/j.eap.2025.12.002
Gianpiero Chironna , Giuseppe Orlando
Although the probability of default (PD) modeling has reached a great maturity in both academia and business, for the Italian case we demonstrate that banks’ available PD models would be misleading if today applied directly to Italian banks. We argue that what determines the PD of Italian banks, rather than the liquidity, are the return on assets (ROA), the financial leverage and the type of the bank. Furthermore, we demonstrate that the conventional approach dominates the more trendy machine learning (ML) and that model’s performance could be used as a supervisory tool for retrospective analysis of the bank’s position. This work stands out as the only study to consider state aid in defining bank default over the horizon period from 2010 to 2020, examining bank default in Italy across various types of banks, and employing both conventional and machine learning approaches, while also proposing an easy-to-handle three-variable model for predicting bank defaults.
{"title":"Predicting bank defaults in Italy: A comparative analysis of conventional and machine learning approaches","authors":"Gianpiero Chironna , Giuseppe Orlando","doi":"10.1016/j.eap.2025.12.002","DOIUrl":"10.1016/j.eap.2025.12.002","url":null,"abstract":"<div><div>Although the probability of default (PD) modeling has reached a great maturity in both academia and business, for the Italian case we demonstrate that banks’ available PD models would be misleading if today applied directly to Italian banks. We argue that what determines the PD of Italian banks, rather than the liquidity, are the return on assets (ROA), the financial leverage and the type of the bank. Furthermore, we demonstrate that the conventional approach dominates the more trendy machine learning (ML) and that model’s performance could be used as a supervisory tool for retrospective analysis of the bank’s position. This work stands out as the only study to consider state aid in defining bank default over the horizon period from 2010 to 2020, examining bank default in Italy across various types of banks, and employing both conventional and machine learning approaches, while also proposing an easy-to-handle three-variable model for predicting bank defaults.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 788-833"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925887","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 : 2026-01-01DOI: 10.1016/j.eap.2025.12.035
Xiang Yin , Yan-Lin Yang , Chun-Ping Chang , Qiang Fu
The research on the employment effect of the digital economy not only requires grasping the macro trends but also delving into the micro mechanisms. This study examines the impact of digital enterprise growth on labor employment in the supply chains of upstream and downstream enterprises, exploring the micro-logic of how the development of the digital industry affects employment levels. Our findings suggest that the growth of digital enterprises has a significant negative impact on the employment of their supply chain partners. Currently, the level of digital coordination within supply chains remains relatively low, which limits the job creation potential of digitalisation. Heterogeneity analysis reveals that this suppressive effect is particularly pronounced for digital enterprises in the eastern region, those in the digital technology application sector and technology-intensive enterprises. Conversely, digital enterprise growth in the central region appears to promote supply chain employment. Based on these findings, the paper proposes targeted policy recommendations.
{"title":"Economic forces and the employment paradox in the digital industry: creation and substitution effects from the perspective of supply chains","authors":"Xiang Yin , Yan-Lin Yang , Chun-Ping Chang , Qiang Fu","doi":"10.1016/j.eap.2025.12.035","DOIUrl":"10.1016/j.eap.2025.12.035","url":null,"abstract":"<div><div>The research on the employment effect of the digital economy not only requires grasping the macro trends but also delving into the micro mechanisms. This study examines the impact of digital enterprise growth on labor employment in the supply chains of upstream and downstream enterprises, exploring the micro-logic of how the development of the digital industry affects employment levels. Our findings suggest that the growth of digital enterprises has a significant negative impact on the employment of their supply chain partners. Currently, the level of digital coordination within supply chains remains relatively low, which limits the job creation potential of digitalisation. Heterogeneity analysis reveals that this suppressive effect is particularly pronounced for digital enterprises in the eastern region, those in the digital technology application sector and technology-intensive enterprises. Conversely, digital enterprise growth in the central region appears to promote supply chain employment. Based on these findings, the paper proposes targeted policy recommendations.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 882-899"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925951","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 : 2026-01-01DOI: 10.1016/j.eap.2025.11.017
Mamiko Takeuchi
This paper examines the effects of Japan’s “5-year rule,” implemented in 2018, which mandates the conversion of fixed-term employees to permanent status upon their application after five consecutive years of employment. The analysis employs a difference-in-differences (DiD) approach combined with entropy balancing. Unlike other countries’ reforms, a distinctive feature of this reform is that it grants firms discretion over its implementation. Consequently, the reform significantly increased permanent employment conversions among middle-aged and older women with lower educational attainment, though it did not affect their transition to regular employment or wages. This effect is more pronounced for women in firms, industries, and occupations with conventionally high proportions of renewable contracts. Overall, while the reform enhances women’s employment stability, it entrenches gender and educational disparities in employment conditions, with stability differences persisting even among fixed-term employees based on conversion outcomes. Strengthening the complementary policies that address these issues is warranted.
{"title":"The impact of employment protection reform on the working conditions of fixed-term employees in Japan","authors":"Mamiko Takeuchi","doi":"10.1016/j.eap.2025.11.017","DOIUrl":"10.1016/j.eap.2025.11.017","url":null,"abstract":"<div><div>This paper examines the effects of Japan’s “5-year rule,” implemented in 2018, which mandates the conversion of fixed-term employees to permanent status upon their application after five consecutive years of employment. The analysis employs a difference-in-differences (DiD) approach combined with entropy balancing. Unlike other countries’ reforms, a distinctive feature of this reform is that it grants firms discretion over its implementation. Consequently, the reform significantly increased permanent employment conversions among middle-aged and older women with lower educational attainment, though it did not affect their transition to regular employment or wages. This effect is more pronounced for women in firms, industries, and occupations with conventionally high proportions of renewable contracts. Overall, while the reform enhances women’s employment stability, it entrenches gender and educational disparities in employment conditions, with stability differences persisting even among fixed-term employees based on conversion outcomes. Strengthening the complementary policies that address these issues is warranted.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"89 ","pages":"Pages 1191-1217"},"PeriodicalIF":8.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022645","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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