[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127182-en":3,"doc-seo-127182-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127182,549768072016,"River Wang","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Can digital economy improve urban ecological development? - Evidence based on double machine learning analysis","The study examines whether the digital economy (DE) can enhance urban ecological development (UED) while addressing key limits of traditional causal inference models, including model misspecification and the curse of dimensionality. Using panel data from 282 Chinese cities covering 2006–2021, double machine learning estimates the causal effect of DE on UED. Results show DE significantly improves UED, strengthening ecological resilience and recovery. Mechanisms operate through green innovation, environmental efficiency, and industrial structure optimization, and the effect varies across cities.","TYPE Original Research PUBLISHED 08 April 2025  \nDOI 10.3389/fenvs.2025.1542363  \nOPEN ACCESS  \nEDITED BY  \nRuijun Zhang,  \nSoutheast University, China  \nREVIEWED BY  \nTao Yu,  \nHarbin Institute of Technology, China Nuodi Fu,  \nSoutheast University, China  \n*CORRESPONDENCE  \nYue Xu,  \n [xuyue_szcu@163.com](xuyue_szcu@163.com)  \n†These authors have contributed equally to this work.  \nRECEIVED 10 December 2024  \nACCEPTED 19 March 2025  \nPUBLISHED 08 April 2025  \nCITATION  \nJiang Y, Li L and Xu Y (2025) Can digital economy improve urban ecological development? evidence based on double machine learning analysis.  \nFront. Environ. Sci. 13:1542363 .  \ndoi: 10.3389/fenvs.2025.1542363  \nCOPYRIGHT  \n© 2025 Jiang, Li and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nCan digital economy improve urban ecological development? evidence based on double machine learning analysis  \nYuchen Jiang 1†, Lei Li 2† and Yue Xu 3*  \n1School of Business, Soochow University, Suzhou, China, 2School of Business, Applied Technology College of Soochow University, Suzhou, China, 3School of Digital Economics and Management, Suzhou City University, Suzhou, China  \nThe role of digital economy (DE) in improving urban ecological development (UED) has attracted scholarly attention. Additionally, traditional causal inference models encounter several challenges, such as model misspecification and the“curse of dimensionality.” In response to these problems, the double machine learning method is applied to assess the effect of DE on UED. Leveraging data from 282 Chinese cities in 2006–2021, several valuable conclusions emerge. First, DE improves UED and positively contributes to ecological resilience and recovery. Second, promoting green innovation, enhancing environmental efficiency, and optimizing industrial structures are the pathways through which DE contributes to UED. Third, the influence of DE on UED displays heterogeneity. Based on the results, this work proposes relevant recommendations grounded in empirical research.  \nKEYWORDS  \ndigital economy, urban ecological development, double machine learning, causal mediation model, causal inference model  \n1 Introduction  \nUrban areas are undergoing rapid development, which is accompanied by a swift influx of urban populations. As forecasted by UN-Habitat (2022), 68% of the global population will have been residing in urban regions by 2050 . The rapid expansion of urbanization undoubtedly brings substantial risks to urban ecosystems, including environmental pollution, soil erosion, biodiversity loss, and geological disasters (Song et al., 2020) . In this context, China must advance its urban ecological development (UED) to counteract the detrimental consequences of urbanization (Korhonen and Seager, 2008; Dong et al., 2022) . China has increasingly prioritized UED in recent years. Notably, the restoration and protection of urban ecosystems have been included in China’s 14th Five-Year Plan. However, urban ecosystems are confronted with numerous environmental pollution and ecological degradation issues ([Zhang H. et](Zhang H. et) al., 2023). Identifying new pathways for enhancing UED and fostering high-quality urban ecosystems is crucial.  \nExisting studies indicate a strong connection between digital economy (DE) and UED (Liu et al., 2024) . However, several gaps remain in the existing research. First, the debate over the relationship between DE and UED is far from settled. On the one hand, DE has driven advancements in digital technologies (Farley and Voinov, 2016), thereby enhancing urban ecosystems’ capacity for risk","cbCaidjmrBWtMQ5J","https://ap.wps.com/l/cbCaidjmrBWtMQ5J","pdf",1054154,1,12,"English","en",105,"# Introduction\n## Research background and motivation\n## Research gaps in existing literature\n## Study objectives and main contributions","[{\"question\":\"How does the paper evaluate the impact of the digital economy on urban ecological development?\",\"answer\":\"It applies a double machine learning (DML) approach to estimate the causal effect of digital economy on urban ecological development, using data from 282 Chinese cities from 2006 to 2021.\"},{\"question\":\"What main findings does the study report about the relationship between DE and UED?\",\"answer\":\"DE improves UED and contributes positively to ecological resilience and recovery.\"},{\"question\":\"Through what pathways does DE affect UED, and does the effect differ across cities?\",\"answer\":\"The paper identifies green innovation, environmental efficiency, and industrial structure optimization as key mechanisms, and it finds heterogeneity in DE’s influence across cities based on geographical location and resource endowment.\"}]","Can digital economy improve urban ecological development? 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