暨南学报(哲学社会科学版)

作者：吴小军

单位：南华大学知识产权与技术转移中心。

关键词：数字经济,双重机器学习模型,新质生产力,生产关系

基金：湖南省哲学社会科学项目“新时代伟大斗争研究”(20YBQ085)。

数字经济作为推动城市高质量发展的新引擎,在提升新质生产力和实现可持续发展方面具有重要意义。立足生产关系视角,选取2011—2022年282个地级市面板数据,基于双重机器学习模型探究数字经济对新质生产力的作用机制。研究发现,数字经济能有效赋能城市新质生产力发展,且数字经济对新质劳动对象的影响最大。就区域而言,数字经济对新质生产力的影响程度从大到小依次为东部地区、西部地区、中部地区、东北地区,与经济发展水平低的城市相比,经济发展水平高的城市数字经济对新质生产力的促进作用更大,且在不同资源禀赋下数字经济对新质生产力的影响程度从大到小依次为再生型城市、成长型城市、衰退型城市、非资源型城市、成熟型城市。机制检验结果表明,数字经济能够通过要素配置优化、产业结构转型等机制驱动新质生产力水平的提升。"/>template{display:none;}.mag-rich-xref-fn { cursor: pointer;}//长视频$(document).ready(function(){if($("#showLongArticleVideo") && $("#showLongArticleVideo").length && $("#showLongArticleVideo").length>0){mag_ajax_update({ele_id:'showLongArticleVideo',url:mag_currentQikanUrl() + "/CN/article/showLongArticleVideo.do?id="+$("#articleId").val()});}});$(document).ready(function(){window.metaData = {"journal":{"issn":"1000-5072","qiKanMingCheng_CN":"暨南学报（哲学社会科学版）","id":2,"qiKanMingCheng_EN":"Jinan Journal"},"fundList_cn":["湖南省哲学社会科学项目“新时代伟大斗争研究”(20YBQ085)。"],"article":{"keywordList_cn":["数字经济","双重机器学习模型","新质生产力","生产关系"],"juan":"47","zhaiyao_cn":"数字经济作为推动城市高质量发展的新引擎,在提升新质生产力和实现可持续发展方面具有重要意义。立足生产关系视角,选取2011—2022年282个地级市面板数据,基于双重机器学习模型探究数字经济对新质生产力的作用机制。研究发现,数字经济能有效赋能城市新质生产力发展,且数字经济对新质劳动对象的影响最大。就区域而言,数字经济对新质生产力的影响程度从大到小依次为东部地区、西部地区、中部地区、东北地区,与经济发展水平低的城市相比,经济发展水平高的城市数字经济对新质生产力的促进作用更大,且在不同资源禀赋下数字经济对新质生产力的影响程度从大到小依次为再生型城市、成长型城市、衰退型城市、非资源型城市、成熟型城市。机制检验结果表明,数字经济能够通过要素配置优化、产业结构转型等机制驱动新质生产力水平的提升。","endNoteUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=EndNote&id=7203","reference":"","bibtexUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=BibTeX&id=7203","abstractUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/10.11778/j.jnxb.20242546","qi":"4","id":7203,"nian":2025,"bianHao":"1751353164430-1734664964","zuoZheEn_L":"WU Xiaojun","juanUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2025","shouCiFaBuRiQi":"2025-07-01","qiShiYe":"29","qiUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2025/V47/I4","lanMu_cn":"经济学·新质生产力","pdfSize":"695","zuoZhe_CN":"吴小军","risUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=Ris&id=7203","title_cn":"数字经济何以赋能新质生产力:基于生产关系理论与双重机器学习模型","doi":"10.11778/j.jnxb.20242546","jieShuYe":"44","keywordList_en":["digital economy","double machine learning model","new quality productive forces","production relations"],"endNoteUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=EndNote&id=7203","zhaiyao_en":"With the rapid development of the digital economy, its significance in driving high-quality urban development and enhancing new quality productive forces has become increasingly prominent. However, existing studies mostly focus on the perspectives of technological application or industrial development, and there is still a lack of systematic research on how the digital economy affects new quality productive forces through changes in production relations, especially in terms of in-depth analysis of regional heterogeneity and mechanisms of action.Based on the theory of production relations, this paper selects panel data from 282 prefecture-level cities in China from 2011 to 2022 and employs the double machine learning model to explore the mechanism by which the digital economy empowers new quality productive forces in cities. The study finds that the digital economy can empower the development of new quality productive forces in cities, with the most significant impact on new-form objects of labor. The regional heterogeneity analysis reveals that the impact of the digital economy on new quality productive forces varies across regions, with the degree of influence decreasing in the following order: eastern region, western region, central region, and northeastern region. Additionally, in cities with higher levels of economic development, the digital economy exerts a stronger promoting effect on new quality productive forces. Among cities with different resource endowments, the magnitude of influence follows this sequence: regenerative cities, growing cities, declining cities, non-resource-based cities, and mature cities. The mechanism test results indicate that the digital economy empowers the level of new quality productive forces in cities through mechanisms such as optimizing factor allocation and promoting industrial structure transformation.Compared with previous studies, this paper makes threefold contributions: First, it constructs a scientific and rational index system from the perspective of production relations theory to measure new quality productive forces, providing a new perspective for the study of new quality productive forces. Second, it systematically analyzes the impact pathways of the digital economy on new quality productive forces and identifies heterogeneous effects across different regions, filling the gap in existing research. Third, it introduces the double machine learning model to effectively address estimation biases and model instability in high-dimensional data environments, enhancing the robustness of causal inference.This study not only enriches the theoretical research on the digital economy and high-quality urban development but also provides a scientific basis for local governments to formulate more targeted regional development policies in the digital economy era. It can better guide the allocation of digital economy resources to the weak links of new quality productive forces, promoting regional coordinated development and sustainable urban development.","bibtexUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=BibTeX&id=7203","abstractUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/10.11778/j.jnxb.20242546","zuoZheCn_L":"吴小军","juanUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2025","lanMu_en":"","qiUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2025/V47/I4","zuoZhe_EN":"WU Xiaojun","risUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=Ris&id=7203","title_en":"How Does the Digital Economy Empower New Quality Productive Forces:Based on Production Relations Theory and Double Machine Learning Model","hasPdf":"true"},"authorNotes_cn":["吴小军,南华大学知识产权与技术转移中心。"]};if(window.metaData && (!window.metaData.authorNotesCommon_cn && !window.metaData.authorNotesCorresp_cn && window.metaData.authorNotes_cn)){window.metaData.authorNotesCommon_cn = window.metaData.authorNotes_cn;}if(window.metaData && (!window.metaData.authorNotesCommon_en && !window.metaData.authorNotesCorresp_en && window.metaData.authorNotes_en)){window.metaData.authorNotesCommon_en = window.metaData.authorNotes_en;}var _nlmdtdXml = $("#article_nlmdtdXml").val();var magDir = _nlmdtdXml.replace(/\/[^\/]+$/,'');window.metaData.magDir = magDir;new mag_vue({ el: '#metaVue', //dataUrl: mag_currentQikanUrl() + '/EN/article/getRichHtmlJson.do?articleId='+$("#articleId").val(), data:window.metaData, loading:true, doTextFun:function(text){ return doDataJsonText(text); 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