随着2020年脱贫攻坚战的胜利，我国实现了第一个百年奋斗目标。伴随着第二个百年奋斗目标的提出，如何促使共同富裕获得更为实质性的进展成为我们接下来要解决的重中之重问题。共同富裕与我国扶贫进展紧密相关，我国贫困状态由绝对贫困转变为相对贫困，相对贫困与绝对贫困相比更侧重于社会发展过程中的不平等现象，而这种不平等不仅体现在经济收入水平的差距上，也体现于获取公共服务的能力以及社会参与度中。要实现共同富裕，解决相对贫困问题，关键是要提高社会群体参与度，促使经济发展成果全民共享。数字普惠金融利用数字化优势全面覆盖贫困地区，使其享有同等权利，十四五规划提出提高产业链现代化水平，帮助贫困群体提升自我能力，提高其社会参与度。因此，发挥产业结构优化升级在数字普惠金融减贫中的作用有利于提高经济发展质量，提升居民社会参与度，缩小社会差距，更助于实现共同富裕。

本文在梳理数字普惠金融、产业结构升级及贫困减缓的国内外文献以及三者相关概念界定的基础上，以2011-2020年我国31省份面板数据为研究样本，运用熵值法构建多维相对贫困评价指标体系及其分维度作为被解释变量，将数字普惠金融及其子维度作为解释变量，产业结构优化的分维度产业结构合理化与高级化作为中介变量，产业结构优化作为门槛变量，以及选取城镇化水平、经济发展水平和就业水平等指标作为控制变量，运用中介效应模型和门槛效应模型实证分析产业结构优化对数字普惠金融减贫的影响。结果表明：（1）数字普惠金融对多维相对贫困的减缓起直接促进作用；（2）产业结构合理化与高级化在数字普惠金融减缓多维相对贫困中起间接促进作用，其中产业结构合理化的中介作用大于产业结构高级化的；（3）当产业结构优化为门槛变量时，数字普惠金融与多维相对贫困间存在双重门槛，与收入贫困间存在单门槛；数字普惠金融覆盖广度、使用深度与多维相对贫困间存在双重门槛，数字普惠金融数字化程度与多维相对贫困间存在单门槛；（4）对于东部地区来说，产业结构高级化在数字普惠金融减缓多维相对贫困中起到的中介作用大于产业结构合理化的；对于中、西部地区来说，产业结构合理化在数字普惠金融减贫中起到的中介作用大于产业结构高级化的。最后，结合实证分析结果，提出分地区提高数字普惠金融发展水平、优化完善贫困地区教育资源与医疗保障机制以及探索产融模式，助力共同富裕等对策建议。

With the victory of the battle against poverty in 2020, China has achieved the first centenary Goal. With the proposal of the second Centenary Goal, how to promote common prosperity to achieve more substantial progress has become the top priority for us to solve. Common prosperity is closely related to the progress of poverty alleviation in China. The poverty status in China has changed from absolute poverty to relative poverty. Compared with absolute poverty, relative poverty focuses more on the inequality in the process of social development, which is not only reflected in the gap of economic income level, but also in the ability to obtain public services and social participation. To achieve common prosperity and solve the problem of relative poverty, the key is to increase the participation of social groups and ensure that the benefits of economic development are shared by all. Digital inclusive finance takes advantage of digitalization to fully cover poor areas and make them enjoy the same rights. The 14th Five-Year Plan proposes to improve the modernization of the industrial chain and help poor groups improve their self-ability and social participation. Therefore, giving play to the role of industrial structure optimization and upgrading in digital financial inclusion and poverty reduction will help improve the quality of economic development, increase residents' social participation, narrow the social gap, and better achieve common prosperity.

Based on the review of domestic and foreign literatures on digital financial inclusion, industrial structure upgrading and poverty alleviation and the definition of their related concepts, this paper takes the panel data of 31 provinces in China from 2011 to 2020 as research samples, uses the entropy method to construct a multidimensional poverty evaluation index system and its sub-dimensions as explained variables, and takes digital financial inclusion and its sub-dimensions as explanatory variables. The dimensional rationalization and upgrading of industrial structure were used as the intermediary variables, and the indicators such as urbanization level, economic development level and employment level were selected as the control variables. The intermediary effect model and threshold effect model were used to analyze the impact of industrial structure optimization on digital financial inclusion and poverty reduction. The results show that: (1) Digital financial inclusion contributes directly to the alleviation of multidimensional poverty; (2) The rationalization and upgrading of industrial structure play an indirect role in alleviating multidimensional poverty in digital financial inclusion, and the intermediary role of the rationalization of industrial structure is greater than that of the upgrading of industrial structure; (3) When the industrial structure is optimized as the threshold variable, there is a double threshold between digital financial inclusion and multidimensional poverty, and a single threshold between it and income poverty; There is a double threshold between the coverage breadth and depth of use of digital inclusive finance and multidimensional poverty, and a single threshold between the digitalization degree of digital inclusive finance and multidimensional poverty. (4) For the eastern region, the role of industrial structure upgrading in digital financial inclusion in alleviating multidimensional poverty is greater than that of industrial structure rationalization; For the central and western regions, the intermediary role of industrial structure rationalization in digital financial inclusion in poverty reduction is greater than that of industrial structure upgrading. Finally, based on the empirical analysis results, countermeasures and suggestions are put forward to improve the development level of digital inclusive finance by region, optimize the educational resources and medical security mechanism in poor areas, and explore the mode of industry and finance to help common prosperity.

[1]Burgess R,Pande R.Do rural banks matter? Evidence from the Indian social banking experiment[J].The American Economic Review,2005(3):20-27．

[2]Claessens S.Feijen E.Finance and Hunger:Empirical Evidence of the Agricultural Productivity channel [R].Policy research Working Paper,2006(6):34-42.

[3]Dev S M.Financial Inclusion:Issues and Challenges[J].Economic and Political Weekly,2006,41(41):4310-4313.

[4]Schmied J. and Marr A..Financial Inclusion and Poverty:The Case of Peru [J]. Regional and Sectoral Economic Studies,2016,16(2):1-26.

[5]Jie Li,Yu Wu,Jing Jian Xiao.The impact of digital finance on householdconsumption: Evidence from China [J].Economic Modelling,2019(9):1-10.

[6]Ozili P K.Contesting digital finance for the poor [J].Digital Policy,Regulation and Governance,2020,22(2):135-151.

[7]Fisman R,Love I.Trade credit，financial intermediary development,and industry growth [J].The Journal of finance,2003,58(1):353-374.

[8]Aghion p.,Howitt,and F.D.Mayer.The Effect of Financial Development on Convergence：Theory and Evidence [J].The Quarterly Journal of Economics，2005,120(1):173-222.

[9]Brown JRG．Martinsson et al．Do Financing Constraints Mat-ter For R＆D? [J].European Economic Review,2012(8):32-45．

[10]Kapoor, A.Financial Inclusion and the Future of the Indian Economy [J].Futures, 2014(56):35-42.

[11]Bruhn M, LOVE I．The real impact of improved access to finance: evidence from Mexico[J].Journal of finance,2014(3):102-126．

[12]Sasidharan S, Jijo ELukose P J, Komera S.Financing constraints and investments in R＆D:evidence from Indian manufacturing firms [J].The quarterly review of economics and finance,2015(55):28-39.

[13]Foster D,Rose Zweig M R.Agricultural development, industrialization and rural in Equality [J]. Journal of the acoustical society of America ,2003 ,99 (4):509-542.

[14]Kay C.Development Strategies and Rual Development:Exploring Synergies,Eradicating Poverty [J].The Journal of Peasant Studies,2009,36(1):103-137.

[15]Montalvo J G, Ravallion M.The pattern of growth and poverty reduction in China [J]. Journal of Comparative Economics,2010,38(1):2-16.

[16]Dong-Kun L I ,Yin Z M .Research on the Urban Poverty Reduction Effect of Optimizing and Upgrading the Industrial Structure in the Western Ethnic Minority Regions of China [J]. Journal of Yunnan University of Finance and Economics, 2019,24(3):12-18.

[17]黄倩,李政,熊德平.数字普惠金融的减贫效应及其传导机制[J].改革,2019,309(11):90-101.

[18]钱鹏岁,孙姝.数字普惠金融发展与贫困减缓——基于空间杜宾模型的实证研究[J].武汉金融,2019,234(6):39-46.

[19]姚凤阁,李丽佳.数字普惠金融减贫效应及区域差异研究[J].哈尔滨商业大学学报(社会科学版),2020,175(6):3-18.

[20]刘锦怡,刘纯阳.数字普惠金融的农村减贫效应:效果与机制[J].财经论丛,2020,255(1):43-53.

[21]熊德平,黄倩.数字普惠金融、农户创业与多维相对贫困[J].东岳论丛,2022,43(9):38-48.

[22]陈平,王书华,王小腾.数字普惠金融对多维相对贫困的影响研究——基于老龄化的视角[J].经济问题,2022,519(11):36-43.

[23]龚沁宜,成学真.数字普惠金融、农村贫困与经济增长[J].甘肃社会科学,2018,237(6):139-145.

[24]陈慧卿,陈国生,魏晓博,彭六妍,张星星.数字普惠金融的增收减贫效应——基于省际面板数据的实证分析[J].经济地理,2021,41(3):184-191.

[25]吴庆田,王欣宇.财政支持、数字普惠金融与多维贫困缓解[J].南方金融,2021,540(8):53-66.

[26]杨琳,李建伟.金融结构转变与实体经济结构升级(上)[J].财贸经济,2002(2):9-13.

[27]黄明清.我国普惠金融发展的产业升级效应研究——基于SYS-GMM的动态面板数据模型的实证分析[J].当代金融研究,2019,14(5):61-73.

[28]唐文进,李爽,陶云清.数字普惠金融发展与产业结构升级——来自283个城市的经验证据[J].广东财经大学学报,2019,34(6):35-49.

[29]葛和平,张立.数字普惠金融发展对产业结构升级的影响[J].财会月刊,2021,901(9):135-141.

[30]杜金岷,韦施威,吴文洋.数字普惠金融促进了产业结构优化吗?[J].经济社会体制比较,2020,212(6):38-49.

[31]谢汝宗,杨明婉,白福臣.数字普惠金融、居民消费与产业结构升级——基于广东省地级面板数据的PVAR动态分析[J].调研世界,2022,341(2):59-70.

[32]张凤华,叶初升.经济增长、产业结构与农村减贫——基于省际面板数据的实证分析[J].当代财经,2011,325(12):14-21.

[33]汪三贵,胡联.产业劳动密集度、产业发展与减贫效应研究[J].财贸研究,2014,25(3):1-5.

[34]李慧玲,徐妍.交通基础设施、产业结构与减贫效应研究——基于面板VAR模型[J].技术经济与管理研究,2016,241(8):25-30.

[35]单德朋,王英,郑长德.专业化、多样化与产业结构减贫效应的动态异质表现研究[J].中国人口·资源与环境,2017,27(7):157-168.

[36]王汉杰,温涛,韩佳丽.贫困地区农村金融减贫的产业结构门槛效应[J].财经科学,2018,366(9):26-37.

[37]谭昶,吴海涛,黄大湖.产业结构、空间溢出与农村减贫[J].华中农业大学学报(社会科学版),2019,140(2):8-17.

[38]孟维福,任碧云.包容性金融发展、产业结构优化升级与贫困减缓[J].西南民族大学学报(人文社科版),2020,41(6):97-107.

[39]郭峰,王靖一,王芳,孔涛,张勋,程志云.测度中国数字普惠金融发展:指数编制与空间特征[J].经济学(季刊),2020,19(4):1401-1418.

[40]Sen.A.Poverty:an ordinal approach to Sen. A.Poverty:an ordinal approach to measurement[J].Econometric,1976(2):219-231.

[41]梁树广,黄继忠.基于贫困含义及测定的演进视角看我国的贫困[J].云南财经大学学报,2011,27(1):55-61.

[42]陈闻鹤,常志朋.国内外多维贫困研究进展[J].长江师范学院学报,2019,35(5):31-41.

[43]宋扬,王暖盈.生命周期视角下收入主导型多维贫困的识别与成因分析[J].经济理论与经济管理,2019,339(3):70-83.

[44]苏静,胡宗义,肖攀.中国农村金融发展的多维减贫效应非线性研究——基于面板平滑转换模型的分析[J].金融经济学研究,2014,29(4):86-96.

[45]傅鹏,张鹏,周颖.多维贫困的空间集聚与金融减贫的空间溢出——来自中国的经验证据[J].财经研究,2018,44(2):115-126.

[46]刘宏霞,汪慧玲,谢宗棠.农村金融发展、财政支农与西部地区减贫效应分析——基于面板门槛模型的研究[J].统计与信息论坛,2018,33(3):51-57.

[47]朱冬元,杨潇宇,孙浩然.城镇化发展多维减贫效应的实证分析[J].统计与决策,2019,35(21):88-92.

[48]干春晖,郑若谷,余典范.中国产业结构变迁对经济增长和波动的影响[J].经济研究,2011,46(5):4-16.

[49]郑万吉,叶阿忠.城乡收入差距、产业结构升级与经济增长——基于半参数空间面板VAR模型的研究[J]经济学家,2015,202(10):61-67．

[50]于斌斌.金融集聚促进了产业结构升级吗:空间溢出的视角——基于中国城市动态空间面板模型的分析[J].国际金融研究,2017,358(2):12-23.

[51]Schutz,T.W.“Investing in Poor People:An Economist’s View”[J]. American Economic Review,1965(40):510-20.

[52]盛丹,王永进.产业集聚、信贷资源配置效率与企业的融资成本——来自世界银行调查数据和中国工业企业数据的证据[J].管理世界,2013,237(6):85-98.

[53]刘湘云,吴文洋.科技金融与高新技术产业协同演化机制及实证检验——源于广东实践[J].广东财经大学学报,2018,33(3):20-32.

[54]韩晶,酒二科.以产业结构为中介的创新影响中国经济增长的机理[J].经济理论与经济管理,2018,330(6):51-63.

[55]李英杰,韩平.中国数字经济发展综合评价与预测[J].统计与决策,2022,38(2):90-94.

[56]田霖,张园园,张仕杰.数字普惠金融对乡村振兴的动态影响研究——基于系统GMM及门槛效应的检验[J].重庆大学学报(社会科学版),2022,28(3):25-38.

[57]刘华珂.普惠金融对农村减贫的效应研究[J].金融与经济,2021,526(5):84-91.

[58]孙英杰,林春.中国普惠金融发展的影响因素及其收敛性——基于中国省级面板数据检验[J].广东财经大学学报,2018,33(2):89-98.

[59]徐光顺,冯林.数字普惠金融对城乡收入差距影响的再检验——基于农户人力资本投资调节效应的视角[J].农业经济问题,2022,509(5):60-82.

[60]刘新智,刘雨松.城镇化进程中农村人力资本积累对农民收入增长的影响[J].当代经济研究,2016,250(6):69-78.

[61]崔万田,何春.城镇化的农村减贫效应:理论机制与实证检验[J].经济科学,2018,226(4):89-102.

[62]汪伟,刘玉飞,彭冬冬.人口老龄化的产业结构升级效应研究[J].中国工业经济,2015,332(11):47-61.

[63]李建军,韩珣.普惠金融、收入分配和贫困减缓——推进效率和公平的政策框架选择[J].金融研究,2019,456(3):129-148.

[64]苏建军,徐璋勇.金融发展、产业结构升级与经济增长——理论与经验研究[J].工业技术经济,2014,33(2):139-149.

[65]陈晓玲,张毅.金融发展、产业升级与经济增长的动态关系研究——基于省际数据的面板VAR分析[J].财贸研究,2017,28(10):19-25.

[66]谢汝宗,蒙利婷,谢妮.高职教育投入与产业结构升级的动态关系[J].重庆高教研究,2022,10(6):72-84.

[67]温忠麟,叶宝娟.中介效应分析:方法和模型发展[J].心理科学进展,2014,22(5):731-745.

[68]HANSEN B E.Threshold effects in non-dynamic panels: estimation,testing,and inference[J].Journal of Econometrics,1999,93(2):345-368．

[69]刘华珂.产业结构变迁视角下普惠金融的城镇反贫困效应——基于中介效应模型的实证检验[J].投资研究,2020,39(8):92-106.

[70]杨德勇,代海川,黄帆帆.数字普惠金融对城乡居民收入差距的门限效应研究——基于不同发展维度的实证分析[J].经济与管理评论,2022,38(3):89-101.

[71]康书生,杨娜娜.数字普惠金融发展促进乡村产业振兴的效应分析[J].金融理论与实践,2022,511(2):110-118.