| 1,687 | 1 | 263 |
| 下载次数 | 被引频次 | 阅读次数 |
探讨数字普惠金融对农业净碳汇效率的影响，对于丰富数字金融理论体系和促进农业低碳发展提质增效具有理论与现实意义。本文基于2011—2020年全国30个省市级数据，采用Malmquist指数方法测算碳排放效率，运用面板门槛模型探究数字普惠金融对农业净碳汇效率的直接影响，采用逐步回归法探究以技术创新为中介的间接影响，鉴于地理区位和政策倾斜等原因，进一步对其影响效应的异质性进行研究。研究发现，数字普惠金融对农业净碳汇效率具有正向促进作用，且作用大小在数字普惠金融的不同门槛值区间存在差异性，在数字普惠金融低值区的影响效应大于高值区的影响效应，两者间存在非线性关系，技术创新是影响农业净碳汇效率的重要作用渠道。数字普惠金融与农业净碳汇效率的影响作用存在时间段差异，现阶段的正向促进作用明显高于2016年之前。经济发展低水平地区的数字普惠金融影响效应高于经济发展高水平地区。本文提出，加强数字金融服务，促进数字普惠金融在农业领域的推广；缩小区域发展差异，实施异质性治理策略适度规范数字金融监管；通过财政补贴等方式鼓励农民和农业企业采用低碳农业技术和管理方法，提高净碳汇效率等建议。
Abstract：Exploring the impact of digital inclusive finance on agricultural net carbon sink efficiency has theoretical and practical significance for enriching the theoretical system of digital finance and promoting the quality and efficiency of agricultural low-carbon development. Based on the data of 30 provinces and municipalities in China from 2011 to 2020, the Malmquist index method is used to measure the carbon emission efficiency, the panel threshold model is used to explore the direct impact of digital inclusive finance on the efficiency of agricultural net carbon sink, and the stepwise regression method is used to explore the indirect impact of technological innovation as an intermediary. In view of geographical location and policy inclination, the heterogeneity of its impact effect is further studied. Digital inclusive finance has a positive effect on the efficiency of agricultural net carbon sinks, and the effect is different in different threshold ranges of digital inclusive finance. The effect in the low value area of digital inclusive finance is greater than that in the high value area. There is a nonlinear relationship between the two. Technological innovation is an important channel to affect the efficiency of agricultural net carbon sinks. There are time differences in the impact of digital inclusive finance and agricultural net carbon sink efficiency, and the positive promotion effect at this stage is significantly higher than that before 2016.The impact of digital inclusive finance in regions with low economic development is higher than that in regions with high economic development. It is proposed to strengthen digital financial services and promote the promotion of digital inclusive finance in the agricultural field; reduce regional development differences and implement heterogeneous governance strategies to appropriately regulate digital financial supervision; through financial subsidies and other ways to encourage farmers and agricultural enterprises to adopt low-carbon agricultural technology and management methods, improve the efficiency of net carbon sinks and other recommendations.
陈罗烨，薛领，雪燕.2016.中国农业净碳汇时空演化特征分析[J].自然资源学报，31(4):596-607.Chen L Y,Xue L,Xue Y.2016.Spatial-temporal characteristics of China's agricultural net carbon sink[J].Journal of Natural Resources,31(4):596-607.(in Chinese)
程秋旺，许安心，陈钦.2022.“双碳”目标背景下农业碳减排的实现路径——基于数字普惠金融之验证[J].西南民族大学学报(人文社会科学版),43(2):115-126.Cheng Q W,Xu A X,Chen Q.2022.The realization path of agricultural carbon emission reduction under the background of ‘double carbon’ goal—Based on the verification of digital inclusive finance[J].Journal of Southwest Minzu University (Humanities and Social Sciences Edition),43(2):115-126.(in Chinese)
丁凡琳.2022.中国数字普惠金融对碳强度的影响[J].武汉大学学报(哲学社会科学版),75(6):110-120.Ding F L.2022.Effects of digital inclusive finance on carbon intensity of China[J].Wuhan University Journal (Philosophy & Social Science),75(6):110-120.(in Chinese)
付伟，李龙，罗明灿，等.2023.数字普惠金融助推农业低碳发展的实证研究[J].农林经济管理学报，22(1):11-19.Fu W,Li L,Luo M C,et al.2023.An empirical study of digital inclusive finance to facilitate agricultural low-carbon development[J].Journal of Agro-Forestry Economics and Management,22(1):11-19.(in Chinese)
高鸣，宋洪远.2015.中国农业碳排放绩效的空间收敛与分异——基于Malmquist-Luenberger指数与空间计量的实证分析[J].经济地理，35(4):142-148,185.Gao M,Song H Y.2015.Dynamic changes and spatial agglomeration analysis of the Chinese agricultural carbon emissions performance[J].Economic Geography,35(4):142-148,185.(in Chinese)
郭峰，王靖一，王芳，等.2020.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),19(4):1401-1418.Guo F,Wang J Y,Wang F,et al.2020.Measuring China's digital financial inclusion:index compilation and spatial characteristics[J].China Economic Quarterly,19(4):1401-1418.(in Chinese)
贺俊，程锐，刘庭.2019.金融发展、技术创新与环境污染[J].东北大学学报(社会科学版),21(2):139-148.He J,Cheng R,Liu T.2019.Financial development,technological innovation and environmental pollution[J].Journal of Northeastern University (Social Science),21(2):139-148.(in Chinese)
贺茂斌，杨晓维.2021.数字普惠金融、碳排放与全要素生产率[J].金融论坛，26(2):18-25.He M B,Yang X W.2021.Digital inclusive finance,carbon emissions and total factor productivity[J].Finance Forum,26(2):18-25.(in Chinese)
何学松，孔荣.2017.普惠金融减缓农村贫困的机理分析与实证检验[J].西北农林科技大学学报(社会科学版),17(3):76-83.He X S,Kong R.2017.Mechanism analysis and empirical test of inclusive financial system alleviating rural poverty[J].Journal of Northwest A & F University (Social Science Edition),17(3):76-83.(in Chinese)
黄益平.2017.数字普惠金融的机会与风险[J].金融发展评论，(8):14-19.Huang Y P.2017.The opportunities and challenges of digital inclusive finance[J].Financial Development Review,(8):14-19.(in Chinese)
黄益平，黄卓.2018.中国的数字金融发展：现在与未来[J].经济学(季刊),17(4):1489-1502.Huang Y P,Huang Z.2018.The development of digital finance in China:present and future[J].China Economic Quarterly,17(4):1489-1502.(in Chinese)
吉雪强，李卓群，张跃松.2023.农地流转对农业碳排放的影响及空间特性[J].资源科学，45(1):77-90.Ji X Q,Li Z Q,Zhang Y S.2023.Influence of rural land transfer on agricultural carbon emissions and its spatial characteristics[J].Resources Science,45(1):77-90.(in Chinese)
蒋庆正，李红，刘香甜.2019.农村数字普惠金融发展水平测度及影响因素研究[J].金融经济学研究，34(4):123-133.Jiang Q Z,Li H,Liu X T.2019.The measurement of the development level of digital inclusive finance in rural areas and its influencing factors[J].Financial Economics Research,34(4):123-133.(in Chinese)
江艇.2022.因果推断经验研究中的中介效应与调节效应[J].中国工业经济，(5):100-120.Jiang T.2022.Mediating effects and moderating effects in causal inference[J].China Industrial Economics,(5):100-120.(in Chinese)
李波，张俊飚.2012.基于投入视角的我国农业碳排放与经济发展脱钩研究[J].经济经纬，(4):27-31.Li B,Zhang J B.2012.Decoupling of China's agriculture carbon emissions and economic development based on the input perspective[J].Economic Survey,(4):27-31.(in Chinese)
李波，王春妤，张俊飚.2019.中国农业净碳汇效率动态演进与空间溢出效应[J].中国人口·资源与环境，29(12):68-76.Li B,Wang C Y,Zhang J B.2019.Dynamic evolution and spatial spillover of China's agricultural net carbon sink[J].China Population,Resources and Environment,29(12):68-76.(in Chinese)
李谷成，范丽霞，冯中朝.2014.资本积累、制度变迁与农业增长——对1978～2011年中国农业增长与资本存量的实证估计[J].管理世界，30(5):67-79,92.Li G C,Fan L X,Feng Z C.2014.Capital accumulation,institutional change and agricultural growth-an empirical estimation of China's agricultural growth and capital stock from 1978 to 2011[J].Journal of Management World,30(5):67-79,92.(in Chinese)
李寿喜，张珈豪.2023.数字普惠金融、技术创新与城市碳排放强度[J].华东师范大学学报(哲学社会科学版),55(2):161-172.Li S X,Zhang J H.2023.Digital financial inclusion,technological innovation and urban carbon emissions intensity[J].Journal of East China Normal University (Humanities and Social Sciences),55(2):161-172.(in Chinese)
李远航，郝兴明，张静静，等.2022.近17 a阿克苏绿洲农田净碳汇功能的时空变化[J].干旱区研究，39(4):1303-1311.Li Y H,Hao X M,Zhang J J,et al.2022.Spatial and temporal variation of net carbon sink function of farmland in Aksu oasis in the past 17 years[J].Arid Zone Research,39(4):1303-1311.(in Chinese)
刘乃全，邓敏，曹希广.2021.城市的电商化转型推动了绿色高质量发展吗?——基于国家电子商务示范城市建设的准自然实验[J].财经研究，47(4):49-63.Liu N Q,Deng M,Cao X G.2021.Does the E-commerce transformation of cities promote green and high-quality development?Evidence from a quasi-natural experiment based on national E-commerce demonstration cities[J].Journal of Finance and Economics,47(4):49-63.(in Chinese)
龙志，孙颖琦，郎丽霞，等.2022.黄土高原典型县域碳排放特征与时空格局——以庆城县为例[J].干旱区研究，39(5):1631-1641.Long Z,Sun Y Q,Lang L X,et al.2022.Spatiotemporal patterns and characteristics of carbon emissions in the Loess Plateau:A case study of Qingcheng County[J].Arid Zone Research,39(5):1631-1641.(in Chinese)
吕斯涵，张小平.2019.山东省农业净碳汇时空演化特征分析[J].水土保持学报，33(2):227-234.Lü S H,Zhang X P.2019.Spatial-temporal characteristics of agricultural net carbon sink in Shandong province[J].Journal of Soil and Water Conservation,33(2):227-234.(in Chinese)
闵继胜，胡浩.2012.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境，22(7):21-27.Min J S,Hu H.2012.Calculation of greenhouse gases emission from agricultural production in China[J].China Population,Resources and Environment,22(7):21-27.(in Chinese)
邵汉华，刘耀彬.2017.金融发展与碳排放的非线性关系研究——基于面板平滑转换模型的实证检验[J].软科学，31(5):80-84.Shao H H,Liu Y B.2017.The nonlinear relationship between financial development and carbon emission—Based on panel smooth transition regression model[J].Soft Science,31(5):80-84.(in Chinese)
宋晓玲.2017.数字普惠金融缩小城乡收入差距的实证检验[J].财经科学(6):14-25.Song X L.2017.Empirical analysis of digital inclusive finance bridging the urban-rural residents' income gap[J].Finance & Economics,(6):14-25.(in Chinese)
王劼，朱朝枝.2018.农业部门碳排放效率的国际比较及影响因素研究——基于32个国家1995—2011年的数据研究[J].生态经济，34(7):25-32.Wang J,Zhu C Z.2018.International comparison of carbon emission efficiency in agricultural sector and its influencing factors based on date from 32 countries from 1995 to 2011[J].Ecological Economy,34(7):25-32.(in Chinese)
王巧，尹晓波.2022.数字普惠金融能否有效促进碳减排?——基于阶段性效应与区域异质性视角[J].首都经济贸易大学学报，24(6):3-13.Wang Q,Yin X B.2022.Can digital inclusive finance reduce carbon emissions?—From the perspective of threshold effect and regional heterogeneity[J].Journal of Capital University of Economics and Business,24(6):3-13.(in Chinese)
王群伟，周鹏，周德群.2010.我国二氧化碳排放绩效的动态变化、区域差异及影响因素[J].中国工业经济，(1):45-54.Wang Q W,Zhou P,Zhou D Q.2010.Research on dynamic carbon dioxide emissions performance,regional disparity and affecting factors in China[J].China Industrial Economics,(1):45-54.(in Chinese)
王守坤，范文诚.2022.数字普惠金融与碳减排——基于中国县级数据的实证分析[J].当代财经，(11):53-64.Wang S K,Fan W C.2022.Digital inclusive finance and carbon emission reduction:an empirical analysis based on China's county-level data[J].Contemporary Finance & Economics,(11):53-64.(in Chinese)
王元彬，张尧，李计广.2022.数字金融与碳排放：基于微观数据和机器学习模型的研究[J].中国人口·资源与环境，32(6):1-11.Wang Y B,Zhang Y,Li J G.2022.Digital finance and carbon emissions:an empirical test based on micro data and machine learning model[J].China Population,Resources and Environment,32(6):1-11.(in Chinese)
吴贤荣，张俊飚，田云，等.2014.中国省域农业碳排放：测算、效率变动及影响因素研究——基于DEA-Malmquist指数分解方法与Tobit模型运用[J].资源科学，36(1):129-138.Wu X R,Zhang J B,Tian Y,et al.2014.Provincial agricultural carbon emissions in China:Calculation,performance change and influencing factors[J].Resources Science,36(1):129-138.(in Chinese)
吴昊玥，何艳秋，陈柔.2017.中国农业碳排放绩效评价及随机性收敛研究——基于SBM-Undesirable模型与面板单位根检验[J].中国生态农业学报，25(9):1381-1391.Wu H Y,He Y Q,Chen R.2017.Assessment of agricultural carbon emission performance and stochastic convergence in China using SBM-undesirable model and panel unit root test[J].Chinese Journal of Eco-Agriculture,25(9):1381-1391.(in Chinese)
吴昊玥，黄瀚蛟，何宇，等.2021.中国农业碳排放效率测度、空间溢出与影响因素[J].中国生态农业学报(中英文),29(10):1762-1773.Wu H Y,Huang H J,He Y,et al.2021.Measurement,spatial spillover and influencing factors of agricultural carbon emissions efficiency in China[J].Chinese Journal of Eco-Agriculture,29(10):1762-1773.(in Chinese)
徐国泉，刘则渊，姜照华.2006.中国碳排放的因素分解模型及实证分析：1995—2004[J].中国人口·资源与环境，16(6):158-161.Xu G Q,Liu Z Y,Jiang Z H.2006.Decomposition model and empirical study of carbon emissions for China,1995—2004[J].China Population,Resources and Environment,16(6):158-161.(in Chinese)
许钊，高煜，霍治方.2021.数字金融的污染减排效应[J].财经科学，(4):28-39.Xu Z,Gao Y,Huo Z F.2021.Research on pollution reduction effect of digital finance[J].Finance Economics,(4):28-39.(in Chinese)
严成樑，李涛，兰伟.2016.金融发展、创新与二氧化碳排放[J].金融研究，(1):14-30.Yan C L,Li T,Lan W.2016.Financial development,innovation and carbon emission[J].Journal of Financial Research,(1):14-30.(in Chinese)
姚凤阁，王天航，谈丽萍.2021.数字普惠金融对碳排放效率的影响——空间视角下的实证分析[J].金融经济学研究，36(6):142-158.Yao F G,Wang T H,Tan L P.2021.The impact of digital financial inclusion on carbon efficiency:Empirical analysis based on a spatial perspective[J].Financial Economics Research,36(6):142-158.(in Chinese)
姚凤阁，王天航，谈丽萍.2022.数字普惠金融对城市全要素碳排放生产率的影响[J].商业研究，(3):112-121.Yao F G,Wang T H,Tan L P.2022.The impact of digital inclusive finance on urban total factor carbon emission productivity[J].Commercial Research,(3):112-121.(in Chinese)
易行健，周利.2018.数字普惠金融发展是否显著影响了居民消费——来自中国家庭的微观证据[J].金融研究，(11):47-67.Yi X J,Zhou L.2018.Does digital financial inclusion significantly influence household consumption?Evidence from household survey data in China[J].Journal of Financial Research,(11):47-67.(in Chinese)
张生玲，王瑶，李跃.2018.地区雾霾舆论对空气质量有影响吗?——来自中国北方54个地级市月度数据证据[J].干旱区资源与环境，32(8):100-106.Zhang S L,Wang Y,Li Y.2018.Does regional haze opinion affect air quality?[J].Journal of Arid Land Resources and Environment,32(8):100-106.(in Chinese)
朱承亮，师萍，岳宏志，等.2011.人力资本、人力资本结构与区域经济增长效率[J].中国软科学，(2):110-119.Zhu C L,Shi P,Yue H Z,et al.2011.The study on bind of human capital,human capital structure and regional economic growth efficiency[J].China Soft Science,(2):110-119.(in Chinese)
Federici S,Tubiello F N,Salvatore M,et al.2015.New estimates of CO2 forest emissions and removals:1990—2015[J].Forest Ecology & Management,352:89-98.
Ouyang Y F,Li P.2018.On the nexus of financial development,economic growth,and energy consumption in China:New perspective from a GMM panel VAR approach[J].Energy Economics,71:238-252.
Paustian K,Six J,Elliott E T,et al.2000.Management options for reducing CO2 emissions from agricultural soils[J].Biogeochemistry,48(1):147-163.
Sadorsky P.2010.The impact of financial development on energy consumption in emerging economies[J].Energy Policy,38(5):2528-2535.
Sorrell S,Dimitropoulos J,Sommerville M.2009.Empirical estimates of the direct rebound effect:A review[J].Energy Policy,37(4):1356-1371.
Steenblik R,M?isé E,Evdokia M?isé.2010.Counting the carbon emissions from agricultural products:Technical complexities and trade implications[J].Food & Agricultural Trade,(1):1-6.
Tamazian A,Chousa J P,Vadlamannati K C.2009.Does higher economic and financial development lead to environmental degradation:evidence from BRIC countries[J].Energy Policy,37(1):246-253.
Tian Y,Zhang J B,He Y Y.2014.Research on spatial-temporal characteristics and driving factor of agricultural carbon emissions in China[J].Journal of Integrative Agriculture,13(6):1393-1403.
Zhou P,Ang B W,Han J Y.2010.Total factor carbon emission performance:a Malmquist index analysis[J].Energy Economics,32(1):194-201.
(1)研究期内GDP水平高于均值的地区有北京、天津、内蒙古、辽宁、上海、江苏、浙江、福建、山东、湖北、广东、重庆;研究期内GDP水平低于均值的地区有河北、山西、吉林、黑龙江、安徽、江西、河南、湖南、广西、海南、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆。
基本信息:
DOI：
中图分类号:F49;F832;F323;X322
引用信息:
[1]钱力,张轲,宋俊秀.数字普惠金融能否促进农业净碳汇效率——基于面板门槛模型的检验[J].经济学报,2024,11(04):123-149.
基金信息:
安徽省高校科研计划重大项目“劳动力流动对城乡融合发展的影响研究”(项目编号:2022AH040085); 安徽省新时代育人质量工程项目(研究生教育)“数字普惠金融对农业净碳汇效率的影响研究”(项目编号:2023xscx082)的资助