To maintain a relatively fast growth of residents' income in key ecological function areas is of great significance to promote the ecological protection and construction. This study measured the residents' income level at three spatial scales in the first batch of national key ecological function areas (NKEFA) in 2010 and 2020,analyzed the spatial-temporal characteristics and driving factors of residents' income level using the methods of scale variance,Dagum Gini coefficient,kernel density estimation,and econometric model. The results show that: 1) The growth rate of residents' income level is faster in NKEFA than that at the whole country,but its income level are still significantly lower than the national average. The growth rate is slower in the east side of the HU Huanyong Line than that in the west side,the absolute gap of income widens between the east side of the HU Huanyong Line and the west. The growth rate is faster in the south side of the Qinhuai Line than that in the north side,which leads to a shift from 'higher in the north side of the Qinhuai Line' to 'lower in the north side of the Qinhuai Line. 2) The differences in residents' income level decreases but the income gap is still significant. The income differences mainly present at the obvious shift from the county scale to both county and functional area scales. The income differences at regional scale are mainly manifested in respective intra-regional differences,and the differences among regions are mainly among the west China and other regions. 3) The spatial characteristics and change trend of residents' income level are similar at county and functional area scales,the trend surface of income changes is not obvious in the middle of China and the west of China,but it has obvious changes in the east of China and the northeast of China. 4) The driving factors of residents' income tend to be diversified and their role has generally enhanced. Urbanization, population scale, agricultural development and local public finance are important driving factors of the residents' income level,and economic development mainly affects residents' income through the transmission mechanism. Finally,some suggestions are given to improve residents' income,such as accelerating urbanization,promoting green development,enhancing employment,optimizing the use of financial funds,and implementing differentiated policies.
[1] Yu F Q,Lu C X,Xiao Y,et al.Ecosystem service value assessment for national key eco-function zones for water and soil conservation[J]. Journal of Resources and Ecology,2017,8(4):369-377.
[2] 丁斐,庄贵阳. 国家重点生态功能区设立是否促进了经济发展[J]. 中国人口·资源与环境,2021,31(10):19-28.
[3] 赵振芳,张亮. 我国生态功能区可持续发展面临的问题与建议[J]. 经济纵横,2017(6):28-32.
[4] 王蓉,赵雪雁,刘江华,等. 重点生态功能区农户生计对环境资源的依赖性——以甘南高原为例[J]. 应用生态学报,2020,31(2):554-562.
[5] 李卫华. 缩小居民收入城乡差距与地区差距的制度创新[J]. 经济地理,2019,39(3):195-200.
[6] 孙杰,苗振龙,陈修颖. 中国信息化鸿沟对区域收入差异的影响[J]. 经济地理,2019,39(12):31-38.
[7] 刘华军,孙东旭,丁晓晓. 中国居民收入的南北差距分析[J]. 中国人口科学,2022(4):30-43,126-127.
[8] 孙晓一,徐勇,刘艳华. 中国居民收入差距及空间分异特征[J]. 经济地理,2015,35(12):18-25,42.
[9] 吴彬彬,李实. 中国地区之间收入差距变化:2002—2013年[J]. 经济与管理研究,2018,39(10):31-44.
[10] 罗楚亮,李实,岳希明. 中国居民收入差距变动分析(2013-2018)[J]. 中国社会科学,2021(1):33-54.
[11] Xie Y,Zhou X.Income inequality in today’s China[J]. Proceedings of the National Academy of Sciences of the United States of America,2014,111(19):6928-6933.
[12] 李建新,梁曼,吴巍. 21世纪以来中国居民收入与经济增长水平的多尺度时空耦合研究[J]. 热带地理,2022,42(8):1253-1263.
[13] 卢倩倩,许光建,许坤. 城镇化、经济周期与地区收入分配差距——基于面板门限模型的分析[J]. 经济问题,2020(2):25-32.
[14] 吴培冠,朱婕. 居民收入水平影响因素及其城乡和区域差异[J]. 中国农业大学学报,2015,20(2):251-258.
[15] 吴万宗,刘玉博,徐琳. 产业结构变迁与收入不平等——来自中国的微观证据[J]. 管理世界,2018,34(2):22-33.
[16] 蔡萌,岳希明. 我国居民收入不平等的主要原因:市场还是政府政策[J]. 财经研究,2016,42(4):4-14.
[17] 王平,刘俊浩,苗海民. 新常态下西北边境多民族贫困地区居民增收实证分析——以新疆塔城地区为例[J]. 新疆社会科学,2017(1):47-52.
[18] 齐义军,巩蓉蓉. 内蒙古少数民族聚居区稳定脱贫长效机制研究[J]. 中央民族大学学报:哲学社会科学版,2019(1):109-119.
[19] 曹诗颂,赵文吉,段福洲. 秦巴特困连片区生态资产与经济贫困的耦合关系[J]. 地理研究,2015,34(7):1259-1309.
[20] 黄炜,孟霏,肖淑靓. 精准扶贫视域下乡村旅游产业发展动力因素实证研究——以武陵山片区为例[J]. 中央民族大学学报:哲学社会科学版,2017(5):57-68.
[21] 文玉钊,钟业喜,熊文平. 江西省农村居民收入时空差异及其影响因素[J]. 经济地理,2012,32(5):133-139.
[22] 穆哈拜提·帕热提,赵羽. 农村居民收入差异时空演变及其影响因素分析[J]. 统计与决策,2018(5):88-91.
[23] Alia A,Rahut D B.Forest-based livelihoods,income and poverty:Empirical evidence from the Himalayan region of rural Pakistan[J]. Journal of Rural Studies,2018,57(1):44-54.
[24] 杨喆,李晴晴,薛文皓. 国家重点生态功能区设立对农村居民收入的影响:基于PSM-DID的实证分析[J]. 资源科学,2023,45(1):144-157.
[25] 吴中全,杨志红,王志章. 生态补偿、精英俘获与农村居民收入——基于重庆市酉阳县11个易地扶贫搬迁安置点的微观数据[J]. 西南大学学报:社会科学版,2020(2):69-78,194.
[26] Zilberman D,Lipper L,Mccarthy N.When could payments for environmental services benefit the poor[J]. Environment and Development Economics,2008,13(3):255-278.
[27] 段伟,赵正,刘梦婕,等. 保护区周边农户自然资源依赖度研究[J]. 农业技术经济,2016(3):93-102.
[28] Alix-Garcia J,Sims K,Yan?ez-Pagans P. Only one tree from each seed?Environmental effectiveness and poverty alleviation in Mexico’s payments for ecosystem services program[J]. American Economic Journal:Economic Policy,2015,7(4):1-40.
[29] Wang P,Poe G,Wolf S,et al.Payments for ecosystem services and wealth distribution[J]. Ecological Economics,2017,132(2):63-68.
[30] 袁梁,张光强,霍学喜. 生态补偿、生计资本对居民可持续生计影响研究——以陕西省国家重点生态功能区为例[J]. 经济地理,2017,37(10):188-196.
[31] Wang C C,Yang Y S,Zhang Y Q.Economic development,rural livelihoods,and ecological restoration,evidence from China[J]. AMBIO,2011,40(1):78-87.
[32] 高平,温亚利. 我国自然保护区周边社区贫困特征、成因及对策[J]. 农业现代化研究,2004,25(4):255-257.
[33] 吴乐,孔德帅,靳乐山. 生态补偿有利于减贫吗?——基于倾向得分匹配法对贵州省三县的实证分析[J]. 农村经济,2017(9):48-55.
[34] 陈培阳,朱喜钢. 基于不同尺度的中国区域经济差异[J]. 地理学报,2012,67(8):1085-1097.
[35] 葛鹏飞,韩永楠,武宵旭. 中国创新与经济发展的耦合协调性测度与评价[J]. 数量经济技术经济研究,2020,37(10):102-118.
[36] 陈明华,刘文斐,王山,等. 长江经济带城市生态效率的空间格局及演进趋势[J]. 资源科学,2020,42(6):1087-1098.
[37] 侯孟阳,席增雷,张晓,等. 国家重点生态功能区的环境质量与经济增长效应评估[J]. 中国人口·资源与环境,2023,33(1):24-37.
[38] 刘桂环,文一惠,谢婧,等.国家重点生态功能区转移支付政策演进及完善建议[J]. 环境保护,2020,48(17):9-14.
