中文题名: | 共同富裕统计指标体系构建及应用研究 |
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保密级别: | 公开 |
论文语种: | chi |
学科代码: | 025200 |
学科专业: | |
学生类型: | 硕士 |
学位: | 应用统计硕士 |
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学位年度: | 2024 |
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研究方向: | 经济与金融统计 |
第一导师姓名: | |
第一导师单位: | |
提交日期: | 2024-06-11 |
答辩日期: | 2024-05-21 |
外文题名: | Study On The Construction And Application Of A Statistical Indicator System For Common Prosperity |
中文关键词: | |
外文关键词: | Common Prosperity ; Indicator System ; Regional Disparity ; Convergence Analysis ; Influencing Factors |
中文摘要: |
实现共同富裕是社会主义的奋斗目标,也是万千中国人民心中的期待和向往。在我国迈入第二个百年奋斗目标的历史节点上,实现共同富裕既是党和国家领导人关心的重点问题,也是普通人民群众翘首期盼的实现美好生活的愿望。在此背景下,本文从富裕和共同两个维度出发,基于30个省市的数据,结合共同富裕的理论内涵,从区域层面构建共同富裕统计指标体系,并利用指标体系进行后续的应用研究。首先,本文利用熵值法计算各三级指标权重,并在此基础上测算得到2010-2021年各省份的共同富裕得分,分析各省份的共同富裕及子维度的得分演变。在得分的基础上,利用核密度分析和Dagum基尼系数等方法研究了共同富裕的分布情况、地区差异及来源,并采用β收敛和莫兰指数验证共同富裕的收敛情况和空间自相关性;最后,本文综合采用静态面板模型和空间面板模型来分析各省份共同富裕背后的影响因素。 本文的研究结果如下:第一,各省的共同富裕、富裕性和共同性得分均呈现逐年递增的趋势,说明我国各省的共同富裕水平整体呈上升趋势;其中,北京、上海、浙江的共同富裕平均得分位居前三,共同富裕发展较为领先。第二,目前各省的共同富裕水平仍然存在着一定的差异,差异主要源于地区之间共同富裕水平的差异;从时间来看,总体差异、地区内差异和地区间差异均呈现下降趋势,说明不同省份的共同富裕差距在逐渐缩小。第三,各省份的共同富裕及子维度之间存在着明显的收敛特征,说明从整体来看,各省份之间共同富裕水平的差距在逐渐收敛。第四,从共同富裕的影响因素来看,产业结构高级化、科学技术水平、直接税占比、市场化进程对各省份共同富裕有着正向促进作用。此外,科学技术水平和直接税占比对临近省份共同富裕存在正向的空间溢出效应;而周边省份产业结构高级化和市场化进程的提高则对本省共同富裕发展存在一定负向影响。 基于本文研究结论,提出如下政策建议:首先,对共同富裕发展较慢的地区提供政策和资源倾斜,在整体上提高共同富裕水平。其次,充分发挥地区带动作用,中西部地区应该参考东部地区的成功经验,加强地区内各省份之间的密切联系,带动周边地区的共同富裕发展。最后,逐步进行产业结构升级、完善税收制度、加大科技投入、推进市场化改革,从而有效促进我国共同富裕的提高。同时加大全国范围内的资源统筹配置力度,推进区域一体化发展,避免一省独大带来的“虹吸效应”,打造各省互联互通格局,共同推进我国各省共同富裕的实现。 |
外文摘要: |
The aim of socialism is to attain common prosperity, which countless Chinese people hope for and strive towards. At the historical juncture of China's entering the second hundred years of struggle, realizing common prosperity is not only a key issue of concern for the leaders of the Party and the State, but also the aspiration of the ordinary people to achieve a better life. Beginning with the two dimensions of affluence and common, this paper amalgamates theoretical notions of common prosperity, constructs a statistical index system of common prosperity from regional levels, and the index system was also used for subsequent applied research. This is based on data from 30 provinces and municipalities. Firstly, this paper uses the entropy value method to calculate the weights of each three-level indicator, and on this basis measures to obtain the common wealth score of each province from 2010 to 2021, and then scrutinizes the development of the score of common prosperity and its sub-dimensions in each province. On the basis of the scores, the distribution, regional differences and sources of the common prosperity level are studied by using kernel density analysis and Dagum’s Gini coefficient, and the beta convergence and Moran index are used to verify the convergence and spatial autocorrelation of the common prosperity level; finally, this paper comprehensively adopts the static and spatial panel models to analyze the drivers behind the common prosperity level of each province. The findings of this paper are as follows: Firstly, the scores for common prosperity, affluence and commonality in all provinces show a year-on-year increase, suggesting that the overall level of common prosperity in China is on the rise as a whole; among them, the average scores of common prosperity in Beijing, Shanghai and Zhejiang are in the top three, with the development of common prosperity being more prominent. Secondly, there are still some differences in the level of shared prosperity among provinces, with the differences stemming mainly from differences in the level of shared prosperity among regions; in terms of time, overall, both intra-regional and inter-regional differences are on the decline, suggesting that the gap in shared prosperity among different provinces is gradually narrowing. Third, there is a clear convergence feature between the common prosperity and sub-dimensions of each province, indicating that, as a whole, the gap between the common prosperity levels of each province is gradually converging. Fourthly, in terms of the influencing factors of common prosperity, the level of common prosperity in each province has been positively advanced by the influence of a sophisticated industrial structure, science and technology, direct tax, and marketisation. Furthermore, neighboring provinces benefit from positive influences of higher levels of science and technology and a greater percentage of direct taxes on the overall level of common prosperity. However, the presence of advanced industrial structures and marketization processes in neighboring provinces may hamper the development of common prosperity in this particular province. Based on the findings of this paper, the following policy recommendations are made: first, provide policies and resources in favor of regions where the development of common prosperity is slow, so as to improve the level of common prosperity as a whole. Secondly, give full play to the role of regional drive, the central and western regions should refer to the successful experience of the eastern region, strengthen the close links between the provinces within the region, and drive the development of common prosperity in the neighboring regions. Finally, we should gradually upgrade the industrial structure, improve the tax system, increase investment in science and technology, and promote market-oriented reforms, so as to effectively promote the improvement of the common prosperity of China, while increasing the overall allocation of resources nationwide, promoting regional integration, avoiding the "siphon effect" brought about by the dominance of a single province, and create a pattern of interconnectivity among provinces. In order to work together to advance the achievement of common prosperity across Chinese provinces. |
参考文献总数: | 90 |
馆藏号: | 硕025200/24049 |
开放日期: | 2025-06-11 |