高质量发展的新疆实践：评估体系构建及测度研究

doi:10.12118/j.issn.1000-6060.2024.079

Abstract

Abstract:

High-quality development is the cornerstone of building a modern socialist country. To advance high-quality development in Xinjiang, China, and accelerate its modernization, there is an urgent need for a scientific and rational evaluation index system to both reflect and guide progress. This study constructs a high-quality development evaluation index system for Xinjiang, incorporating primary indicators such as economic life, resource environment, innovation and opening up, regional integration and coordination, agricultural and cultural tourism industries, and eight major industrial clusters. Using the entropy method, the high-quality development index of Xinjiang is estimated. The coupling coordination degree model evaluates the degree of coordinated development of high-quality indicators in Xinjiang, while obstacle analysis identifies the factors constraining high-quality development. The findings reveal the following: (1) Xinjiang’s comprehensive high-quality development index increased from 0.172 in 2011 to 0.785 in 2022, reflecting a relatively favorable overall development level. The opening to the outside world, financial and insurance industries, economic development, and agricultural, cultural, and tourism industries have made increasingly significant contributions to high-quality development. However, challenges remain in the areas of science and technology input-output efficiency, human capital, the development gap with the national average, and low-carbon development. (2) The coupling coordination degree of Xinjiang’s high-quality development improved from 0.365 in 2011 to 0.883 in 2022, indicating strong inter-indicator correlation and a virtuous cycle. Between 2011 and 2014, the coupling and coordination degree of first-class indicators increased by 0.0715 per year, 0.0384 higher than the growth rate observed from 2015 to 2022, signaling a gradual slowdown. The degree of collaborative development between the two primary indicators, namely regional integration coordination and resource environment, is relatively low. (3) Analysis of indicators with obstacle values exceeding 0.05 over the years identifies forest coverage, natural gas production, added value of the financial industry, daily per capita domestic water consumption in cities, urban sewage treatment capacity, RMB deposits of financial institutions, registered urban unemployment rates, green coverage of built-up areas, rural electricity consumption, and reductions in chemical fertilizer use as key factors restricting Xinjiang’s high-quality development. To address these constraints, the study proposes optimizing the allocation of scientific and technological resources, enhancing the efficiency of technological investments, leveraging latecomer advantages, accelerating integration into national strategies, deepening supply-side structural reforms, and promoting industrial structural transformation.

Key words: high quality development, evaluation indicator system, development index, Xinjiang

LI Gang. Practice of high quality development in Xinjiang: Construction and measurement of evaluation system[J].Arid Land Geography, 2025, 48(1): 143-152.

Figures/Tables 5

Tab. 1

Evaluation index system for high-quality development in Xinjiang"

一级指标（代码）	二级指标（代码）	三级指标（代码；单位；权重）
经济生活（A₁）	经济发展（B₁）	人均地区生产总值（C₁；元·人^-1；0.0118）、地方财政一般预算收入（C₂；10⁸元；0.0112）、地方财政一般预算支出（C₃；10⁸元；0.0116）
	金融保险业（B₂）	原保险保费收入（C₄；10⁸元；0.0119）、金融机构人民币存款（C₅；10⁸元；0.0116）、金融业增加值（C₆；10⁸元；0.0115）、金融业城镇就业平均工资（C₇；元；0.0117）
	收入消费（B₃）	居民人均可支配收入（C₈；元；0.0116）、居民人均消费支出（C₉；元；0.0114）
	社会条件（B₄）	总抚养比^（C₁₀；%；0.0111）、城镇登记失业率^（C₁₁；%；0.0121）、城市人口密度^*（C₁₂；人·km^-2；0.0120）
	生活水平（B₅）	农村用电量（C₁₃；10⁸kW·h；0.0129）、每百人使用计算机数（C₁₄；台；0.0118）、城市人均日生活用水量（C₁₅；10^-3m³；0.0121）
资源环境（A₂）	低碳环保（B₆）	化肥施用折纯量^（C₁₆；10⁴t；0.0130）、化学需氧量排放量^（C₁₇；10⁴t；0.0147）
	资源禀赋（B₇）	人均水资源量（C₁₈；m³·人^-1；0.0122）、森林覆盖率（C₁₉；%；0.0119）、天然气生产量（C₂₀；10⁸ m³；0.0119）、电力消费量（C₂₁；10⁸kW·h；0.0114）
	环境治理（B₈）	地方财政环境保护支出（C₂₂；10⁸元；0.0122）、森林病虫鼠害防治率（C₂₃；%；0.0113）、城市污水日处理能力（C₂₄；10⁴m³；0.0115）
	环境设施（B₉）	建成区绿化覆盖率（C₂₅；%；0.0119）、每万人拥有公共厕所（C₂₆；座；0.0116）、人均公园绿地面积（C₂₇；m²·人^-1；0.0119）
创新开放（A₃）	人力资本（B₁₀）	高等学校正高级教师数（C₂₈；10⁴人；0.0131）、十万人口高等学校在校生数（C₂₉；人；0.0122）
	科创投入产出（B₁₁）	自治区重大科技成果数（C₃₀；项；0.0118）、规模以上工业企业R&D人员全时当量（C₃₁；人年；0.0119）、科技支出占财政比重（C₃₂；%；0.0124）
	科创基础（B₁₂）	科技服务业法人数（C₃₃；个；0.0125）、科技地质勘查城镇就业平均工资（C₃₄；元；0.0116）
	对外开放（B₁₃）	对外非金融类直接投资存量（C₃₅；10⁴USD；0.0118）、经营单位所在地进出口总额（C₃₆；10³USD；0.0119）、境内货源地进出口总额（C₃₇；10³USD；0.0120）、外商投资企业数（C₃₈；户；0.0123）、外商投资企业投资总额（C₃₉；10⁶USD；0.0139）
	数字经济（B₁₄）	数字金融覆盖广度（C₄₀；无；0.0114）、数字普惠金融指数（C₄₁；无；0.0112）、有电子商务交易活动的企业数比重（C₄₂；%；0.0112）
区域融合协调（A₄）	融入全国发展（B₁₅）	全国新疆城镇失业率比^（C₄₃；无；0.0113）、全国新疆人均水资源比（C₄₄；无；0.0112）、全国新疆人均粮食产量比（C₄₅；无；0.0129）、全国新疆十万人口高等学校在校生比^（C₄₆；无；0.0118）、全国新疆人均产值比^（C₄₇；无；0.0120）、全国新疆居民人均消费比^（C₄₈；无；0.0110）
	城乡融合（B₁₆）	城乡居民可支配收入比^（C₄₉；无；0.0130）、城乡居民消费比^（C₅₀；无；0.0128）、城乡每万人医疗机构床位数比^*（C₅₁；无；0.0112）、城镇化率（C₅₂；%；0.0120）
	兵地融合（B₁₇）	兵地人均地区生产总值比^（C₅₃；无；0.0114）、兵地城乡居民可支配收入比差异绝对值^（C₅₄；无；0.0112）、兵地第三产业就业人员占比差异绝对值^*（C₅₅；无；0.0114）
农文旅产业（A₅）	农业产业基础（B₁₈）	农林牧渔业总产值（C₅₆；10⁸元；0.0118）、农业机械总动力（C₅₇；10⁴kW；0.0113）、有效灌溉面积（C₅₈；10³ hm²；0.0115）、农村发电设备容量（C₅₉；kW；0.0119）
	文化产业基础（B₁₉）	博物馆文物藏品（C₆₀；件·套^-1；0.0116）、每万人拥有公共图书馆建筑面积（C₆₁；m²；0.0123）、电视节目综合人口覆盖率（C₆₂；%；0.0116）、出版印刷企业数（C₆₃；个；0.0127）、文化体育与传媒占财政支出比重（C₆₄；%；0.0124）
	旅游及相关产业（B₂₀）	连锁餐饮企业营业额（C₆₅；10⁸元；0.0123）、住宿企业营业额（C₆₆；10⁸元；0.0118）、国际旅游外汇收入（C₆₇；10⁶USD；0.0120）、住宿餐饮城镇私营单位平均工资（C₆₈；元；0.0116）
八大产业集群（A₆）	油气生产加工产业集群（B₂₁）	原油生产量（C₆₉；10⁴t；0.0123）、汽油生产量（C₇₀；10⁴t；0.0117）
	绿色矿业产业集群（B₂₂）	城市天然气供气总量（C₇₁；10⁸m³；0.0111）、采矿业城镇就业平均工资（C₇₂；元；0.0119）
	煤炭煤电化工产业集群（B₂₃）	火力发电量（C₇₃；10⁸kW·h；0.0116）、焦炭生产量（C₇₄；10⁴t；0.0115）
	粮油产业集群（B₂₄）	地方财政粮油储备管理等支出（C₇₅；10⁸元；0.0117）、人均粮食产量（C₇₆；kg；0.0131）
	棉花纺织服装产业集群（B₂₅）	绵羊毛产量（C₇₇；t；0.0125）、棉花单位面积产量（C₇₈；kg·hm^-2；0.0114）
	绿色有机果蔬产业集群（B₂₆）	单位面积果园产量（C₇₉；t·hm^-2；0.0113）、蔬菜产量（C₈₀；10⁴t；0.0123）
	优质畜产品产业集群（B₂₇）	牛奶产量（C₈₁；10⁴t；0.0123）、肉类产量（C₈₂；10⁴t；0.0117）
	新能源新材料产业集群（B₂₈）	汽车产量（C₈₃；10⁴辆；0.0116）、平板玻璃产量（C₈₄；10⁴重量箱；0.0114）

Tab. 1

Fig. 1

Fig. 2

Tab. 2

Tab. 3

References 22

[1]	蔡昉. 中国经济增长如何转向全要素生产率驱动型[J]. 中国社会科学, 2013(1): 56-71, 206.
	[Cai Fang. How can Chinese economy achieve the transition toward total factor productivity growth[J]. Socil Sciences in China, 2013(1): 56-71, 206.]
[2]	田秋生. 高质量发展的理论内涵和实践要求[J]. 山东大学学报(哲学社会科学版), 2018(6): 1-8.
	[Tian Qiusheng. Theoretical connotation and practical requirements for high-quality development[J]. Journal of Shandong University (Philosophy and Social Sciences Edition), 2018(6): 1-8.]
[3]	任保平. 新时代中国经济从高速增长转向高质量发展: 理论阐释与实践取向[J]. 学术月刊, 2018, 50(3): 66-74, 86.
	[Ren Baoping. Theoretical interpretation and practical orientation of China’s economy from high speed growth to high quality development in new era[J]. Academic Monthly, 2018, 50(3): 66-74, 86.]
[4]	赵剑波, 史丹, 邓洲. 高质量发展的内涵研究[J]. 经济与管理研究, 2019, 40(11): 15-31.
	[Zhao Jianbo, Shi Dan, Deng Zhou. A framework of China’s high-quality economic development[J]. Research on Economics and Management, 2019, 40(11): 15-31.]
[5]	Boldrin M, Canova F. Inequality and convergence in Europe’s regions: Reconsidering European regional policies[J]. Economic Policy, 2001, 16(32): 206-253.
[6]	Globerman S, Cfa V Z. Best policy practices for promoting inward and outward foreign direct investment[R]. Ottawa: Conference Board of Canada, 2010.
[7]	聂长飞, 简新华. 中国高质量发展的测度及省际现状的分析比较[J]. 数量经济技术经济研究, 2020, 37(2): 26-47.
	[Nie Changfei, Jian Xinhua. Measurement of China’s high-quality development and analysis of provincial status[J]. Journal of Quantitative & Technological Economics, 2020, 37(2): 26-47.]
[8]	Svensson L. Factor trade and goods trade[J]. Journal of International Economics, 1984, 16(3-4): 365-378.
[9]	Montfort M, Tapsoba R, Sampawende J, et al. A quality of growth index for developing countries: A proposal[J]. Social Indicators Research, 2017, 134(2): 675-710.
[10]	方大春, 马为彪. 中国省际高质量发展的测度及时空特征[J]. 区域经济评论, 2019(2): 61-70.
	[Fang Dachun, Ma Weibiao. Study on the measurement of China’s inter-provincial high-quality development and its spatial-temporal characteristics[J]. Regional Economic Review, 2019(2): 61-70.]
[11]	李俊佳, 赵美风. 中国民族地区高质量发展空间演变及其影响机理[J]. 干旱区地理, 2024, 47(3): 496-505. doi: 10.12118/j.issn.1000-6060.2023.405
	[Li Junjia, Zhao Meifeng. Spatial evolution and influencing mechanism of high quality development in ethnic minority areas of China[J]. Arid Land Geography, 2024, 47(3): 496-505.] doi: 10.12118/j.issn.1000-6060.2023.405
[12]	张侠, 许启发. 新时代中国省域经济高质量发展测度分析[J]. 经济问题, 2021(3): 16-25.
	[Zhang Xia, Xu Qifa. Measurement and analysis of China’s provincial economic high-quality development in the new era[J]. On Economic Problems, 2021(3): 16-25.]
[13]	王伟. 中国经济高质量发展的测度与评估[J]. 华东经济管理, 2020, 34(6): 1-9.
	[Wang Wei. A study on the measurement and evaluation of the high-quality development of China’s economy[J]. East China Economic Management, 2020, 34(6): 1-9.]
[14]	吕承超, 崔悦. 中国高质量发展地区差距及时空收敛性研究[J]. 数量经济技术经济研究, 2020, 37(9): 62-79.
	[Lü Chengchao, Cui Yue. Research on the regional in equality and temporal-spatial convergence of high-quality development in China[J]. Journal of Quantitative & Technological Economics, 2020, 37(9): 62-79.]
[15]	张震, 王泽宇, 李瑛. 中国区域经济高质量发展研究综述[J]. 资源开发与市场, 2021, 37(8): 928-933.
	[Zhang Zhen, Wang Zeyu, Li Ying. Review of researches on the high quality development of regional economy in China[J]. Resource Development Market, 2021, 37(8): 928-933.]
[16]	孙豪, 桂河清, 杨冬. 中国省域经济高质量发展的测度与评价[J]. 浙江社会科学, 2020(8): 4-14, 155.
	[Sun Hao, Gui Heqing, Yang Dong. Measurement and evaluation of the high-quality of China’s provincial economic development[J]. Zhejiang Social Sciences, 2020(8): 4-14, 155.]
[17]	孟晓, 田明华, 杜磊, 等. 中国农业农村现代化发展水平测度及其协调性研究[J]. 干旱区地理, 2024, 47(1): 137-146. doi: 10.12118/j.issn.1000－6060.2023.339
	[Meng Xiao, Tian Minghua, Du Lei, et al. Measurement and its coordination of the development level of agricultural and rural modernization in China[J]. Arid Land Geography, 2024, 47(1): 137-146.] doi: 10.12118/j.issn.1000－6060.2023.339
[18]	刘会武, 赵祚翔, 马金秋. 区域高质量发展测度与创新驱动效应的耦合检验[J]. 技术经济, 2021, 40(9): 1-13.
	[Liu Huiwu, Zhao Zuoxiang, Ma Jinqiu. Coupling test of regional high-quality development measurement and innovation driving effect[J]. Journal of Technology Economics, 2021, 40(9): 1-13.]
[19]	杨建, 方浩. 区域创新能力与高质量发展的耦合评价研究[J]. 技术经济与管理研究, 2022(6): 35-40.
	[Yang Jian, Fang Hao. Coupling evaluation research on regional innovation ability and high-quality development[J]. Journal of Technical Economics & Management, 2022(6): 35-40.]
[20]	赵宏波, 马延吉. 东北粮食主产区耕地生态安全的时空格局及障碍因子——以吉林省为例[J]. 应用生态学报, 2014, 25(2): 515-524.
	[Zhao Hongbo, Ma Yanji. Spatial-temporal pattern and obstacle factors of cultivated land ecological security in major grain producing areas of northeast China: A case study in Jilin Province[J]. Chinese Journal of Applied Ecology, 2014, 25(2): 515-524.] pmid: 24830253
[21]	鲁邦克, 邢茂源, 杨青龙. 中国经济高质量发展水平的测度与时空差异分析[J]. 统计与决策, 2019, 35(21): 113-117.
	[Lu Bangke, Xing Maoyuan, Yang Qinglong. Measurement and spatio-temporal differences analysis of high quality development level of China’s economy[J]. Statistics & Decision, 2019, 35(21): 113-117.]
[22]	马茹, 罗晖, 王宏伟, 等. 中国区域经济高质量发展评价指标体系及测度研究[J]. 中国软科学, 2019(7): 60-67.
	[Ma Ru, Luo Hui, Wang Hongwei, et al. Study of evaluating high-quality economic development in Chinese regions[J]. China Soft Science, 2019(7): 60-67.]

年份	高质量系统			一级指标
年份	耦合度	耦合协调度	耦合度与耦合协调度差值	A₁	A₂	A₃	A₄	A₅	A₆
2011	0.774	0.365	0.409	0.022	0.465	0.048	0.620	0.108	0.095
2012	0.935	0.478	0.457	0.382	0.503	0.344	0.576	0.428	0.361
2013	0.928	0.560	0.368	0.465	0.520	0.465	0.773	0.473	0.564
2014	0.971	0.604	0.367	0.547	0.549	0.544	0.724	0.534	0.632
2015	0.990	0.651	0.339	0.627	0.603	0.516	0.661	0.656	0.669
2016	0.980	0.654	0.326	0.667	0.735	0.548	0.583	0.603	0.708
2017	0.990	0.701	0.289	0.754	0.750	0.622	0.641	0.669	0.644
2018	0.992	0.721	0.271	0.805	0.771	0.658	0.692	0.679	0.636
2019	0.991	0.750	0.241	0.802	0.787	0.687	0.673	0.793	0.633
2020	0.993	0.744	0.249	0.785	0.616	0.733	0.625	0.725	0.747
2021	0.996	0.833	0.163	0.882	0.713	0.861	0.750	0.842	0.762
2022	0.993	0.883	0.110	0.919	0.714	0.960	0.803	0.820	0.873

年份	障碍度 [0.05, 0.06]	障碍度（0.06, 0.08]	障碍度（0.08, 0.10]	障碍度（0.10, 0.20]
2011	B₁₈、B₂、B₂₀、B₁₆	B₁₉、B₁₃	-	-
2012	B₁₈、B₂、B₇	B₁₃、B₁₉、B₁₆	-	-
2013	B₂、B₁₈、B₁₆	B₁₃、B₁₉、B₂₀	-	-
2014	B₁₆、B₂、B₁₈	B₁₃、B₂₀、B₁₉	-	-
2015	B₂₀、B₂	B₁₆	-	B₁₃
2016	-	B₁₅、B₁₉、B₁₆、B₂₀	-	B₁₃
2017	B₂₀、B₁₁	B₁₃、B₁₉、B₁₅、B₁₆	-	-
2018	B₁₁	B₁₃、B₁₆	B₁₉、B₁₅	-
2019	B₁₃、B₁₆、B₂₄	B₁₉、B₁₁	-	B₁₅
2020	B₆、B₂₀	B₁₉、B₁₃、B₁₁	-	B₁₅
2021	B₁₃、B₂₅、B₁₁	B₆、B₂₄	B₁₉	B₁₅
2022	B₂₅、B₁₁	B₅、B₂₄	-	B₁₅、B₆、B₂₀、B₁₉

Practice of high quality development in Xinjiang: Construction and measurement of evaluation system

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