我国区域高技术产业高质量发展水平测度及区域差异分析

Measurement and Difference Analysis of High?quality Development Level of Regional High?tech Industry in China

摘要:

摘要：为更为全面了解我国区域高技术产业高质量发展水平状况及区域差异，促进科技进步和提升国家科技实力。从创新、开放、协调、绿色、共享、规模6个维度构建我国高技术产业高质量发展水平综合评价体系，基于2013－2020年30个省份的高技术产业数据，运用熵权TOPSIS模型测度区域高技术产业高质量发展水平，并分别从三大经济带、七大地理区域、三大经济圈的地理划分维度，运用障碍因子诊断模型和空间杜宾模型进行障碍因子诊断和收敛性分析。结果发现：（1）按照2013－2020年的高技术产业高质量发展水平指数均值，广东、北京、江苏、天津、上海、浙江分居前六，甘肃、宁夏、青海提升进步快速，其中一级指标指数整体呈现“规模＞创新＞开放＞绿色＞共享＞协调”；（2）按照地理分区的高技术产业高质量发展水平指数变化趋势，东部处于领先地位，华南、华东、西北地区和泛长三角经济圈的均值均大于全样本均值水平，2020年呈现“华东＞华南＞西北＞全样本均值＞华北＞华中＞西南＞东北”，其中规模因素均为各区域高技术产业高质量发展水平的关键障碍因子；（3）2013－2020年样本区域高技术产业高质量发展水平存在绝对β收敛，3类地理分区均存在绝对俱乐部收敛，其中互联网普及率、政府投资、外商投资、劳动力素质、数字金融等的影响作用加快了高技术产业高质量发展水平的收敛速度。由此得到启示，需正确认识高技术产业高质量发展水平的区域差距，各地区应因地制宜和因地施策，并不断探索向高水平收敛的机制。

Abstract:

Abstract: In order to fully understand the high quality development level of China's regional high?tech industry and regional differences, promote scientific and technological progress and enhance national scientific and technological strength. This paper constructs a comprehensive evaluation system for the high?quality development level of China's high?tech industries from six dimensions: innovation, openness, coordination, green, sharing and scale. Based on the high?tech industry data of 30 provinces from 2013 to 2020, the entropy?weight TOPSIS model is used to measure the high?quality development level of regional high?tech industries. From three economic zones, seven geographical regions and three economic circles, the obstacle factor diagnosis model and spatial Durbin model are used to diagnose the obstacle factor and analyze the convergence. The results showed that: (1) According to the average quality development level index of high?tech industries from 2013 to 2020, Guangdong, Beijing, Jiangsu, Tianjin, Shanghai and Zhejiang ranked the top six, while Gansu, Ningxia and Qinghai made rapid progress, among which the overall first?level index showed "scale > Innovation > opening > Green > Sharing > coordination"; (2) According to the change trend of the index of high quality development level of high?tech industries in geographical regions, the eastern region is in the leading position, and the average values of South China, East China, Northwest China and Pan?Yangtze River Delta economic circle are all larger than the average value of the whole sample, showing "East China > South China > Northwest China > Average value of the whole sample > North China > Central China > Southwest China > Northeast China" in 2020. Among them, the scale factor is the key obstacle factor for the high quality development level of high?tech industry in each region. (3) There is absolute β convergence in the high?quality development level of high?tech industries in the sample region from 2013 to 2020, and there is absolute club convergence in all three categories of geographical regions, among which the influence of Internet penetration, government investment, foreign investment, labor quality, digital finance, etc., accelerates the convergence rate of high?quality development level of high?tech industries. From this, we need to correctly understand the regional gap in the level of high?quality development of high?tech industries, and all regions should adopt policies according to local conditions and continue to explore the mechanism of convergence to a high level.