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税收数据显示:10月份高端制造、创新产业、数实融合三大领域保持稳健增长
Xin Hua Wang· 2025-11-24 14:27
记者11月24日从国家税务总局获悉,从最新增值税发票数据看,2025年10月,我国新质生产力持续 培育壮大,高端制造、创新产业、数实融合三大领域均呈现稳健增长态势,为经济发展持续注入新活 力。 在数实融合领域,最新增值税发票数据显示,10月份,数字经济核心产业销售收入同比增长 8.5%,全国企业采购数字技术金额同比增长9.6%,反映数字产业化和产业数字化持续推进。其中,数 字产品服务业、数字技术应用业销售收入同比分别增长10.2%和13.1%;数字消费拉动作用明显,数字 内容与媒体业销售收入同比增长15.2%。 中国人民大学财政金融学院教授朱青认为,10月份新质生产力相关领域的税收数据,直观展现了我 国产业结构升级与经济发展方式转型成效。尤其是"人工智能+"行动带动前沿产业持续增长,数字技术 与实体经济深度融合,为经济高质量发展提供了强劲且可持续的动力,彰显了我国经济转型升级的坚实 基础与广阔空间。(记者刘开雄) 【纠错】 【责任编辑:王雪】 在高端制造方面,最新增值税发票数据显示,10月份,装备制造业销售收入同比增长7.3%,今年 以来持续高于制造业平均水平,占制造业比重已近半。其中,计算机通信设备制造业、 ...
税收数据显示:10月高端制造、创新产业、数实融合三大领域均呈现稳健增长态势
Xin Hua Cai Jing· 2025-11-24 12:51
新华财经北京11月24日电(记者董道勇)国家税务总局公布的最新增值税发票数据显示,2025年10月, 我国新质生产力持续培育壮大,高端制造、创新产业、数实融合三大领域均呈现稳健增长态势,为经济 发展持续注入新活力。 ——数实融合不断突破。10月份,数字经济核心产业销售收入同比增长8.5%,全国企业采购数字技术 金额同比增长9.6%,反映数字产业化和产业数字化持续推进。其中,数字产品服务业、数字技术应用 业销售收入同比分别增长10.2%和13.1%;数字消费拉动作用明显,数字内容与媒体业销售收入同比增 长15.2%。 中国人民大学财政金融学院教授朱青认为,10月份新质生产力相关领域的税收数据,直观展现了我国产 业结构升级与经济发展方式转型成效。尤其是"人工智能+"行动带动前沿产业持续增长,数字技术与实 体经济深度融合,为经济高质量发展提供了强劲且可持续的动力,彰显了我国经济转型升级的坚实基础 与广阔空间。 (文章来源:新华财经) ——高端制造持续发力。10月份,装备制造业销售收入同比增长7.3%,今年以来持续高于制造业平均 水平,占制造业比重已近半。其中,计算机通信设备制造业、船舶及相关装置制造业、电池制造业销 ...
10月份新质生产力加速培育 工业机器人销售增长超40%
Yang Shi Xin Wen· 2025-11-24 11:30
国家税务总局发布的最新增值税发票数据显示,10月份,我国新质生产力持续培育壮大。创新产业加快 发展,高技术产业销售收入同比增长13.6%,延续较快增长。其中,高技术服务业、高技术制造业销售 收入同比均保持两位数以上增长。特别是随着"人工智能+"行动加快落地,集成电路、工业机器人、无 人机制造销售收入同比分别增长32.5%、41.7%和38.4%。 高端制造持续发力 装备制造业销售收入同比增长7.3%,今年以来持续高于制造业平均水平,占制造业比重已近一半。 其中,计算机通信设备制造业、船舶及相关装置制造业、电池制造业销售收入同比分别增长10.1%、 24.4%和27.2%,展现强劲发展势头。 数实融合不断突破 10月份,数字经济核心产业销售收入同比增长8.5%,全国企业采购数字技术金额同比增长9.6%,反映 数字产业化和产业数字化持续推进。 其中,数字产品服务业、数字技术应用业销售收入同比分别增长10.2%和13.1%,数字消费拉动作用明 显,为经济发展持续注入新活力。 (文章来源:央视新闻) ...
核心产业增加值突破5300亿元,四川数字经济产业筑起新高地
Sou Hu Cai Jing· 2025-10-09 11:46
Core Insights - The digital economy is a strategic focus of the "14th Five-Year Plan" and serves as a new engine for high-quality development in Sichuan [3][4] Group 1: Digital Economy Growth - The core industry of the digital economy in Sichuan is projected to exceed 530 billion yuan in added value by 2024, with a significant growth rate [3] - The revenue share of large-scale digital economy enterprises in Sichuan is 16.7%, placing it among the top in the nation [3] - Key sectors such as digital product manufacturing and services have seen substantial growth, with increases of 34.1%, 112.7%, 62.9%, and 172.3% respectively compared to 2020 [3] Group 2: Computing Power Infrastructure - Sichuan has established a total computing power scale of 16.8 EFLOPS, supporting national initiatives in data circulation and computing power security [3] - The province has developed an integrated computing power monitoring and scheduling service platform, enhancing accessibility to various computing resources [3] Group 3: Integration of Digital and Real Economies - The digital transformation coverage among large-scale industrial enterprises in Sichuan has reached 45.5%, with over 800 smart factories established [4] - The province has created 55 provincial-level digital transformation promotion centers, connecting over 250,000 enterprises [4] Group 4: Digital Consumption Trends - From January to July this year, Sichuan's online transaction volume surpassed 3 trillion yuan, with over 5.5 million people employed in the sector [4] - Major e-commerce platforms have established regional headquarters in Sichuan, contributing to the rapid growth of local high-potential enterprises [4] Future Directions - Sichuan aims to continue focusing on high-quality development by leveraging data elements and implementing the "Artificial Intelligence+" initiative to build digital industry clusters [5]
培育壮大数字经济核心产业
Jing Ji Ri Bao· 2025-05-17 21:50
Core Insights - The digital economy in China is rapidly growing, with the core industries expected to account for about 10% of GDP by 2024 [1][2][19] - The core industries of the digital economy include digital product manufacturing, digital product services, digital technology applications, and data-driven industries [2][19] - In 2023, the added value of the digital economy's core industries reached 12.7555 trillion yuan, with significant contributions from various sectors [2][19] Industry Development - The number of enterprises in the digital economy core industries reached 4.5741 million by the end of November 2024, marking a 17.99% increase from the end of 2023 [3][19] - The growth in enterprise numbers reflects the acceleration of digital China construction and the increasing support of the digital economy for high-quality economic development [3][19] Technological Innovation - Technological innovation is a key driver for the development of the digital economy core industries, with significant advancements in areas such as 5G, artificial intelligence, and quantum computing [7][8] - In 2023, the number of invention patents authorized in the digital economy core industries reached 406,000, accounting for 45% of the total authorized patents in society [2][7] Infrastructure and Market Development - China has established the world's largest mobile communication and fiber broadband network, with 5G base stations reaching 4.251 million by the end of 2024 [4] - The online retail sales in China for 2024 are projected to be 15.5225 trillion yuan, reflecting a 7.2% increase from the previous year [4] Data Resource Utilization - The digital economy core industries have significantly improved the level of data resource development and utilization, providing advanced technology and tools for deeper data resource utilization [19] - The added value of the digital technology application industry was 5.56 trillion yuan in 2023, while the digital product manufacturing industry contributed 4.31 trillion yuan [19][20] Challenges and Recommendations - Despite the rapid growth, challenges remain, including a lack of specialized institutions, the need for improved technical levels, and the expansion of application ranges [20] - Recommendations include encouraging traditional enterprises to develop data businesses, enhancing collaboration among industry, academia, and research, and supporting enterprises in transitioning from business-driven to data-driven models [20]