从1985到2023年，中国劳动力平均年龄从32.25岁增加到39.66岁。 中国老龄化进程正逐步迈向成熟阶段。在全国劳动力人口数量持续下降的同时，劳动力人口的平均年龄也在不断上升。 "尽管年龄增长、人数减少，但劳动力人力资本总量仍持续增加，主要原因是劳动力整体教育水平提升，尤其是新增劳动力的平均人力资本高于退 休劳动力。"中国人力资本度量项目负责人李海峥教授对第一财经表示。 在劳动力人力资本总量排名前五的省（自治区、直辖市）中，广东位居第一，其后依次为江苏、山东、浙江、河南；排名后五位的省（自治区、 直辖市）则依次是（从高到低）甘肃、海南、宁夏、西藏、青海。 未来的人口结构变化将进一步影响相关数据。 《报告》显示，中国0-15岁人口数量持续下降。从1985年至2023年，中国0-15岁人口占非退休人口（女性退休年龄为55岁，男性退休年龄为60 岁）的比例从38.61%下降至22.71%；而46岁至退休年龄人口占比则由10.44%上升至23.80%。 "0-15岁人口是未来的后备劳动力，其占比变化预示着未来劳动力年龄结构的走向。"李海峥表示。 12月14日，中央财经大学人力资本与劳动经济研究中心发布《中国人力 ...

人口是现代化建设最基本的支撑。人口规模、结构、素质和布局深刻影响现代化的发展进程和质 量。习近平总书记指出，人口发展是关系中华民族伟大复兴的大事，必须着力提高人口整体素质，以人 口高质量发展支撑中国式现代化。"十五五"规划建议指出，促进人口高质量发展，健全覆盖全人群、全 生命周期的人口服务体系。人口高质量发展是将巨大人口规模转化为巨大发展优势的关键环节，也 是"人口规模巨大的现代化"的重要呈现形态。深入认识和把握人口高质量发展的深刻内涵，是贯彻高质 量发展要求的题中之义，也是夯实中国式现代化人口支撑的重要前提。 人口素质提升是实现人口高质量发展的核心目标。当前，充分发挥我国人口规模优势，关键在于 将"人口红利"转变为"人才红利"。国际经验表明，人口规模不会自动转化为现代化的内生动力，人口的 知识、技能和健康素质才是人口总量转化为人力资源优势的关键所在。从现实基础看，我国人口素质提 升已取得显著成效。知识素质方面，高等教育毛入学率已超过60%，各级各类学历教育在校生2.86亿 人，较高的劳动者素质为创新发展提供了重要前提；健康素质方面，人均预期寿命达到79岁，并建成世 界上规模最大的医疗服务体系，为经济社会发展 ...

人口是现代化建设最基本的支撑。人口规模、结构、素质和布局深刻影响现代化的发展进程和质量。习 近平总书记指出，人口发展是关系中华民族伟大复兴的大事，必须着力提高人口整体素质，以人口高质 量发展支撑中国式现代化。"十五五"规划建议指出，促进人口高质量发展，健全覆盖全人群、全生命周 期的人口服务体系。人口高质量发展是将巨大人口规模转化为巨大发展优势的关键环节，也是"人口规 模巨大的现代化"的重要呈现形态。深入认识和把握人口高质量发展的深刻内涵，是贯彻高质量发展要 求的题中之义，也是夯实中国式现代化人口支撑的重要前提。 人口高质量发展还要求形成科学合理的人口分布。促进城乡、区域之间形成畅通有序、合理均衡的人口 流动和分布格局，是人口高质量发展的一个重要目标。从城乡分布来看，我国城镇化率不断提升，2024 年已经达到67%，与发达国家的差距不断缩小。同时，城乡融合发展不断取得新成果，城乡公共服务高 效衔接，要素双向流动畅通运行，基础设施互联互通，产业协同深度发展。农业转移人口市民化不再是 单纯的空间迁移，"进城落户"有了更加丰富、便利、坚实的综合性公共服务支持。从区域分布来看，人 口持续向沿江、沿海地区及内地城区集聚， ...

Core Viewpoint - The article discusses the impact of demographic changes, particularly population aging, on tax revenue growth in China, emphasizing the need for policy adjustments to maintain tax bases and adapt to new economic realities [1][2][3]. Group 1: Population Dividend and Human Capital - China's large population creates a significant human capital base, which has been a source of economic value and tax revenue through various taxes such as value-added tax, corporate income tax, and personal income tax [2][3]. - The transition from a demographic dividend to a talent dividend is crucial for sustaining tax revenue growth as human capital becomes increasingly important in high-quality development [2][3]. Group 2: Challenges from Population Aging - By the end of 2024, over 220 million people in China will be aged 65 and above, accounting for 15.6% of the total population, posing challenges to tax revenue growth due to changes in labor supply and economic output [3][4]. - Aging leads to a reduction in the working-age population, increasing labor costs and compressing taxable profits, which negatively impacts corporate income tax revenue [3][4]. Group 3: Investment and Consumption Impacts - The rising proportion of retirees may decrease production investment, affecting value-added tax growth as older populations tend to spend on healthcare and basic services rather than productive investments [4][5]. - Changes in consumption patterns due to an aging population can limit the expansion of consumption tax bases, as older individuals have lower consumption elasticity and focus on essential spending [5][6]. Group 4: Policy Recommendations - To address the structural impacts of demographic changes on tax revenue, a comprehensive approach is needed, including optimizing tax sources, improving tax systems, and aligning industrial policies [6][7]. - Enhancing the adaptability of value-added tax to investment structure changes and reforming consumption tax to align with new consumption patterns are critical steps to maintain tax revenue [7][8]. - Strengthening the consistency of macroeconomic policies, including social and tax policies, is essential to create a dynamic balance between tax growth and demographic changes [8].

Group 1 - The core viewpoint emphasizes the need for a comprehensive response to the structural impact of demographic changes on tax revenue, focusing on tax source optimization, tax system improvement, and coordinated industrial policies to foster a positive interaction between tax growth and demographic changes [1][6] Group 2 - The demographic dividend in China, characterized by a large population, is seen as a significant contributor to tax revenue, especially as human capital accumulates through advancements in education and technology, leading to increased economic value creation [2] - The transition from a demographic dividend to a talent dividend is crucial for enhancing tax bases, particularly as human capital becomes a key driver of tax revenue growth during the high-quality development phase [2] Group 3 - Population aging presents challenges to tax revenue growth by affecting labor supply, investment, and consumption, with projections indicating that by the end of 2024, over 220 million people aged 65 and above will represent 15.6% of the total population [3] - The reduction in the working-age population due to aging leads to increased labor costs and a potential decline in corporate profits, which negatively impacts corporate income tax revenue [3][4] Group 4 - The increase in retirees and the shift towards pension income, which contributes less to personal income tax compared to labor income, is expected to slow the growth of personal income tax revenue [4] - Aging populations tend to reduce the proportion of savings and investments, which can adversely affect value-added tax (VAT) growth, as older individuals prioritize spending on healthcare and basic services over productive investments [5] Group 5 - The consumption patterns of an aging population, characterized by lower elasticity and a focus on essential services, limit the expansion of traditional consumption tax bases, necessitating reforms to adapt to new consumption trends [5][8] - The need for tax reforms is highlighted to align consumption tax structures with the evolving consumption landscape, particularly in high-value and luxury service sectors, to ensure sustainable tax revenue growth [8] Group 6 - Recommendations include enhancing the personal income tax base by improving labor supply quality and stabilizing corporate profits through support for technological upgrades and automation [6][7] - The VAT system should be adapted to address the challenges posed by an aging population, including stabilizing input tax deductions and refining tax incentives to prevent revenue loss [7] Group 7 - A dynamic updating mechanism for the consumption tax system is proposed to align with emerging consumption patterns in green, digital, and shared economies, ensuring that tax bases remain relevant and effective [8] - The alignment of macroeconomic policies, including social and industrial policies with tax policies, is essential to maintain a controllable balance between tax growth and demographic changes [8]

点击上图▲立即报名 文 / 巴九灵（微信公众号：吴晓波频道） 11月27日—11月29日，"吴晓波激荡讲堂"冬季课《中国式商业模式及成败探讨》在福建泉州圆满落幕。吴老师带领企业家走进这座千年商港，共 探商业本质。 初冬的泉州，依然暖阳和煦。在这座宋元时期的"东方第一大港"，曾经的"海丝精神"与当代商业智慧交相辉映，一场关于商业模式的深度思辨在此 展开。 三天两晚的课程中，吴老师以中国式商业模式的成功逻辑为起点，系统拆解了渠道变革的路径与品牌转型的得失，并结合当前中国市场的演化趋 势，前瞻性地提出了商业模式迭代的方向。 课后，不少学员在朋友圈分享感悟： "一场学习的盛宴，一场文化的碰撞，一场心智的洗礼，一场商业的启迪！" "吴晓波老师串联了商业模式、渠道革命、城市经济、产品力、品牌力与AI 时代的变化，看似横跨不同行业，本质却都指向同一个答案——真正赢 得时代的，是能读懂中国、坚持好产品、并不断迭代自己的人。" "激荡讲堂对我来说不仅是一堂关于商业的课，更是一堂关于'怎么看世界、怎么规划自己'的课。它让我意识到：无论是企业还是个人，真正重要 的不是一时的高光，而是在长期结构变化中，找到自己的位置，守住自己的节奏 ...

Core Insights - Liang Jianzhang, founder of Ctrip and a professor at Peking University's Guanghua School of Management, warns that if China does not intervene in its population issues, India's population could be three times that of China in forty years [1][4][17] - The decline in China's population began after reaching a peak of 1.41 billion in 2022, with projections indicating a further decrease to 1.40828 billion by 2024, marking three consecutive years of negative growth [6][7] - The birth rate in China has dropped to 6.77‰, with predictions suggesting that the number of newborns could fall below 7 million by 2025, exacerbating the already low total fertility rate [7][12] Population Trends - In 2024, the number of newborns is projected to be 9.54 million, while deaths could reach 10.93 million, resulting in a net population decrease of 1.39 million [7] - The total fertility rate in China has been below 1.0, leading to significant demographic challenges, including a shrinking labor force [7][8] - By 2050, China's labor force is expected to decline from 800 million to 750 million, impacting economic foundations [8] Economic Implications - The reduction in the working-age population will lead to rising labor costs, challenging the competitiveness of traditional manufacturing sectors in China [7][12] - Liang Jianzhang emphasizes that innovation relies on a sufficient number of young people, and a decline in this demographic could hinder technological advancement [10] Aging Population - The proportion of individuals aged 60 and above in China has surpassed 21% and is projected to exceed 30% by 2035, creating immense pressure on the pension and healthcare systems [13] - The social security system may face funding shortages due to the increasing elderly population [13] Comparative Analysis - Japan serves as a cautionary example of delayed action on population issues, having faced negative growth and severe aging since the mid-1990s, despite various government interventions [15] - In contrast, India has a younger population with a fertility rate of 2.05, which is nearly double that of China, positioning it for potential economic advantages in the coming decades [17][19] Societal Factors - Economic pressures, time constraints, and changing social attitudes are significant factors contributing to the reluctance of young people in China to have children [21][23] - Women face particularly difficult choices between career and family, compounded by societal expectations and workplace discrimination [23] Proposed Solutions - Liang Jianzhang advocates for reforms that support families willing to have children, including financial assistance, improved education and healthcare systems, and changes to workplace culture [25] - A societal consensus on the importance of addressing population issues is crucial for creating a favorable environment for childbirth [25]

Core Insights - The article discusses the dependency ratio in China, highlighting that in 2024, 15 provinces will have a total dependency ratio higher than the national average, with five provinces exceeding 50% [2][3]. Regional Population Age Structure and Dependency Ratio (2024) - The national total dependency ratio is 45.93%, with a child dependency ratio of 23.08% and an elderly dependency ratio of 22.85% [3]. - Provinces with total dependency ratios exceeding 50% include: - Guizhou: 53.37% - Guangxi: 53.08% - Shandong: 52.72% - Henan: 52.43% - Hebei: 50.2% [3][4]. - High total dependency ratios are linked to labor outflow and high proportions of children or elderly populations [3]. Future Population Dividend - Provinces like Guizhou and Guangxi have child dependency ratios above 30%, indicating potential for urbanization [4]. - 18 provinces have a child population ratio exceeding the national average of 15.81%, with 13 provinces above 17%, predominantly in the western region [4]. Guangdong Province Insights - Guangdong has a permanent urban population of 97.01 million, with an urbanization rate of 75.91%, ranking fourth nationally [5]. - The province's birth rate is 8.89‰, with 113,000 births in 2024, maintaining its status as the largest birth province for seven consecutive years [5]. - The influx of young, marriage-age individuals contributes to the province's high birth rates despite declining fertility intentions in some areas [5]. Labor Age Population Proportion - 12 provinces have a labor age population ratio exceeding 70%, including Guangdong (72.28%), which has the highest influx of labor-age individuals [6]. - The Northeast region has a low child population ratio, resulting in a lower total dependency ratio despite a relatively high labor age population [6]. Elderly Dependency Ratio - 11 provinces have an elderly dependency ratio of 25% or higher, primarily located in Northeast, Yangtze River Delta, and Bohai Rim regions [6].

Core Viewpoint - The article discusses the dependency ratio in China, highlighting the challenges and opportunities presented by the demographic structure across different provinces in 2024, with a focus on the implications for urbanization and economic growth [3][5]. Summary by Sections Dependency Ratio Overview - The dependency ratio, or support ratio, measures the ratio of non-working-age population to working-age population (ages 15-64). In 2024, 15 provinces had a total dependency ratio above the national average, with five provinces exceeding 50%: Guizhou, Guangxi, Shandong, Henan, and Hebei [3][5]. Provincial Analysis - The article provides a detailed breakdown of the dependency ratios across various provinces, indicating that high dependency ratios are often linked to population outflows, particularly of the working-age population, and high proportions of children or elderly individuals [5][6]. - For instance, Guizhou and Guangxi have child dependency ratios exceeding 30%, indicating potential future demographic advantages due to a larger base of young people [5]. Urbanization Potential - Provinces with high child populations and low urbanization rates, such as those in the western regions, show significant potential for urbanization. In contrast, provinces like Guangdong and Fujian, despite high urbanization rates, also maintain a substantial proportion of children in their populations [5][6]. Birth Rates and Population Trends - Guangdong has the highest urban population, with a rate of 75.91% and a birth rate of 8.89‰, leading the nation in births for seven consecutive years, with 1.13 million births in 2024 [5][6]. - The influx of young, working-age individuals into Guangdong contributes to its high labor force participation, with 72.28% of its population in the working-age group [6]. Regional Disparities - The article notes that while some provinces have high ratios of elderly dependents, such as those in Northeast China, they also have a relatively low birth rate, leading to a lower overall dependency ratio [6].

Core Insights - The overall dependency ratio in five provinces exceeds 50%, indicating a significant proportion of non-working age population compared to the working-age population [1][3] - In 2024, 15 provinces have a total dependency ratio higher than the national average, with notable figures in Guizhou, Guangxi, Shandong, Henan, and Hebei [1][2] Dependency Ratios by Region - The national total dependency ratio is 45.93%, with a breakdown of 23.08% for children and 22.85% for the elderly [2] - Provinces with the highest total dependency ratios include: - Guizhou: 53.37% (children: 33.58%, elderly: 19.79%) - Guangxi: 53.08% (children: 31.69%, elderly: 21.39%) - Shandong: 52.72% (children: 25.64%, elderly: 27.08%) - Henan: 52.43% (children: 29.51%, elderly: 22.92%) - Hebei: 50.2% (children: 25.48%, elderly: 24.72%) [2][3] Population Composition and Urbanization Potential - High total dependency ratios are linked to both out-migration of the working-age population and high proportions of children or elderly in certain provinces [3] - Provinces like Guizhou and Guangxi, despite high dependency ratios, have significant potential for urbanization due to their high child dependency ratios (over 30%) [3] Child Population Statistics - Eighteen provinces have a child population ratio exceeding the national average of 15.81%, with 13 provinces above 17%, predominantly in the western region [4] - Guangdong, despite its high urbanization rate (75.91%), has a child population ratio exceeding 17% and continues to lead in birth rates, with 1.13 million births in 2024 [4] Working-Age Population Insights - Twelve provinces have a working-age population ratio above 70%, including Guangdong, Zhejiang, Beijing, and Shanghai, which are major destinations for labor migration [5] - Guangdong has the highest working-age population ratio at 72.28%, reflecting its status as the province with the most significant inflow of young labor [5]