（文章来源：第一财经） 中信建投研报表示，"十五五"时期是中国跨越中等收入陷阱、应对全球产业链重构的关键窗口期。当前 中国制造业增加值占GDP比重虽降至24.87%，但仍处于符合国际规律的合理区间。面对外部地缘政治 博弈与内部要素成本上升的双重挤压，保持制造业合理比重不仅是经济安全的"压舱石"，更是培育新质 生产力的核心载体。未来五年，制造业发展的核心逻辑将从"保总量"向"优结构"跃迁：在总量上，参考 德日经验，努力维持在20%-25%的底线区间；在结构上，以全要素生产率（TFP）提升为导向，通 过"有进有退"的产业置换，推动高技术制造业占比提升，实现从要素驱动向创新驱动的本质转变，确立 全球竞争新优势。 ...

现实中稀缺的公共资源很多时候未必是通过价格机制分配，而主要是通过行政等级分配。以 下文章出自中国人民大学经济学教授聂辉华所著《基层中国的运行逻辑》一书，它能帮助读 者理解中国城市的等级体系，从而更好地理解城市之间的发展差异、发展路径和营商环境， 特此转载。 中国城市的等级金字塔 中国的国家治理架构是"条块结合，以块为主"的中央集权体制。在这套体制下，上级党委和政府领导下 级党委和政府，并且前者决定了后者的资源配置。而上级领导下级的机制，就是通过上级的职能部门对 口领导或指导下级的职能部门。比如，省政府要出资支持市政府的一个大项目，那么市发改委就需要向 省发改委申报。按照类似的逻辑，县政府需要项目资金，就需要通过县发改委向市发改委申报。因此， 在中国这种单一制政治制度下，国家的资源一定是自上而下分配的，高级别的城市相对于低级别的城市 一定会优先获得各种资源。总之，不同于市场通过价格配置资源，体制内是通过等级来配置资源。 理解了这个城市金字塔体系有什么用呢？最大的用处是，它从一个全新的角度告诉我们，现实中稀缺的 公共资源很多时候未必是通过价格机制分配，而主要是通过另一种机制——行政等级——分配。这有助 于我们理解 ...

12 月 20 日，在华尔街见闻和中欧国际工商学院联合主办的「 Alpha 峰会」上， 知名经济学家付鹏发表了题为《 AI 时代下 -- 秩序的重构》的演讲。 付鹏表示，当前 AI 产业的核心矛盾在于"路修好了，等待车跑"。上游算力基建投入已基本完成， 2026 年将进入下游企业级应用能否落地并兑现盈利 的"证伪之年"。 他还表示，2026年投资者应重点关注特斯拉。它将在明年面临类似当年英伟达的"身份验证"时刻：究竟只是一一家汽车公司，还是真正的企业级"重AI应 用"载体。付鹏指出，这正如检验"高速公路修好后有没有车跑"，如果特斯拉能证明其作为AI应用的价值，市值空间将巨大；否则以当前作为汽车股的逻辑 看，其估值并不具备吸引力。 付鹏还强调， 如果AI被证伪，全球股市都将面临剧烈波动。 当前美股（特别是 AI 板块）是全球"生产力"的核心，全球主要资产的波动率都与其高度绑 定。如果 AI 最终被证实为泡沫，那不仅是美股，包括日本、欧洲在内的全球股市都会崩盘，"这是一根绳上的蚂蚱"。 他认为，目前加息或降息已不重要，核心在于资产端（ AI ）能否产生真实回报率，若资产端出问题，负债端的调整无济于事。 以下为演讲 ...

Core Insights - China's TFP (Total Factor Productivity) level is only 0.37 of that of the United States, indicating significant growth potential [1] - The traditional growth model in China has relied heavily on capital and labor input, but this approach is facing challenges due to diminishing returns and the exhaustion of demographic dividends [1] - A structural shift is necessary for China's economy to transition from input-driven growth to efficiency-driven growth, focusing on improving TFP rather than merely increasing inputs [1] Group 1: Understanding TFP - TFP has long been viewed as a "black box," representing the residual factors contributing to output growth beyond capital and labor, but lacks clarity on its underlying mechanisms [2] - Existing research often measures TFP changes without fully understanding the driving forces behind these changes, limiting the practical applicability of findings [2] Group 2: Components of TFP - TFP can be decomposed into measurable components such as innovation, digitalization, institutional and organizational management, and externalities [3] - Innovation and technological advancement are traditional sources of TFP growth, with an emphasis on the diffusion and absorption of innovations rather than just research outcomes [3] - Digital assets are emerging as new production factors, reshaping production functions and enhancing overall efficiency through improved resource allocation and operational optimization [3] Group 3: Institutional and Organizational Factors - A conducive institutional and organizational management system is essential for fostering innovation and driving TFP growth [4] - Institutional arrangements influence resource allocation efficiency across sectors, with improved management practices potentially increasing output without additional input [4] Group 4: External Effects and Social Responsibility - Traditional TFP measurements often overlook the external effects and social responsibilities that contribute to overall efficiency [5] - Enhancing productivity in one sector can lead to efficiency improvements across supply chains and service networks, suggesting a broader definition of TFP that includes social contributions [5] Group 5: Policy Implications - Establishing a unified TFP data and analysis system is crucial for dynamic assessment and policy evaluation [6] - Expanding the scope of TFP assessments to include social value and externalities can lead to a more comprehensive understanding of efficiency [6] - Policy reforms should focus on improving resource allocation efficiency, with TFP enhancement as a common goal across various sectors [6] Group 6: From Metrics to Management Tools - TFP should transition from a statistical measure to a management tool, allowing policymakers to design targeted incentives for innovation and efficiency improvements [7] - Understanding TFP as a dynamic system connecting macroeconomic policies with micro-level behaviors can enhance China's economic competitiveness [7]

Group 1 - The core argument emphasizes that the key to future economic growth in China lies in improving Total Factor Productivity (TFP) rather than merely increasing inputs of capital and labor [1] - China's TFP level is only 0.37 of that of the United States, indicating significant growth potential [1] - The traditional growth model based on capital and labor accumulation is facing challenges due to diminishing returns and the exhaustion of factor input growth [1] Group 2 - TFP has long been viewed as a "black box," with its definition and application lacking clarity, often treated as a residual that does not explain the sources of efficiency [2] - Existing research has primarily focused on measuring TFP changes without adequately analyzing the underlying mechanisms driving these changes [2] Group 3 - To understand TFP, it should be decomposed into measurable components such as innovation, digitalization, institutional and organizational management, and externalities [3] - Innovation and technological progress are traditional sources of TFP growth, with an emphasis on the diffusion and absorption of innovation rather than just research outcomes [3] - Digital assets are emerging as new production factors that can enhance TFP by reshaping production functions and improving overall efficiency [3] Group 4 - A conducive institutional and organizational management system is essential for fostering innovation and driving TFP growth [4] - Institutional arrangements determine the efficiency of resource allocation across different sectors and regions, highlighting the importance of management and governance improvements [4] Group 5 - External effects and social responsibility should redefine the boundaries of productivity, as improvements in one sector can enhance overall efficiency across supply chains [5] - Social responsibility costs, often seen as efficiency losses, should be recognized as contributions to systemic stability and sustainability [5] Group 6 - The goal of "opening the black box" is to create a more scientific approach to development and governance, with TFP enhancement serving as a starting point for policy design [6] - A unified TFP data and analysis system is necessary to break down data silos and provide a quantitative basis for policy evaluation [6] Group 7 - Expanding the assessment criteria for TFP to include social value and externalities is crucial for a comprehensive evaluation of efficiency [6] - Policies should focus on improving resource allocation efficiency rather than merely reducing inputs, with TFP as a guiding principle for reforms [6] Group 8 - TFP should transition from a statistical measure to a management tool, allowing policymakers to design targeted incentives for innovation and digitalization efforts [7] - Understanding TFP as a dynamic system connecting macroeconomic policies with micro-level behaviors is essential for enhancing China's economic competitiveness [7]

Core Insights - The Nobel Prize in Economic Sciences was awarded to Joel Mokyr, Philippe Aghion, and Peter Howitt (KAH) for their research on "innovation-driven economic growth," which is closely related to China's push for new productivity [1][5] - The unexpected aspect of the award is the high overlap of KAH's findings with the anticipated 2024 and 2025 Nobel Prize winners [5][10] - The historical trend shows a preference for macroeconomic and growth fields in Nobel Prize awards, with seven awards given in this area since 2000, indicating a significant focus on these themes [11] Group 1 - KAH's contributions to economic growth theory are significant, particularly in the context of current global technological innovations and competition, especially in AI [5][24] - The research of KAH and the previous winners, Aghion, Johnson, and Robinson (AJR), overlaps significantly, particularly in the area of how innovation and technology impact economic growth and social equality [10][11] - The historical context of the Industrial Revolution and its spread from Britain to Europe is a critical area of study, with various scholars, including AJR and Mokyr, exploring the factors behind this phenomenon [12][13] Group 2 - AJR's research emphasizes the role of inclusive institutions in economic growth, while Mokyr highlights the importance of the combination of theoretical and practical knowledge for sustained growth [12][13] - The integration of geographical, economic, social, and cultural factors into a comprehensive framework for understanding the Industrial Revolution is a notable development in economic thought [15] - The concept of "creative destruction" as a driver of economic growth is explored, with findings indicating that moderate competition fosters innovation, while excessive competition can stifle it [21][28] Group 3 - The decline in total factor productivity (TFP) in various countries, including China, raises questions about the effectiveness of technological advancements in driving economic growth [26][27] - The phenomenon of "superstar firms" dominating markets and potentially hindering innovation among smaller competitors is a critical concern for future economic dynamics [28][30] - The need for policies that promote fair competition and limit the monopolistic practices of large firms is emphasized to ensure a balanced economic environment [33]

Core Viewpoint - Japan's economy is experiencing a "new normal" characterized by inflation, labor shortages, and rising wages, coinciding with a significant political transition as Shigeru Ishiba steps down and Sanae Takaichi is elected as the new president of the Liberal Democratic Party [1][7]. Group 1: Economic Policy and Market Reactions - The stock market welcomed Takaichi's advocacy for "responsible active fiscal policy," while the bond market expressed concerns over potential increases in government bond issuance [1]. - Despite Ishiba's lack of focus on economic policy, the Nikkei average stock price reached historical highs during his tenure, indicating a paradox in market performance [3]. Group 2: Software Investment Trends - The Bank of Japan's September survey revealed explosive growth in software investment among companies, with large enterprises planning a 10.7% increase in 2025, while medium-sized and small enterprises plan increases of 14.6% and 28.1%, respectively [3][5]. - In contrast, software investment among medium-sized and small enterprises saw declines of 4.8% and 6.4% in 2024, highlighting a significant shift in investment strategy for 2025 to address labor shortages [3]. Group 3: Industry-Specific Insights - The wholesale and retail sectors are projected to increase software investment by 39.5% in 2025, recovering from a 23.9% decrease in 2024, while the accommodation and food services sector is expected to shift from a slight decrease to a 39.5% increase [5]. - The Bank of Japan's report emphasizes that investments should not only address immediate labor shortages but also enhance marginal productivity, aligning with the goal of achieving a nominal GDP of 1,000 trillion yen by 2040 [6]. Group 4: Future Economic Outlook - Despite Japan's declining population, achieving an average nominal investment growth rate of 4.0% could lead to a nominal GDP growth of 3.1% annually, with real GDP growth projected at 1.7% [6]. - The current economic transformation presents an opportunity for the new administration to capitalize on these trends, potentially benefiting businesses and the general public [8].

Group 1 - The Federal Reserve's recent interest rate cut has led to a weakening of the US dollar, providing strong upward momentum for non-US currencies, including the Renminbi [1][2] - On September 17, the offshore Renminbi broke the 7.10 mark against the US dollar, reaching a high of 7.0995, the first time since November of the previous year [1][2] - The narrowing interest rate differential between China and the US is a significant factor contributing to the Renminbi's strength, although the fundamental economic conditions also play a crucial role [2][3] Group 2 - International capital flows are a key determinant of exchange rates, and the expectation of a weaker dollar is becoming more likely as the Fed continues its rate-cutting path [2] - China's economic resilience and the relative decline in productivity growth in Western countries are supporting the Renminbi's appreciation [3][4] - Deutsche Bank has expressed optimism about the Renminbi, predicting it could break the 7 mark by 2025 and appreciate to 6.7 by 2026, reflecting a positive outlook on Chinese assets [3] Group 3 - The willingness of foreign trade enterprises to engage in currency exchange is increasing, leading to a net inflow in the foreign exchange market [4] - The People's Bank of China's monetary policy is effectively stabilizing exchange rate expectations, reducing the likelihood of rapid appreciation or depreciation of the Renminbi [4] - The market's expectation of a stable Renminbi value is likely to persist, although the introduction of more exchange rate hedging tools may increase the volatility of the Renminbi in the future [4]

Group 1: Economic Transformation Insights - The core theme of the event was "Transforming Chinese Economy: Pathways and Prospects," focusing on macroeconomic background, opportunities, challenges, and policy directions [2] - Liu Qiao emphasized that China's strategy to maintain growth is through productivity enhancement, framing the US-China trade friction as a competition of total factor productivity (TFP) rather than a trade imbalance issue [4] - Liu Qiao noted that despite a decline in TFP growth, the "new quality productivity" strategy centered on technological innovation, industrial upgrading, and structural reform could restore TFP growth to 2%, supporting a sustainable GDP growth of 5% in the future [4] Group 2: Inflation and Demand Challenges - Color analyzed the current deflationary pressures in China, highlighting that both CPI and PPI are on a downward trend, with CPI recently turning negative, indicating increasing deflationary pressure [6] - The main causes of this deflation include strong supply capacity, weak demand, and tight monetary policy, with GDP growth projected at 5.3% and industrial value-added growth at 6.4% for the first half of 2025, while retail sales growth is only 5% [6][8] - Color pointed out that structural and long-term characteristics of deflation are evident, with traditional manufacturing facing overcapacity and a shift in demand towards high-end sectors [8] Group 3: Consumption and Trade Structure - Tang Yao focused on the need to develop consumer demand in China to lay a foundation for long-term economic growth, noting that while goods consumption is comparable to the US, service consumption is significantly lower [10] - The booming concert market and local sports leagues indicate a strong consumer willingness for service consumption, with the service sector seen as a key area for consumption growth [10] - Tang Yao observed that despite the turbulence caused by the Trump administration, global trade has shown resilience, with China's trade becoming more diversified and increasing integration with emerging economies [10]

Group 1 - Generative AI (GenAI) is expected to significantly reshape global productivity, industry dynamics, and regional economies over the next decade, with a focus on its impact on total factor productivity (TFP) across various sectors [1][4][22] - The healthcare sector is projected to be the largest beneficiary of GenAI, with TFP growth estimated between 1.2% and 2.5% by 2033, driven by advancements in diagnostics, patient management, and operational efficiencies [2][35] - Advanced manufacturing, particularly in computer and medical equipment, is also set to experience substantial TFP gains, estimated at 1.0% to 2.4%, as GenAI transforms production processes and supply chain management [3][35] Group 2 - Developed regions such as Asia-Pacific, Western Europe, and North America are expected to see the most significant GDP growth due to GenAI, with increases ranging from 1.0% to 2.3% in these areas by 2033 [4][22] - In contrast, regions like South Asia and Sub-Saharan Africa are anticipated to experience limited GDP growth, with TFP improvements only between 0.05% and 0.1%, due to weaker technological infrastructure and talent shortages [4][8] - The report highlights that GenAI's influence extends beyond direct productivity gains, as it also affects trade and capital flows, creating a cycle of economic expansion in regions that rapidly adopt these technologies [5][22] Group 3 - The report indicates a widening gap between industries benefiting from GenAI and those lagging behind, with sectors like education, public administration, and professional services also poised for significant productivity enhancements [6][22] - Conversely, industries such as agriculture, construction, and traditional mining are expected to see modest TFP growth, ranging from 0.2% to 1.0%, due to their lower labor cost structures and higher dependency on manual processes [6][22] - The spillover effects of GenAI are noted, where industries with limited direct application can still benefit indirectly from growth in manufacturing and services, leading to increased demand in sectors like real estate and utilities [6][8] Group 4 - The uneven distribution of GenAI's productivity benefits is reshaping global competitiveness, with Western economies likely to achieve TFP increases of 0.9% to 1.8%, primarily in healthcare and manufacturing [7][22] - Emerging markets in Central and Eastern Europe, Latin America, and ASEAN are expected to see moderate TFP growth of 0.3% to 0.7%, often through the adoption of GenAI technologies in manufacturing processes [7][8] - The report emphasizes that regions with lower capital mobility may find new opportunities in traditional sectors as demand for basic products rises in developed countries focusing on GenAI-intensive industries [8][22]