
美国国债收益率升至二十年来的高位,这引发了诸多疑问:其背后的原因是什么?这种趋势会持续多久?又会对美国经济产生何种影响?尽管今年美国通胀率一直远高于美联储2%的目标值,但自8月下旬以来国债收益率的上升却并未伴随通胀预期的提高。实际上,这一现象主要源于实际收益率的上升。
The surge in U.S. bond yields to two-decade highs has raised questions about what is causing it, how long it will last and how it will impact the U.S. economy. Although inflation has been well above the Fed’s 2 percent target this year, the rise in bond yields since late August has not been associated with an increase in inflation expectations. Instead, it is mainly attributable to a rise in real yields.
在9月份的联邦公开市场委员会新闻发布会上,美联储主席凯文·沃什指出了三个影响因素:强劲的经济基本面、资本支出的激增以及地缘政治因素。其中前两点与人工智能基础设施前所未有的大规模建设密切相关。
Fed Chair Kevin Warsh cited three forces at play in his September Federal Open Market Committee press conference, including underlying economic strength, surging capital spending and geopolitical factors. The first two of these are related to the unprecedented buildout in artificial intelligence infrastructure.
此前我曾指出,人工智能基础设施的蓬勃发展正成为推动美国经济增长的另一动力,与消费支出相辅相成。目前预计,亚马逊、谷歌母公司Alphabet、Meta、微软和甲骨文这五家大型科技企业的资本支出今年将突破8000亿美元,明年更将达到1.1万亿美元。
I previously highlighted how the boom in AI infrastructure was supplementing consumer spending as a driver of U.S. economic growth. The current estimates of capital spending for five hyper-scalers — Amazon, Alphabet, Meta, Microsoft and Oracle — call for it to surpass $800 billion this year and $1.1 trillion next year.
哥伦比亚大学商学院的斯泰恩·范纽维尔堡教授则从历史角度对人工智能领域的资本支出前景进行了分析。他估计,从2025年至2032年期间,相关投资总额有望超过10万亿美元,相当于每年占美国GDP的3.6%。若这一预测成真,其规模将远超历史上运河、铁路、电气化、高速公路及电信网络建设时期的投入水平。
Professor Stijn Van Nieuwerburgh of Columbia Business School puts the prospective AI capital expenditure spend into historical perspective. He estimates that the pipeline of investments being contemplated would entail more than $10 trillion from 2025 to 2032, representing 3.6 percent of GDP per year. If so, it would far exceed the respective infrastructure buildouts for canals, railroads, electrification, highways or telecommunications.
不过需要注意的是,单纯以人工智能资本支出占GDP的比重来衡量其对经济的整体影响其实存在偏差,因为其中很大一部分资金最终会转化为进口支出。目前来看,该领域对经济增长的推动作用主要源于企业资本支出的增加。但随着更多企业开始应用人工智能技术,生产效率也将逐步提升,人工智能最终将成为美国经济结构中不可或缺的一环。
One caveat is that calculations of AI capital expenditure to GDP overstate the overall economic impact, because a substantial portion will leak out as increased imports. The effect on economic growth thus far is mainly driven by increased business capital spending. However, as more businesses adopt AI and productivity increases over time, it will become more ingrained.
美联储理事会的一项研究显示,目前人工智能的普及情况仍呈现参差不齐的态势。总体来看,相关迹象表明人工智能仍处于发展建设阶段,尚未引发大规模劳动力替代现象:“尽管部分高度依赖人工智能的行业生产力表现相对强劲,但对劳动力市场的影响仍较为集中,尚未在整体层面广泛显现。”那么,这些发展趋势究竟会对美国债券收益率产生何种影响呢?
A study by the Federal Reserve Board of Governors finds that adoption trends thus far provide a mixed picture of the ubiquity of AI. The evidence overall is consistent with a buildout phase rather than the onset of broad-based displacement: “While some highly exposed sectors show relatively strong productivity, labor market impacts remain concentrated and have not yet broadened in the aggregate.”So, how are these developments impacting U.S. bond yields?
答案是:如今这些大型科技企业的资本支出规模极为庞大,仅靠其内部现金流已无法满足融资需求。摩根士丹利预测,在2025年至2028年期间,这些企业所需的3万亿美元资金中,超过一半将来自外部资本。这些资金来源既包括债务融资,也包括第三方股权投资。
The answer is that the volume of capital spending by the hyper-scalers is so large now that the financing requires more than internal cash flows can generate. Morgan Stanley estimates that more than half of the $3 trillion required to meet their incremental requirements over 2025-2028 will come from outside capital. The funding sources include both debt financing and third-party equity.
在债务融资方面,总部位于瑞士的丰德奥资产管理公司指出,华尔街分析师预计,截至今年年底,这些大型科技企业将在美国发行2500亿美元规模的美元债券,全球范围内则将达到4000亿美元。此外,该报告还显示,这五家企业发行的债券中,超过40%的期限在15年以上。发行长期债券的原因在于数据中心这类资产的经济使用寿命较长。
On the debt side, Swiss-based Vontobel Asset Management reports that Wall Street estimates point to $250 billion of U.S. dollar bond issuance by hyper-scalers in the U.S as of year-end, and $400 billion globally. Beyond this, the report estimates the five companies have placed more than 40 percent of their issuance beyond 15 years. The rationale for issuing long-term debt is that data center assets have long economic lives.
在私营部门融资模式发生上述变化的同时,美国联邦预算赤字预计将占到GDP的6%,公众持有的联邦债务规模也正逼近历史峰值。受此影响,当前市场对资本的争夺愈发激烈。
This shift in private sector financing is occurring while the federal budget deficit is an estimated 6 percent of GDP and federal debt outstanding held by the public is approaching a record high. As a result, there is now increased competition for capital.
各经济领域均感受到了资金紧张带来的压力,尤其是数据中心建设以外的建筑行业。展望未来,随着抵押贷款利率已升至7%以上,住宅房地产市场也可能受到波及。这一现象也引发了各界争论:不断走高的债券收益率究竟会抑制整体经济活力,还是能与强劲的经济增长并存呢?
Various sectors of the economy are feeling the squeeze, especially the construction sector, excluding data centers. Looking ahead, residential housing is also likely to be impacted as mortgage rates have surged above 7 percent. This has fueled a debate about whether rising yields will curb overall economic activity or co-exist with strong economic growth.
目前的情况与“人工智能投资热潮正推动经济发展”这一观点相符。近期的经济数据表明,制造业与服务业均呈现增长势头,失业率也维持在低位。《金融时报》曾对多位知名债券投资者进行调查,结果显示他们普遍认为当前飙升的债券收益率远不足以给美国经济降温。
What is playing out thus far is consistent with the view that the AI investment boom is powering the economy. Recent economic data, for example, show a strengthening of both the manufacturing and service sectors of the economy and continued low unemployment. A Financial Times article surveyed prominent bond investors, and the prevailing view was that soaring bond yields were “not even close” to cooling the U.S. economy.
在我看来,2008年金融危机后美国经济增长一度异常疲软,如今债券收益率回归至较为正常的水平。更恰当的参照对象应是20世纪90年代下半叶的互联网热潮时期,当时电信行业正是推动经济强劲增长的关键动力。
My own take is that bond yields are back to more normal levels after U.S. economic growth was abnormally low in the aftermath of the 2008 financial crisis. The more relevant comparison is with the internet boom in the second half of the 1990s when the telecom sector was a key driver of strong economic growth.
在此背景下,美联储必须评估美国经济的长期潜在增长率是否高于目前1.8%的预估值,以及资本竞争现象是否只是暂时性的。若前者成立,美联储则需上调对长期实际债券收益率的预测值。
Amid this, the Federal Reserve must assess whether the economy’s long-term potential growth rate is above its current estimate of 1.8 percent, or whether the competition for capital is a transitory phenomenon. If the former is true, its calculation of the long-term real bond yield would need to be adjusted higher.
最后,美联储还需评估相关金融风险。正如范纽维尔伯格教授所言,当前人工智能产业建设日益依赖外部资源。不过最大的风险或许在于,市场对该产业建设的预期回报率过高。
Finally, the Fed also needs to assess the financial risks, as the AI buildout is increasingly reliant on external sources that Professor Van Nieuwerburgh cites. The biggest risk, however, could be that return expectations for the buildout are too high.
尼古拉斯·萨根博士是一名经济咨询专家,现任职于达顿商学院。他著有《特朗普时代的投资》等三本著作。
Nicholas Sargen, Ph.D., is an economic consultant and is affiliated with the Darden Business School. He has authored three books including “Investing in the Trump Era.”