Why people can’t agree on where interest rates are going | 为什么人们无法就利率走向达成一致 - FT中文网
登录×
电子邮件/用户名
密码
记住我
请输入邮箱和密码进行绑定操作:
请输入手机号码,通过短信验证(目前仅支持中国大陆地区的手机号):
请您阅读我们的用户注册协议隐私权保护政策,点击下方按钮即视为您接受。
FT英语电台

Why people can’t agree on where interest rates are going
为什么人们无法就利率走向达成一致

Methods of estimating so-called R-star are in the spotlight — unfortunately, none are good
估计所谓R-star的方法备受关注——不幸的是,没有一个是好的
00:00

undefined

Everyone is struggling to see where interest rates are headed. Investors are jittery, as shown by gyrating long-term Treasury yields. America’s central bankers are trying to project calm, but they are in a fog too. On August 25, Federal Reserve chair Jay Powell summarised the mood when he said “we are navigating by the stars under cloudy skies”. Economists do have some tools to illuminate the path ahead. But they aren’t very helpful.

The object everyone is searching for is the neutral rate of interest, or R-star for short. (Economists seem to struggle with nicknames.) It is the (real) rate that neither buoys nor depresses the economy once temporary shocks have faded away. Central bankers believe that they can neither influence it nor observe it. Their task is merely to divine it.

Although most agree that over recent decades R-star has fallen, its recent moves are more mysterious. An estimate published by the Richmond Fed suggests that it fell from around 2.2 per cent in April 2008 to 0.8 per cent two years later, but by April 2023 had recovered. By contrast, an estimate from the New York Fed finds that in April 2023 it was still around two percentage points lower than before the global financial crisis. In April, the IMF used a more complicated model to argue that it is probably still very low.

These estimates diverge because of different trade-offs made by their designers. One approach is to make lots of assumptions about how the economy works to strip out the noise associated with shocks. But it suffers the risk that the assumptions — and therefore the results — are rubbish. An alternative relies more on recent data. But that risks results that reflect temporary shocks, not the future once they fade.

Take the data-heavy method deployed by the Richmond Fed, which uses a very sophisticated moving average to forecast long-run rates. Given the recent resilience of America’s economy, it should probably be no surprise that it suggests a rising R-star. Unfortunately, it suffers from statistical error bands the size of a bus. Although the median estimate is 2.3 per cent, the lower bound is 1.4 per cent and upper bound is 3.6 per cent. That is about as useful as being told that one’s Friday night pizza will arrive anytime between 6pm and 11pm.

The New York Fed’s method uses more theory. It assumes a relationship between inflation, the position of the economy relative to its potential and interest rates, then brings in data to infer the position of R-star. The cost of this approach became apparent over the pandemic, when the model was spitting out such implausible numbers that it was temporarily suspended. Now the tweaked model describing America’s R-star is back.

The approach deployed by the IMF is the most theory-driven of them all. In the long run, factors like demographic change, productivity growth and fiscal policy should influence the balance of savings and investment. And the model delivers fantastically detailed breakdowns of exactly how much. Between 1975-79 and 2015-19, demographic change tugged down America’s R-star by 0.5 percentage points, and weak productivity growth by 1.23 percentage points.

undefined

Again, the danger is that these results tell you more about modelling than reality. Particularly if you believe a 2017 study from the Bank for International Settlements which argued that the simultaneous events of falling real interest rates, stalling productivity growth and ageing populations “appear coincidental”. Scouring data between 1860 and 2016, they reckon that changing monetary policy frameworks matter more.

The other way of measuring R-star is to look at the long-term interest rates implicit in investors’ pricing. One interesting study calculates the long-term interest rate implicit in the value of British flats before and after their leases are extended. It concludes that the natural rate of return on capital has not risen much since the pandemic. But that rate includes a risk premium associated with owning British property, and may be affected by other distortions. And of course, says Atif Mian, one of the study’s authors, the collective wisdom of the housing market “could be wrong”.

An anxious central banker could drive themselves mad worrying about the uncertainty ahead. What if R-star is indeed slow-moving, but the pandemic has revealed that we overestimated its fall during the 2010s? What if the expectations of central bankers and investors feed off each other? It’s probably not much comfort to say that these estimates of R-star are the best we have. But it should be more soothing to say that any mistakes will be just as hard to pin down.

版权声明:本文版权归FT中文网所有,未经允许任何单位或个人不得转载,复制或以任何其他方式使用本文全部或部分,侵权必究。

华尔街对大型科技公司2000亿美元的人工智能支出感到担忧

本周,美国四大互联网集团的AI效益初现端倪,但也警告说将增加支出。

地中海已经变成危险的“汽油桶”了吗?

暴雨的部分原因是海水温度的危险上升。

从错失的投资机会中得到的教训

我是如何错过OpenAI、BrewDog和英国电信的?

决定特朗普贸易政策的内部竞争

在这位共和党候选人的第一个总统任期,其政府内部内斗不断。

政府顾问表示,英国应简化人工智能专家的签证程序

马特•克利福德关于促进科技产业发展的建议还包括设立数据中心特区。

为什么卡玛拉•哈里斯会赢

因为这仍然是经济问题,傻瓜。
设置字号×
最小
较小
默认
较大
最大
分享×