Measuring Restrictiveness

R*

Frank Chen, a subscriber to Macro Musings, is a student at Georgia Tech studying computational finance and will graduate in December 2024. I have enjoyed learning about his interest and passion for macro in his pursuit of an investment, trading, or quant-related role. If there is something I miss the most about running a hedge fund, it was the opportunity to mentor young, eager and talented analysts and work with them on research projects. Frank asked if there was anything I wanted his help in researching, so I was happy to guide him on the below. If you are looking to hire an ambitious analyst in the near future, get in touch with Frank via LinkedIn here: Frank Chen.

When I was a guest on the Forward Guidance Podcast in February, the market was pricing in 5 cuts for this year (we peaked at 8) while I argued that policy is not restrictive and may in fact be loose. My argument has been that the Fed is looking at the Fed Funds vs. a neutral rate estimate of 2.5% and deeming it restrictive, so they argue they must cut rates soon to avoid economic damage. I posited that both aspects of that calculus were flawed: the neutral rate estimate is far too low, and the Fed Funds rate is the least impactful rate in the economy. The right metrics would be to look at 10y versus a variety of metrics, whether it be a better neutral rate estimate, or versus Nominal GDP or core CPI. Let’s look at this empirically.

The Fed publishes two models on the neutral rate: the HLW (referred to as the Williams model after its founder, President of the NY Fed), and the Lubik (published by the Richmond Fed). Both models publish real neutral rate estimates, so to get a nominal rate, we add 2% inflation. However, as we have seen after nearly 4 years of this inflation episode, inflation may in fact be sticky at higher levels of 3.5% or so. We conservatively include a 3% trend inflation estimate as alternative nominal neutral rates for both models, and we compare all of these versus the 10y rate.