It looks like it's referring to Wu and Xia (2016) shadow rates. Some more media coverage is here. The core idea of a shadow rate goes back at least to Fischer Black.
Black (1995)
Fischer Black's idea was that the nominal short rate $r_t$ is an option. One can either:
- Invest and earn the real shadow rate $s_t$, which is based on the investment opportunity set, plus expected inflation.
- Hold currency and earn 0.
Thus the shadow rate $s_t$ can go negative while the short rate $r_t$ observed in markets is always non-negative.
Wu and Xia (2016)
Wu and Xia (2016) take that idea and estimate a shadow federal funds rate.
The short rate is maximum of a lower bound $\underline{r}$ and the shadow rate $s_t$:
$$ r_t = \max(\underline{r}, s_t) $$
In a Gaussian affine term structure model (GATSM), the forward rates are affine in state variables $X_t$:
$$ f^{GATSM}_{n, n+1, t} = a_n + b_n'X_t $$
In Wu and Xia (2016), their non-linear model implies the forward rate can be approximated by:
$$ f^{SRSTM}_{n, n+1, t} = \underline{r} + \sigma^\mathbb{Q}_n g\left(\frac{a_n + {b_n^\mathbb{Q}}'X_t - \underline{r}}{\sigma^\mathbb{Q}_n}\right) $$
They linearize $g$ around the current estimate and apply a Kalman filter to estimate. You'll want to read their paper to see precisely what they do and it's possible I'm butchering something (this isn't my area).
References:
Black, Fischer, "Interest Rates as Options," Journal of Finance, 1995
Wu, Cynthia Jing and Fan Dora Xia, "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit, and Banking, 2016