The monthly Wu-Xia shadow federal funds rate from Wu and Xia (2016),
maintained and published by the Federal Reserve Bank of Atlanta. The
shadow rate is the authors' estimate of what the federal funds rate
would have been during zero-lower-bound episodes (2008-12 to 2015-12
and 2020-03 to 2022-02) had policy rates been allowed to go negative.
The companion effective federal funds rate (effr) is included for
reference.
Format
A data frame with columns:
- date
Date. First day of the observation month.- shock
numeric. First difference of shadow rate (percentage points per annum).- shadow_rate
numeric. Wu-Xia shadow federal funds rate at last business day of the month (percentage points per annum).- effr
numeric. Effective federal funds rate at last business day of the month (percentage points per annum).- series
character. Series identifier"wu_xia".
Source
Wu, J. C., & Xia, F. D. (2016). "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound." Journal of Money, Credit and Banking 48(2-3): 253-291. doi:10.1111/jmcb.12300 . Data: https://www.atlantafed.org/cqer/research/wu-xia-shadow-federal-funds-rate. US Federal Reserve research output; not subject to copyright under 17 U.S.C. s. 105.
Details
Stance vs shock. The shadow rate is a stance measure, not a
policy shock. The shock column is the first difference of
shadow_rate and is provided for pipeline compatibility with other
series in the package. It conflates genuine policy news with Kalman-
filter revisions of the latent state. Users estimating shock IRFs
should prefer an event-study series (nakamura_steinsson,
bauer_swanson, miranda_agrippino_ricco) and reserve wu_xia
for characterising the zero-lower-bound policy stance.
Model sensitivity. Krippner (2020, Journal of Money, Credit and Banking 52(4)) documents that shadow-rate estimates are sensitive to the choice of effective lower bound, the number of factors (two versus three), and the set of yield maturities used in estimation. Wu-Xia's three-factor shadow-rate term-structure model (SRTSM) and Krippner's two-factor SSR can differ by 50 to 150 basis points at the 2014 and 2021 troughs. Results that rely on Wu-Xia alone should be replicated with at least one alternative shadow-rate series.
Vintage. This bundled series is the Atlanta Fed monthly update current as of the package build. Historical values are filtered estimates and can change when new data arrives; users needing a fixed vintage should download the archived Atlanta Fed file directly.