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Daniel Buncic

Publications and source records attributed to Daniel Buncic.

2 recordsLinked to original sources

On a Standard Method for Measuring the Natural Rate of Interest

I show that Holston, Laubach and Williams' (2017) implementation of Median Unbiased Estimation (MUE) cannot recover the signal-to-noise ratio of interest from their Stage 2 model. Moreover, their implementation of the structural break regressions which are used as an auxiliary model in MUE deviates from Stock and Watson's (1998) formulation. This leads to spuriously large estimates of the signal-to-noise parameter $λ_{z}$ and thereby an excessive downward trend in other factor $z_{t}$ and the natural rate. I provide a correction to the Stage 2 model specification and the implementation of the structural break regressions in MUE. This correction is quantitatively important. It results in substantially smaller point estimates of $λ_{z}$ which affects the severity of the downward trend in other factor $z_{t}$. For the US, the estimate of $λ_{z}$ shrinks from $0.040$ to $0.013$ and is statistically highly insignificant. For the Euro Area, the UK and Canada, the MUE point estimates of $λ_{z}$ are \emph{exactly} zero. Natural rate estimates from HLW's model using the correct Stage 2 MUE implementation are up to 100 basis points larger than originally computed.

econ.EM

Econometric issues with Laubach and Williams' estimates of the natural rate of interest

Holston, Laubach and Williams' (2017) estimates of the natural rate of interest are driven by the downward trending behaviour of 'other factor' $z_{t}$. I show that their implementation of Stock and Watson's (1998) Median Unbiased Estimation (MUE) to determine the size of the $λ_{z}$ parameter which drives this downward trend in $z_{t}$ is unsound. It cannot recover the ratio of interest $λ_{z}=a_{r}σ_{z}/σ_{\tilde{y}}$ from MUE required for the estimation of the full structural model. This failure is due to an 'unnecessary' misspecification in Holston et al.'s (2017) formulation of the Stage 2 model. More importantly, their implementation of MUE on this misspecified Stage 2 model spuriously amplifies the point estimate of $λ_{z}$. Using a simulation experiment, I show that their procedure generates excessively large estimates of $λ_{z}$ when applied to data generated from a model where the true $λ_{z}$ is equal to zero. Correcting the misspecification in their Stage 2 model and the implementation of MUE leads to a substantially smaller $λ_{z}$ estimate, and with this, a more subdued downward trending influence of 'other factor' $z_{t}$ on the natural rate. Moreover, the $λ_{z}$ point estimate is statistically highly insignificant, suggesting that there is no role for 'other factor' $z_{t}$ in this model. I also discuss various other estimation issues that arise in Holston et al.'s (2017) model of the natural rate that make it unsuitable for policy analysis.

econ.EM