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Working Paper
The Macroeconomic Risks of Undesirably Low Inflation
This paper investigates the macroeconomic risks associated with undesirably low inflation using a medium-sized New Keynesian model. We consider different causes of persistently low inflation, including a downward shift in long-run inflation expectations, a fall in nominal wage growth, and a favorable supply-side shock. We show that the macroeconomic effects of persistently low inflation depend crucially on its underlying cause, as well as on the extent to which monetary policy is constrained by the zero lower bound. Finally, we discuss policy options to mitigate these effects.
Working Paper
Uniform Priors for Impulse Responses
There has been a call for caution when using the conventional method for Bayesian inference in set-identified structural vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for individual impulse responses or other quantity of interest. This paper challenges this call by formally showing that, when the focus is on joint inference, the uniform prior over the set of orthogonal matrices is not only sufficient but also necessary for inference based on a uniform joint prior distribution over the identified set for the vector of ...
Working Paper
Inference in Bayesian Proxy-SVARs
Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop an algorithm for exact finite sample inference in this class of time series models, commonly known as Proxy-SVARs. Our algorithm makes independent draws from any posterior distribution over the structural parameterization of a Proxy-SVAR. Our approach allows researchers to simultaneously use proxies and traditional zero and sign restrictions to identify structural shocks. We illustrate our methods with two applications. In particular, we show how to generalize the ...
Journal Article
Tracking U.S. Real GDP Growth During the Pandemic
During this fast-moving pandemic, it's vital that policymakers can rely on real-time estimates of real GDP growth. Jonas Arias and Minchul Shin show us how it's done.
Working Paper
Monetary Policy, Trend Inflation and the Great Moderation: An Alternative Interpretation - Comment
Working with a small-scale calibrated New-Keynesian model, Coibion and Gorodnichenko (2011) find that the reduction in trend inflation during Volcker's mandate was a key factor behind the Great Moderation. We revisit this finding with an estimated New-Keynesian model with trend inflation and no indexation based on Christiano, Eichenbaum and Evans (2005). First, our simulations confirm Coibion and Gorodnichenko's (2011) main finding. Second, we show that a trend inflation-immune Taylor rule based on economic theory can avoid indeterminacy even at high levels of trend inflation such as those ...
Working Paper
Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications
In this paper, we develop algorithms to independently draw from a family of conjugate posterior distributions over the structural parameterization when sign and zero restrictions are used to identify SVARs. We call this family of conjugate posterior distributions normal-generalized-normal. Our algorithms draw from a conjugate uniform-normal-inverse-Wishart posterior over the orthogonal reduced-form parameterization and transform the draws into the structural parameterization; this transformation induces a normal-generalized-normal posterior distribution over the structural parameterization. ...
Working Paper
Inference Based on Time-Varying SVARs Identified with Sign Restrictions
We propose an approach for Bayesian inference in time-varying SVARs identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of orthogonal matrices given the reduced-form ...
Working Paper
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs
We develop a new algorithm for inference based on structural vector autoregressions (SVARs) identified with sign restrictions. The key insight of our algorithm is to break from the accept-reject tradition associated with sign-identified SVARs. We show that embedding an elliptical slice sampling within a Gibbs sampler approach can deliver dramatic gains in speed and turn previously infeasible applications into feasible ones. We provide a tractable example to illustrate the power of the elliptical slice sampling applied to sign-identified SVARs. We demonstrate the usefulness of our algorithm by ...
Journal Article
Breaking Down the Latest Fight Against Inflation
We apply a novel empirical approach to understand the role monetary policy played in post-COVID inflation.
Working Paper
Inference Based On Time-Varying SVARs Identified with Time Restrictions
We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of ...