Search Results
Working Paper
Inference in Bayesian Proxy-SVARs
Motivated by the increasing use of external instruments to identify structural vector autoregressions SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often ...
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.
Journal Article
Tracking Business Conditions in Delaware
To meet the need for a gauge of current regional conditions at high frequency, we have built a real-time daily index to monitor business conditions in Delaware. What are the current conditions in the First State? How have these conditions evolved since the 1990s?
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 in Bayesian Proxy-SVARs
Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often ...
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
Alternative Strategies: How Do They Work? How Might They Help?
Several structural developments in the U.S. economy—including lower neutral interest rates and a flatter Phillips curve—have challenged the ability of the current monetary policy framework to deliver on the Federal Open Market Committee’s (FOMC) dual-mandate goals. This paper explores whether makeup strategies, in which policymakers seek to stabilize average inflation around the inflation target over some horizon, could strengthen the FOMC’s ability to fulfill its dual mandate. The quantitative analysis discussed here suggests that credible makeup strategies may provide some moderate ...
Working Paper
Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models
We document five novel empirical findings on the well-known potential ordering drawback associated with the time-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP-SV. First, the ordering does not affect point prediction. Second, the standard deviation of the predictive densities implied by different orderings can differ substantially. Third, the average length of the prediction intervals is also sensitive to the ordering. Fourth, the best ordering for one variable in terms of log-predictive scores does not ...
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 ...
Journal Article
The Economic Effects of Changes in Personal Income Tax Rates
We apply an empirical perspective to understand the macroeconomic consequences of changes in personal income taxes.