Search Results
Showing results 1 to 10 of approximately 21.
(refine search)
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 ...
Working Paper
The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes
We assess the causal impact of epidemic-induced lockdowns on health and macroeconomic outcomes and measure the trade-off between containing the spread of an epidemic and economic activity. To do so, we estimate an epidemiological model with time-varying parameters and use its output as information for estimating SVARs and LPs that quantify the causal effects of nonpharmaceutical policy interventions. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. We find that additional government mandated mobility curtailments would have reduced deaths at a very small cost in ...
Working Paper
The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure
Following Leeper, Sims, and Zha (1996), we identify monetary policy shocks in SVARs by restricting the systematic component of monetary policy. In particular, we impose sign and zero restrictions only on the monetary policy equation. Since we do not restrict the response of output to a monetary policy shock, we are agnostic in Uhlig's (2005) sense. But, in contrast to Uhlig (2005), our results support the conventional view that a monetary policy shock leads to a decline in output. Hence, our results show that the contractionary effects of monetary policy shocks do not hinge on questionable ...
Working Paper
POSITIVE TREND INFLATION AND DETERMINACY IN A MEDIUM-SIZED NEW KEYNESIAN MODEL
This paper studies the challenge that increasing the inflation target poses to equilibrium determinacy in a medium-sized New Keynesian model without indexation fitted to the Great Moderation era. For moderate targets of the inflation rate, such as 2 or 4 percent, the probability of determinacy is near one conditional on the monetary policy rule of the estimated model. However, this probability drops significantly conditional on model-free estimates of the monetary policy rule based on real-time data. The difference is driven by the larger response of the federal funds rate to the output gap ...
Working Paper
Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs
We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. Our estimated time-varying-parameters SIRD model ...
Working Paper
Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications
Are optimism shocks an important source of business cycle fluctuations? Are deficit-financed tax cuts better than deficit-financed spending to increase output? These questions have been previously studied using SVARs identified with sign and zero restrictions and the answers have been positive and definite in both cases. While the identification of SVARs with sign and zero restrictions is theoretically attractive because it allows the researcher to remain agnostic with respect to the responses of the key variables of interest, we show that current implementation of these techniques does not ...
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 ...
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 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 ...