This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this single hierarchical Bayes formulation....

This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic (linear and nonlinear) VARs. The performance...

I generate priors for a VAR from four competing models of economic fluctuations: a standard RBC model, Fisher’s (2006) investment-specific technology shocks model, an RBC model with capital adjustment costs and habit formation, and a sticky price model with an unaccommodating monetary...

This paper develops and estimates a dynamic stochastic general equilibrium model of a closed economy which provides a quantitative description of the monetary transmission mechanism, yields a mutually consistent set of indicators of inflationary pressure together with confidence intervals, and...

This paper develops and estimates a dynamic stochastic general equilibrium model of a closed economy which approximately accounts for the empirical evidence concerning the monetary transmission mechanism, as summarized by impulse response functions derived from an estimated structural vector...

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the...

In this paper I assess the ability of Bayesian vector autoregressions (BVARs) and dynamic stochastic general equilibrium (DSGE) models of different size to forecast comovements of major macroeconomic series in the euro area. Both approaches are compared to unrestricted VARs in terms of...

Using Bayesian maximum likelihood and data for Portugal, I estimate a New Keynesian DSGE model allowing for the presence of non-Ricardian households and test the stability of the model's prediction when the fraction of liquidity-constrained households changes. In particular, I assess the impacts...

In this paper we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also...

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this...