I propose a method to estimate cyclical DSGE models using the raw data. The approach links the observables to the model counterparts via a ‡exible speci…cation which does not require that the cyclical component is solely located at business cycle frequencies and allows the noncyclical component to take various time series patterns. Applying standard data transformation induces distortions in st...

In this paper we develop new Markov chain Monte Carlo schemes for the estimation of Bayesian models. One key feature of our method, which we call the tailored randomized block Metropolis-Hastings (TaRB-MH) method, is the random clustering of the parameters at every iteration into an arbitrary number of blocks. Then each block is sequentially updated through an M-H step. Another feature is that ...

The relation between macroeconomic fundamentals and the cross section of asset returns is studied through the lens of dynamic stochastic general equilibrium (DSGE) models. We provide a full-information Bayesian estimation of the model using seven macroeconomic variables and extract the time series of three fundamental shocks to the economy for the period of 1966Q1-2010Q3: neutral technology (NT...

This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and proposes a new algorithm that correctly applies the procedure proposed by Kim, Shephard, and Chib (1998) to the estimation of VAR or DSGE models with stochastic volatility. Relative to Primiceri (2005), the correct algorithm involves a different ordering of...

Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of "economic theory" includes a broad range of examples, such as accounting identities, disaggregation and spatial restrictions when forecasting aggregate variables, cointegration and forecasting with Dynamic Sto...