Abstract Exchange rates have raised the ire of economists for more than 20 years. A problem is that there appears to be no exchange rate model that systematically beats a naive random walk in out of sample forecasts. Economists also find it irksome that theoretical models are unable to explain short-, medium-, and long-run exchange rate movements. Engel and West (2005) show that these failures ...

Tractable Latent State Filtering for Non-Linear DSGE Models Using a Second-Order Approximation* This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a statespace representation of the second-order solution based on the ‘pruning’ ...

Stylized facts on U.S. output and interest rates have so far proved hard to match with simple DSGE models. I estimate covariances between output, nominal and real interest rate conditional on structural shocks, since such evidence has largely been lacking in previous discussions of the output-interest rate puzzle. Conditional on shocks to technology and monetary policy, the results square with ...

Rational expectations solutions are usually derived by assuming that all state variables relevant to forward-looking behaviour are directly observable, or that they are "...an invertible function of observables" (Mehra and Prescott, 1980). Using a framework that nests linearised DSGE models, we give a number of results useful for the analysis of linear rational expectations models with restrict...

Deep downturns • The world has been plagued by episodic deep downturns • 2008 crisis most recent • In spite of alleged " better " knowledge of economic system, and belief among many that we had put economic fluctuations behind us • Evidence is belief in those models may have contributed to crisis • Ideas about Great Moderation, ability of economy through diversification to effectively eliminate...

This paper estimates the parameters of a stylized dynamic stochastic general equilibrium model using maximum likelihood and Bayesian methods, paying special attention to the issue of weak parameter identification. Given the model and the available data, the posterior estimates of the weakly identified parameters are very sensitive to the choice of priors. We provide a set of tools to diagnose w...

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with occasionally-binding constraint. The functional form of the allows us derive a conditionally optimal particle filter (COPF) evaluation likelihood function exploits structure solution. document accuracy approximation embed it into Markov chain Monte Carlo conduct Bayesian...