Evaluating Point and Density Forecasts of DSGE Models

Evaluating density forecasts: a comment

Posterior Predictive Analysis for Evaluating DSGE Models

In this paper, we develop and apply certain tools to evaluate the strengths and weaknesses of dynamic stochastic general equilibrium (DSGE) models. In particular, this paper makes three contributions: One, it argues the need for such tools to evaluate the usefulness of the these models; two, it defines these tools which take the form of prior and particularly posterior predictive analysis and p...

Evaluating Density Forecasts via the Copula Approach

In this paper, we develop parametric tests for the correct density forecasts. Similar to Berkowitz (2001), we construct our tests by nesting a series of i.i.d. uniform random variables in a class of stationary Markov processes. Unlike Berkowitz (2001), the class of Markov processes in this paper is constructed via the copula approach, which allows the separate modeling of the marginal distribut...

Evaluating DSGE Models for Monetary and Fiscal Policy Analysis

This paper evaluates the suitability of current DSGE models for monetary policy analysis from a Bayesian perspective, recognizing that these models may be useful even if they are misspecified along some dimensions, using the framework laid out in Faust and Gupta (2009). The paper argues that practical monetary policy analysis deals with determining how intended policy should be revised in light...

Evaluating the Forecasts of Risk Models

The forecast evaluation literature has traditionally focused on methods for assessing point-forecasts. However, in the context of risk models, interest centers on more than just a single point of the forecast distribution. For example, value-at-risk (VaR) models which are currently in extremely wide use form interval forecasts. Many other important financial calculations also involve estimates ...