We develop a general framework for analyzing the usefulness of imposing parameter restrictions on a forecasting model. We propose a measure of the usefulness of the restrictions that depends on the forecaster's loss function and that could be time varying. We show how to conduct inference about...

This chapter reviews the literature on the econometric relationship between DSGE and VAR models from the point of view of estimation and model validation. The mapping between DSGE and VAR models is broken down into three stages: 1) from DSGE to state-space model; 2) from state-space model to VAR...

The goal of this paper is to develop formal tests to evaluate the relative in-sample performance of two competing, misspeciÂ…ed non-nested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global...

We propose new methods for comparing the out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative local forecasting performance for the two models, and to investigate its stability over time by...

We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...

The dynamic behaviour of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations are accurate predictors of yields, but only...

We propose a method for conducting inference on impulse responses in structural vector autoregressions (SVARs) when the impulse response is not point identified because the number of equality restrictions one can credibly impose is not sufficient for point identification and/or one imposes sign...

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...

This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set‐identified models by adopting a multiple‐prior (robust) Bayesian approach. We propose new tools for Bayesian inference in set‐identified models and show that they have a well‐defined...

In this paper we compare the relative efficiency of different methods of forecasting the aggregate of spatially correlated variables. Small sample simulations confirm the asymptotic result that improved forecasting performance can be obtained by imposing a priori constraints on the amount of...