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...

We analyze fast procedures for conducting Monte Carlo experiments involving bootstrap estimators, providing formal results establishing the properties of these methods under general conditions.

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...

The goal of this paper is to develop formal techniques for analyzing the relative in-sample performance of two competing, misspeci?ed models in the presence of possible data instability. The central idea of our methodology is to propose a measure of the models? local relative performance: the...

This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook...

We consider a method for producing multivariate density forecasts that satisfy moment restrictions implied by economic theory, such as Euler conditions. The method starts from a base forecast that might not satisfy the theoretical restrictions and forces it to satisfy the moment conditions using...

We propose a method for modifying a given density forecast in a way that incorporates the information contained in theory-based moment conditions. An example is "improving" the forecasts from atheoretical econometric models, such as factor models or Bayesian VARs, by ensuring that they satisfy...

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...

We provide an extensive evaluation of the predictive performance of the US yield curve for US gross domestic product growth by using new tests for forecast breakdown, in addition to a variety of in-sample and out-of-sample evaluation procedures. Empirical research over the past decades has...