This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and efficiency tests, commonly referred to as tests of forecast rationality. Our framework is general: it can be applied to...

We evaluate various models' relative performance in forecasting future US output growth and inflation on a monthly basis. Our approach takes into account the possibility that the models' relative performance can be varying over time. We show that the models' relative performance has, in fact,...

We propose a new methodology to identify the sources of models’ forecasting performance. The methodology decomposes the models’ forecasting performance into asymptotically uncorrelated components that measure instabilities in the forecasting performance, predictive content, and over-fitting....

The forecasting literature has identi ed two important issues: (i) several predictors have substantial and statistically signi cant predictive content, although only sporadically, and it is unclear whether this predictive content can be exploited reliably; (ii) in-sample predictive content does...

This paper analyzes the importance of monetary and fiscal policy shocks in explaining US macroeconomic fluctuations, and establishes new stylized facts. The novelty of our empirical analysis is that we jointly consider both monetary and fiscal policy, whereas the existing literature only focuses...

The goal of this paper is to develop formal techniques for analyzing the relative in-sample performance of two competing, misspecified 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...

We propose new information criteria for impulse response function matching estimators (IRFMEs). These estimators yield sampling distributions of the structural parameters of dynamic stochastic general equilibrium (DSGE) models by minimizing the distance between sample and theoretical impulse...

In this paper we propose a chi-square test for identification. Our proposed test statistic is based on the distance between two shrinkage extremum estimators. The two estimators converge in probability to the same limit when identification is strong, and their asymptotic distributions are...

This paper demonstrates that quot;commodity currencyquot; exchange rates have remarkably robust power in predicting future global commodity prices, both in sample and out-of-sample. A critical element of our in-sample approach is to allow for structural breaks, endemic to empirical exchange rate...