While forecasting is a common practice in academia, government and business alike, practitioners are often left wondering how to choose the sample for estimating forecasting models. When we forecast in ation in 2014, for example, should we use the last 30 years of data or the last 10 years of...

We propose new methods for evaluating predictive densities in an environment where the estimation error of the parameters used to construct the densities is preserved asymptotically under the null hypothesis. The tests offer a simple way to evaluate the correct specification of predictive...

This paper studies empirical facts regarding the effects of unexpected changes in aggregate macroeconomic fiscal policies on consumers that are allowed to differ depending on their individual characteristics. We use data from the Consumption Expenditure Survey (CEX) to estimate individual-level...

The Great Recession has challenged the adequacy of existing models to explain key macroeconomic data, and raised the concern that the models might be misspecified. This paper investigates the importance of misspecification in structural models using a novel approach to detect and identify the...

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

This review provides an overview of forecasting methods that can help researchers forecast in the presence of non-stationarities caused by instabilities. The emphasis of the review is both theoretical and applied, and provides several examples of interest to economists. We show that modeling...

The Great Recession of 2007:IV-2009:II sparked great interest in understanding uncertainty and its effects on the macroeconomy. This paper introduces a new approach to measure uncertainty. We start from the same premise as in Jurado et al. (2014), that is: "What matters for economic decision...

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. We show that the tests...

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known that exchange rate fluctuations are very difficult to predict using economic models, and that a random walk forecasts exchange rates...

We evaluate conditional predictive densities for U.S. output growth and inflation using a number of commonly used forecasting models that rely on a large number of macroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used...