Much of the US inflation forecasting literature deals with examining the ability of macroeconomic indicators to predict the mean of future inflation, and the overwhelming evidence suggests that the macroeconomic indicators provide little or no predictability. In this paper, we expand the scope...

The interest in density forecasts (as opposed to solely modeling the conditional mean) arises from the possibility of dynamics in higher moments of a time series as well as, in some applications, the interest in forecasting the probability of future events. By combining the idea of Markov...

We use a large data set of over 12 million residential mortgages observed over time to investigate the loan default behavior in several European countries. We model the occurrence of default as a function of borrower characteristics, loan-specific variables, and a set of local economic...

The goal of this paper is to evaluate the informational content of sentiment extracted from news articles about the state of the economy. We propose a Fine-Grained Aspect-based Sentiment analysis that has two main characteristics: 1) we consider only the text in the article that is semantically...

I evaluate whether expectations of professional forecasters are consistent with the property of Bayesian learning that the expected uncertainty of a fixed target forecast should decline with the horizon. I obtain a measure of individual uncertainty from the density forecasts of the Survey of...

The aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a...

In this paper we estimate a simple Bayesian learning model to expectations data from the Survey of Professional Forecasters. We reformulate the model in terms of forecast revisions, which allows to abstract from differences in priors and to focus the analysis on the relationship between...