We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of...

Standard present-value models suggest that exchange rates are driven by expected future fundamentals, implying that exchange rates contain information about future fundamentals. We test this key empirical prediction of present-value models in a sample of 35 currency pairs ranging from 1900 to...

Much has been written about why economists failed to predict the latest financial and real crisis. Reading the recent literature, it seems that the crisis was so obvious that economists must have been blind when looking at data not to see it coming. In this paper, we illustrate this failure by...

Prediction markets--markets used to forecast future events--have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by...

This paper develops a method for producing current-quarter forecasts of GDP growth with a (possibly large) range of available within-the-quarter monthly observations of economic indicators, such as employment and industrial production, and financial indicators, such as stock prices and interest...

This paper introduces a new regression model - Markov-switching mixed data sampling (MS-MIDAS) - that incorporates regime changes in the parameters of the mixed data sampling (MIDAS) models and allows for the use of mixed-frequency data in Markov-switching models. After a discussion of...