The stochastic error distance (SED) introduced by Diebold & Shin (2017) ranks forecast models by divergence between distributions of the errors of the actual and prefect forecast models. The basic SED is defined by the variation distance and provides a representation of the mean absolute error,...

This paper employs econometric tests of rational bubbles to identify housing bubbles, especially during the COVID-19 pandemic. It then examines monetary policy impacts on housing bubbles through a hierarchical Bayesian framework. The S&P/Case-Shiller U.S. national home price adjusted by rental...

This paper shows that CEO tweets contain informational content on the U.S. stock markets and provide investors with value-relevant information on predicting the stock price movement. We create a large, unique sample of CEO users on Twitter, extract hashtags and sentiments that can be used as...

"Conventional VAR estimation and forecasting ignores the fact that economic data are often subject to revision many months or years after their initial release. This paper shows how VAR analysis can be modified to account for such revisions. The proposed approach assumes that government...

Using state-space modeling, we extract information from surveys of long-term inflation expectations and multiple quarterly inflation series to undertake a real-time decomposition of quarterly headline PCE and GDP-deflator inflation rates into a common long-term trend, common cyclical component,...