The Real-Time Predictive Content of Asset Price Bubbles for Macro Forecasts

Abstract

This paper contributes to the debate of whether central banks can lean against the wind of emerging stock or house price bubbles. Against this background, the paper evaluates if new advances in real-time bubble detection, as brought forward by Phillips et al. (2011), can timely detect bubble emergences and collapses. Building on simulations, the paper shows that the detection capabilities of all indicators are sensitive to their exact specifications and to the characteristics of the bubbles in the sample. Therefore, the paper suggests a combination approach of different bubble indicators which helps to account for the uncertainty around start and end dates of asset price bubbles. Additionally, the paper then investigates if the individual and combination indicators carry predictive content for inflation and output growth when the real-time availability of all variables is taken into account. It finds that a combination indicator is best suited to uncover the most common stock and house price bubbles in the U.S. and shows that this indicator improves output forecasts.