Testing for financial bubbles in the presence of auto-correlated errors

Abstract

How to detect financial bubble? In response to this question, a vast amount of empirical research is devoted spanning almost half-century. However, identifying unambiguously the presence of a bubble in the financial time series remains an unsolved problem in standard econometric and financial economic approaches. In this paper, we study the impact of auto-correlated innovations, which is a most common feature of the financial time series, on recently developed unit root tests with varying lag to detect financial bubbles. We apply the more powerful test procedure to identify bubble on the quarterly observations of house price-rent ratios of 4 counties. The results of the study suggest that rolling Max Supremum Augmented Dickey-Fuller (MSADF) test as the best test procedure to detect financial bubbles in the future.