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Testing for Speculative Bubbles in Large Dimensional Financial Panel Data Sets

  • Date 2017-08-15 (Tue)
  • Time 02:30 PM
  • Venue Conference Room B110
  • Presider Professor Wen-Jen Tsay
  • Speaker Professor Yohei Yamamoto
  • Background Professor Yamamoto received his Ph.D. from Boston University in 2009. He is currently a Professor of Economics at Hitotsubashi University. His research interests include econometrics, applied econometrics for macroeconomics and finance.
  • Abstract Towards the 2007-2008 financial crisis, speculative bubbles prevailed in various financial assets. Whether these bubbles are an economy-wide phenomenon or market-specific events is an important question. This study develops a testing approach to investigate whether the bubbles lie in the common or in the idiosyncratic components of large-dimensional financial panel data sets. To this end, we extend the right-tailed unit root tests to common factor models, benchmarking the panel analysis of non-stationarity in idiosyncratic and common component (PANIC) proposed by Bai and Ng (2004). We find that when the PANIC test is applied to the explosive alternative hypothesis as opposed to the stationary alternative hypothesis, the test for the idiosyncratic component may suffer from the nonmonotonic power problem. This paper proposes a new cross-sectional (CS) approach to disentangle the common and idiosyncratic components in a relatively short explosive window. This method first estimates the factor loadings in the training sample and then uses them in cross-sectional regressions to extract the common factors in the explosive window. A Monte Carlo simulation shows that the CS approach is robust to the nonmonotonic power problem. We provide an empirical example using house price indexes of the U.S.'s 50 largest metropolitan areas.