Publication Type

Journal Article

Version

Publisher’s Version

Publication Date

11-2011

Abstract

A new recursive regression methodology is introduced to analyze the bubble characteristics of various financial time series during the subprime crisis. The methods modify a technique proposed in Phillips, Wu, and Yu (2011) and provide a technology for identifying bubble behavior with consistent dating of their origination and collapse. The tests serve as an early warning diagnostic of bubble activity and a new procedure is introduced for testing bubble migration across markets. Three relevant financial series are investigated, including a financial asset price (a house price index), a commodity price (the crude oil price), and one bond price (the spread between Baa and Aaa). Statistically significant bubble characteristics are found in all of these series. The empirical estimates of the origination and collapse dates suggest a migration mechanism among the financial variables. A bubble emerged in the real estate market in February 2002. After the subprime crisis erupted in 2007, the phenomenon migrated selectively into the commodity market and the bond market, creating bubbles which subsequently burst at the end of 2008, just as the effects on the real economy and economic growth became manifest. Our empirical estimates of the origination and collapse dates and tests of migration across markets match well with the general dateline of the crisis put forward in the recent study by Caballero, Farhi, and Gourinchas (2008a).

Keywords

Financial bubbles, crashes, date stamping, explosive behavior, migration, mildly explosive process, subprime crisis, timeline

Discipline

Econometrics | Economics | Finance

Research Areas

Econometrics

Publication

Quantitative Economics

Volume

2

Issue

3

First Page

455

Last Page

491

ISSN

1759-7331

Identifier

10.3982/QE82

Publisher

Wiley

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.3982/QE82

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