Testing for Explosive Bubbles in the Presence of Autocorrelated Innovations

37 Pages Posted: 14 Feb 2017 Last revised: 18 Jun 2020

Date Written: September 27, 2017

Abstract

We analyze an empirically important issue with recursive right-tailed unit root tests for bubbles
in asset prices. First, we show that serially correlated innovations, which is a feature that
is present in most financial series used to test for bubbles, can lead to severe size distortions
when using either fixed or automatic (based on information criteria) lag-length selection in
the auxiliary regressions underlying the test. Second, we propose a sieve-bootstrap version
of these tests and show that this results in tests which control size well across a number of
simulation designs both with and without highly autocorrelated innovations. We also find
that these improvements in size come at a relatively low cost for the power of the tests. Finally,
we apply the bootstrap tests on the housing market of OECD countries, and generally
find much weaker evidence of housing bubbles compared to existing evidence.

Keywords: Right-tailed unit root tests, GSADF, size and power properties, sieve bootstrap, international housing market

JEL Classification: C58, G12

Suggested Citation

Pedersen, Thomas Quistgaard and Schütte, Erik Christian Montes, Testing for Explosive Bubbles in the Presence of Autocorrelated Innovations (September 27, 2017). Journal of Empirical Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2916616 or http://dx.doi.org/10.2139/ssrn.2916616

Thomas Quistgaard Pedersen (Contact Author)

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Erik Christian Montes Schütte

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
382
Abstract Views
1,330
rank
97,258
PlumX Metrics