Testing for explosive bubbles in the presence of autocorrelated innovations

Thomas Quistgaard Pedersen; Erik Christian Montes Schütte

doi:10.1016/j.jempfin.2020.06.002

Testing for explosive bubbles in the presence of autocorrelated innovations

Thomas Quistgaard Pedersen, Erik Christian Montes Schütte^*

^*Corresponding author for this work

Department of Economics and Business Economics - CREATES

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

13 Citations (Scopus)

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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.

Original language	English
Journal	Journal of Empirical Finance
Volume	58
Pages (from-to)	207-225
ISSN	0927-5398
DOIs	https://doi.org/10.1016/j.jempfin.2020.06.002
Publication status	Published - Sept 2020

Keywords

GSADF
International housing market
Right-tailed unit root tests
SADF
Sieve bootstrap
Size and power properties

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10.1016/j.jempfin.2020.06.002

TQP_ECMS_Testing_2020_AMAccepted manuscript, 1.35 MBLicence: CC BY-NC-ND

Cite this

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title = "Testing for explosive bubbles in the presence of autocorrelated innovations",

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.",

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N2 - 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.

AB - 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.

KW - GSADF

KW - International housing market

KW - Right-tailed unit root tests

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DO - 10.1016/j.jempfin.2020.06.002

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Testing for explosive bubbles in the presence of autocorrelated innovations

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Keywords

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