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  • Pavlidis_etal2018_Blinded

    Rights statement: This is the author’s version of a work that was accepted for publication in Economic Modelling. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Economic Modelling, 80, 2018 DOI: 10.1016/j.econmod.2018.07.021

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Detecting Periods of Exuberance: A Look at the Role of Aggregation with an Application to House Prices

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<mark>Journal publication date</mark>1/08/2019
<mark>Journal</mark>Economic Modelling
Volume80
Number of pages16
Pages (from-to)87-102
Publication StatusPublished
Early online date10/08/18
<mark>Original language</mark>English

Abstract

The recently developed SADF and GSADF unit root tests of Phillips and Yu (2011) and Phillips et al. (2015a,b) have become popular in the literature for detecting exuberance in asset prices. In this paper, we examine through simulation experiments the effect of cross-sectional aggregation on the power properties of these tests. The simulation design considered is based on simulated data and actual housing data for both U.S. metropolitan areas and international housing markets and thus allows us to draw conclusions for different levels of aggregation. Our findings suggest that aggregation lowers the power of both the SADF and GSADF tests. The effect, however, is much larger for the SADF test. We also provide evidence that tests based on panel data techniques, namely the panel GSADF test recently proposed by Pavlidis et al. (2016), can perform substantially better than univariate tests applied to aggregated series. Furthermore, we also illustrate the date-stamping procedure under the univariate/panel GSADF procedure uncovering novel evidence on the role of interest rates and policy uncertainty as factors explaining episodes of widespread mildly explosive dynamics in housing markets.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Economic Modelling. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Economic Modelling, 80, 2018 DOI: 10.1016/j.econmod.2018.07.021