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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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Detecting Periods of Exuberance
T2 - A Look at the Role of Aggregation with an Application to House Prices
AU - Pavlidis, Efthymios
AU - Martínez-García, Enrique
AU - Grossman, Valerie
N1 - 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
PY - 2019/8/1
Y1 - 2019/8/1
N2 - 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.
AB - 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.
KW - Aggregation
KW - Mildly explosive time series
KW - Right-tailed unit-root tests
KW - Sup ADF (SADF) test
KW - Generalized sup ADF (GSADF) test
KW - House prices
U2 - 10.1016/j.econmod.2018.07.021
DO - 10.1016/j.econmod.2018.07.021
M3 - Journal article
VL - 80
SP - 87
EP - 102
JO - Economic Modelling
JF - Economic Modelling
SN - 0264-9993
ER -