Spurious Factor Analysis
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Onatskiy, A., & Wang, C. (2021). Spurious Factor Analysis. Econometrica, 89 (2), 591-614. https://doi.org/10.3982/ECTA16703
This paper draws parallels between the Principal Components Analysis of factorless high-dimensional nonstationary data and the classical spurious regression. We show that a few of the principal components of such data absorb nearly all the data variation. The corresponding scree plot suggests that the data contain a few factors, which is collaborated by the standard panel information criteria. Furthermore, the Dickey-Fuller tests of the unit root hypothesis applied to the estimated \textquotedblleft idiosyncratic terms\textquotedblright\ often reject, creating an impression that a few factors are responsible for most of the non-stationarity in the data. We warn empirical researchers of these peculiar effects and suggest to always compare the analysis in levels with that in differences.
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External DOI: https://doi.org/10.3982/ECTA16703
This record's URL: https://www.repository.cam.ac.uk/handle/1810/307277
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