Econometrica: Mar 2021, Volume 89, Issue 2

Spurious Factor Analysis

https://doi.org/10.3982/ECTA16703
p. 591-614

Alexei Onatski, Chen Wang

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 corroborated by the standard panel information criteria. Furthermore, the Dickey–Fuller tests of the unit root hypothesis applied to the estimated “idiosyncratic terms” often reject, creating an impression that a few factors are responsible for most of the nonstationarity 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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Supplement to "Spurious Factor Analysis"

This note contains supplementary material for Onatski and Wang (2019) (OW in what follows). It is lined up with sections in the main text to make it easy to locate the required proofs.

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