Spurious Factor Analysis

Alexei Onatski (ao319@cam.ac.uk) and Chen Wang

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: 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 “idiosyncratic terms” 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.

Keywords: Spurious regression; principal components; factor models; Karhunen-Loève expansion. (search for similar items in EconPapers)
Date: 2020-01-13
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: ao319
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Citations: View citations in EconPapers (3)

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Journal Article: Spurious Factor Analysis (2021)
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