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SMU SOE Seminar (Apr 5, 2019): Spurious Factor Analysis
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TOPIC:
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SPURIOUS FACTOR ANALYSIS
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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 princpal components of such data absorbs nearly all the data variation. The corresponding scree plot suggests that the data contains 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.
Click here to view the CV.
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PRESENTER
Alexey Onatskiy
University of Cambridge
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RESEARCH FIELDS
Econometrics
Statistics
Factor Models
Large Random Matrices
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DATE:
5 April 2019 (Friday)
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TIME:
4pm - 5.30pm
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VENUE:
Meeting Room 5.1, Level 5
School of Economics
Singapore Management University
90 Stamford Road
Singapore 178903
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