Spurious principal components

Philip Hans Franses and Eva Janssens

Applied Economics Letters, 2019, vol. 26, issue 1, 37-39

Abstract: The principal component regression (PCR) is often used to forecast macroeconomic variables when there are many predictors. In this letter, we argue that it makes sense to pre-whiten the predictors before including these in a PCR. With simulation experiments, we show that without such pre-whitening, spurious principal components can appear and that these can become spuriously significant in a PCR. With an illustration to annual inflation rates for five African countries, we show that non-spurious principal components can be genuinely relevant in empirical forecasting models.

Date: 2019
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Working Paper: Spurious Principal Components (2017)
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DOI: 10.1080/13504851.2018.1433292

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