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.

Additional Metadata
Keywords pre-whitening, Principal component regression, spurious regressions
JEL Model Evaluation and Testing (jel C52)
Persistent URL dx.doi.org/10.1080/13504851.2018.1433292, hdl.handle.net/1765/104559
Series Econometric Institute Reprint Series
Journal Applied Economics Letters
Citation
Franses, Ph.H.B.F, & Janssens, E. (2018). Spurious principal components. Applied Economics Letters, 26(1), 37–39. doi:10.1080/13504851.2018.1433292