Spurious Principal Components
The Principal Component Regression 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.
|Keywords||Principal Component Regression, Pre-whitening, Spurious Regressions|
|JEL||Model Evaluation and Testing (jel C52)|
|Series||Econometric Institute Research Papers|
Franses, Ph.H.B.F, & Janssens, E. (2017). Spurious Principal Components (No. EI2017-31). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/102704