Document Type
Article
Publication Date
2019
Terms of Use & License Information
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Smith, Gary N. and Artigue, Heidi Margaret, "The Principal Problem with Principal Components Regression" (2019). Pomona Economics. 15.
https://scholarship.claremont.edu/pomona_fac_econ/15
Comments
Principal components regression (PCR) reduces a large number of explanatory variables in a regression model down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.