On Standard-Error-Decreasing Complementarity: Why Collinearity is Not the Whole Story
MAGKS No. 03-2017
18 Pages Posted: 25 Feb 2017
Date Written: January 9, 2017
There is a widespread belief among economists that adding additional variables to a regression model causes higher standard errors. This note shows that, in general, this belief is unfounded and that the impact of adding variables on coefficients’ standard errors is unclear. The concept of standard-error-decreasing complementarity is introduced, which works against the collinearity-induced increase in standard errors. How standard-error-decreasing complementarity works is illustrated with the help of a nontechnical heuristic, and, using an example based on artificial data, it is shown that the outcome of popular econometric approaches can be potentially misleading.
Keywords: Standard-error-decreasing complementarity, multivariate regression model, standard error, econometric methodology, multicollinearity, collinearity
JEL Classification: C1, B4
Suggested Citation: Suggested Citation