Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/162649
Authors: 
Hayo, Bernd
Year of Publication: 
2017
Series/Report no.: 
Joint Discussion Paper Series in Economics 03-2017
Abstract: 
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 collinearityinduced 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.
Subjects: 
standard-error-decreasing complementarity
multivariate regression model
standard error
econometric methodology
multicollinearity
collinearity
JEL: 
C1
B4
Document Type: 
Working Paper

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