Publikationsserver der Universitätsbibliothek Marburg

Titel:On Standard-Error-Decreasing Complementarity: Why Collinearity is Not the Whole Story
Autor:Hayo, Bernd
Veröffentlicht:2017
URI:https://archiv.ub.uni-marburg.de/es/2024/0462
DOI: https://doi.org/10.17192/es2024.0462
ISSN: 1867-3678
DDC:330 Wirtschaft
Publikationsdatum:2024-01-19
Lizenz:https://creativecommons.org/publicdomain/mark/1.0

Dokument

Schlagwörter:
econometric methodology, collinearity, multivariate regression model, standard error, multicollinearity, Standard-error-decreasing complementarity

Summary:
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.


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