On Standard-Error-Decreasing Complementarity: Why Collinearity is Not the Whole Story

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-...

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书目详细资料
发表在:MAGKS - Joint Discussion Paper Series in Economics (Band 03-2017)
主要作者: Hayo, Bernd
格式: 文件
语言:英语
出版: Philipps-Universität Marburg 2017
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总结: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.
实物描述:18 Seiten
ISSN:1867-3678
DOI:10.17192/es2024.0462