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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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| Publicado en: | MAGKS - Joint Discussion Paper Series in Economics (Band 03-2017) |
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| Autor principal: | |
| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
Philipps-Universität Marburg
2017
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| Materias: | |
| Acceso en línea: | Texto Completo PDF |
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| Sumario: | 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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| Descripción Física: | 18 Seiten |
| ISSN: | 1867-3678 |
| DOI: | 10.17192/es2024.0462 |