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-...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Publicado no:MAGKS - Joint Discussion Paper Series in Economics (Band 03-2017)
Autor principal: Hayo, Bernd
Formato: Artigo
Idioma:inglês
Publicado em: Philipps-Universität Marburg 2017
Assuntos:
Acesso em linha:Texto Completo em Formato PDF
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
Descrição
Resumo: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.
Descrição Física:18 Seiten
ISSN:1867-3678
DOI:10.17192/es2024.0462