Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/288529 
Year of Publication: 
2020
Citation: 
[Journal:] KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie [ISSN:] 1861-891X [Volume:] 72 [Issue:] 2 [Publisher:] Springer Fachmedien Wiesbaden [Place:] Wiesbaden [Year:] 2020 [Pages:] 289-299
Publisher: 
Springer Fachmedien Wiesbaden, Wiesbaden
Abstract: 
With the broader availability of panel data, fixed effects (FE) regression models are becoming increasingly important in sociology. However, in some studies the potential pitfalls of these models may be ignored, and common critiques of FE models may not always be applicable in comparison to other methods. This article provides an overview of linear FE models and their pitfalls for applied researchers. Throughout the article, we contrast FE and classical pooled ordinary least squares (OLS) models. We argue that in most cases FE models are at least as good as pooled OLS models. Therefore, we encourage scholars to use FE models if possible. Nevertheless, the limitations of FE models should be known and considered.
Subjects: 
Fixed effects
Quantitative methods
Causality
Panel data
Exogeneity
Fixed effects
Quantitative Methoden
Kausalität
Paneldaten
Exogenität
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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