The Phantom Menace: Omitted Variable Bias in Econometric Research

Clarke, Kevin A.

doi:10.1080/07388940500339183

Cited by 485Advanced Causal Inference TechniquesPolitical Science Research and EducationSpatial and Panel Data Analysis

The Phantom Menace: Omitted Variable Bias in Econometric Research

Clarke, Kevin A.·2005·Conflict Management and Peace Science

DOI 10.1080/07388940500339183

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Abstract

Quantitative political science is awash in control variables. The justification for these bloated specifications is usually the fear of omitted variable bias. A key underlying assumption is that the danger posed by omitted variable bias can be ameliorated by the inclusion of relevant control variables. Unfortunately, as this article demonstrates, there is nothing in the mathematics of regression analysis that supports this conclusion. The inclusion of additional control variables may increase or decrease the bias, and we cannot know for sure which is the case in any particular situation. A brief discussion of alternative strategies for achieving experimental control follows the main result.

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Determining which combination(s) of variables to blind is non-trivial.
“Yet, determining which combination(s) of variables to blind is non-trivial and the risk of omitted variable bias should not be downplayed [71,160].”
From Fairness in machine learning: A survey (2024) · cites this paper as [71]
The risk of omitted variable bias should not be downplayed.
“Yet, determining which combination(s) of variables to blind is non-trivial and the risk of omitted variable bias should not be downplayed [71,160].”
From Fairness in machine learning: A survey (2024) · cites this paper as [71]

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Authors: Clarke, K. A.
Affiliations: University of Rochester (US)
Corresponding author: Clarke, Kevin A.
ORCID: Clarke, Kevin A.
Venue: Conflict Management and Peace Science
Publisher: SAGE Publications
Published: 2005-09
Volume: 22
Issue: 4
Pages: 341-352
ISSN: 0738-8942 (ISSN-L)
1549-9219
DOI: 10.1080/07388940500339183
OpenAlex: W2146807455
Cited by: 484
References: 42
Citations by year: 2026: 8 · 2025: 22 · 2024: 23 · 2023: 24 · 2022: 33 · 2021: 28 · 2020: 58 · 2019: 23 · 2018: 30 · 2017: 26 · 2016: 32 · 2015: 25 · 2014: 26 · 2013: 24 · 2012: 32
FWCI: 11.74
Type: journal article
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Conflict Management and Peace Science (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Social Sciences › Political Science and International Relations › Political Science Research and Education
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Keywords: omitted variable bias, control variables, regression analysis, specification bias, experimental control, econometric methodology, political science research

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