Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
Conflict Management and Peace Science
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Clarke, K. A.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

The Phantom Menace: Omitted Variable Bias in Econometric Research

Kevin A. Clarke

Department of Political Science University of Rochester Rochester, New York, USA, kevin.clarke{at}rochester.edu

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.

Key Words: omitted variable bias • specification • control variables • research design

Conflict Management and Peace Science, Vol. 22, No. 4, 341-352 (2005)
DOI: 10.1080/07388940500339183
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 POLIT ANALHome page
S. Hug
The Effect of Misclassifications in Probit Models: Monte Carlo Simulations and Applications
Political Analysis, November 20, 2009; (2009) mpp033v1.
[Abstract] [Full Text] [PDF]

Home page
 Conflict Management and Peace ScienceHome page
K. A. Clarke
Return of the Phantom Menace: Omitted Variable Bias in Political Research
Conflict Management and Peace Science, February 1, 2009; 26(1): 46 - 66.
[Abstract] [PDF]

Home page
 Comparative Political StudiesHome page
J. S. Levy
Qualitative Methods and Cross-Method Dialogue in Political Science
Comparative Political Studies, February 1, 2007; 40(2): 196 - 214.
[Abstract] [PDF]

Home page
 Journal of Conflict ResolutionHome page
H. Hegre and N. Sambanis
Sensitivity Analysis of Empirical Results on Civil War Onset
Journal of Conflict Resolution, August 1, 2006; 50(4): 508 - 535.
[Abstract] [PDF]

Home page
 POLIT ANALHome page
G. Goertz
Introduction to the Special Issue "Causal Complexity and Qualitative Methods"
Political Analysis, July 1, 2006; 14(3): 223 - 226.
[Full Text] [PDF]

Home page
 POLIT ANALHome page
J. Mahoney and G. Goertz
A Tale of Two Cultures: Contrasting Quantitative and Qualitative Research
Political Analysis, July 1, 2006; 14(3): 227 - 249.
[Abstract] [Full Text] [PDF]