arXiv 20 May 2020 · Econometrics · 21 citations (OpenAlex)
arXiv:2005.10314 · PDF · DOI · OpenAlex · Extracted main text
Control variables are included in regression analyses to estimate the causal effect of a treatment on an outcome. In this paper, we argue that the estimated effect sizes of controls are unlikely to have a causal interpretation themselves, though. This is because even valid controls are possibly endogenous and represent a combination of several different causal mechanisms operating jointly on the outcome, which is hard to interpret theoretically. Therefore, we recommend refraining from interpreting marginal effects of controls and focusing on the main variables of interest, for which a plausible identification argument can be established. To prevent erroneous managerial or policy implications, coefficients of control variables should be clearly marked as not having a causal interpretation or omitted from regression tables altogether. Moreover, we advise against using control variable estimates for subsequent theory building and meta-analyses.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Cinelli, Carlos, Forney, Andrew, Pearl, Judea (2022) A crash course in good and bad controls | 0.928 | 4 | 3 | 100% |
| 2 | Becker, Thomas E (2005) Potential Problems in the Statistical Control of Variables in Organizational Research: A Qualitative Analysis With Recommendations | 0.874 | 5 | 2 | 100% |
| 3 | Atinc, Guclu, Simmering, Marcia J., Kroll, Mark J (2012) Control Variable Use and Reporting in Macro and Micro Management Research | 0.811 | 4 | 2 | 100% |
| 4 | Pearl, Judea (2000) Causality: Models, Reasoning, and Inference | 0.811 | 4 | 2 | 100% |
| 5 | Azoulay, Pierre, Greenblatt, Wesley H., Heggeness, Misty L (2021) Long-term effects from early exposure to research: Evidence from the NIH “Yellow Berets” | 0.737 | 3 | 2 | 100% |
| 6 | Carlson, Kevin D., Wu, Jinpei (2012) The Illusion of Statistical Control: Control Variable Practice in Management Research | 0.737 | 3 | 2 | 100% |
| 7 | Spector, Paul E., Brannick, Michael T (2011) Methodological Urban Legends: The Misuse of Statistical Control Variables | 0.737 | 3 | 2 | 100% |
| 8 | Aguinis, Herman, Pierce, Charles A., Bosco, Frank A., Dalton, Dan R.… (2010) Debunking Myths and Urban Legends About Meta-Analysis | 0.644 | 2 | 2 | 100% |
| 9 | Durand, R., Vaara, E (2009) Causation, counterfactuals, and competitive advantage | 0.644 | 2 | 2 | 100% |
| 10 | Frölich, Markus (2008) Parametric and nonparametricregression in the presence of endogenous control Variables | 0.644 | 2 | 2 | 100% |
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