Controlling for endogeneity with instrumental variables in strategic management research
Open accessAbstract
This article offers a framework to understand how endogeneity arises and how to control for it with instrumental variables to estimate causal relations with observational data. It builds on the state-of-the-art research in applied and theoretical econometrics to highlight the importance of endogeneity and review the methods that can be used to address it with instrumental variables.The article also discusses when the Heckman two-step procedure can be used, as well as the tests, methods and assumptions that researchers should check when using instrumental variables.To ease implementation of the instrumental variables techniques, the author offers the STATA commands of the exposed tests and methods. Further, an empirical example is provided along with the utilized STATA codes. In the end, this article serves as a`toolkit' allowing scholars not only to understand whether endogeneity is present in their empirical setting, but also to assess the empirical validity of their work when using instrumental variables.
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Self-selection could bias results if factors that predict the likelihood of becoming certified also influence the likelihood of publicizing the certification.
“Such selection could nevertheless bias our results if factors that predict the likelihood of becoming certified also influence the likelihood of publicizing the certification (Hamilton and Nickerson, 2003;Bascle, 2008).”
From Strategic Silence: Withholding Certification Status as a Hypocrisy Avoidance Tactic (2018) · cites this paper as Bascle, 2008
Cites
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779 · see citing works
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820 · see citing works
A Simple Test for Heteroscedasticity and Random Coefficient Variation
Breusch, T. S., & Pagan, A. R. (1979) · Econometrica · doi:10.2307/1911963 · Cited by 5,647 · see citing works
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302 · cited 4× · see citing works
“I focus on the most robust and conservative test that should always be reported: the firststage F-statistic developed by Stock and his colleagues (Staiger and Stock, 1997; Stock et al., 2002; Stock and Yogo, 2004).”
BackgroundMethodInfluentialIdentification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230 · see citing works
Identification and estimation of local average treatment effects
Imbens, G. W., & Angrist, J. D. (1994) · Econometrica · doi:10.2307/2951620 · Cited by 4,101 · see citing works
Angrist, J. D., & Krueger, A. B. (2001) · Journal of Economic Perspectives · doi:10.1257/jep.15.4.69 · Cited by 2,355 · see citing works
Shadow Prices, Market Wages, and Labor Supply
Heckman, J. (1974) · Econometrica · doi:10.2307/1913937 · Cited by 1,852 · see citing works
Models for Sample Selection Bias
Winship, C., & Mare, R. D. (1992) · Annual Review of Sociology · doi:10.1146/annurev.so.18.080192.001551 · Cited by 812 · see citing works
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Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541 · see citing works
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441 · see citing works
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Executing and interpreting applications of PLS-SEM: updates for family business researchers
Hair, J. F., Astrachan, C. B., Moisescu, O. I., Radomir, L., Sarstedt, M., Vaithilingam, S., & Ringle, C. M. (2021) · Journal of Family Business Strategy · doi:10.1016/j.jfbs.2020.100392 · Cited by 860 · see citing works
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Carlos, W. C., & Lewis, B. W. (2018) · Administrative Science Quarterly · doi:10.1177/0001839217695089 · Cited by 393 · see citing works
Generating global brand equity through corporate social responsibility to key stakeholders
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- Authors
- Bascle, G.
- Affiliations
- HEC Paris (FR)
- Corresponding author
- Bascle, Guilhem
- ORCID
- Bascle, Guilhem
- Venue
- Strategic Organization
- Publisher
- SAGE Publications
- Published
- 2008-08
- Volume
- 6
- Issue
- 3
- Pages
- 285-327
- ISSN
- 1476-1270 (ISSN-L)
- 1741-315X
- OpenAlex
- W2161215293
- Cited by
- 1,133
- References
- 9
- Citations by year
- 2026: 81 · 2025: 92 · 2024: 99 · 2023: 87 · 2022: 94 · 2021: 94 · 2020: 76 · 2019: 77 · 2018: 71 · 2017: 70 · 2016: 57 · 2015: 43 · 2014: 58 · 2013: 39 · 2012: 34
- FWCI
- 18.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Strategic Organization (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- HAL (submittedVersion)
- Digital Access to Libraries (submittedVersion)
- Funders
- Harvard University
- Fondation HEC
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Social Sciences › Decision Sciences › Management Science and Operations Research › Business Strategies and Management Research
- Keywords
- endogeneity, instrumental variables, causal inference, observational data, selection bias, Stata command, strategic management research
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