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Cited by 305Advanced Causal Inference TechniquesBusiness Strategies and Management ResearchSpatial and Panel Data Analysis

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Causality and Endogeneity

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Antonakis, John, Bendahan, Samuel, Jacquart, Philippe, Lalive, Rafael·2014·Oxford Handbooks Online
DOI 10.1093/oxfordhb/9780199755615.013.007
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Abstract

Most leadership and management researchers ignore one key design and estimation problem rendering parameter estimates uninterpretable: Endogeneity. We discuss the problem of endogeneity in depth and explain conditions that engender it using examples grounded in the leadership literature. We show how consistent causal estimates can be derived from the randomized experiment, where endogeneity is eliminated by experimental design. We then review the reasons why estimates may become biased (i.e., inconsistent) in non-experimental designs and present a number of useful remedies for examining causal relations with non-experimental data. We write in intuitive terms using nontechnical language to make this chapter accessible to a large audience.

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  • No servant leadership studies explored reverse causation or discussed issues of endogeneity.

    “Nor have any of the studies explored reverse causation or discussed issues of endogeneity (see Antonakis et al., 2010;Antonakis, Bendahan, et al., 2014).”

    From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Antonakis, Bendahan, et al., 2014

    The Abstract says many leadership researchers do not understand designs for identifying causal relationships, and Future directions names servant leadership as a potentially endogenous regressor. Neither passage establishes that no servant-leadership study explored reverse causation or discussed endogeneity; the claim is more specific and absolute than this source supports. Page numbers are unavailable in our copy. (LLM, conf=0.76)

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  • Experimental designs protect against endogeneity and enable causal inferences.

    “Considering the importance of experimental designs to protect against endogeneity (Antonakis, Bendahan, Jacquart, & Lalive, 2014), as well as the capability for making causal inferences, we endorse increased use of experimental research on servant leadership.”

    From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Antonakis, Bendahan, Jacquart, & Lalive, 2014

  • Servant leadership is potentially an endogenous independent variable within research designs.

    “Third, researchers need to deal with the potential that servant leadership is an endogenous independent variable within their designs (see Antonakis et al., 2010;Antonakis, Bendahan, et al., 2014).”

    From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Antonakis, Bendahan, et al., 2014

  • This is not unique to servant leadership and there have been a number of efforts to improve survey design within the leadership field.

    “This is not unique to servant leadership and there have been a number of efforts to improve survey design within the leadership field (see Antonakis et al., 2010;Antonakis et al., 2016;Antonakis, Bendahan, et al., 2014;Antonakis & House, 2014).”

    From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Antonakis, Bendahan, et al., 2014

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Metadata

Authors
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R.
Affiliations
  • University of Lausanne (CH)
  • University of Pennsylvania (US)
ORCID
Venue
Oxford Handbooks Online
Publisher
Oxford University Press
Published
2014-01-13
DOI
10.1093/oxfordhb/9780199755615.013.007
OpenAlex
W275034999
Cited by
305
References
18
Citations by year
2026: 14 · 2025: 14 · 2024: 20 · 2023: 28 · 2022: 16 · 2021: 40 · 2020: 43 · 2019: 33 · 2018: 28 · 2017: 27 · 2016: 14 · 2015: 17 · 2014: 9
FWCI
4.95
Type
book
Language
en
Open access
Locations
  • Oxford University Press eBooks (publishedVersion)
  • IRIS (submittedVersion)
  • SERVAL (Université de Lausanne) (submittedVersion, other-oa)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Keywords
endogeneity, causality, leadership research, management research, randomized experiments, non-experimental design, estimation bias, causal inference, estimator consistency

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