Endogeneity: A Review and Agenda for the Methodology-Practice Divide Affecting Micro and Macro Research
By A. Hill, Scott G. Johnson, Lindsey M Greco, Ernest H. O’Boyle, Sheryl L. Walter. Journal of Management, 2020
669 citations recorded by the source corpus.
An expanding number of methodological resources, reviews, and commentaries both highlight endogeneity as a threat to causal claims in management research and note that practices for addressing endogeneity in empirical work frequently diverge from the recommendations of the methodological literature. We aim to bridge this divergence, helping both macro and micro researchers understand fundamental endogeneity concepts by: (1) defining a typology of four distinct causes of endogeneity, (2) summarizing endogeneity causes and methods used in management research, (3) organizing the expansive methodological literature by matching the various methods to address endogeneity to the appropriate resources, and (4) setting an agenda for future scholarship by recommending practices for researchers and gatekeepers about identifying, discussing, and reporting evidence related to endogeneity. The resulting review builds literacy about endogeneity and ways to address it so that scholars and reviewers can better produce and evaluate research. It also facilitates communication about the topic so that both micro- and macro-oriented researchers can understand, evaluate, and implement methods across disciplines.
Subfields: Economics and Econometrics, Marketing, Safety Research
View Paper: https://www.semanticscholar.org/paper/1dbbdf0b87862acf50a7bde8952378eb8efc1099
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Marketing
In Safety Research
Citations in the corpus
- Omitted Variable Bias: Examining Management Research With the Impact Threshold of a Confounding Variable (ITCV) (2021, background): “Although we realize all sources of endogeneity are potentially problematic, omitted variables bias represents one of the most pervasive issues for management researchers (Hamilton & Nickerson, 2003; Hill et al., 2021).”