Endogeneity bias in marketing research: Problem, causes and remedies
By Ghasem Zaefarian, Vita Kadile, Stephan C. Henneberg, Alexander Leischnig. 2017
294 citations recorded by the source corpus.
Endogeneity bias represents a critical issue for the analysis of cause and effect relationships. Although the existence of endogeneity can produce severely biased results, it has hitherto received only limited attention from researchers in marketing and related disciplines. Thus, this article aims to sensitize researchers intending to publish in the Industrial Marketing Management (IMM) journal to the topic of endogeneity. It outlines the problem of endogeneity bias, and provides an overview of potential sources, i.e. omission of variables, errors-in-variables, and simultaneous causality. Furthermore, the article shows ways to deal with endogeneity, including techniques based on instrumental variables as well as instrument-free approaches. Our methodological contribution relates to providing researchers aiming to publish in IMM with an initial overview of the causes of and remedies for endogeneity bias, which should be considered in designing research projects as well as when analysing data to obtain insights into cause and effect relationships (causal models).
Subfields: Economics and Econometrics, Management Science and Operations Research, Marketing
View Paper: https://www.semanticscholar.org/paper/fab6c2e7fd4c5bd3baf1b4a1f270c5a9823f903a
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 Management Science and Operations Research
In Marketing
Citations in the corpus
- Dealing with endogeneity bias: The generalized method of moments (GMM) for panel data (2018, methodology): “Some researchers have recently provided reviews to understand the key endogeneity concepts and relevant techniques (e.g., see Zaefarian et al., 2017).”