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Revisiting Gaussian copulas to handle endogenous regressors
Citation Link: https://doi.org/10.15480/882.3911
Publikationstyp
Journal Article
Date Issued
2022-01
Sprache
English
TORE-DOI
Volume
50
Issue
1
Start Page
46
End Page
66
Citation
Journal of the Academy of Marketing Science 50 (1): 46-66 (2022-01)
Publisher DOI
Scopus ID
Publisher
Springer Netherlands
Peer Reviewed
true
Marketing researchers are increasingly taking advantage of the instrumental variable (IV)-free Gaussian copula approach. They use this method to identify and correct endogeneity when estimating regression models with non-experimental data. The Gaussian copula approach’s original presentation and performance demonstration via a series of simulation studies focused primarily on regression models without intercept. However, marketing and other disciplines’ researchers mainly use regression models with intercept. This research expands our knowledge of the Gaussian copula approach to regression models with intercept and to multilevel models. The results of our simulation studies reveal a fundamental bias and concerns statistical power at smaller sample sizes and when the approach’s primary assumptions are not fully met. This key finding opposes the method’s potential advantages and raises concerns about its appropriate use in prior studies. As a remedy, we derive boundary conditions and guidelines that contribute to the Gaussian copula approach’s proper use. Thereby, this research contributes to ensuring the validity of results and conclusions of empirical research applying the Gaussian copula approach.
Subjects
Endogeneity
Gaussian copula
Intercept
Linear regression
Multilevel models
Sample size
Simulation
DDC Class
330: Wirtschaft
Funding(s)
Funding Organisations
More Funding Information
This research was partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—VO 1555/1-1.
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