After doing some research on the topic of how to test your model for endogeinity I came across the Guassian copla approach, which is the less restrictive in this category but has some limitations as well as for example that only Second, the endogenous regressor needs to be sufficiently nonnormal to enable the identification of the modelit can be applied to nonlinear models (e.g., Random Coefficient Logit with structural error from the normal distribution); and it can handle multiple endogenous regressors as well as interactions (Papies, Ebbes, & Van Heerde, 2016). Any idea of how to test without using instrument variables with the same features as the Gaussian copula approach but with the endogenous variable being normal or is every endogenous variable always nonormal? (The papers I am referring to can be accessed via those links https://cran.r-hub.io/web/packages/REndo/vignettes/REndo-introduction.pdf and https://journals.sagepub.com/doi/full/10.1177/01492063221085913) Any help is greatly appreciated!
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