COVID-19 Model Iteration 3-a-1 Endogeneity Evaluation

The code for the assessment of endogeneity using the Gaussian Copula approach comes from

Hult, G. T. M., J. F. Hair, D. Proksch, M. Sarstedt, A. Pinkwart, & C. M. Ringle (2018). Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling. Journal of International Marketing, 26(3), 1–21. https://doi.org/10.1509/jim.17.0151

Test of non-normality

The Gaussian Copula approach can only be used if the independent variable in question is non-normally distributed. So we first test the distribution of the construct scores.

All independent (or endogenous) variables are non-normally distributed. Therefore, the Gaussian Copula approach can be used for all of them.

Regression of Response Beliefs on Distrusting Beliefs and Knowledge

Neither the Distrusting Beliefs nor the Knowledge copula is significant, indicating that there is no endogeneity in the regression of Response Beliefs on its predictors.

Regression of Behavioral Intention on its predictors

The copula for Response Beliefs achieves a significant p-value in almost all constellations (p < 0.1). Further, adding the single copula increases the Response Belief path coefficient by about 0.06. Both of this indicates that Response Beliefs might be endogenous. There is nothing pointing to endogeneity in any of the other predictors.

The copula will be integrated in the final model to improve the model.