Testing and controlling for endogeneity in PLS-SEM with stochastic instrumental variables

The article below discusses a procedure that can be used to simultaneously test and control for endogeneity, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2022). Testing and controlling for endogeneity in PLS-SEM with stochastic instrumental variables. Data Analysis Perspectives Journal, 3(3), 1-6.

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Abstract:

We discuss a procedure that can be used to simultaneously test and control for endogeneity in models analyzed with structural equation modeling via partial least squares (PLS-SEM). It relies on the creation of stochastic instrumental variables for endogenous latent variables, and their use as control variables. The procedure can be seen as an implementation of the Durbin–Wu–Hausman test, often referred to as the Hausman test, with stochastic instrumental variables. It can also be seen as a generalization of the two-stage least squares procedure. We illustrate the procedure with WarpPLS, a leading PLS-SEM tool.

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