  Regression analysis is one of the most popularly used statistical technique
which only measures the direct effect of independent variables on dependent
variable. Path analysis looks for both direct and indirect effects of
independent variables and may overcome several hurdles allied with regression
models. It utilizes one or more structural regression equations in the model
which are used to estimate the unknown parameters. The aim of this work is to
study the path analysis models when the endogenous (dependent) variable and
exogenous (independent) variables are linked through the elliptical copulas.
Using well-organized numerical schemes, we investigate the performance of path
models when direct and indirect effects are estimated applying classical
ordinary least squares and copula-based regression approaches in different
scenarios. Finally, two real data applications are also presented to
demonstrate the performance of path analysis using copula approach.
