The job satisfaction model is considered as motivating example; for developing a performance comparative study between the GME and PLS regression methods. Both GME and PLS methods are implemented on the job satisfaction model; where several level of correlation are generated among the predictors. For each level of correlation; regression coefficients and diagnostic values are calculated; for showing the performance of both methods in case of ill-posed problems.
The paper is divided in two main sections: The first part consider the introduction of the two estimation methods; in way to give a general overview of both techniques and also the main characteristics.
The second part gives a brief introduction to the job satisfaction model and then starts with the simulation study; comparing both estimation results; giving a discussion in case of multicollinearity problem.
Keywords: Generalized Maximum Entropy; Partial Least Squares; Job Satisfaction; Multicollinearity; Bootstrap