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Simulation, Panel Data Regression Model, Fixed Effects, Random Effects Methods
This real model simulation study attempts to shed more light on the predictive performances of two of the most commonly used panel data regression methods - fixed effects and random effects. In particular, this paper attempts to address the question, How do these two alternative estimators perform in prediction when errors follow non-normal distributions? The simulation results support the random effects approach as the better choice.