Preliminary test estimation in system regression models in view of asymmetry

In this paper, we consider the system regression model introduced by Arashi and Roozbeh (Comput Stat 30:359–376, 2015) and study the performance of the feasible preliminary test estimator (FPTE) both analytically and computationally, under the assumption that constraints may hold on the vector parameter space. The performance of the FPTE is analysed through a Monte Carlo simulation study under bounded and or asymmetric loss functions. An application of the so-called Cobb–Douglas production function in economic modelling together with the results from the simulation study shows that the bounded linear exponential (BLINEX) loss function outperforms the linear exponential loss function (LINEX) by comparing risk values.