Quantile regression approach for measuring production inefficiency with empirical application to the primary production sector for the Xinjiang Production and Construction Corps in China

Abstract

We propose a new method to measure production inefficiency by estimating the target and production technology of individual units using quantile regression. This method not only measures inefficiency in total factor productivity but also inefficiencies in input utilizations. We also propose two methods for decomposing the estimated inefficiency. We apply this proposed method for measuring the inefficiency of primary sector production for the Xinjiang Production and Construction Corps in China to clarify its usefulness and advantages. We specify the capital stock using the area sown and other inputs to estimate the production function with the restriction of constant returns-to-scale. Results indicate that lower labor inputs make production inefficient, and the inefficiency of labor utilization makes a large contribution to the mean and variance of total inefficiency. We also compare the proposed inefficiency measure to those employing corrected ordinary least squares and data envelopment analysis. The estimated efficiencies obtained are similar to those for existing methods. However, the proposed method provides additional advantages, including information on the inefficiencies in input utilization.