Robust Semi-Parametric Inference for Two-Stage Production Models: A Beta Regression Approach

The data envelopment analysis is related to a non-parametric mathematical tool used assess the relative efficiency of productive units. In different studies on efficiency, it common employ semi-parametric procedures in two stages determine whether any exogenous factors interest affect performance However, some these procedures, particularly those based conventional statistical inference, generate inconsistent estimates when dealing with incoherent data-generating processes. This inconsistency arises due scores being limited unit interval, and estimated often exhibit serial correlation have observations. To address such inconsistency, several strategies been suggested, most well-known an algorithm parametric bootstrap procedure using truncated normal distribution its regression model. this work, we present modification that utilizes beta structure. model allows for better accommodation asymmetry distribution. Our proposed introduces inferential characteristics are superior original algorithm, resulting more statistically coherent process improving consistency property. We conducted computational experiments demonstrate improved results achieved by our proposal.