Robust semi-parametric inference for two-stage production models: a beta regression approach

• Autor(a) principal: Ospina, Raydonal
• Data de Publicação: 2023
• Outros Autores: Baltazar, Samuel G. F., Leiva, Víctor, Figueroa-Zúñiga, Jorge, Castro, Cecília
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/1822/85512
• topic: Asymmetry; Bootstrapping; Data envelopment analysis; Decision-making units; Efficiency; Optimization methods; Simar and Wilson algorithm; Statistical consistency; R software; Ciências Naturais::Matemáticas; Parcerias para a implementação dos objetivos

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