Abstract
This paper presents a simple methodology, built upon the bootstrapping technique originally developed by Simar and Wilson (Handbook on Data Envelopment Analysis, Kluwer International Series, Boston, 2004), in order to evaluate, unambiguously, returns to scale and convexity assumptions in DEA. The basic idea is to use confidence intervals and bias corrected central estimates to test for significant differences on distance functions and returns-to-scale indicators provided by different DEA models. This methodology is illustrated by means of a case study in the Brazilian port sector, where anecdotal evidence regarding an eventual capacity shortfall is corroborated.
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Wanke, P.F., Barros, C.P. (2016). Evaluating Returns to Scale and Convexity in DEA Via Bootstrap: A Case Study with Brazilian Port Terminals. In: Hwang, SN., Lee, HS., Zhu, J. (eds) Handbook of Operations Analytics Using Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 239. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7705-2_8
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