Stochastic Data Envelopment Analysis in Measuring the Efficiency of Electricity Distribution Companies

Abstract

Performance benchmarking of electricity distribution markets is essential for improving industry performance parameters. In a benchmarking study, the most important problem is that regulators often do not have accurate, specific, and sufficient information to determine current input use to achieve expected amount of output. The study combines statistical symmetric error structure with stochastic chance constrained DEA models and compares deterministic data envelopment analysis (DEA) models with stochastic chance-constrained DEA models within random input and output variables. The proposed models were applied on Turkey's electricity distribution units for assessment of energy efficiency. Study revealed that the results obtained with random data softened efficiency frontier. This study contains symmetric error structure and random inputs and outputs for performance benchmarking of electricity distribution markets by stochastic data envelopment analysis within a symmetric error structure in Turkey.