Urban Energy Efficiency Assessment Using Stochastic and Deterministic Data Analysis

Abstract

The present study puts forward an approach that aids in the achievement of significant technical urban energy efficiency results and that identifies the coherence of different frontier methods through a case study. The aim of the study is to show the effects and results of deterministic and stochastic approaches in urban energy efficiency measurement and to evaluate how data envelopment analysis (DEA), stochastic data envelopment analysis (SDEA), and stochastic frontier analysis (SFA) can be used to derive measures of efficiency and productivity change over time in complex multi‐output multi‐input contexts. With stochastic models, the authors aim to decrease the effect of extreme values on the efficiency frontier. It was found that nonparametric methods are sensitive to measurement error, while stochastic models have a more flexible frontier than deterministic models. This is the first study to put forward a novel approach to the measurement of urban energy efficiency of Turkey's metropolitans involving both deterministic and stochastic methods.