Benchmarking the performance of Indian electricity distribution companies: The applications of multi-stage robust DEA and SFA models

Abstract

Efficiency measures and benchmarking of Electricity Distribution Companies (DISCOMs) are crucial in price-cap monopoly market regulations. Benchmarking methods provide the necessary information for institutions to provide incentives or penalize based on performance. This study applies multi-stage parametric (SFA) and non-parametric (DEA) methods to benchmark the performance of Indian DISCOMs from 2015-16 to 2022–23. The DEA analysis includes SBM DEA, bootstrap DEA, and the panel Malmquist DEA model, which assesses efficiency changes over time. The parametric analysis involves three generations of time-varying panel data random effect SFA models. These models are first generational Random Effect (RE), second generational True Random Effect (TRE), and an advanced four-component model which decomposes persistent and transient efficiency and uses Monte Carlo Simulation to robust the analysis. The results indicate that transient inefficiency contributes more than persistent inefficiency to overall inefficiency. Results suggest that short-term government policies and regulatory changes will enhance the DISCOMs' performance more effectively than internal managerial changes. The study concludes that a stable regulatory environment, fair tariff structures, market competition, and subsidy policy are crucial for enhancing the efficiency of Indian DISCOMs. These findings have a significant role in developing policies and managerial strategies to enhance the performance of underperforming DISCOMs.