Ownership Structure and CO2 Emission-Adjusted Efficiency of Coal-Fired Power Plants: Evidence From India
Modeling Economic Growth in Contemporary India
ISBN: 978-1-80382-752-0, eISBN: 978-1-80382-751-3
Publication date: 22 July 2024
Abstract
Using the most recent dataset from 2013–2014 to 2017–2018, the study examines the efficiency of 75 coal-fired power plants in the Indian thermal power sector. The authors obtained robust estimates of efficiency scores by employing Seiford and Zhu’s (2002) DEA-based classification invariance technique to account for CO2 emissions as an undesirable output. Meta-frontier analysis and the Tobit regression are used to compute technology heterogeneity across power plants belonging to public and private groups and investigate the factors driving carbon-adjusted efficiency, respectively. The results reveal that, on average, the efficiency of power plants during the study period is 78.26%, showing significant room for reduction in CO2 emissions alongside augmentation in electricity generation. Private plants are more efficient than public ones, and relative performance inefficiency is the primary source of inefficiency in the thermal power sector. Regression analysis indicates that domestic-equipped plants perform with lesser levels of efficiency, and plants with more units are more inefficient than plants with fewer units. Carbon productivity significantly improves efficiency since fewer fossil fuels with high carbon will generate more electricity.
Keywords
Citation
Dadia, V.S. and Gulati, R. (2024), "Ownership Structure and CO2 Emission-Adjusted Efficiency of Coal-Fired Power Plants: Evidence From India", Sergi, B.S., Tiwari, A.K. and Nasreen, S. (Ed.) Modeling Economic Growth in Contemporary India (Entrepreneurship and Global Economic Growth), Emerald Publishing Limited, Leeds, pp. 233-260. https://doi.org/10.1108/978-1-80382-751-320241013
Publisher
:Emerald Publishing Limited
Copyright © 2024 Varsha Singh Dadia and Rachita Gulati. Published under exclusive licence by Emerald Publishing Limited