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Performance Analysis of Power Plants under Heterogeneous Technologies with Meta Frontier Framework
Department of Food and Resource Economics, College of Life Sciences and Biotechnology, Korea University.ORCID iD: 0000-0002-7902-4683
Technology Management Economics and Policy Program (TEMEP), College of Engineering, Seoul National University.
Technology Management Economics and Policy Program (TEMEP), College of Engineering, Seoul National University.
2012 (English)In: International Journal of Economics and Management Engineering, ISSN 2225-742X, Vol. 2, no 1, 5-14 p.Article in journal (Refereed) Published
Abstract [en]

There have been numerous studies measuring efficiency and productivity in the electricity industry worldwide but little research focusing on the comparisons of generation technologies. This study provides a better direction for the proper analysis of the electricity generation sector by examining the performance changes and comparing efficiencies among different types of electric power plants. To account for technology heterogeneity, we apply a meta frontier framework, which is composed of technology specific frontiers. This method allows analyses of the existing gap between generation technologies in the generation part of the electricity industry. The inter- and intra-efficiency variations of the technology groups are investigated using determinant analysis. The overall process is composed of two parts: efficiency measurement by deterministic meta frontier framework and regression analysis for determinant analysis. In the determinant analysis of efficiency differences, we exploit several common and time invariant characteristics of the plants. The results based on panel data of power plants indicate that there are significant technological gaps among different types of plants and several external factors affect performance of the plants.

Place, publisher, year, edition, pages
2012. Vol. 2, no 1, 5-14 p.
Keyword [en]
Meta Frontier; Panel Data; Efficiency; Electricity Industry; Heterogeneous Technologies
National Category
Economics
Identifiers
URN: urn:nbn:se:hj:diva-24665OAI: oai:DiVA.org:hj-24665DiVA: diva2:743992
Available from: 2014-09-05 Created: 2014-09-05 Last updated: 2016-01-14Bibliographically approved

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  • apa
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