Pillai N., Vijayamohanan (2019): Measuring Energy Efficiency: An Application of Stochastic Frontier Production Function Analysis to Power Sector in Kerala.

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Abstract
Traditionally, there are two basically reciprocal energy efficiency Indicators: one, in terms of energy intensity, that is, energy use per unit of activity output, and the other, in terms of energy productivity, that is, activity output per unit of energy use. The enquiry that has proceeded from the problems associated with this method of a single energy input factor in terms of productivity has led to multifactor productivity analysis. We have here two approaches: parametric and nonparametric. Parametric approach famously includes two methods: the erstwhile popular total factor energy productivity analysis and the currently fanciful stochastic frontier production function analysis; The nonparametric approach is popularly represented by data envelopment analysis. The present paper is an attempt to measure efficiency in electrical energy consumption in Kerala, India. We apply the parametric method of stochastic frontier production function analysis on a panel data of the Kerala power sector with three sectors (Primary, Secondary and Tertiary) for the period from 197071 to 201617. For a comparative purpose, we also have a regression with a pooled data stochastic frontier. The results indicate that the sectorwise technical efficiency estimates of the Kerala power sector are independent of time, which can significantly refer to a technically stagnant situation in energy efficiency. The implication of the timevarying decay model, even though statistically insignificant, of a falling trend in the technical efficiency of all the three sectors also is a hot matter of serious concerns.
Item Type:  MPRA Paper 

Original Title:  Measuring Energy Efficiency: An Application of Stochastic Frontier Production Function Analysis to Power Sector in Kerala 
Language:  English 
Keywords:  Energy efficiency, Kerala, Power sector, Stochastic frontier, Technical efficiency. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C51  Model Construction and Estimation Q  Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4  Energy 
Item ID:  101944 
Depositing User:  Vijayamohanan Pillai N 
Date Deposited:  23 Jul 2020 02:21 
Last Modified:  23 Jul 2020 02:21 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/101944 