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 multi-factor productivity analysis. We have here two approaches: parametric and non-parametric. Parametric approach famously includes two methods: the erstwhile popular total factor energy productivity analysis and the currently fanciful stochastic frontier production function analysis; The non-parametric 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 non-parametric mathematical programming method of data envelopment analysis of the multi-factor productivity approach, and estimate the efficiency measures under the two scale assumptions of constant returns to scale (CRS) and variable returns to scale (VRS); the latter includes both increasing (IRS) and decreasing returns to scale (DRS). Scale efficiency measures are also given to find out whether a firm is operating at its optimal size or not, implying degrees of capacity utilization.
Highlights
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 traditional interest in energy efficiency has centred on a single energy input factor in terms of productivity that has become famous through the index method proposed by Patterson (1996)
In this paper we have taken up the non-parametric mathematical programming method of data envelopment analysis, the second approach in multi-factor productivity analysis
Summary
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. If a production unit is producing at point R, its technical inefficiency is given by the distance AR, which implies that the unit could proportionally reduce all inputs by this amount without reducing its output This distance can be represented in percentage terms by the ratio AR/OR. The linear programming (LP) problem is to choose the optimal weights such as to maximize the efficiency measure (the weighted output-input ratio) subject to the constraints that this measure (ratio) is less than or equal to unity and the weights are non-negative: Maxa,b (a'Yi / b'Xi), s t a'Yi / b'Xi ≤ 1, i = 1, 2,..., N, a, b ≥ 0 This formulation has a problem that it would yield an infinite number of solutions.
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