Using Supervised Environmental Composites in Production and Efficiency Analyses: An Application to Norwegian Electricity Networks
Supervised dimension reduction methods have been extensively applied in different scientific fields like biology and medicine in recent years. However, they have hardly ever been used in micro economics, and in particular cost function modeling. Nonetheless, these methods can also be useful in regulation of natural monopolies such as gas, water, and electricity networks, where firms’ cost and performance can be affected by a large number of environmental factors. In order to deal with this ‘dimensionality’ problem we propose using a supervised dimension reduction approach that aims to reduce the dimension of data without loss of information. Economic theory suggests that in the presence of other relevant production (cost) drivers, the traditional all-inclusive assumption is not satisfied and, hence, production or cost predictions (and efficiency estimates) might be biased. This paper shows that purging the data using a partial regression approach allows us to address this issue when analyzing the effect of weather and geography on cost efficiency in the context of the Norwegian electricity distribution networks.
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- Bura, E. & Yang, J., 2011. "Dimension estimation in sufficient dimension reduction: A unifying approach," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 130-142, January.
- Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
- Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
- Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
- Giannakis, Dimitrios & Jamasb, Tooraj & Pollitt, Michael, 2005. "Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks," Energy Policy, Elsevier, vol. 33(17), pages 2256-2271, November.
- Growitsch, Christian & Jamasb, Tooraj & Wetzel, Heike, 2012. "Efficiency effects of observed and unobserved heterogeneity: Evidence from Norwegian electricity distribution networks," Energy Economics, Elsevier, vol. 34(2), pages 542-548.
- Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
- Førsund, Finn R. & Kittelsen, Sverre A. C., 1998. "Productivity development of Norwegian electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 20(3), pages 207-224, September.
- William Yu & Tooraj Jamasb & Michael Pollitt, 2009. "Willingness-to-Pay for Quality of Service: An Application to Efficiency Analysis of the UK Electricity Distribution Utilities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-48.
- Kjell G. Salvanes & Sigve Tjøtta, 1998. "A Test for Natural Monopoly with Application to Norwegian Electricity Distribution," Review of Industrial Organization, Springer, vol. 13(6), pages 669-685, December.
- Yu, William & Jamasb, Tooraj & Pollitt, Michael, 2009. "Does weather explain cost and quality performance? An analysis of UK electricity distribution companies," Energy Policy, Elsevier, vol. 37(11), pages 4177-4188, November.
- Efstathia Bura & R. Dennis Cook, 2001. "Estimating the structural dimension of regressions via parametric inverse regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 393-410.
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