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Observed and unobserved heterogeneity in stochastic frontier models: An application to the electricity distribution industry

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  • Kopsakangas-Savolainen, Maria
  • Svento, Rauli

Abstract

In this study we combine different possibilities to model firm level heterogeneity in stochastic frontier analysis. We show that both observed and unobserved heterogeneities cause serious biases in inefficiency results. Modelling observed and unobserved heterogeneities treat individual firms in different ways and even though the expected mean inefficiency scores in both cases diminish the firm level efficiency rank orders turn out to be very different. The best fit with the data is obtained by modelling unobserved heterogeneity through randomizing frontier parameters and at the same time explicitly modelling the observed heterogeneity into the inefficiency distribution. These results are obtained by using data from Finnish electricity distribution utilities and the results are relevant in relation to electricity distribution pricing and regulation.

Suggested Citation

  • Kopsakangas-Savolainen, Maria & Svento, Rauli, 2011. "Observed and unobserved heterogeneity in stochastic frontier models: An application to the electricity distribution industry," Energy Economics, Elsevier, vol. 33(2), pages 304-310, March.
    • Handle: RePEc:eee:eneeco:v:33:y:2011:i:2:p:304-310
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    1. Dag Dalen & Andres Gómez-Lobo, 2003. "Yardsticks on the road: Regulatory contracts and cost efficiency in the Norwegian bus industry," Transportation, Springer, vol. 30(4), pages 371-386, November.
    2. Mehdi Farsi & Massimo Filippini, 2004. "Regulation and Measuring Cost-Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 25(1), pages 1-19, August.
    3. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    4. James Odeck, 2007. "Measuring technical efficiency and productivity growth: a comparison of SFA and DEA on Norwegian grain production data," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2617-2630.
    5. 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.
    6. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2006. "Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 95-118, January.
    7. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    8. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    9. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    10. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    11. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    12. Mehdi Farsi & Massimo Filippini & William Greene, 2006. "Application Of Panel Data Models In Benchmarking Analysis Of The Electricity Distribution Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(3), pages 271-290, September.
    13. Kopsakangas-Savolainen, Maria & Svento, Rauli, 2008. "Estimation of cost-effectiveness of the Finnish electricity distribution utilities," Energy Economics, Elsevier, vol. 30(2), pages 212-229, March.
    14. Farsi, Mehdi & Filippini, Massimo & Kuenzle, Michael, 2007. "Cost efficiency in the Swiss gas distribution sector," Energy Economics, Elsevier, vol. 29(1), pages 64-78, January.
    15. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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