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A one-stage random effect counterpart of the fixed-effect vector decomposition model with an application to UK electricity distribution utilities

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  • Greene, William
  • Orea, Luis
  • Wall, Alan

Abstract

To deal with the presence of slowly changing variables, Plümper and Troeger (2007) proposed a fixed effects vector decomposition (FEVD) estimator, which is a three-stage procedure based on the fixed effects estimator. We show that this estimator moves between fixed effect and ordinary least squares depending on how its second stage is specified. This provides an alternative interpretation of the FEVD estimator that allows us to introduce a one-stage counterpart of the FEVD model, which can be viewed as a partial Mundlak (1978) transformation of the random effects model. We illustrate our 7 approach with an application to UK electricity distribution utilities using the same data as Yu et al. (2009). Our application suggests that our estimator and the FEVD yield similar results when the pooled OLS estimates for a given panel are similar to the random effects estimates.

Suggested Citation

  • Greene, William & Orea, Luis & Wall, Alan, 2011. "A one-stage random effect counterpart of the fixed-effect vector decomposition model with an application to UK electricity distribution utilities," Efficiency Series Papers 2011/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Handle: RePEc:oeg:wpaper:2011/01
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    File URL: https://www.unioviedo.es/oeg/ESP/esp_2011_01.pdf
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    References listed on IDEAS

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    1. Jamasb, T. & Orea, L. & Pollitt, M.G., 2010. "Weather Factors and Performance of Network Utilities: A Methodology and Application to Electricity Distribution," Cambridge Working Papers in Economics 1042, Faculty of Economics, University of Cambridge.
    2. Greene, William, 2011. "Fixed Effects Vector Decomposition: A Magical Solution to the Problem of Time-Invariant Variables in Fixed Effects Models?," Political Analysis, Cambridge University Press, vol. 19(2), pages 135-146, April.
    3. 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.
    4. 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.
    5. Breusch, Trevor & Ward, Michael B. & Nguyen, Hoa Thi Minh & Kompas, Tom, 2011. "On the Fixed-Effects Vector Decomposition," Political Analysis, Cambridge University Press, vol. 19(2), pages 123-134, April.
    6. Plümper, Thomas & Troeger, Vera E., 2007. "Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects," Political Analysis, Cambridge University Press, vol. 15(2), pages 124-139, April.
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    Cited by:

    1. Orea, Luis & Álvarez, Inmaculada C. & Jamasb, Tooraj, 2016. "A spatial approach to control for unobserved environmental conditions when measuring firms’ technology: an application to Norwegian electricity distribution networks," Efficiency Series Papers 2016/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    2. Greene, William & Orea, Luis & Wall, Alan, 2010. "Stochastic Frontiers using a Fixed-effect Vector Decomposition Approach with an Application to ICT and Regional Productivity in Spain," Efficiency Series Papers 2010/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    4. Luis Orea & Inmaculada C. Álvarez & Tooraj Jamasb, 2016. "Using a spatial econometric approach to mitigate omitted variables in stochastic frontier models: An application to Norwegian electricity distribution networks," Working Papers EPRG 1630, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.

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