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Semi-parametric analysis of efficiency and productivity using Gaussian processes
[Estimation of long-run inefficiency levels: A dynamic frontier approach]

Author

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  • Grigorios Emvalomatis

Abstract

SummaryThis paper proposes a fully Bayesian semi-parametric method for efficiency and productivity analysis based on Gaussian processes. The proposed technique frees the researcher from having to specify a functional form for the production frontier, and it is shown in simulated data to perform as well as flexible parametric models when correct distributional assumptions are imposed on the inefficiency component of the error term, and slightly better when incorrect assumptions are made. The technique is applied to a panel dataset of US electric utilities, where total-factor productivity growth is estimated and decomposed with both parametric and semi-parametric techniques.

Suggested Citation

  • Grigorios Emvalomatis, 2020. "Semi-parametric analysis of efficiency and productivity using Gaussian processes [Estimation of long-run inefficiency levels: A dynamic frontier approach]," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 48-67.
    • Handle: RePEc:oup:emjrnl:v:23:y:2020:i:1:p:48-67.
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    File URL: http://hdl.handle.net/10.1093/ectj/utz013
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