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Stochastic non-smooth envelopment of data for multi-dimensional output

Author

Listed:
  • Julia Schaefer

    (RWTH Aachen University)

  • Marcel Clermont

    () (Duale Hochschule Gera-Eisenach)

Abstract

Abstract The proposed method of Stochastic Non-smooth Envelopment of Data (StoNED) for measuring efficiency has to date mainly found application in the analysis of production systems which have exactly one output. Therefore, the objective of this paper is to examine the applicability of StoNED when a ray production function models a production technology with multi-dimensional input and output. In addition to a general analysis of properties required by a ray production function for StoNED to be applicable, we conduct a Monte Carlo simulation in order to evaluate the quality of the frontier and efficiencies estimated by StoNED. The results are compared with those derived via Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We show that StoNED provides competitive estimates in regard to other methods and especially in regard to the real functional form and efficiency.

Suggested Citation

  • Julia Schaefer & Marcel Clermont, 2018. "Stochastic non-smooth envelopment of data for multi-dimensional output," Journal of Productivity Analysis, Springer, vol. 50(3), pages 139-154, December.
  • Handle: RePEc:kap:jproda:v:50:y:2018:i:3:d:10.1007_s11123-018-0539-5
    DOI: 10.1007/s11123-018-0539-5
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    References listed on IDEAS

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