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Smooth coefficient estimation of stochastic frontier models

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  • Lopez Gomez, Daniel
  • Parmeter, Christopher F.

Abstract

This paper proposes two alternative estimators for the semiparametric smooth coefficient stochastic frontier model which do not require parametric specification of the parameters of the distribution of inefficiency to identify all of the model primitives. These new estimators offer avenues for testing for correct specification. A small Monte Carlo simulation study reveals that the new methods perform similarly when correct specification is present and that the existing smooth coefficient estimator can perform poorly when it is incorrectly specified.

Suggested Citation

  • Lopez Gomez, Daniel & Parmeter, Christopher F., 2020. "Smooth coefficient estimation of stochastic frontier models," Economics Letters, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:ecolet:v:193:y:2020:i:c:s0165176520302202
    DOI: 10.1016/j.econlet.2020.109340
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    References listed on IDEAS

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