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The noise error component in stochastic frontier analysis

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  • Alecos Papadopoulos

    (Athens University of Economics and Business)

Abstract

With a little help from a handful of scholars, the noise component of the composed error in a production model created the stochastic frontier analysis field. But after that glorious moment, it was confined to obscurity. We review what little research has been done on it. We present two cases where it torments us from the shadows, by sabotaging identification, and by distorting the sample skewness. We examine the relation between predicted noise and predicted inefficiency. For the Normal-Half Normal and the Normal-Exponential error specification, we provide its conditional expectation as predictor and we examine its distribution in relation to the marginal law. We also derive the conditional distribution of the noise and we compute confidence intervals and the probability of over-predicting it. Finally, we present a model where the noise, as the carrier of uncertainty, induces directly inefficiency. We conclude by showcasing our theoretical results through an empirical illustration.

Suggested Citation

  • Alecos Papadopoulos, 2023. "The noise error component in stochastic frontier analysis," Empirical Economics, Springer, vol. 64(6), pages 2795-2829, June.
    • Handle: RePEc:spr:empeco:v:64:y:2023:i:6:d:10.1007_s00181-022-02339-w
    DOI: 10.1007/s00181-022-02339-w
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    References listed on IDEAS

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    Cited by:

    1. Alecos Papadopoulos & Christopher F. Parmeter, 2024. "The wrong skewness problem in stochastic frontier analysis: a review," Journal of Productivity Analysis, Springer, vol. 61(2), pages 121-134, April.

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    More about this item

    Keywords

    Noise; Stochastic frontier; Identification; Wrong skewness; Dependence;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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