Wrong Skewness and Finite Sample Correction in Parametric Stochastic Frontier Models
نویسندگان
چکیده
In parametric stochastic frontier models, the composed error is specified as the sum of a two-sided noise component and a one-sided inefficiency component, which is usually assumed to be half-normal, implying that the error distribution is skewed in one direction. In practice, however, estimation residuals may display skewness in the wrong direction. Model respecification or pulling a new sample is often prescribed. Since wrong skewness is considered a finite sample problem, this paper proposes a finite sample adjustment to existing estimators to obtain the desired direction of residual skewness. This provides another empirical approach to dealing with the so-called wrong skewness problem. JEL No. C13, C23, D24
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