On the Distributional Assumptions in the StoNED model
In a recent paper Johnson and Kuosmanen (2011) propose a new, semi-parametric, general cost-frontier model, the stochastic nonparametric envelopment of data (StoNED). The model is semi-parametric in the sense that the cost function is estimated nonparametrically, while the functional form of the distribution for the error term is parametrically specified. A common assumption for this distribution is that it is a convolution of a truncated normal distribution, representing inefficiency, and a normal distribution, representing noise. This parametric form has the drawback that a negative skewness implies a negative expected inefficiency. It can thus never capture a negatively skewed distribution with a positive expectation. In this paper we investigate this assumption and its consequences for an analysis of inefficiency. Furthermore, we propose a solution to the problem and investigate its performance by means of a Monte Carlo simulation.
|Date of creation:||17 Sep 2015|
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- Kumbhakar, Subal C., 1991. "Estimation of technical inefficiency in panel data models with firm- and time-specific effects," Economics Letters, Elsevier, vol. 36(1), pages 43-48, May.
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