Goodness--of--fit tests for the distribution of the composed error term in a Stochastic Frontier Model (SFM) are suggested. The focus is on the case of a normal/gamma SFM and the heavy--tailed stable/gamma SFM. In the first case the moment generating function is used as tool while in the latter case the characteristic function of the error term is employed. In both cases our test statistics are formulated as weighted integrals of properly standardized data. The new normal/gamma test is consistent, and is shown to have an intrinsic relation to moment--based tests. The finite--sample behavior of resampling versions of both tests is investigated by Monte Carlo simulation, while several real--data applications are also included.

翻译：本文提出了针对随机前沿模型中复合误差项分布拟合优度的检验方法。研究重点集中于正态/伽马随机前沿模型与厚尾稳定/伽马随机前沿模型两种情形。前者采用矩母函数作为分析工具，后者则利用误差项的特征函数。两种情形下的检验统计量均被构造为适当标准化数据的加权积分形式。新构建的正态/伽马检验具有一致性，并显示出与基于矩的检验方法存在内在关联。通过蒙特卡洛模拟研究了两种检验重抽样版本的有限样本表现，同时提供了若干实际数据应用案例。