Goodness-of-fit tests for the distribution of the composed error term in a Stochastic Frontier Model (SFM) are suggested. We focus on the case of a normal/gamma SFM and the heavy-tailed stable/gamma SFM. In the first case we use the moment generating function as tool while in the latter case the characteristic function of the error term and formulate our test statistics as weighted integrals of properly standardized data. The new tests are consistent, and for the normal/gamma SFM are shown to have an intrinsic relation to moment-based tests. The finite-sample behavior of a resampling version of the new test for the normal/gamma SFM is investigated by Monte Carlo simulations, while the corresponding test for the stable/gamma SFM is applied on several real-data sets.
翻译:提出了用于分配Stochastistic Front模型(SFM)中组成错误术语的良好测试。我们侧重于正常/伽马-SFM和重尾稳定/伽马-SFM的情况。在第一种情况下,我们使用瞬时生成功能作为工具,而在后一种情况下,则使用错误术语的特征功能,并将我们的测试统计数据作为适当标准化数据的加权组成部分。新的测试是一致的,正常/伽马-SFM与基于时刻的测试有内在关系。正常/伽马-SFM新测试的抽印版本的有限抽样行为由蒙特卡洛模拟调查,而稳定/伽马-SFM的相应测试则适用于若干套真实数据。