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关注这篇论文的作者
Ray Byron

需求系统假设检验:基于 Edgeworth 近似的检验水平修正

研究问题
在需求系统的对称性检验中,Edgeworth 临界值修正能否缓解渐近卡方检验的小样本水平偏差,其效果如何随系统规模变化?
方法与思路
作者在 SUR 框架中,对 Wald、似然比和拉格朗日乘子检验计算一阶样本量倒数级修正,并使用既有模拟数据考察效果。
材料陈述的贡献
摘要称,31 个观测下,修正在较小系统中具有实用价值;14 方程时通常仅补足所需调整的约六成,大系统计算成本也较高。
阅读关注点
应核对临界值修正公式、检验水平的评价方式、方程与限制数量的关系,以及所用模拟数据和计算成本的具体设定。
阅读边界
仅据所给 Crossref 摘要解读;所述效果来自特定模拟设定,不能保证更小样本或其他需求系统中的表现,也不推断刊本变化。

原文摘要

A size correction to adjust the critical values of asymptotic χ 2 tests in a SUR context has been developed by Rothenberg and verified by Phillips. The adjustment centers the distribution of the observed test statistic so that it coincides more closely with its hypothetical distribution. The correction itself is an approximation to O ( T −1 ), and while the adjustment should be superior to the asymptotic test (no adjustment) in small-sample situations, its performance can be expected to deteriorate as the sample size decreases. The Edgeworth corrections, using formulas provided by Phillips, are calculated for the Wald, likelihood ratio, and Lagrange multiplier tests in the context of symmetry testing in demand analysis using the Laitinen–Meisner simulated data set. The sample consists of 31 observations and the corrections were “adequate to useful” in the context of 5, 8, and 11 equations. However, in the extreme case of 14 equations the corrections typically only took up 60% of the adjustment required. The computational cost of calculating the Edgeworth correction for large SUR systems with a large number of restrictions also turns out to be quite heavy. The conclusion reached is that while Edgeworth corrections are not totally satisfactory, they are easy to include in a program and provide a useful critical value correction.

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