Confidence Intervals for Elasticity Estimators in Translog Models
研究超越对数需求模型中弹性估计量的分布函数，提出基于正态分布和正态比分布的置信区间，发现只有基于实际成本份额均值的估计量才可能服从这些分布，并通过三个实证研究说明点估计不足以推断弹性值，且存在聚合水平与置信区间宽度之间的权衡。
This paper examines the distribution fu nctions of elasticity estimators in translog demand models. The authors consider the normaland ratio-of-normals distributions and present confidence intervals for the elasticity estimators. The results suggest that only elasticity estimato rs based on the means of the actual cost shares are likely to follow either the normal or ratio-of-normals distribution function. Examination of three published empirical studies demonstrates that inferences regarding the values of elasticities cannot be made from point estimates alone and suggests a trade- off between the level of aggregation and the width of confidence intervals for the elasticit y estimators. Copyright 1986 by MIT Press.