Finite sample inference methods for dynamic energy demand models
针对动态能源需求模型，提出有限样本推断方法，解决常用计量方法仅适用于大样本的问题，重点检验结构稳定性和精确估计弹性置信集，实证表明使用识别稳健推断方法的重要性。
Abstract This paper considers finite sample motivated inference methods in dynamic energy demand models, in which case commonly used econometric methods remain asymptotic. We focus on structural stability, and on exact confidence set estimation of elasticities. We account for intractable and nuisance parameter dependant distributions through Monte Carlo test procedures. For long‐run elasticities which depend on parameter ratios, we assess available asymptotic and exact methods with Fieller based alternatives. Fieller based and exact methods invert approximate and exact relevant test criteria (respectively) and may lead to unbounded set estimates. Our empirical results underscore the importance of using identification‐robust inference methods. Copyright © 2007 John Wiley & Sons, Ltd.