Testing Symmetry and Homogeneity in the Almost Ideal Demand System with Co‐integrated Data using Fully Modified Estimation and the Bootstrap
研究发现，在协整数据下，传统似无关估计几乎理想需求系统会导致小样本偏差和Wald检验的规模扭曲；完全修正估计能减少偏差但无法消除扭曲，而自助法能有效消除规模扭曲。
Abstract Conventional seemingly unrelated estimation of the almost ideal demand system is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are co‐integrated. A fully modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective, however, as a method of removing size distortion and performs equally well in this respect with both estimators.