This estimator was generalized by Lee to account for a nonscalar covariance matrix and yielded the LMT-G2SLS estimator. Lee demonstrated that in a simultaneous-equation Tobit model the LMT-G2SLS estimator is more efficient than the Amemiya GLS estimator. However, Amemiya's GLS estimator is merely a member of the class of Amemiya GLS estimators containing members which beat the LMT-G2SLS, as well as one which is asymptotically equivalent to the LMT-G2SLS. Equations, notes, and six references are supplied.
Downloads
Similar Publications
- Improved Embeddings With Easy Positive Triplet Mining
- Using Citizen Notification To Interrupt Near-Repeat Residential Burglary Patterns: the Micro-Level Near-Repeat Experiment
- Social network analysis as a tool for understanding mass shooting prevention: A case study of the Marjory Stoneman Douglas High School shooting