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GMM 与广义经验似然估计量的高阶性质AI 解读

In an effort to improve the small sample properties of generalized method of mo-ments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilt-ing estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find…

用简化似然比统计量检验受限因变量模型的外生性AI 解读

Abstract A simple likelihood‐ratio statistic for the weak exogeneity of the continuously observed endogenous variables is presented for the limited information simultaneous equations models in which a single endogenous variable is censored. The statistic is a likelihood ratio test statistic for the exclusion of the reduced form residuals of the continuously observed endogenous variables and is asymptotically locally most powerful. The procedure is illustrated by an…

联立方程 Tobit 模型的外生性检验及其劳动供给应用AI 解读

A test of weak exogeneity in the simultaneous equation Tobit model is proposed and illustrated using a female labour supply model estimated using cross-section data. The test statistic can be simply output from any standard Tobit maximum likelihood package, and is asymptotically efficient. The procedure provides consistent estimators for the simultaneous Tobit model whose asymptotic covariance matrix is a simple extension of the usual Tobit formula. We also provide the…