An Asymptotic Expansion of the Distribution of the Limited Information Maximum Likelihood Estimate of a Coefficient in a Simultaneous Equation System
An Asymptotic Expansion of the Distribution of the Limited Information Maximum Likelihood Estimate of a Coefficient in a Simultaneous Equation System
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联立方程组系数有限信息最大似然估计分布的渐近展开
DOI：
10.1080/01621459.1974.10482994
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发表时间：
1974
影响因子：
3.7
通讯作者：
T. W. Anderson
中科院分区：
文献类型：
--
作者：
T. W. Anderson
本文对两个内生变量方程中一个内生变量的系数的有限信息极大似然估计的分布作了渐近展开，当另一个内生变量的系数为1时。该方程是联立方程组中的一个，并且系统中的所有预定变量被假设为外生的。非中心性参数的展开随着样本量的增加而增加，其数量级为非中心性参数的负幂（即，四项）。与两阶段最小二乘估计的分布的扩展进行了比较。
Abstract An asymptotic expansion is made of the distribution of the limited information maximum likelihood estimate of the coefficient of one endogenous variable in an equation with two endogenous variables when the coefficient of the other endogenous variable is prescribed to be unity. The equation is one of a system of simultaneous equations, and all the predetermined variables in the system are assumed to be exogenous. The expansion in terms of the noncentrality parameter, which increases with the sample size, is carried out to the order of the negative power of the noncentrality parameter (i.e., four terms). Comparison is made with the expansion of the distribution of the two-stage least squares estimate.