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奇异方程系统中的自回归误差AI 解读

We consider a system of m general linear models, where the system error vector has a singular covariance matrix owing to various “adding up” requirements and, in addition, the error vector obeys an autoregressive scheme. The paper reformulates the problem considered earlier by Berndt and Savin [8] (BS), as well as others before them; the solution, thus obtained, is far simpler, being the natural extension of a restricted least-squares-like procedure to a system of equations…

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自相关误差动态联立方程模型中若干有限信息估计量的比较AI 解读

Phoebus J. Dhrymes, R. Berner, D. Cummins, A Comparison of Some Limited Information Estimators for Dynamic Simultaneous Equations Models with Autocorrelated Errors, Econometrica, Vol. 42, No. 2 (Mar., 1974), pp. 311-332

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This paper deals with similarities and differences in the equations defining the full information maximum likelihood and three stage least squares estimators. It shows that the twp sets of equations are similar, the difference being that the two estimators purge the jointly dependent variables differently. Hence, even if three stage least squares is iterated, it will not give an estimator which is the same as the maximum likelihood one. On the other hand, it is quite…

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计量经济学：统计基础与应用AI 解读

1. Elementary Aspects of Multivariate Analysis.- 1.1 Preliminaries.- 1.2 Joint, Marginal, and Conditional Distributions.- 1.3 A Mathematical Digression.- 1.4 The Multivariate Normal Distribution.- 1.5 Correlation Coefficients and Related Topics.- 1.6 Estimators of the Mean Vector and Covariance Matrix and their Distribution.- 1.7 Tests of Significance.- 2. Applications of Multivariate Analysis.- 2.1 Canonical Correlations and Canonical Variables.- 2.2 Principal Components.-…

两阶段最小二乘估计量一次迭代的渐近性质AI 解读

In this article we obtain the asymptotic distribution of the first iterate of iterated two stage least squares; we demonstrate that this distribution is different from that of the usual two stage least squares estimator. Moreover, we show that the difference in the covariance matrices of their respective asymptotic distributions is, generally, neither positive nor negative semidefinite. In particular, we produce examples in which for some parametric configurations this…

两阶段最小二乘首次迭代估计量的渐近性质AI 解读

In this article we obtain the asymptotic distribution of the first iterate of iterated two stage least squares; we demonstrate that this distribution is different from that of the usual two stage least squares estimator. Moreover, we show that the difference in the covariance matrices of their respective asymptotic distributions is, generally, neither positive nor negative semidefinite. In particular, we produce examples in which for some parametric configurations this…

柯布—道格拉斯生产函数参数的无偏估计量构造AI 解读

1. IN MANY empirical investigations the geometric mean of observed factor shares serves as an estimator of the factor exponents in a Cobb-Douglas2 production function. This particular estimator is due to Klein [7, p. 194]. It is here shown that such an estimator is biased. Under certain conditions an alternative estimator is derived which is unbiased, sufficient, efficient, and consistent.