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Nonparametric Time-Series Estimation of Joint DGP, Conditional DGP, and Vector Autoregression

联合及条件数据生成过程与向量自回归的非参数时间序列估计

In this paper we develop nonparametric estimators of the joint time series data generating process (DGP) of ( x t , y t ) at different t -values, of conditional DGP, of the conditional mean of x t given the past values of x and y , and, more generally, the conditional mean of ( x t , y t ) given their past values (vector autoregression). We establish, among other results, the central limit theorems for these estimators under far weaker mixing conditions than those used in…

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On the Robustness of LM, LR, and W Tests in Regression Models

回归模型中 LM、LR 与 Wald 检验的稳健性

In this paper we show that, in the small sample case, while the LR test is robust, the LM and W tests are not robust when the errors are Student t. For the large sample, however, all three tests are found to be robust. A variation of the W test is also considered and it turns out to be nonrobust. The implications of assuming the errors to be distributed as multivariate Student t, rather than multivariate normal, are also discussed. It is found that not all of Evans and…

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The Exact Mean of the Two-Stage Least Squares Estimator of the Structural Parameters in an Equation Having Three Endogenous Variables

含三个内生变量方程中结构参数两阶段最小二乘估计量的精确均值

Aman Ullah, A. L. Nagar, The Exact Mean of the Two-Stage Least Squares Estimator of the Structural Parameters in an Equation Having Three Endogenous Variables, Econometrica, Vol. 42, No. 4 (Jul., 1974), pp. 749-758

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Estimation of Seemingly Unrelated Regressions with Random Coefficients

随机系数似乎不相关回归的估计

This article deals with the problem of estimating the set of seemingly unrelated regressions (SUR) when the regression coefficients are random. In the article, an estimator has been proposed which is consistent and has the same asymptotic normal distribution as the Aitken generalized least squares estimator which assumes the covariance matrix to be known. Further, it has been shown that the proposed estimator is asymptotically more efficient than Zellner's SUR estimator…

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Estimation of Seemingly Unrelated Regressions with Random Coefficients

随机系数似不相关回归的估计

This article deals with the problem of estimating the set of seemingly unrelated regressions (SUR) when the regression coefficients are random. In the article, an estimator has been proposed which is consistent and has the same asymptotic normal distribution as the Aitken generalized least squares estimator which assumes the covariance matrix to be known. Further, it has been shown that the proposed estimator is asymptotically more efficient than Zellner's SUR estimator…

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