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A Proof that Both the Bias and the Mean Square Error of the Two-Stage Least Squares Estimator are Monotonically Non-Increasing Functions of Sample Size

两阶段最小二乘估计量的偏差与均方误差随样本量单调不增的证明

A. D. Owen, A Proof that Both the Bias and the Mean Square Error of the Two-Stage Least Squares Estimator are Monotonically Non-Increasing Functions of Sample Size, Econometrica, Vol. 44, No. 2 (Mar., 1976), pp. 409-411

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An Instrumental Variable Approach to Full Information Estimators for Linear and Certain Nonlinear Econometric Models

线性与若干非线性计量模型全信息估计量的工具变量方法

FIML is shown to be an instrumental variables estimator where the instruments embody all the over-identifying a priori restrictions. FIML is compared to the two alternative estimators 3SLS and full information instrumental variables. 3SLS differs from FIML in not using all a priori restrictions in forming the instruments. The full information instrumental variables estimator when iterated to convergence yields the FIML estimate. For the case of nonlinearity in the parameters…

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A Comparative Monte Carlo Study of the Properties of Econometric Estimators

计量经济估计量性质的蒙特卡洛比较研究

Together with straightforward simulation, this study makes use of antithetic-variate and control-variate techniques in investigating the properties of econometric estimators. It is shown that when the covariances between the disturbances are small, the results on the relative standing of the estimators are indeterminate; but when they are sufficiently large, full-information methods are superior to single-equation methods. FIML gave the best performance and 2SLS was the best…

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Gram-Charlier Approximations Applied to t Ratios of k-Class Estimators

This paper obtains Edgeworth or Gram-Charlier expansions for the t ratio of instrumental variable and k-class estimators, and uses them to give approximations to the confidence intervals obtained from these t ratios. These confidence intervals for large sample size are more accurate than the usual asymptotic confidence interval. Charlier expansions is applied to the t ratio of 2SLS and non-stochastic k-class estimators. Previous general theorems in this field, with the…

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Errors in Variables: A Consistent Estimator with Smaller MSE in Finite Samples

变量测量误差:有限样本均方误差更小的一致估计量

This article develops and examines the small sample properties of alternative estimators when the data is suspected to contain measurement error. Two types of estimators are considered: (1) a linear combination of the OLS and instrumental variable (IV) estimators and (2) a method of choosing between the OLS and IV estimators on the basis of sample information. Large sample approximations are used to derive optimal procedures that are then evaluated by Monte Carlo experiments…

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Iterative Instrumental Variables Method and Estimation of a Large Simultaneous System

迭代工具变量法与大型联立方程系统的估计

The estimation method proposed here offers a way to achieve consistent estimates of simultaneous systems for which the number of observations falls short of the number of predetermined variables in the system as a whole. This method, called the iterative instrumental variables (IIV) method, can be described as iterative use of the instrumental variable interpretation of the 2SLS as given by Klein. A discussion is presented on convergence of the iterative procedure and the…

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Errors in Variables: A Consistent Estimator with Smaller MSE in Finite Samples

变量测量误差:有限样本中均方误差更小的一致估计量

This article develops and examines the small sample properties of alternative estimators when the data is suspected to contain measurement error. Two types of estimators are considered: (1) a linear combination of the OLS and instrumental variable (IV) estimators and (2) a method of choosing between the OLS and IV estimators on the basis of sample information. Large sample approximations are used to derive optimal procedures that are then evaluated by Monte Carlo experiments…

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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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An Asymptotic Expansion of the Distribution of the Limited Information Maximum Likelihood Estimate of a Coefficient in a Simultaneous Equation System

联立方程系统中系数的有限信息最大似然估计分布的渐近展开

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…

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Alternative Tests of Independence between Stochastic Regressors and Disturbances: Finite Sample Results

随机解释变量与扰动独立性的替代检验:有限样本结果

RegWuTest performs a Wu (or Durbin-Wu-Hausman) specification test on a regression just estimated by instrumental variables. Because it works off the last regression, there are no parameters. Wu(1973), Alternative tests of independence between stochastic regressors and disturbances, Econometrica vol 42, 529-546.(This abstract was borrowed from another version of this item.)

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A Consistent Estimator of the Slope in a Regression Model with Errors in the Variables

变量含测量误差的回归模型中斜率的一致估计

Consistent estimators for the slope coefficient in a regression model, where both variables are subject to errors, do not exist without some restrictions on the model. When the serial correlation of (lag 1) of the regression is known to be nonzero, one can obtain extra information from the first differences and get a consistent estimator for the slope. It turns out that this estimator is (asymptotically) equivalent to an estimator which uses as instrumental variable the…

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A Consistent Estimator of the Slope in a Regression Model with Errors in the Variables

变量含测量误差回归模型中斜率的一致估计

Consistent estimators for the slope coefficient in a regression model, where both variables are subject to errors, do not exist without some restrictions on the model. When the serial correlation of (lag 1) of the regression is known to be nonzero, one can obtain extra information from the first differences and get a consistent estimator for the slope. It turns out that this estimator is (asymptotically) equivalent to an estimator which uses as instrumental variable the…

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The Bias of the Two-Stage Least Squares Estimator

两阶段最小二乘估计量的偏差

This article derives the bias of the two-stage least squares estimator to the order of T-2, T being the number of observations. It is found that when the degree of overidentification in the equation concerned is unity, the 2SLS bias is zero to this order of approximation.

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Small-Sample Estimation of a Structural Equation with Autocorrelated Errors

自相关误差下结构方程的小样本估计

Many time series models have autocorrelated errors. A further problem may be that some of the right-hand variables are correlated with the error. Using Monte Carlo methods we investigated several estimators of such a model. We found that a transformation to correct the autocorrelation often improved matters, but that techniques to correct the other problems such as instrumental variables were usually ineffective. In many cases ordinary least squares had the smallest mean…

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The Bias of the Two-Stage Least Squares Estimator

两阶段最小二乘估计量的偏误

This article derives the bias of the two-stage least squares estimator to the order of T-2, T being the number of observations. It is found that when the degree of overidentification in the equation concerned is unity, the 2SLS bias is zero to this order of approximation.

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Comparison of Some Two-Sample Location Tests for Non-Normal Alternatives

非正态备择下若干两样本位置检验的比较

Summary Small to moderate sample size performance of the two-sample χ2, Kolmogorov–Smirnov, Wilcoxon and F-tests of location is investigated in a class of non-normal distributions through Monte Carlo sampling. The class of distributions is that of mixtures of two normal distributions with different means and/or variances. The cases of mixtures considered represent part of the regions for types I, II, IV, VI and VII of the Pearson system of continuous distributions. The…

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Econometrics: Statistical Foundations and Applications

计量经济学:统计基础与应用

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.-…

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Asymptotic Properties of an Iterate of the Two-Stage Least Squares Estimator

两阶段最小二乘估计量一次迭代的渐近性质

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…

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Measures of Association for Cross Classifications, IV: Simplification of Asymptotic Variances

交叉分类的关联度量(四):渐近方差的简化

The asymptotic sampling theory discussed in our 1963 article [3] for measures of association presented in earlier articles [1, 2] turns on the derivation of asymptotic variances that may be complex and tedious in specific cases. In the present article, we simplify and unify these derivations by exploiting the expression of measures of association as ratios. Comments on the use of asymptotic variances, and on a trap in their calculation, are also given.

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Asymptotic Properties of an Iterate of the Two-Stage Least Squares Estimator

两阶段最小二乘首次迭代估计量的渐近性质

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…

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