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未知变化点下参数不稳定与结构变化的检验AI 解读

This paper considers tests for parameter instability and structural change with unknown change point. The results apply to a wide class of parametric models that are suitable for estimation by generalized method of moments procedures. The asymptotic distributions of the test statistics considered here are nonstandard because the change point parameter only appears under the alternative hypothesis and not under the null. The tests considered here are shown to have nontrivial…

一阶自回归／单位根模型的精确中位无偏估计AI 解读

First-order autoregressive/unit root models with independent identically distributed normal errors are considered, including those without an intercept, those with an intercept, and those with an intercept and time trend. The autoregressive parameter is allowed to lie in the interval (-1, 1], which includes the unit root case. Exactly median-unbiased estimators and exact confidence intervals of the autoregressive parameter are introduced. Corresponding exactly…

改进的异方差与自相关一致协方差矩阵估计量AI 解读

This paper considers a new class of heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators. The estimators considered are prewhitened kernel estimators with vector autoregressions employed in the prewhitening stage. The paper establishes consistency, rate of convergence, and asymptotic truncated mean squared error (MSE) results for the estimators when a fixed or automatic bandwidth procedure is employed. Conditions are obtained under which…

大萧条、石油价格冲击与单位根假说的进一步证据AI 解读

Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. Here a variation of Perron's test is considered in which the break point is estimated rather than fixed. The asymptotic distribution of the "estimated break point" test statistic is determined and the data considered by Perron are reanalyzed. The authors find…

异方差与自相关一致的协方差矩阵估计AI 解读

This paper is concerned with the estimation of covariance matrices in the presence of heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that are designed for this context depend upon the choice of a lag truncation parameter and a weighting scheme. No results are available regarding the choice of lag truncation parameter for a fixed sample size, regarding data-dependent automatic lag truncation parameters, or regarding the choice of…

非参数与半参数回归模型中级数估计量的渐近正态性AI 解读

This paper establishes the asymptotic normality of series estimators for nonparametric regression models. Gallant's Fourier flexible form estimators, trigonometric series estimators, and polynomial series estimators are prime examples of the estimators covered by the results. The results apply to a wide variety of estimates in the regression model under consideration, including derivatives and integrals of the regression function. The errors in the model may be homoskedastic…

计量经济应用中的检验功效AI 解读

This paper is concerned with the use of power properties of tests in econometric applications. Inverse power functions are defined. These functions are designed to yield summary measures of power that facilitate the interpretation of test results in practice. Simple approximations are introduced for the inverse power functions of Wald, likelihood ratio, Lagrange multiplier, and Hausman tests. These approximations readily convey the general qualitative features of the power…

计量经济模型的卡方诊断检验：理论AI 解读

This paper extends the Pearson chi-square testing method to nondynam ic parametric econometric models, in particular, to models with covar iates. The paper establishes the asymptotic distribution of the test statistic when the test statistic is based on data-dependent random cells of a general form and on an arbitrary asymptotically normal estimator. These results a re attained by extending recent probabilistic results for the weak convergence of empirical processes indexed…

非线性计量模型的一致性：通用一致大数定律AI 解读

A basic tool of modern econometrics is a uniform law of large numbers (LLN). It is a primary ingredient used in proving consistency and asymptotic normality of parametric and nonparametric estimators in nonlinear econometric models. Thus, in a well-known review article, Burguete, Gallant, and Sousa [8, p. 162] introduce a uniform LLN with the statement: "The following theorem is the result upon which the asymptotic theory of nonlinear econometrics rests. "So pervasive is the…

有界非对称损失下线性回归的最优中位数无偏估计AI 解读

This article considers optimal median-unbiased estimation in a linear regression model with the distribution of the errors lying in a subclass of the elliptically symmetric distributions. The generalized least squares (GLS) estimator is shown to be best for any monotone loss function, that is, any loss function that is nondecreasing as the magnitude of underestimation or overestimation increases. This includes bounded asymmetric loss functions. For the same loss functions, a…

广义 Wald 检验的渐近结果AI 解读

This paper presents conditions under which a quadratic form based on a g- inverted weighting matrix converges to a chi-square distribution as the sample size goes to infinity. Subject to fairly weak underlying conditions, a necessary and sufficient condition is given for this result. The result is of interest because it is needed to establish asymptotic significance levels and local power properties of generalized Wald tests (i.e., Wald tests with singular limiting…

弱误差假设下含单整或动态回归量的最小二乘回归AI 解读

This paper establishes consistency of least squares estimators in (i) a multiple regression model with integrated regressors and explosive, non-mixing errors, and (ii) a dynamic linear regression model with regressors and errors that may have infinite variances. In the former context, the asymptotic distribution of the least squares estimator also is obtained, in certain cases.

估计量的稳定性比较AI 解读

THIS PAPER INVESTIGATES a property of estimators called stability. The stability exponent of an estimator is a measure of the magnitude of the effect of any single observation in the sample on the realized value of the estimator. A number of reasons related to robustness suggest that often it is desirable for an estimator to be relatively insensitive to any particular observation in the sample, i.e., to have high stability. In addition, it is useful for diagnostic purposes…

关于线性模型中可行 GLS、准极大似然、稳健、自适应和谱估计量无偏性的札记AI 解读

Donald W. K. Andrews, A Note on the Unbiasedness of Feasible GLS, Quasi-Maximum Likelihood, Robust, Adaptive, and Spectral Estimators of the Linear Model, Econometrica, Vol. 54, No. 3 (May, 1986), pp. 687-698

最小二乘估计量的零一律结果AI 解读

The least squares estimator for the linear regression model is shown to converge to the true parameter vector either with probability one or with probability zero. In the latter case, it either converges to a point not equal to the true parameter with probability one, or it diverges with probability one. These results are shown to hold under weak conditions on the dependent random variable and regressor variables. No additional conditions are placed on the errors. The…