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对 Kabaila《模型选择对置信区域和预测区域的影响》的评论AI 解读

In this comment, I first want to offer a few general remarks on the problems caused by nonuniformity in the convergence of coverage probabilities as pointed out in Kabaila's (1995) very stimulating paper. Second, I also argue that within the context of set estimation after model selection one typically will be more interested in conditional coverage probabilities than in unconditional ones. Concentrating on the last example of Section 2 in Kabaila, I then illustrate how a…

模型选择对置信区域与预测区域的影响AI 解读

Pötscher (1991, Econometric Theory 7, 163–181) has recently considered the question of how the use of a model selection procedure affects the asymptotic distribution of parameter estimators and related statistics. An important potential application of such results is to the generation of confidence regions for the parameters of interest. It is demonstrated that a great deal of care must be exercised in any attempt at such an application. We also consider the effect of model…

单方程中外生变量系数估计量的若干精确结果AI 解读

This paper is devoted to a detailed examination of the exact sampling properties of the instrumental variables (IV) estimator of the vector of coefficients on the exogenous variables in a single structural equation. The first two moments of a linear combination of the elements of this estimator and the joint distribution of these elements are considered. Estimable bounds for the first moment that can readily be incorporated into any IV estimation package are provided. The…

线性回归中突变的最小绝对偏差估计AI 解读

This paper develops the asymptotic theory for least absolute deviation estimation of a shift in linear regressions. Rates of convergence and asymptotic distributions for the estimated regression parameters and the estimated shift point are derived. The asymptotic theory is developed both for fixed magnitude of shift and for shift with magnitude converging to zero as the sample size increases. Asymptotic distributions are also obtained for trending regressors and for…

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近积分 AR 过程中若干检验统计量的渐近分布AI 解读

Asymptotic distributions of some test statistics in near-integrated AR processes are studied. Some exact formulas for the distribution functions are given as well as approximative results obtained by saddlepoint approximation techniques.

人工回归在某些微观计量模型中的使用AI 解读

Conditional moment tests check to see whether or not population moment equalities, implied by the null model specification, hold approximately in the sample. Asymptotically valid conditional statistics can easily be calculated from the output of a so-called outer product of the gradient (OPG) artificial regression. However, several studies have now found that this OPG variant exhibits extremely poor finite sample behavior and that significant improvements can be made by…

非线性 ARCH 时间序列的非参数估计与识别：强收敛和渐近正态性AI 解读

We consider the estimation and identification of the functional structures of nonlinear econometric systems of the ARCH type. We employ nonparametric kernel estimates for the nonlinear functions characterizing the systems, and we establish strong consistency along with sharp rates of convergence under mild regularity conditions. We also prove the asymptotic normality of the estimates.

动态计量模型的检验、涵盖与模拟AI 解读

We define, in a dynamic framework, the notions of binding functions, images, reflecting sets, indirect identification, indirect information, and encompassing. We study the properties of the notion of encompassing when the true distribution does not necessarily belong to one of the two competing models of interest. In this context we propose various test procedures of the encompassing hypothesis. Some of these procedures are based on simulations, and some of them are linked…

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相依异质过程的大数定律AI 解读

This paper provides weak and strong laws of large numbers for weakly dependent heterogeneous random variables. The weak laws of large numbers presented extend known results to the case of trended random variables. The main feature of our strong law of large numbers for mixingale sequences is the less strict decay rate that is imposed on the mixingale numbers as compared to previous results.

基于 M 估计量的单位根检验AI 解读

This paper considers unit root tests based on M estimators. The asymptotic theory for these tests is developed. It is shown how the asymptotic distributions of the tests depend on nuisance parameters and how tests can be constructed that are invariant to these parameters. It is also shown that a particular linear combination of a unit root test based on the ordinary least-squares (OLS) estimator and on an M estimator converges to a normal random variate. The interpretation…

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变量测量误差与协整AI 解读

In this article it is shown how the cointegration or joint trending behavior of economic time series helps to alleviate the errors in variables problem.