特邀编辑导言第一部分:2018年耶鲁大学计量经济理论研讨会特刊，纪念彼得·c·b·菲利普斯

IF 1 4区经济学 Q3 ECONOMICS Econometric Theory Pub Date : 2022-10-01 DOI:10.1017/S0266466622000330

D. Andrews, Y. Kitamura, G. Kuersteiner

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引用次数: 0

摘要

随维数增加的时间序列协方差矩阵。在合理的横截面相关条件下，表明所提估计器达到了理想的收敛速度。给出了基于协方差矩阵估计的时间序列均值向量的推理过程，并得到了LM/ wald型统计量的适当归一化版本的渐近正态性结果。

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GUEST EDITORS’ INTRODUCTION PART ONE: SPECIAL DUAL ISSUE OF ECONOMETRIC THEORY ON YALE 2018 CONFERENCE IN HONOR OF PETER C. B. PHILLIPS

covariance matrix of time series with increasing dimension. Under a reasonable condition on cross-sectional dependence, it shows that the proposed estimator achieves desirable rates of convergence. It also offers inferential procedures for the mean vector of the time series based on the covariance matrix estimator, and obtains asymptotic normality results for suitably normalized versions of LM/Wald-type statistics.

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来源期刊

Econometric Theory MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY

CiteScore

1.90

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Since its inception, Econometric Theory has aimed to endow econometrics with an innovative journal dedicated to advance theoretical research in econometrics. It provides a centralized professional outlet for original theoretical contributions in all of the major areas of econometrics, and all fields of research in econometric theory fall within the scope of ET. In addition, ET fosters the multidisciplinary features of econometrics that extend beyond economics. Particularly welcome are articles that promote original econometric research in relation to mathematical finance, stochastic processes, statistics, and probability theory, as well as computationally intensive areas of economics such as modern industrial organization and dynamic macroeconomics.

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