具有细尾的时间序列的简单非参数条件分位数估计

IF 2.1 4区经济学 Q2 ECONOMICS

Economics Letters Pub Date : 2023-09-14 DOI:10.1016/j.econlet.2023.111349

Qiao Wang

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引用次数: 0

摘要

在这项研究中，我们考虑了一个具有时间序列数据的非参数框架中的简单条件分位数估计。我们证明了绝对正则过程（β-混合）的简单估计量的一致性和渐近正态性。与基于检验函数的估计器相比，这种简单的估计员可以在细尾处获得更好的有限样本性能。有限样本模拟结果表明，在时间序列数据的细尾处，我们的简单估计器具有更好的有限样本性能。

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A simple nonparametric conditional quantile estimator for time series with thin tails

In this study, we consider a simple conditional quantile estimator in a nonparametric framework with time series data. We prove the consistency and asymptotic normality of our simple estimator for absolutely regular processes ( $β$ -mixing). This simple estimator can get better finite sample performances at thin tails than the check-function-based estimator. Finite sample simulation results show that our simple estimators have better finite sample performances at thin tails of time series data.

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来源期刊

Economics Letters ECONOMICS-

CiteScore

3.20

自引率

5.00%

发文量

348

审稿时长

30 days

期刊介绍： Many economists today are concerned by the proliferation of journals and the concomitant labyrinth of research to be conquered in order to reach the specific information they require. To combat this tendency, Economics Letters has been conceived and designed outside the realm of the traditional economics journal. As a Letters Journal, it consists of concise communications (letters) that provide a means of rapid and efficient dissemination of new results, models and methods in all fields of economic research.