.png){kind=icon}
返回
An Adaptive Kernel-Based Structural Change Test for Copulas
.png){kind=icon}
PRE
AI
DOI：10.1080/07350015.2024.2422980.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article proposes a structural change test for copula models based on the kernel smoothing method. The proposed approach enables adaptable estimation of the dynamic marginal distributions, either parametrically or semi-parametrically. The test statistic is formulated via the weighted quadratic distance between the local smoothing copula and the empirical copula function, using pseudo-observations of marginal distributions. The test statistic is pivotal with an asymptotic standard Normal distribution, irrespective of the marginal distributions, parameters, and estimations, and is consistent against a wide range of smoothly transitioning structural changes as well as abrupt structural breaks for copula models. Monte Carlo simulations show that the test performs well in finite samples and outperforms existing tests in the case of periodic changes.
Keyword:
Kernel smoothing
Pseudo-observation
Structural change
Weighted empirical process
期刊
J
IF:
2.5
论文数:
96
被引数:
9.1K
机构
引用论文
Testing for Smooth Structural Changes in Time Series Models via Nonparametric Regression通过非参数回归测试时间序列模型中的平滑结构变化.png)
ECONOMETRICA
ECONOMETRICAIF7.1
PREAI
分享收藏
查看更多内容