.png){kind=icon}
返回
Nested forecast model comparisons: A new approach to testing equal accuracy
.png){kind=icon}
OA
AI
DOI：10.1016/j.jeconom.2014.06.016.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We develop methods for testing whether, in a finite sample, forecasts from nested models are equally accurate. Most prior work has focused on a null of equal accuracy in population basically, whether the additional coefficients of the larger model are zero. Our asymptotic approximation instead treats the coefficients as non-zero but small, such that, in a finite sample, forecasts from the small and large models are expected to be equally accurate. We derive the limiting distributions of tests of equal mean square error, and develop a bootstrap for inference. Simulations show that our procedures have good size and power properties. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Mean square error
Prediction
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
5.3K
被引数:
3.0W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容