摘要
本文以长记忆性的两种对数周期图方法为研究对象,在小样本下,从长记忆性的估计均值,估计精度和检验效果等方面比较分析了短期噪声对Geweke,Portert和Hidak(1983,GPH)和Andrews,Guggenberger(2003,AG)两种方法的影响及作用机理.结果发现当存在短期噪声时,尽管AG方法的大样本性质优于GPH方法,但其小样本性质并不十分稳健.主要而言,AG方法仅在较小负根情形下对GPH方法的修正效果明显;当噪声中含有较大负根时,存在过度修正问题;而当噪声中含有正根时,存在修正不足问题.此外,还研究了短期噪声下的带宽选择问题.通过对不同带宽下两种方法小样本性质的比较研究,发现在带宽极小处,两种方法的统计特征非常敏感;而带宽较大时,两种方法的统计特征不再收敛.笔者认为按照误差均方根最小选择带宽是一个相对可以接受的方案.
This paper makes research on two log-periodogram methods of long memory, that is the Geweke, Portert, Hidak （1983, GPH） and Andrews, Guggenberger （2003, AG） method; and takes impor- tance to the short-term noise effects on the estimates and its mechanism under finite sample, including mean and precision of the estimates, test performance. It turned out that although AG method has a better asymptotic property, its finite sample performance under short-term noise is not robust. Mostly, the modification effects of AG estimator are evident only when the short noise has small negative roots. However, in the presence of large negative roots and positive roots, it appears over-modification and under-modification respectively. In addition, bandwidth choice under short-term noise is also studied by comparing the finite sample property in presence of different sample. Experiments found that the property of two methods is very sensitive in small bandwidth, and is not convergent in large bandwidth. The author recommends that the minimum RMSE criterion is a relatively acceptable choice.
出处
《数理统计与管理》
CSSCI
北大核心
2014年第2期276-285,共10页
Journal of Applied Statistics and Management
基金
教育部人文社会科学研究青年基金(12YJC790028)
中央财经大学科研创新团队支持计划资助
关键词
短期噪声
长记忆性
对数周期图方法
小样本
short-term noise, long memory, log-periodogram method, finite sample
