交通运输系统工程与信息

交通运输系统工程与信息 ›› 2009, Vol. 9 ›› Issue (4): 15-19 .

• 综合交通运输体系论坛 • 上一篇    下一篇

基于谱估计的中国物流业发展周期测定

贺兴东1 ;刘凯*1;邵伟如2   

  1. 1 北京交通大学 交通运输学院，北京 100044; 2 河北交通职业技术学院，石家庄 050091
  • 收稿日期:2009-04-22 修回日期:2009-05-21 出版日期:2009-08-25 发布日期:2009-08-25
  • 通讯作者: 刘凯
  • 作者简介:贺兴东（1981-），男，河北省衡水人，博士生.

Evaluation of Chinese Logistics Development Period Using Spectrum Estimation

HE Xing-dong 1; LIU Kai 1; SHAO Wei-ru2   

  1. 1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 2. Hebei Jiaotong Vocational & Technical College, Shijiazhuang 050091，China
  • Received:2009-04-22 Revised:2009-05-21 Online:2009-08-25 Published:2009-08-25
  • Contact: LIU Kai

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被引次数

8

摘要： 物流业作为宏观经济的组成部分，其发展存在一定的周期性波动，揭示物流业发展的周期规律，测定其波动周期，具有一定的理论和实践意义。中国物流统计数据缺乏，客观上限制了对其周期规律的研究，本文选取社会物流总额作为测度指标，设计了一种人工序列，解决了统计数据过短问题；谱估计法从频域角度揭示客观事物的时间特性，在研究时间序列周期波动方面具有时域分析法所不具备的优势，作者采用谱估计法对中国物流发展周期进行测定，检验了指标序列平稳性，分析了截断点参数灵敏度，比较了6种不同滞后窗下周期值，并检验了所测得周期的显著性。研究表明，中国物流业发展在0.001显著水平下存在2个周期波动，分别是周期约为15.2年的长周期强波动和周期约为3.4年的短周期弱波动。

关键词: 物流, 周期, 谱估计, 人工序列, 滞后窗

Abstract: As an important component of macro-economy, logistics experiences certain periodic fluctuation during its development. It is important to study the regularity of logistics fluctuation and evaluate its periods theoretically and practically. In this paper, total logistics amounts are chosen as evaluation index, and artificial time series are designed to solve the shortness of statistical data in Chinese logistics. Spectrum estimation theory depicts time characteristics in frequency domain thus has such benefit than time domain methods. This paper evaluates the period of Chinese logistics using spectrum estimation. Stationarity of artificial series is verified, parameter sensitivity of truncation point is analyzed, six periods with different delay window are compared, and significance of period evaluated is tested. Result indicates that there are two fluctuating periods in Chinese logistics development at a significance level of 0.001, the long period of 15.2 years with stronger fluctuation, and the short period of 3.4 years with weaker fluctuation respectively.

Key words: logistics, periods, spectrum estimation, artificial series, delay window

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