基于零空间追踪算法的信贷投放对中国区域经济贡献度的比较研究

doi:10.16088/j.issn.1001-6600.2020.02.018

摘要/Abstract

摘要： 采用信号分解方法对时间序列分解提取出子成分及趋势,可以更好地研究时间序列的趋势性和周期性。以零空间追踪算法(NSP)和经验模态分解(EMD)方法为代表的信号提取方法已经被应用于经济、金融等时间序列研究中。一定时期内存、贷款与GDP的统计数据存在着随时间变动的波动性和趋势性特征。本文在研究信贷投放对于我国东北、中部、西部、东部地区的贡献度及各区域存贷比时,采用信号分解算法中的零空间追踪算法在分解出时间序列的趋势成分后再进行相关性分析和区域间对比,能够更好地展现信贷对于经济增长的作用,进而研究信贷投放对我国不同区域经济增长贡献度的差异。

关键词: 零空间追踪, 区域经济, 存贷比, 国内生产总值, 经济增长

Abstract: Signal separation approaches are often used for time series analysis because the extracted subcomponents of a complex signal can be helpful for analyzing its trend and periodicity. In recent years, with the emergence of adaptive signal separation algorithms, such as Null Space Pursuit (NSP) and Empirical Mode Decomposition (EMD), those methods have been widely used in the field of economic and financial time series analysis. The statistical data of loan/deposit and GDP have characteristics of developing trend and periodical fluctuation. Based on the NSP method, in this paper, a multi-scale study is conducted on the dynamic of regional economic disparity of 31 provinces in China during 2005-2017, and the volatility mechanism is investigated in the view of credit scale.

Key words: null space pursuit, regional economies, loan-to-deposit ratio, GDP, economic growth

中图分类号:

TN911.6

孔雯, 胡晰远. 基于零空间追踪算法的信贷投放对中国区域经济贡献度的比较研究[J]. 广西师范大学学报（自然科学版）, 2020, 38(2): 156-164.

KONG Wen, HU Xiyuan. A Comparative Study on the Contribution of Credit Allocationto Regional Economies of China Using Null Space Pursuit[J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(2): 156-164.

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