Skip navigation

An empirical investigation on the temporal properties of China's GDP

An empirical investigation on the temporal properties of China's GDP

Chen, Yen-Hsiao, Quan, Lianfeng and Liu, Yang (2013) An empirical investigation on the temporal properties of China's GDP. China Economic Review, 27. pp. 69-81. ISSN 1043-951X (doi:10.1016/j.chieco.2013.07.007)

[thumbnail of Publisher's PDF] PDF (Publisher's PDF)
14751_QUAN_An_Empirical_Investigation_(pub_PDF)_2013.pdf - Published Version
Restricted to Repository staff only

Download (223kB)

Abstract

This paper employs a structural time series model designed with three components of stochastic seasonality, trigonometric expression of cyclicality and local linear trend to investigate the evolutionary process of China's GDP. In particular, the model is able to detect the stop–go feature of China's economic growth, i.e., growth cycle, as well as business cycle. The empirical result suggests that most variation in China's macroeconomic performance came from business cycle. The investigation of the three components along with historical events suggests that the Chinese economy had been largely influenced by political activities up to the early 1990s. In the mid-1990s China entered a period of stable and highly growing economy, thanks to the economic reform and the successful implementation of macroeconomic policies. However, since the mid-2000s China has become more sensitive to the turbulences in international markets. In the foreseeable future, the challenge facing China is a more volatile economy with possible slowdown in the economic growth, although the growth rate would still be high compared to developed economies.

Item Type: Article
Uncontrolled Keywords: Unobserved components, State space model, Output gap, Structural break, Five-Year Plan
Faculty / School / Research Centre / Research Group: Faculty of Business > Department of Accounting & Finance
Last Modified: 15 Oct 2016 07:19
URI: http://gala.gre.ac.uk/id/eprint/14751

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics