Asymmetric and nonlinear pass-through of global crude oil price to China’s PPI and CPI inflation

Shaobo Long and Jun Liang

Economic Research-Ekonomska Istraživanja, 2018, vol. 31, issue 1, 240-251

Abstract: With China’s expanding import demand of crude oil and the gradually relaxing regulation of domestic oil prices, the global oil price is likely to affect China’s price level more closely. Based on an augmented Phillips curve framework, this article employs both the autoregressive distribution lag (ARDL) and nonlinear and asymmetric autoregressive distribution lag (NARDL) model to investigate pass-through effects of crude oil price on China’s producer prices index (PPI) and consumer prices index (CPI) in China. It is found that the impact of global oil price fluctuations to China’s PPI and CPI are asymmetrical in the long-run, and the long-term impacts of the rise in global oil prices on PPI and CPI are greater than the global oil price decline on PPI and CPI. However, the symmetric ARDL model fails to diagnose the impact of oil price to China’s PPI and CPI. Therefore, it is necessary to consider asymmetric relationship in the study of global oil price’s influence on China’s domestic prices.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/1331677X.2018.1429292 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:reroxx:v:31:y:2018:i:1:p:240-251

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rero20

DOI: 10.1080/1331677X.2018.1429292

Access Statistics for this article

Economic Research-Ekonomska Istraživanja is currently edited by Marinko Skare

More articles in Economic Research-Ekonomska Istraživanja from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().