Why Chinese central bank should focus on headline inflation

2014 ◽  
Vol 64 (Supplement-2) ◽  
pp. 39-51
Author(s):  
Zhifang Su

In this paper, we explore the change in short-term headline-core inflation dynamic relationship using threshold error correction model, and explain why the Chinese central bank should focus on headline inflation when conducting monetary policy. The results find that: (1) the deviation between core and headline inflation is eliminated mainly through reverting core inflation to headline inflation in high inflation period, indicating that headline inflation catches the long-term trend of inflation much better than core inflation does; (2) movements in food price have become a significant source of public’s inflation expectations and food inflation persistence is increasing, reflecting that the rising food price may not have been a transient phenomenon but has become a part of the long-term trend of inflation. The above conclusions imply Chinese central bank should not implement the monetary policy based on core inflation excluding food price but should make a certain response to the surging food price.

Author(s):  
Albert E. Beaton ◽  
James R. Chromy
Keyword(s):  

2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.


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