scholarly journals How Do Oil Price Forecast Errors Impact Inflation Forecast Errors? An Empirical Analysis from French and US Inflation Forecasts

Author(s):  
Frederique Bec ◽  
Annabelle de Gaye
Author(s):  
Farhad Taghizadeh Hesary ◽  
Ehsan Rasolinezhad ◽  
Yoshikazu Kobayashi

2015 ◽  
Vol 8 (1) ◽  
pp. 457-462
Author(s):  
Li Quan

Oil is the lifeblood of the industrial economy, oil prices are affected by many factors. China is a major industrial country, changes in the price of oil will affect many aspects of economic development, and therefore the price of crude oil research is extremely important. In this paper, monthly average prices of crude oil in Daqing from January 2000 to December 2010 are utilized to do the research. Based on ARIMA model by building software using EVIEWS, rule of oil price movements is found and a prediction of oil price is made using the data from the first 10 months of 2011.


1994 ◽  
Vol 32 (3) ◽  
pp. 486-497 ◽  
Author(s):  
W. Douglas Mcmillin ◽  
Randall E. Parker

2007 ◽  
Vol 27 (4) ◽  
pp. 404 ◽  
Author(s):  
Ying Fan ◽  
Jian Ling Jiao ◽  
Qiao Mei Liang ◽  
Zhi Yong Han ◽  
Yi Ming Wei

2003 ◽  
Vol 183 ◽  
pp. 41-42 ◽  

All forecasts are hedged around with uncertainties, and for some time we have been publishing error bands on our forecasts. The National Institute was the first mainstream forecaster to provide an indication of the chances that two key forecast variables, output growth and inflation, would be in particular ranges. The error ranges we used were calculated from past forecast errors and on the assumption (consistent with the data) that these errors were normally distributed. Shortly after we began publishing our probability bands, the Bank of England started to provide its own indication of the error range for its inflation forecasts and, some time later, for its projection of output growth. The Treasury, by contrast, provides no indication of the chance that the Government current account will be in any particular range although this is arguably the most important variable discussed in the Pre-budget Report.


2020 ◽  
Vol 2020 (089) ◽  
pp. 1-56
Author(s):  
Andrew C. Chang ◽  
◽  
Trace J. Levinson ◽  

We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's GDP forecast errors correlate with its GDP forecast revisions, particularly for forecasts made more than two weeks from the start of a FOMC meeting, implying GDP forecasts exhibit time-varying inefficiency between FOMC meetings. We find some weaker evidence for inefficient inflation forecasts.


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