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

2014 ◽  
Author(s):  
Frederique Bec ◽  
Annabelle de Gaye
Keyword(s):  
Empirical Analysis ◽  
Oil Price ◽  
Forecast Errors ◽  
Price Forecast ◽  
Inflation Forecasts

scholarly journals Oil Price Fluctuations and Oil Consuming Sectors: An Empirical Analysis of Japan

2015 ◽  
Author(s):  
Farhad Taghizadeh Hesary ◽  
Ehsan Rasolinezhad ◽  
Yoshikazu Kobayashi
Keyword(s):  
Empirical Analysis ◽  
Oil Price ◽  
Price Fluctuations

scholarly journals Daqing Crude Oil Price Forecast Based on the ARIMA Model

2015 ◽  
Vol 8 (1) ◽  
pp. 457-462
Author(s):  
Li Quan
Keyword(s):  
Crude Oil ◽  
Arima Model ◽  
Oil Prices ◽  
Industrial Country ◽  
Oil Price ◽  
Crude Oil Price ◽  
Major Industrial Country ◽  
Price Forecast ◽  
Industrial Economy ◽  
Monthly Average

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.

AN EMPIRICAL ANALYSIS OF OIL PRICE SHOCKS IN THE INTERWAR PERIOD

1994 ◽  
Vol 32 (3) ◽  
pp. 486-497 ◽  
Author(s):  
W. Douglas Mcmillin ◽  
Randall E. Parker
Keyword(s):  
Empirical Analysis ◽  
Interwar Period ◽  
Oil Price ◽  
Oil Price Shocks ◽  
Price Shocks

The impact of rising international crude oil price on China's economy: an empirical analysis with CGE model

2007 ◽  
Vol 27 (4) ◽  
pp. 404 ◽  
Author(s):  
Ying Fan ◽  
Jian Ling Jiao ◽  
Qiao Mei Liang ◽  
Zhi Yong Han ◽  
Yi Ming Wei
Keyword(s):  
Crude Oil ◽  
Empirical Analysis ◽  
Oil Price ◽  
Cge Model ◽  
Crude Oil Price ◽  
The Impact ◽  
China’S Economy

Section II. Uncertainties in the public sector forecast

2003 ◽  
Vol 183 ◽  
pp. 41-42 ◽  
Keyword(s):  
Public Sector ◽  
Current Account ◽  
Important Variable ◽  
Output Growth ◽  
Forecast Errors ◽  
The Public ◽  
Inflation Forecasts ◽  
Error Range ◽  
Bank Of England ◽  
The Government

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.

scholarly journals Empirical Analysis of Oil price changes on Inflation in Nigeria

2021 ◽  
Vol 3 (3) ◽  
pp. 84-101
Author(s):  
Melemi Abatcha
Keyword(s):  
Empirical Analysis ◽  
Oil Price ◽  
Price Changes

scholarly journals Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting

2020 ◽  
Vol 2020 (089) ◽  
pp. 1-56
Author(s):  
Andrew C. Chang ◽  
◽  
Trace J. Levinson ◽  
Keyword(s):  
Forecast Errors ◽  
Time Varying ◽  
Open Market ◽  
Federal Open Market Committee ◽  
Forecast Revisions ◽  
Consumption Expenditures ◽  
Inflation Forecasts ◽  
Board Of Governors ◽  
Personal Consumption ◽  
Reserve System

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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