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Inside the crystal ball: new approaches to predicting the gasoline price at the pump
- Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore a range of new forecasting approaches for the retail price of gasoline and compare their accuracy with the no-change forecast. Our key finding is that substantial reductions in the mean-squared prediction error (MSPE) of gasoline price forecasts are feasible in real time at horizons up to two years, as are substantial increases in directional accuracy. The most accurate individual model is a VAR(1) model for real retail gasoline and Brent crude oil prices. Even greater reductions in MSPEs are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the EIA gasoline price forecasts and the gasoline price expectations in the Michigan Survey of Consumers. We also show that as much as 39% of the decline in gas prices between June and December 2014 was predictable.
Author: | Christiane BaumeisterORCiDGND, Lutz KilianGND, Thomas K. Lee |
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URN: | urn:nbn:de:hebis:30:3-363815 |
URL: | http://ssrn.com/abstract=2550731 |
Parent Title (English): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 500 |
Series (Serial Number): | CFS working paper series (500) |
Publisher: | Center for Financial Studies |
Place of publication: | Frankfurt, M. |
Document Type: | Working Paper |
Language: | English |
Year of Completion: | 2015 |
Year of first Publication: | 2015 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2015/01/21 |
Tag: | Brent; Retail gasoline price; WTI; expert forecasts; forecast combination; oil market; real-time data; survey expectations |
Issue: | January 13, 2015 |
Page Number: | 46 |
HeBIS-PPN: | 354667122 |
Institutes: | Wirtschaftswissenschaften / Wirtschaftswissenschaften |
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS) | |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
JEL-Classification: | C Mathematical and Quantitative Methods / C5 Econometric Modeling / C53 Forecasting and Other Model Applications |
Sammlungen: | Universitätspublikationen |
Licence (German): | Deutsches Urheberrecht |