A comparison of state space and multiple regression for monthly forecasts: U.S. Fuel consumption |
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| Authors: | Kyungcho Bae Recent PhD graduate in Mineral Economics DeVerle Harris |
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| Institution: | (1) Department of Mining and Geological Engineering, University of Arizona, 95721 Tucson, Arizona, USA;(2) Department of Geoscience, University of Arizona, 95721 Tucson, Arizona, USA |
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| Abstract: | Monthly consumption forecasts for U.S. oil, natural gas, and coal are made using state space and multiple regression applied to the same data. These forecasts are compared with actual consumption for a test period. The forecasts made using state space are preferred to those made using multiple regression models for both expost and exante cases. The state space forecasts track data cycles better than do the regression forecasts. Average absolute forecast errors are less for the state space models than they are for the multiple regression models. |
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| Keywords: | Short-term forecasting Fuel consumption forecasts State space Comparison of forecasting methods |
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