Econometric versus Univariate and Bivariate Time-Series Forecasts: The Case of Softwood Lumber Imports
Abstract:An econometric model based on housing starts, prices, and past imports; a univariate time-series model using past imports only; and a bivariate time-series model of imports and housing starts were used to forecast United States softwood lumber imports. Experiments were performed to test the forecasting accuracy of each model assuming either perfect knowledge of the future value of determining variables, or complete ignorance. These experiments were repeated to forecast 1 month or 3 months ahead. The results suggested that the bivariate time-series model based on lumber imports and housing starts was the most useful from the point of view of pure forecasting. It was at least as accurate as the econometric model, both in 1-month and 3-month forecasts, and it required much less information. Under comparable assumptions it was superior to the univariate model for 1-month forecasts. The accuracy of the bivariate model improved significantly for 3-month forecasts if good forecasts of housing starts were available. The econometric model was more suitable for policy analysis. Future advances would be possible by a theoretical synthesis of the multivariate and econometric approaches. Forest Sci. 30:194-208.
Document Type: Journal Article
Affiliations: Project Assistant (Assistant Professor, Department of Economics, Georgetown University, Washington, DC), Department of Forestry, University of Wisconsin, Madison, WI 53706
Publication date: March 1, 1984
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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