Projecting county pulpwood production with historical production and macro-economic variables |
| |
| Affiliation: | 1. USDA Forest Service, Southern Research Station, 4700 Old Kingston Pike, Knoxville, TN 37919, United States;2. University of Tennessee Institute of Agriculture, Department of Agricultural and Resource Economics, Knoxville, United States;1. Department of Applied Economics (Mathematics), Universidad de Málaga, Campus El Ejido s/n, 29071 Málaga, Spain;2. Department of Mathematics, University of Pinar del Río, Pinar del Río, Cuba;1. Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI, USA;2. Observatory for European Forests, European Forest Institute, EFICENT-OEF, Nancy, France;3. Forest Economics Laboratory, INRA, Nancy, France;1. Sustainable Forest Management Research Institute, INIA-CIFOR & School of Agricultural Engineering of the University of Valladolid, Avda. Madrid s/n, 34004 Palencia, Spain;2. European Forest Institute, Mediterranean Regional Office, EFIMED, Recinte Històric de Sant Pau, Pavelló de Sant Leopold, St. Antoni M. Claret, 167, 08025 Barcelona, Spain;3. LEMNA, University of Nantes, 44 322 Nantes Cedex, France;4. Department of Economic Sciences, University of Warsaw, 00241 Warsaw, Poland;5. Autonomous University of Barcelona, Institut de Ciencia i Tecnologia Ambientals, 08193 Bellatera, Spain;6. National Institute for Agriculture and Food Research and Technology (INIA), Forest Research Centre (CIFOR), Ctra. de la Coruña, km. 7.5, 28040 Madrid, Spain;1. Department of Applied Mathematics and Informatics, Faculty of Economics, University of South Bohemia, České Budějovice, Czech Republic;2. BioSP, INRA, 84914, Avignon, France;4. Institute of Physico-Chemical and Biological Problems in Soil Science, the Russian Academy of Sciences, Pushchino, Russia;5. Centre for Stochastic Geometry and Advanced Bioimaging, Department of Mathematics, Aarhus University, 8000 Aarhus C, Denmark;1. Economics and Management College, Northwest Agricultural and Forestry University, Shaanxi 712100, China;2. Economics Department at the University of Montana, Missoula, MT 59812-5472, United States;3. China National Forestry Economics and Development Research Center, Beijing 100714, China;4. China Agricultural University, Beijing 100083, China;1. Département de biologie, chimie et géographie, Centre for Northern Studies, Université du Québec à Rimouski, 300 allée des Ursulines, Rimouski, QC G5L 3A1, Canada;2. Direction de la faune terrestre et de l’avifaune, Ministère des Forêts, de la Faune et des Parcs du Québec, 880 chemin Sainte-Foy, Québec, QC G1S 4X4, Canada;3. Département de biologie, chimie et géographie, Centre for Northern Studies and Centre for Forest Research, Université du Québec à Rimouski, 300 allée des Ursulines, Rimouski, QC G5L 3A1, Canada |
| |
| Abstract: | We explored forecasting of county roundwood pulpwood production with county-vector autoregressive (CVAR) and spatial panel vector autoregressive (SPVAR) methods. The analysis used timber products output data for the state of Florida, together with a set of macro-economic variables. Overall, we found the SPVAR specification produced forecasts with lower error rates compared to CVAR specifications. Nonetheless, high forecast errors across counties revealed the uncertainty associated with projecting volumes of county pulpwood production. |
| |
| Keywords: | County pulpwood forecast Vector autoregressive Spatial panel VAR |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
