Year: 2011
Type: report
Abstract: This report provides an overview of the data used in the two Norwegian forest sector models NorFor and NTMIII. Both models are spatial partial equilibrium models describing the Norwegian forest and bioenergy sectors, including harvest of timber, processing in industry, demand of final products and trade and transport between regions and to/from Norway. Both models have endogenous prices of timber and wood products, but differ in the timber supply side, in the time horizon and the foresight information of agents. NTM has econometrically specified timber supply curves and no option of changing forest management and investment from the predetermined path. In NorFor, simulated growth and yields of all National Forest Inventory plots are included for several future management options. NTM is mostly applied for projections 10 – 20 years into future, while NorFor can currently be applied up to 100 years in future. NTM is a myopic model employing a recursive optimization, assuming that agents do not possess any information about the future beyond the current period. NorFor optimizes for all periods at once, and assumes that agents have perfect foresight.\n\n2008 is base year for both models. Different methods and source are applied to establish the data sets documented in this report. Public statistics from Statistics Norway are used for prices, international trade, harvest and energy consumption. Data from the National Forest Inventory sample plots are used to estimate county‐specific timber supply in NorFor. Elasticities of timber supply (only NTM) and demand for final products (both models) are based on econometric studies. Supply curves for harvest residues are based on available biomass and hauling costs. Plant level data in the pulp, paper and board industry are collected through interviews in the forest industries and annual reports. Input‐output coefficients in bioenergy production are based on other studies and own analyses of data from Statistics Norway and Enova. Costs for expanding district heating systems are based on the heating market model X‐Varme runs. Other parameters are forest management costs (only NorFor), transport costs and GDP growth as a basis for demand growth.\n\nData quality is an important factor in the quality of the results. Several aspects are related to data quality, as representativeness and data uncertainty. Data representativeness indicates how well the analyzed chain or products are represented, as the data often are taken from other geographical areas or adjacent products. Data limitations always exist, and models are simplified representations of the systems. However, consequences of data deficiency vary with the analyses. In general, data regarding production, prices and trade of wood, energy and forest industrial products based on figures from Statistics Norway are of high quality, whereas data of inputs and costs in the industry have weaker empirical basis and thus higher uncertainty.
Authors: Erik Trømborg, Hanne K. Sjølie
Language: English
Topic: Forest Management and Policy
Subfield: Forestry
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2347391994