Timber market Model for policy-Based Analysis

TiMBA is a partial economic equilibrium model for the global forest products market. The market equilibrium is subject to market clearance and constraints balancing necessary raw materials and produced wood products and limiting the trade. The model structure distinguishes between raw, intermediate and end products. TiMBA differentiates three types of roundwood (wood fuel, coniferous and non-coniferous industrial roundwood), two additional raw products for paper production (other fibre pulp and waste paper), two intermediate products (mechanical and chemical pulp) and eight finished products (coniferous and non-coniferous sawnwoods, veneer sheets and plywood, particle board, fibreboard, newsprint, printing and writing paper, and other paper and paperboards). Except for sawnwoods, intermediate and end products are produced from a mix of coniferous and non-coniferous industrial roundwood. Scenario simulations with TiMBA are guided by parameters and assumptions shaping future developments. In the model framework, wood products are implicitly treated as perfect substitutes, regardless of their origin, as long as they belong to the same commodity group.

TiMBA offer analytical support throughout the different phases of the policy cycle in the forest sector. The model outcomes help policymakers to assess complex interactions between markets, resources, and policy interventions in a transparent and data-driven manner. TiMBA use scenario analysis, allowing policymakers to evaluate the potential impacts of different regulatory pathways or legislative proposals, which are otherwise difficult to grasp in their complexity.

During agenda setting, the model results can support the help identification of emerging challenges by projecting market trends and resource needs. In policy formulation, different model runs support the comparison of policy options by simulating their impacts on production, trade and forest resource use. TiMBA can contribute to legitimation (or non-legitimation) of policies by providing evidence-based assessment for proposed measures.

During implementation and evaluation, the analysis can guide practical decisions by highlighting possible market responses and assess whether the policy implementation would achieve intended outcomes, helping to anticipate and manage project disruptions. For policy maintenance, succession, or termination, the model can inform strategic decisions by modeling long-term effects under evolving market conditions.

TiMBA calculates production, imports, exports, consumption, and prices for the forest-based sector, taking into account available forest resources, costs, technology, and trade constraints. In each period, the recursive market model consists of a static and a dynamic phase. During the static phase, TiMBA determines a global equilibrium across products and countries for a given year. The optimization problem is solved annually by maximizing economic welfare, defined as the sum of producer and consumer economic surplus. In the dynamic phase, changes in equilibrium conditions, such as shifts in parameters like growing GDP, population, or costs, are updated from one period to the next.

Forest module

The development of forest area is simulated exogenously using the environmental Kuznets curve (EKC) approach (Kuznets 1955; Grossmann and Krueger 1991). This concept describes an inverted U-shaped relationship between income development and deforestation. Initially, as GDP per capita rises, deforestation increases until it reaches a turning point. Beyond this point, further increases in GDP per capita result in a decreasing rate of deforestation (Panayotou 1993). Forest stock growth is linked to the area’s development.

Supply module

The country-specific supply of roundwood depends on wood prices and forest resources development, which is determined by the growth dynamics of the forest stock, the change in forest area, and harvested volumes.

Demand module

The country-level demand for wood-based products is governed via product-specific elasticities by income and endogenous price development.

Trade module

In TiMBA, each country imports from and exports to one World market. The level of trade depends on the trade volumes of the previous year, domestic supply and demand for a certain product as well as the international competitiveness of the respective country. Trade is further determined transport cost and other trade barriers.

Manufacturing

The production of intermediate and final products is influenced by manufacturing costs and input-output coefficients. Pre-calibrated input-output coefficients indicate the quantity of primary or intermediate inputs required to produce one unit of an intermediate or final product. Manufacturing costs are all costs of inputs except raw materials, implicitly covering expenses for labor, energy, capital, and other materials.

Price Formation

Prices are determined endogenously through market clearing at the global and national level and prices adjust to balance supply, demand, and trade, ensuring market equilibrium

• GDP and development
• Population and development
• Price elasticities
• GDP elasticities
• Forest stock elasticities
• Forest area elasticity
• Production quantity of all products considered Import quantity of all products considered
• Export quantity of all products considered
• Forest area quantity
• Forest stock quantity
• Ratio inventory drain to harvest
• Ad valorem tax rates
• Freight costs
• Input / Output Coefficients (pre-calibrated)
• Manufacturing costs (pre-calibrated)
• Product prices (pre-calibrated)

Sources:

The FAOSTAT Database on Forestry Production and Trade (FAOSTAT 2022), along with the FAO Global Forest Resources Assessment (FRA) (FAO 2022) and the World Bank Development Indicators (World Bank 2022), are essential data sources. In its standard form, demand price and income elasticities are primarily derived from Morland et al. (2018). TiMBA incorporates GDP and population growth projections from the Shared Socioeconomic Pathways scenario “Middle of the road” (SSP2), as presented by Riahi, K et al. (2017) (These projections will be updated as soon as the data are available). Estimates for technology developments, specifically input-output coefficients and manufacturing costs, are based on historical trends from 1993 to 2020. Trade inertia and cost information is grounded in WTO data as featured in the Global Forest Products Model (Buongiorno 2015, 2021). Ad Valorem tax rates are updated according to Schier et al. (2025).

Model input data are optimized processed in a separate model approach, called model calibration. A baseline scenario with SSP2 developments starting in 2020 is delivered with the TiMBA model.