A.5.3.2 Model structure and data
GTEM is a multiregion, multisector, dynamic, general equilibrium model of the global economy. The key structural features of GTEM include:
• A computable general equilibrium (CGE) framework with a sound theoretical foundation based on micro-economic principles that accounts for economic transactions occurring in the global economy. The theoretical structure of the model is based on the optimizing behavior of individual economic agents (e.g., firms and households), as represented by the model equation systems, the database and parameters.
• A recursively dynamic analytical framework characterized by capital and debt accumulation and endogenous population growth, which enables the model to account for transactions between sectors and trade flows between regions over time. As a dynamic model, it accounts for the impacts of changes in labor force and investment on a region's production capabilities.
• The representation of a large number of economies (up to 87 regional economies corresponding to individual countries or country groups) that are linked through trade and investment flows, allowing for detailed analysis of the direct as well as flow-on impacts of policy and exogenous changes for individual economies. The model tracks intraindustry trade flows as well as bilateral trade flows, allowing for detailed trade policy analysis.
• A high level of sectoral disaggregation (up to 67 broad sectors, with an explicit representation of 13 agricultural sectors) that helps to minimize likely biases that may arise from an undue aggregation scheme.
• A bottom-up "technology bundle" approach adopted in modeling energy intensive sectors, as well as interfuel, interfactor and factor-fuel substitution possibilities allowed in modeling the production of commodities. The detailed and explicit treatment of the energy and energy related sectors makes GTEM an ideal tool for analysing trends and policies affecting the energy sector.
• A demographic module that determines the evolution of a region's population (and hence the labor supply) as a function of fertility, migration and mortality, all distinguished by age group and/or gender.
• A detailed greenhouse gas emissions module that accounts for the major gases and sources, incorporates various climate change response policies, including international emissions trading and quota banking, and allows for technology substitution and uptake of backstop technologies.
For each regional economy, the GTEM database consists of six broad components: the input-output flows; bilateral trade flows; elasticities and parameters; population data; technology data; and anthropogenic greenhouse gas emissions data. For the input-output and bilateral trade flows data, and the key elasticities and parameters, the GTAP version 6 database (see https://www.gtap.agecon.purdue .edu/databases/v6/default.asp) has been adapted. The databases for population, energy technology and anthropogenic greenhouse gas emissions, have been assembled by ABARE according to GTEM regions using information from a range of national and international sources. The base-year for |
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GTEM is 2001. For this exercise, the model database has been aggregated to 21 regions that correspond to the five IAASTD sub-global regions and to 36 commodities that include 12 agricultural sectors and one fisheries sector.
GTEM equations are written in log-change forms and the model is solved recursively using the GEMPACK suite of programs (http://www.monash.edu.au/policy/gempack.htm). For IAASTD modeling purposes, the GTEM projection period extends to 2050. The model simulation provides annual projections for many variables including regional gross national product, aggregate consumption, investment, exports and imports; sectoral production, employment and other input demands; final demand and trade for commodities; and greenhouse gas emissions by gas and by source.
A detailed description of the theoretical structure of GTEM can be found in Pant (2002, 2007). Pezzey and Lam-bie (2001) describe the key structural features of GTEM and Ahammad and Mi (2005) discuss an update on the modeling of GTEM agricultural and forestry sectors.
A.5.3.3 Application
GTEM has been applied to a wide range of medium- to long-term policy issues or special events. These include climate change response policy analysis (e.g., Ahammad et al., 2006; Ahammad et al., 2004; Fisher et al., 2003; Heyhoe, 2007; Jakeman et al., 2002; Jakeman et al., 2004; Jotzo, 2000; Matysek et al., 2005; Polidano et al., 2000; Tulpulé et al., 1999); global energy market analysis (e.g., Ball et al., 2003, Fairhead et al., 2002; Heaney et al., 2005; Mélanie et al., 2002; Stuart et al., 2000); and on agricultural trade liberalisation issues (e.g., Bull and Roberts 2001; Fairhead and Ahammad, 2005; Freeman et al., 2000; Nair et al., 2005; Nair et al., 2006; Roberts et al., 1999; Schneider et al., 2000).
A.5.3.4 Uncertainty
(See Table A.5.3.4)
A.5.4 WATERSIM
A.5.4.1Introduction
Watersim is an integrated hydrologic and economic model, written in GAMS, developed by IWMI with input from IF-PRI and the University of Illinois. It seeks to:
• Explore the key linkages between water, food security, and environment.
• Develop scenarios for exploring key questions for food water, food, and environmental security, at the global national and basin scale
A.5.4.2 Model structure and data
The general model structure consists of two integrated modules: the "food demand and supply" module, adapted from IMPACT (Rosegrant et al., 2002), and the "water supply and demand" module which uses a water balance based on the Water Accounting framework (Molden, 1997) that underlies the policy dialogue model, PODIUM combined with elements from IMPACT (Cai and Rosegrant, 2002). The model estimates food demand as a function of population, income and food prices. Crop production depends on economic variables such as crop prices, inputs and subsidies on |