G-RDEM: A GTAP-Based Recursive Dynamic CGE Model for Long-Term Baseline Generation and Analysis

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Wolfgang Britz
Roberto Roson

Abstract

We motivate and detail the new GTAP-based recursive dynamic economic model (G-RDEM), a computable general equilibrium tool for long-term counterfactual analysis and baseline generation from given gross domestic product (GDP) and population projections. It encompasses an implicitly directly additive demand system (AIDADS) demand system with non-linear Engel curves, debt accumulation from foreign saving and introduces sector specific productivity changes, endogenous aggregate saving rates, as well as time-varying cost shares for value added and individual intermediates. Parameters for these relationships are econometrically estimated or taken from published work. The core of the model is derived from the Global Trade Anaylsis Project (GTAP) standard model and seamlessly incorporated into the modular and flexible CGEBox modelling platform, allowing for combined applications with various other extensions, such as GTAP-agro-ecological zones (AEZ) or GTAP-Water. G-RDEM maintains the flexible aggregation from the GTAP Data Base. It is open source, encoded in General Algebraic Modelling System (GAMS) and can be steered by a Graphical User Interface, which also encompasses a tool to analyse results with tables, graphs and maps. Existing GDP and population projections from the Socio-Economic Pathways (SSP) 1-5 can be directly incorporated for baseline construction. A comparison of the generated long-term structural composition of the economy against a simple recursive-dynamic variant, derived from the standard GTAP model, shows that G-RDEM brings about much more plausible results, as well as a more realistic, internally consistent representation of the economic structure in a hypothetical future.

Article Details

How to Cite
Britz, W., & Roson, R. (2019). G-RDEM: A GTAP-Based Recursive Dynamic CGE Model for Long-Term Baseline Generation and Analysis. Journal of Global Economic Analysis, 4(1), 50–96. https://doi.org/10.21642/JGEA.040103AF
Section
Advances in Methods and Theory