Abstract
The massive master database of TERM needs to be aggregated before it can be used for any simulation. There is demand for moving to dynamic TERM simulations and rewards from doing so due to additional insights that arise from the influence that a dynamic baseline may have on a policy simulation. This chapter covers a number of issues concerning dynamic modeling with TERM. We start by outlining the motivations for moving from comparative static to dynamic regional modeling. Following that, we provide an overview of how we go about making a version of TERM dynamic. This includes details of how to vary the time intervals within a dynamic model. Next is an explanation of using the master database of TERM to prepare variable aggregation versions of dynamic TERM. The chapter also outlines how recursive dynamic models are run. RunDynam (specialist software) is a very useful tool for the dynamic CGE practitioner.
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Notes
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Some projects undertaken for clients remain confidential.
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ORANIG is downloadable from http://www.monash.edu.au/policy/oranig.htm
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Mark Horridge and more recently Michael Jerie have played major roles in ongoing development and upgrades to GEMPACK software. Earlier contributors include George Codsi and Jill Harrison.
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ABS prepares census data at the SLA level (1400+ regions). These aggregate to 200+ statistical sub-divisions (SSDs): TERM-H2O represents SSDs in the Murray-Darling Basin with relatively aggregated regions elsewhere.
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Wittwer, G., Verikios, G. (2012). Introducing Dynamics to TERM. In: Wittwer, G. (eds) Economic Modeling of Water. Global Issues in Water Policy, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2876-9_3
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