Forestry - GCAM: Difference between revisions
Jump to navigation
Jump to search
mNo edit summary |
mNo edit summary |
||
Line 3: | Line 3: | ||
|DocumentationCategory=Forestry | |DocumentationCategory=Forestry | ||
}} | }} | ||
Forestry in GCAM is described in the GCAM documentation’s [http://jgcri.github.io/gcam-doc/aglu.html Agriculture, Land-Use, and Bioenergy | Forestry in GCAM is described in the GCAM documentation’s [http://jgcri.github.io/gcam-doc/aglu.html Agriculture, Land-Use, and Bioenergy] section. |
Revision as of 14:41, 2 September 2020
Corresponding documentation | |
---|---|
Previous versions | |
No previous version available | |
Model information | |
Model link | |
Institution | Pacific Northwest National Laboratory, Joint Global Change Research Institute (PNNL, JGCRI), USA, https://www.pnnl.gov/projects/jgcri. |
Solution concept | General equilibrium (closed economy)GCAM solves all energy, water, and land markets simultaneously |
Solution method | Recursive dynamic solution method |
Anticipation | GCAM is a dynamic recursive model, meaning that decision-makers do not know the future when making a decision today. After it solves each period, the model then uses the resulting state of the world, including the consequences of decisions made in that period - such as resource depletion, capital stock retirements and installations, and changes to the landscape - and then moves to the next time step and performs the same exercise. For long-lived investments, decision-makers may account for future profit streams, but those estimates would be based on current prices. For some parts of the model, economic agents use prior experience to form expectations based on multi-period experiences. |
Forestry in GCAM is described in the GCAM documentation’s Agriculture, Land-Use, and Bioenergy section.