Socio-economic drivers - GCAM: Difference between revisions
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}} | }}The socioeconomic component of GCAM sets the scale of economic activity and associated demands for model simulations. Assumptions about population and per capita GDP growth for each of the 32 geo-political regions together determine the Gross Domestic Product (GDP). GDP and population both can drive the demands for a range of different demands within GCAM. | ||
One of the most important determinants of energy, agriculture, and land-use is the scale of economic activity, which we assume is proportional to GDP. In previous versions of GCAM, dating back to the model’s earliest formulations, the level of GDP was prescribed exogenously. There has been an option to endogenously modify the initial GDP assumption to reflect changes in the cost of delivering energy services within a scenario (Edmonds and Reilly, 1983; Edmonds and Reilly, 1985). However, that feedback elasticity was not determined structurally and was a simple scalar parameter. In other words, population and economic activity are used in GCAM through a one-way transfer of information to other GCAM components. For example, neither the price nor quantity of energy nor the quantity of energy services provided to the economy affect the calculation of the principle model output of the GCAM macro-economic system, GDP. | |||
Since GCAM v7, GCAM incorporates a macroeconomic module that allows for fully endogenizing GDP responses. This model creates a two-way coupling between the scale of economic activity, measured as GDP, and the existing energy sector module. In the simple macro-economic model that we employ here, the two-way interaction is developed for each geo-political region in GCAM. The system is assumed to be open, with each of the regions interacting with others in the global economy via trade. See the [http://jgcri.github.io/gcam-doc/economy.html economy] and [https://jgcri.github.io/gcam-doc/inputs_economy.html economic inputs] sections for details, including a detailed description of the GCAM-Macro model. | |||
Latest revision as of 18:35, 10 October 2023
Note: The documentation of GCAM is 'under review' and is not yet 'published'!| Corresponding documentation | |
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| Previous versions | |
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| 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. |
The socioeconomic component of GCAM sets the scale of economic activity and associated demands for model simulations. Assumptions about population and per capita GDP growth for each of the 32 geo-political regions together determine the Gross Domestic Product (GDP). GDP and population both can drive the demands for a range of different demands within GCAM.
One of the most important determinants of energy, agriculture, and land-use is the scale of economic activity, which we assume is proportional to GDP. In previous versions of GCAM, dating back to the model’s earliest formulations, the level of GDP was prescribed exogenously. There has been an option to endogenously modify the initial GDP assumption to reflect changes in the cost of delivering energy services within a scenario (Edmonds and Reilly, 1983; Edmonds and Reilly, 1985). However, that feedback elasticity was not determined structurally and was a simple scalar parameter. In other words, population and economic activity are used in GCAM through a one-way transfer of information to other GCAM components. For example, neither the price nor quantity of energy nor the quantity of energy services provided to the economy affect the calculation of the principle model output of the GCAM macro-economic system, GDP.
Since GCAM v7, GCAM incorporates a macroeconomic module that allows for fully endogenizing GDP responses. This model creates a two-way coupling between the scale of economic activity, measured as GDP, and the existing energy sector module. In the simple macro-economic model that we employ here, the two-way interaction is developed for each geo-political region in GCAM. The system is assumed to be open, with each of the regions interacting with others in the global economy via trade. See the economy and economic inputs sections for details, including a detailed description of the GCAM-Macro model.