The ETC-U RICE model
Short overview
The Endogenous Technical Change with Uncertainty RICE model (ETC-U RICE) is a integrated assessment model with endogenous environmental technical change based on Nordhaus and Yang (1996). It explores the behaviour and interactions between the R&D efforts and endogenous patterns of GDP level and CO2 emissions. The role of ETC-U RICE is to explore how environmental uncertainty can stimulate technical change, long-run growth and pollution.
ETC-U RICE allows users to explore what-if scenarios, quantifying the implications of possible future conditions. These outputs are not predictions of the future; they are a way of analysing the potential impacts of different assumptions about future conditions and technical change dynamics.
It is used to explore and measure the implications of uncertainty in key input assumptions and parameters into implied distributions of outputs, such as Investment/GDP ratio, CO2 emission level, Domestic abatement rate, R&D/GDP ratio. Techniques include scenarios analysis and sensitivity analysis.
ETC-U RICE has been used to produce scenarios for several regions (USA, Japan, EEC, China, Former Soviet Union and Rest of the World).
Key features of the ETC-U RICE model
ETC-U RICE takes in a set of assumptions and then processes those assumptions to create a full scenario of prices, investment decisions, and R&D expenditure. The economy and climate systems are interconnected and interact with each other.
Geographic coverage
The ETC_U RICE core represents the entire world, but it is constructed with different levels of resolution for each of these different systems. The RICE economy system operates at 12 geopolitical regions globally. These regions can be large countries or multi-county region (e.g. EEC)
Hazard rate detail
Environmental uncertainty concerns catastrophes. The "hazard rate" llinks the probability of a catastrophic event, the level of temperature mesured on the planet at a certain moment with the R&D efforts to reduce CO2 emissions and the economic growth.
Economic rationale and model solution
The core operating principle for ETC-U RICE is the ETC- RICE model which views climate change in the framework of economic growth theory (Buonanno et al. 2001). In a standard neoclassical optimal growth model known as the Ramsey model, society invests in capital goods, thereby reducing consumption today, in order to increase consumption in the future (Ramsey 1928, Koopmans 1965). The RICE model modifies the Ramsey model to include climate investments, which are analogous to capital investments in the mainstream model. That is, we can view concentrations of GHGs as “negative natural capital” and emissions reductions as investments that lower the quantity of that negative capital. Emissions reductions lower consumption today but, by preventing economically harmful climate change, increase consumption possibilities in the future. The representative agents in the modules use information to determine the optimal level of R&D expenditures in a context of uncertainty embedding a hazard rate function as Bosello and Moretto (1999).
Key parameters
Key scenario assumptions for the ETC-U RICE core include technology characteristics (e.g. sensitivity to temperature growth); emissions constraints, probability of facing a catastrophe.
Key scenario results (outputs) from the ETC-U RICE model include an analysis of the R&D dynamics; long-run output growth; CO2 emission and abatement rates.
Outcomes in ETC_U RICE depend strongly on the assumptions made for the initial catastrophe probability and its level in year 2090 in case of an increase of 3°C.
Parameters can be revised and updated in the framework of the PARIS REINFORCE project, following the feedback of local experts (stakeholder engagement), the comparative assessment with other modelling experiences, and the discussion with the partners (modellers).
Policy questions and SDGs
Key policies that can be addressed
There are a number of types of policies that can be easily modelled in ETC-U RICE:
- Emissions-related policies
- Technical change policies
Implications for other SDGs
U ETC-RICE does not automatically calculate the implication on SDGs indicators. However, it is possible to use its outputs and calculate the predictions for certain SDGs related indicators.
Recent use cases
| Paper DOI | Paper Title |
|---|---|
| doi.org/10.1016/j.ecolecon.2004.12.036. | Lerning by Doing vs Learning by Researching in a Model of Climate Change Policy Analysis |
| doi.org/10.1023/B:ENMO.0000004582.29948.d4 | Global warming, uncertainty and endogenous technical change |
References
P. Buonanno, C. Carraro, E. Castelnuovo and M. Galeotti, Emission trading restrictions with endogenous technological change, International Agreements: Politics, Law and Economics 3 (2001) 379–395.
F. Bosello and M. Moretto, Dynamic uncertainty and global warming risk, FEEM working paper, n. 80.99 (1999).
F.P. Ramsey. A mathematical theory of saving. Economic Journal 38 (1928) 543–559.
T. C. Koopmans, Tjalling C. 1965. “On the Concept of Optimal Economic Growth.” Academiae Scientiarum Scripta Varia 28(1) (1965) 1-75.
W.D. Nordhaus and Z. Yang, A regional dynamic general-equilibrium model of alternative climate-change strategies, American Economic Review 4 (1996) 741–765.
