A general equilibrium model (GEM/CGE) uses social accounting matrices to represent input-output relations of consumption, production, savings, investments and expenditures of actors in the economy; the production function can allow for changes in the relative use of inputs considering changes in prices and markets. Further each actor in the economy attempts to maximize their profit by shuffling input and outputs around. This is done subject to the constraint that the goods, investment and foreign markets reach equilibrium. As a top-down modelling approach, it focuses on representing macroeconomic trends and relationships.

CLEWs models are bottom-up representations of physical systems and infrastructure. Each component of the systems is described by its technical and economic characteristics.  This includes both natural resources/stocks (e.g. energy reserves, renewable energy flow, land resources, water flows, aquifers etc.) and the human made infrastructure that interacts with and use these resources (e.g. power plants, dams, water pumping and treatment equipment, agricultural machinery, demand devices etc. ). The flows in the model are in natural units (e.g. tonnes, cubic meters, Petajoules etc) and costs are accounted for along each step of the value chain. The models are solved as optimization problems, where the aim is to meet demand at the lowest possible cost subject to constraints.

The main differences are thus that CLEWs only captures parts of the economy and is not suited to look at overall economic variables such as impacts on growth, employment and interest rates. However, CLEWs models provide for representation and study of the role of technology choice and technology change. It lets users explore how structural change within a sector can impact development goals.  CLEWs models also allow direct representation of bio-physical constraints and processes to show non-monetary impacts and outcomes.

Yes. CLEWs allows users to include capital, fixed and variable costs of all system components and options. It can also include external costs related to emissions, land-use change or other variables. This can be weighed against the benefits of the interventions modelled. Note that the analysis is limited to the sectors and interdependencies directly represented in the model.

CLEWs accounts for costs of all resource use, investment in assets, and running costs of all components on the CLEWs system,  but does not directly represent public budgets. Allocations between public and private expenditures would be conducted as a post-processing step. It does not provide a means to evaluate spending on other priorities such as health or education, but only on the sectors directly represented.

In CLEWs models sectors can adapt behavior through decisions such as switching to more efficient technologies or less carbon intensive fuels if energy prices increase or a carbon policy is introduced. A partial equilibrium representation, where output responds to prices of inputs is also possible, but in this introductory course we will cover only fixed outputs/demands

CLEWs models can address social aspects such as food security and access to basic  energy and water services as well as consumption levels of these. Representation of the demands of population groups based on location, income levels and urban/rural is also possible.

CLEWs models are driven by an objective function, which is to minimize the costs  of meeting demand subject to constraints.

Data requirements and general template will be discussed extensively during the course and is highly dependent on the level of detail pursued in an individual model. Typically, base year production and use of each commodity one wants to represent, technology stock and costs for each technology one wants to include, land-cover maps, rainfall data as well as population and GDP projections are needed.

Models are usually built from gridded geospatial data (i.e. layers of rainfall, land-cover, soil etc.) and can be aggregated/adapted to any geographic area. Spatial resolution is therefore a user choice.

Data is usually of reasonable availability and quality for energy, land-use/agriculture, and climate on the national scale. On the sub-national level, the situation is more challenging. Hydrological data and information on costs is sometimes not available at national and subnational levels. Global datasets exist than can provide the basis for a national CLEWs models.  Data can then be substituted with nationally available data as it becomes available. 

The level of data, and its accuracy is a function of the specific question you want to answer. This does not need to be detailed if you are looking for a country 'sketch'. But the more detailed the question, the more detailed the information.

If there is need for support on getting access to the remote sensing data to solve data gaps and other similar data that can help enrich the model, support may be available.

CLEWs models are normally built using an expanded version of the OSeMOSYS modelling system. This is an open source resource, which anyone can use for free without requiring a license. We typically use a version of the model written in GNU-mathprog, but it is also available in other programming languages.

We use a dedicated User Interface called MoManI (alternatives are also available) to develop CLEWs models in OSeMOSYS. We have additional browser or Python-based tools for processing and visualization and also a cloud platform where users can run models and visualize results.

Depending on the specific interests of users, a country tailored model can be developed over the course of 3 months to 1 year. Time requirements are highly dependent on the level of ambition, however learning to master modelling of any kind does require a significant time commitment.

All emissions and emission sources can be represented in a CLEWs model, including waste and industrial processes. Outputs from CLEWs can be used as data inputs into other modelling tools.

Yes. It is important to clarify at an early stage of a project what the ultimate goal and level of ambition is for the use of models like CLEWs within an institution. CLEWs, or any other modelling tool, should be used when it adds value to the program of work of an institution and helps it fulfill its mandate. If this is confirmed, integration into the program of work of relevant divisions/teams and individual staff is a formal step that is highly conducive to successful outcomes and institutionalization. If a capacity development project is seen as an external project, rather than the process to strengthen the analytic capability of the institutions it is a lot less likely to succeed. In some projects we provide specific support for institutional mechanisms and arrangements to support institutionalization and sustained use of the model by partnering institutions.

Yes. Universities and research centers are often valuable hubs for analytic capacity and can be an excellent partner to sustain and build national capacity.

Yes. There are analysts in a number of countries who are applying the tool. Examples will be shared during the course.

No. CLEWs models are built with an open source modelling tool and is completely free to use. There is a growing community of users that anyone seeking partners or collaborators can engage with.

All international meetings are cancelled or postponed due to the COVID-19 pandemic. In the past, meetings were organized annually in Trieste, Italy, and other international, regional and national meetings/workshops were also organized. We hope to resume regional meetings again once it is safe to do so.

The feedback from participants in such events and networks is generally very positive. Most see substantial value in exchange of experience with peers in other countries and regions.

A number of international organizations support CLEWs activities and training including the World Bank, UN regional commissions and some bilateral agencies. There is also a growing community of academics, researcher and government officials who use OSeMOSYS that one can partner with. UNDP and UN DESA collaborate with several of this organizations on regional and country-based projects.  

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