GWS's longstanding experience in model-based analysis and policy advice on economic and social as well as energy and climate policy aspects is customized for and communicated to our clients. Our "capacity building" approach focuses on the development and application of empirically based economic models, which are supplemented with energy, environmental and climate-relevant aspects as needed.

Economic models are often complex, partially due to the expert software used. Our capacity building approach aims to reduce this hurdle by using well-known Microsoft (MS) Excel as the core modelling software and providing customized trainings to our clients.

Input-output (IO) models have proven particularly useful for impact analyses of macroeconomic and sector-specific developments.

Static IO models are simple economic models for comparative-static impact analysis that represent the economic structure of a country based on IO tables.In static IO models, the illustrated industry-specific supplier and customer relationships between suppliers and consumers are the basis for determining the direct and indirect effects of changes in demand. This comparative-static impact analysis is based on ideas of Wassily Leontief, who received the Nobel Prize for the development of the IO model in 1973.

Macro-econometric (dynamic) IO models are an extension of static IO models and additionally consider both induced income and price effects as well as temporal aspects of policy measures and the adaptive responses of affected actors.

IO models are expandable and can be adapted depending on the key questions at hand. Examples are the E3 ("economy-energy-emissions") models, which are supplemented by energy-specific indicators such as energy consumption by sectors and energy sources as well as energy prices and emissions (e.g., E3 models for Algeria e3.dz, Georgia e3.ge, Kazakhstan e3.kz, Uganda e3.ug). Both emission reduction and climate impact adaptation scenarios can be evaluated in terms of their impacts on economic and environmental indicators (Flaute et al. 2022, Großmann et al. 2022; Großmann et al. 2023).

Another example of an extension is the subnational extension of the Kazakh E3 model. Regional economic indicators were linked to corresponding indicators at the national level, using a simplified top-down regionalization approach (Großmann, Hohmann 2023 (forthcoming)). This approach allows for identifying regions that suffer the most from the economic impacts of climate change or benefit from adaptation measures.

For a more intuitive access, interactive maps were created in MS Excel. Past extreme weather events such as droughts, floods, forest fires and their quantified damage were recorded for Kazakhstan in a structured template and form the data basis for the maps. Among other things, the application allows for selecting certain extreme weather events, types of damages (e.g., monetary damage, number of people killed) and years. By clicking on an individual region, a summary of all events recorded for that region is determined based on the selected damage type and year.

The model building framework DIOM-X (Dynamic IO Modeling in Excel) developed by GWS is based on the programming language "Visual Basic for Applications" (VBA) embedded in MS Excel and contains all the necessary tools to create Excel-based macro-econometric (dynamic) IO models and to conduct scenario analyses (Großmann, Hohmann 2022, 2019). Performing scenario analyses does not require any programming knowledge due to the graphical user interface.

The DIOM-X-based modelling approach supports the U4RIA principles (Großmann et al. 2023): The models are self-contained in that, among other things, all data, metadata, model code, and the results are stored in a single MS Excel workbook, which allows unrestricted access to all information ("white box" approach).

Other supporting aspects are the promotion of close collaboration between national and international experts as well as the transfer of ownership of the jointly developed country models and an intensive "capacity building" program. The latter includes online and on-site training as well as additional teaching material such as a model manual (e.g., Großmann, Hohmann 2023) and short videos to help partners in updating the models independently and using them for scenario analyses.

If you have any questions or suggestions, please feel free to contact Ms. Großmann.