The year 2017 was declared to be the year of ecology in Russia, so discussions about humans’ destructive impact on the environment, including climatic effects, intensified.

The Paris Climate Agreement that replaced the Kyoto Protocol sets an ambitious long-term goal of maintaining the average global temperature increase within 1.5–2°C compared to the pre-industrial level. The countries that have ratified the Paris Agreement are trying to radically change the structure of their energy systems in favor of renewable energy sources and low-carbon, energy-efficient technologies. On the one hand, these changes seem very expensive as they require significant investment. On the other hand, the subsequent savings on fuel, reducing the dependence on energy imports, stimulating R&D and innovation create new incentives for growth.

Russia as one of the largest exporters of energy products has to adapt to the new economic reality. The question is what measures are most effective for short- and long-term economic growth and how actively one should adapt to the changes that are taking place. Even for importers of energy products, the answers to these questions are not obvious and require building appropriate models.

Experts from the Gaidar Institute and RANEPA use a “hybrid approach” to modeling, using simultaneously different types of energy models – “Top-Down” (TD) and “Bottom-Up” (BU). The hybrid approach allows assessing structural changes in the energy system as a reaction to external shocks, energy or environmental policies, and associated costs, as well as assessing the overall economic effects of shocks and economic policies on output and welfare.

Several variants of “hybrid” models are being developed and tested at the Gaidar Institute and RANEPA in order to take into account a greater number of macroeconomic effects. The first version of the model includes the “putty-clay” production function, which allows to introduce such effects as the increasing elasticity of substitution among energy sources. Also, a multi-period intertemporal optimization is made, which allows one to avoid the assumption of long-term equilibrium and take into account the effects of investment allocation in time and effects from energy savings. The model is solved by the method of non-linear programming (NLP), which allows for its implementation with standard software packages (GAMS). The second version of the model is a standard general equilibrium model with the possibility of switching between technologies. The model is stated as a problem of Mixed Complimentary Programming (MCP).

Both types of the model are tested as “prototypes” with a small number of sectors and technologies included and are used while developing a “large” model of the Russian economy. Parallel to constructing “hybrid” energy models, we proposed and tested a methodology for forecasting “drivers” and “indicators” of the development level. The method is used to build long-term probabilistic forecasts. The model apparatus that was developed is used for building forecasts within the Deep Decarbonization Pathways Project in which research teams from around the world make predictions of reducing greenhouse gas emissions in their countries.

Vera Barinova – Head of the Gaidar Institute Innovation Economy Department,
Oleg Lugovoy – Leading Researcher at RANEPA Center for Economic Modeling of Energy and Ecology,
Vladimir Potashnikov – Senior Researcher at RANEPA Center for Economic Modeling of Energy and Ecology