Energy and CO2 Emissions (1.1) #
Energy efficiency #
The value of energy aggregate in sector $j$ in country $r$, $ETOT_{j,r,t}$, is subject to productivity improvements, $EE_{j,r,t}$ based on the growth model. These productivity improvements are introduced at the capital–energy bundle level, $KE_{j,r,t}$.
Energy and CO2 emissions accounting #
Using CES functional forms with variables in monetary units leads to inconsistencies when trying to retrieve physical quantities. In our case, this matters for energy consumption, production, and trade, and their consequences for CO2 emissions[(Preliminary simulations of MIRAGE-e showed that there could be a gap of more than 20% between a country’s energy consumption and energy demanded if proportionality was assumed between monetary and physical values.)]. Therefore, in addition to accounting relations in constant dollars, MIRAGE-e integrates a parallel accounting in energy physical quantities (in million tons of oil equivalent, Mtoe) allowing CO2 emissions to be computed (in million tons of carbon dioxide, MtCO2). Since the CES architecture does not maintain coherence in physical quantities, MIRAGE-e introduces energy- and country-specific adjustment coefficients. These two aggregation coefficients allow our basic energy accounting relationships to remain valid. This means that the quantity produced by one country $EY_{e,r,t}$ must equal the demand in this country both local, $ED_{e,r,t}$ and from abroad, $EDEM_{e,r,s,t}$ ; and energy consumption (by households, $EC_{e,s,t}$ and firms, $EEIC_{e,j,s,t}$) in one country must equal its local and foreign demand.
The corresponding adjustment coefficient, $AgDem_{e,r,t}$ (resp. $AgCons_{e,r,t}$) rescales the country’s demand (resp. consumption) such that it matches the physical quantities produced (resp. demanded). In turn, only energy quantity produced is proportional to the volume production $Y$ due to its being above rather than inside the CES. The epsilons below are constant conversion coefficients calibrated from the energy quantity data; they allow us to link energy quantities with corresponding volumes of demand for local good, $D_{e,r,t}$, bilateral demand, $DEM_{e,r,t}$, local final consumption, $C_{e,s,t}$ and local intermediate consumption, $EIC_{e,j,s,t}$.
Finally, CO2 emissions are recovered as proportional to the energy quantities consumed, using energy-, sector- and country-specific factors determined by the data.