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Centre d’Économie de la Sorbonne, University Paris 1 Panthéon Sorbonne (CES), France, https://ces.pantheonsorbonne.fr/., Paris School of Economics (PSE), France, https://www.parisschoolofeconomics.eu/., Macroeconomics Department, Halle Institute for Economic Research, University of Leipzig (IWH), Germany, https://www.iwh-halle.de/., Institute for Theoretical Economics, University of Leipzig (Institute for Theoretical Economics), Germany, https://www.wifa.uni-leipzig.de/institut-fuer-theoretische-volkswirtschaftslehre., World Bank Group (World Bank), United States, https://www.worldbank.org/ext/en/home., School of Public and International Affairs, Princeton University (SPIA), United States, https://spia.princeton.edu/., Potsdam Institute for Climate Impact Research (PIK), Germany, https://www.pik-potsdam.de/en., Economics of Climate Change Department, Technische Universität Berlin (TUB), Germany, https://www.tu.berlin/en/climatecon., Centre International de Recherche sur l’Environnement et le Développement (CNRS, Agro ParisTech, Ponts ParisTech, EHESS, CIRAD) (CIRED), France, https://www.centre-cired.fr/. +
https://www.pnas.org/doi/10.1073/pnas.1513967112; https://github.com/myoungbrun/replication_Young-Brun_et_al_2025/blob/main/src/MimiNICE2020_module.jl; https://www.pnas.org/doi/10.1073/pnas.2505239122; https://www.pnas.org/doi/10.1073/pnas.2529652122 +
NICE 2020 +
published +
Number of regions:179 +
Base year:2020, time steps:yearly, horizon: 2100 +
P
Myopic +
Activity drivers depend on income per capita and energy prices via elasticities.
Energy demand depends on activity drivers, energy prices and technology costs.
Primary energy supply depends on remaining resources, production cost and price effects. +
POLES documentation consists of a referencecard and [[Model Documentation - POLES|detailed model documentation]] +
JRC - Joint Research Centre - European Commission (EC-JRC), Belgium, http://ec.europa.eu/jrc/en/. +
http://ec.europa.eu/jrc/en/poles; https://ec.europa.eu/jrc/en/publication/poles-jrc-model-documentation-0 +
POLES ENGAGE (other versions are in use in other applications) +
POLES was originally developed to assess energy markets, combining a detailed description of energy demand, transformation and primary supply for all energy vectors.
It provides full energy balances on a yearly basis using frequent data updates to as to deliver robust forecasts for both short and long-term horizons.
It has quickly been used, in the late 90s, to assess energy-related CO2 mitigation policies.
Over time other GHG emissions have been included (energy and industry non-CO2 from the early 2000s), and linkages with agricultural and land use models have been progressively implemented. +
published +
Number of regions:66 +
Base year:2015, time steps:Yearly, horizon: 2015-2100 +
The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight. +
PRIMES documentation is limited and consists of a reference card +
E3Modelling (E3M), Greece, https://e3modelling.com/. +
https://e3modelling.com/modelling-tools/primes/ +