The SNOW models share a similar structure and core. There are three SNOW models:
- SNOW-NO models Norway as a small open economy, where world market prices and other international drivers are exogenously given.
- SNOW-GLO is a global model with Norway as a separate region.
- SNOW-DYN is an intertemporal variant with forward-looking behavior, specifically designed for analyses of tax and duty systems.
The work is funded through annual contracts with the Ministry of Finance and aims to develop and update the SNOW models, primarily SNOW-NO, as well as facilitate and support the Ministry of Finance's use of them. Approximately every fourth year, the base year for the models is updated, i.e., the cross-sectoral data used to calibrate the model.
SNOW-NO is a recursive dynamic model that describes how the market behavior of economic agents determines annual macroeconomic variables such as GDP, socio-economic utility, consumption, labor supply, industry structure, energy use, international trade, as well as prices of goods and services, labor, capital, natural resources, and exchange rates. In addition, emissions to the air of greenhouse gases and pollutants are determined. The model is used to generate economic and emission projections for the next decades. Using such projections as a reference, analyses are conducted on changes in public policy or international market conditions. In 2021, the SNOW-NO model was updated with the national accounts' cross-sectoral data for 2018.
SNOW-GLO is a static model calibrated to the latest GTAP data (current year 2017) but can be projected to a desired future year. It is mainly used to study measures to reduce carbon leakage, i.e., emissions moving abroad due to climate policy. The EU's proposal to introduce a carbon border adjustment mechanism (CBAM) is one such measure, and an ongoing study explores the effects of Norway and the EU jointly implementing such a measure. SNOW-GLO also includes a microsimulation module that divides the household sector into ten income groups, allowing for the study of distributional effects (Fæhn and Yonezawa, 2021).
SNOW-DYN has been developed the recent years with a focus on tax policy issues.
Project manager: Kevin R. Kaushal
Participants:
Funder: Ministry of Finance
Publications
Rosnes, O. and H. Yonezawa (2024): The SNOW Model for Norway, SSB Documents 2024/16, Statistisk sentralbyrå.
Kaushal, K. R., L. Lindholt and H. Yonezawa (2023): Emission pricing and CO2 compensation in the EU - The optimal compensation to the power-intensive and trade-exposed industries for increased electricity prices, SSB Discussion papers 1008, Statistisk sentralbyrå.
Bye, B., K. R. Kaushal, Rosnes, O., K. Turner and H. Yonezawa (2023): The road to a low emission society: Costs of interacting climate regulations, Environmental and Resource Economics 86, 565 - 603.
Bye, B., K. R. Kaushal and H. B. Storrøsten (2022): EU’s suggested carbon border adjustment mechanism - Impact on Norwegian industries, SSB rapport 2022/48, Statistisk sentralbyrå.
Kaushal, K. R. and H. Yonezawa (2022): Increasing the CO2 tax towards 2030 - Impacts on the Norwegian economy and CO2 emissions, SSB rapport 2022/43, Statistisk sentralbyrå.
Bye B., T. Fæhn, K. R. Kaushal, H. Storrøsten og H. Yonezawa (2021a): Politikk på politikk - derfor koster klimapolitikken, Samfunnsøkonomen 2, 45-56.
Fæhn, T. and H. Yonezawa (2021): Emission targets and coalition options for a small, ambitious country: An analysis of welfare costs and distributional impacts for Norway, Energy Economics 103.
Fæhn, T., K. R. Kaushal, H. Storrøsten, H. Yonezawa and B. Bye (2020): Abating greenhouse gases in the Norwegian non-ETS sector by 50 per cent by 2030", SSB-rapport 2020/23, Statistisk sentralbyrå.
Rosnes, O., Bye, B. og Fæhn, T. (2019). SNOW-modellen for Norge: Dokumentasjon av framskrivningsmodellen for norsk økonomi og utslipp. SSB notater 2019/1.
Bye, B., T. Fæhn and O. Rosnes (2018): Residential energy efficiency policies: Costs, emissions and rebound effects, Energy 143, 191-201.
Fæhn, T. and E.T. Isaksen (2016): Diffusion of climate technologies in the presence of commitment problems, Energy Journal 37 (2), 155-180.