NEMESIS
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NEMESIS(New Econometric Model for Environment and Sustainable development Implementation Strategies) is a multi-country macro-sectoral econometric model for EU-15 countries plus Norway, which can be used for assessment of structural policies, mainly environmental and R&D policies, for studies of short and medium term consequences of a wide spectrum of economic and fiscal policies, and for forecasts at a macro and sectoral level. It covers 30 production sectors and 27 consumption good categories and incorporates some properties of new theories of growth such as endogenous R&D decisions, process/product innovations and technological/knowledge spillovers between sectors and countries. Interdependencies between activities are described by convert matrices for final consumption, investment goods, intermediate consumption, energy-environment and technological transfers. NEMESIS integrates an energy-environment module, which presents a detailed modelling of the power/steam generation sector and transforms activity indicators into energy relevant indices such as energy prices and polluting emissions. Each individual country is linked to others by external trade. NEMESIS incorporates a complete specification of the long-term solution in the form of estimated equations, which have long-term restrictions imposed on their parameters. Dynamic equations which embody these long-term properties are estimated by time series econometrics in order to allow the model to provide forecasts. The model is solved simultaneously for all sectors and countries.[1]
Contents
- 1 Result
- 1.1 Typical Model Applications:
- 1.2 Standard Model Specification:
- 1.3 Sectoral coverage:
- 1.4 Consumption categories:
- 1.5 Behavioural assumptions:
- 1.6 Energy-environment module
- 1.7 Dynamic structure:
- 1.8 Linkage between regions and countries:
- 1.9 Market Structure:
- 1.10 Main model results:
- 1.11 Required technical infrastructure:
- 1.12 Structure of Input Data:
- 1.13 Model Extensions:
- 1.14 Links to other Models, Projects, Networks:
- 1.15 Foreseen utilizations of the model are:
- 1.16 Regional Scope:
- 2 See also
- 3 References
Result
Typical Model Applications:
- Assessment of short and medium term consequences of energy and environmental (air pollution) policies, R&D, technology-related and economic policies on EU economies and on the state of the environment
- Short-medium term (2-8 years) forecasts at a macro and sectoral level
- Forecasting coherent baseline scenarios for 30 years' time, including sustainable development scenarios[1]
Standard Model Specification:
Sectoral coverage:
30 sectors:
(1) Agriculture, (2) Coal and Coke, (3) Oil & Gas Extraction, (4) Gas Distribution, (5) Refined Oil, (6) Electricity, (7) Water Supply, (8) Ferrous & non Ferrous Metals, (9) Non Metallic Min Products, (10) Chemicals, (11) Metal products, (12) Agriculture & Industrial Machines, (13) Office Machines, (14) Electrical Goods, (15) Transport Equipment, (16) Food, Drink, Tobacco, (17) Textile, Cloth & Footwear, (18) Paper & Printing Products, (19) Rubber & Plastic, (20) Other Manufactures, (21) Construction, (22) Distribution, (23) Lodging & Catering, (24) Inland Transports, (25) Sea & Air Transports, (26) Other Transports, (27) Communication, (28) Bank, Finance & Insurance, (29) Other Market Services, (30) Non Market Services
Consumption categories:
27 consumption goods
(1) Food, (2) Drink, (3) Tobacco, (4) Clothing and Footwear, (5) Gross Rent and Water, (6) Electricity, (7) Gas, (8) Liquid Fuel, (9) Other Fuels, (10) Furniture etc. (11) Household Textile etc., (12) Major Appliances, (13) Hardware, (14) Household Operation, (15) Domestic Services, (16) Medical Care etc., (17) Cars etc., (18) Petrol etc., (19) Rail Transport, (20) Buses and Coaches, (21) Air Transport, (22) Other Transport, (23) Communication, (24) Equipment etc., (25) Entertainment etc, (26) Exp. Rest and Hotel, (27) Misc. Good and Services[1]
Behavioural assumptions:
- Households: The aggregate consumption equation generalises the permanent income and life cycle theories in an error correction model. The equation relates total consumption to regional disposable income, a measure of wealth for the households, interest rates and inflation. Variables covering child and old-age dependency rates are included in an attempt to capture any change in consumption patterns caused by an aging population. Total aggregate consumption is allocated to 27 components as a function of relative prices and total income during a multi-level decision problem (assuming groupwise separability). At the first stage, expenditure is allocated between durable (and complementary non-durable) goods and other non-durable goods At a second stage, expenditure for durables is allocated to clothing, household utilities and transportation (including public transportation, equipment and energy, such as petrol, heavy fuel, oil), while expenditure for non-durables is allocated to necessities (including food, beverages, education, rent, etc.) and luxuries (including communication, tourism and domestic services). Finally, the demand for each category is allocated to product demands using convert matrices with fixed coefficients. The disaggregated consumption module is based on the assumption that there exists a long-run solution, but that rigidities prevent immediate adjustment. The equations are estimated in an Error Correction Model using the Engle-Granger two step procedure.
- Firms: Sectoral demand functions are derived from the flexible "Generalized symmetric McFadden" cost function which retains three variable factors (Labour, Energy, Materials) and two quasi-fixed inputs (physical and R&D capital). Firms R&D effort increases Total Factor Productivity and thus enhances competitiveness. The inter-sectoral diffusion of innovations is described with classical spillover effects methods according to the monopolistic competition framework. The demand system is estimated simultaneously for each sector using pooled panel estimation techniques (data for 1981-1996). Sectoral demands of energy, materials and investments are transformed into product demands using convert matrices with variable coefficients. The firms determine supply prices by applying a rate of mark-up to unit production costs. The rate of mark-up depends on the monopolistic competition pressure and is related to the R&D efforts which explain by sector the imperfect substitution of products.[1]
Energy-environment module
The energy-environment module, first, represents the effects of policy instruments on the behaviour of agents (end of pipe or integrated abatement) and, second, transforms activity indicators (sectoral added value, consumption etc.) into energy-related indicators, such as prices, volumes and pollutant emissions (CO2, N2O, HFC, PFC, SF6), differentiated by sector, country, fuel and durable goods. The model distinguishes several power generating technologies, such as conventional thermal power plants by fuel type, clean coal, supercritical coal, conventional and advanced gas turbines, combined cycle gas turbines, nuclear and renewable energies, and fuel cells.
Dynamic structure:
- Annual, dynamic for the medium-long term (2-15 years)
- Dynamic relationships are specified in terms of Error Correction Mechanisms which converge to a long-term outcome[1]
Linkage between regions and countries:
All trade is treated as if it takes place between two regions: the European pool and the rest of the world. The intra-and extra-EU export volume equations can be each separated into two effects, income and prices. The income effect is captured by a variable dealing with economic activity in the rest of the EU for the intra-EU equation and a variable concerning activity in the rest of the world for extra-EU equation. Prices are split into two effects: the price of exports for the exporting country and the price of exports in other EU-countries for the intra-EU equation, the price of exports for the exporting country and a rest of the world price variable for the extra-EU equation. The intra- und extra-EU import volume equations are both the same. The stock of R&D is included in order to capture the role of innovations in trade performance and structural competitiveness. The import and export prices result from an arbitrage between a competitive behaviour and a mark-up one.[1]
Market Structure:
Product market:
- Imperfect monopolistic competition
- Firms set prices (mark-ups over marginal costs)
Labour market:
- Wage setting is the outcome of a trade union model where utility-maximising unions derive utility from higher levels of sectoral employment and higher real consumption wages (relative to the outside wage), subject to the labour-demand constraint imposed by profit-maximising firms. The sectoral real wage depends on labour productivity, the unemployment rate and changes in the real wage in the rest of the economy.[1]
Main model results:
Macro economic results (EU-wide and country level):
- GDP, production, investment and R&D expenditures, final and intermediate consumption, external trade (intra-European trade, extra-European exports, extra-European imports, trade balance), prices, employment, internal and external financial balances, labour productivity
Sectoral economic results (EU-wide and country level):
- Production, value added, investment and R&D expenditures, final and intermediate consumption, sectoral exports and imports, prices, employment
- Energy production, final and intermediate energy consumption by category, energy prices, pollutant emissions (CO2, N2O, HFC, PFC, SF6), direct energy and environmental costs to each sector, investments in new plants[1]
Required technical infrastructure:
IODE software developed by Federal Planning Bureau
Structure of Input Data:
Exogenous variables on:
- World (extra European) data: exchange rates, activity variables for the rest of the world (world demand), prices of oil, prices of commodities
- Intra European countries data: rate of interest, total population, population structure, labour force, budgetary assumptions (taxation policy and government expenditures)
- Energy-environment assumptions: excise duties, carbon and energy tax rates
Empirical data set for estimation:
- All behavioural equations are econometrically estimated
- The main part of the data comes from Eurostat, OECD, IEA databases, and from national sources
Model Extensions:
Geographical coverage
- Inclusion of United States and Japan
- Inclusion of enlargement countries
European Regions
- NUTS 2/NUTS 3 level for production
- NUTS 2/NUTS 3 level for employment
Social indicators
- Skills by production sector
- Revenue by sector and skill categories
- Gini coefficients for revenue categories at National/European level[1]
Links to other Models, Projects, Networks:
NEMESIS provides forecasting coherent baseline scenarios for 30 years' time, including sustainable development scenarios. It has been used for example to make an assessment of the 3 % RTD objective for European Union and to make an assessment for the employment impacts of greenhouse gases abatement policies for European Commission and OECD.
Foreseen utilizations of the model are:
- Assessment for the European Union 7th RTD program
- Assessment for the European Union action plan for environmental technologies
- Assessment for European Union objectives for green certificates and renewable
- Assessment for EU-15 countries national action plans for RTD
- Assessment for EU-15 countries national action plans for tradable permits
The model developments and utilizations are realized through national and European contracts including notably NEMESIS-ETC, R&D for SD, CASCADES-MINTS, FORASSET and new European 6th PCRD integrated projects.
Regional Scope:
EU-15 countries, Norway (complete country models)
See also
- Equipe de Recherche en Analyse des Systèmes et Modélisation Economique (ERASME), France
- More information
- Using the NEMESIS model
- Environment ans employment: an assessment
References
- Fougeyrollas, A., Le Mouël P., Zagamé P. (2002), The NEMESIS model: New Econometric Model for Environment and Sustainable development Implementation Strategies, Paris, Brussels.
- Brécard, D., Chevallier C., Fougeyrollas, A., Le Mouël P., Zagamé P. (2004), A 3 % R&D effort in Europe in 2010: an analysis of the consequences, using the Nemesis model.
- OECD (2004), Environment and Employment: an Assessment.
