NEWAGE – General model description

The NEWAGE (National European Worldwide Applied General Equilibrium) model is a global, recursive-dynamic Computable General Equilibrium (CGE) model with a detailed specification of the energy sector. Its main objective is to simulate and quantify macroeconomic effects of energy and environmental policy intervention in terms of its economic costs. Due to the total analytical framework of the general equilibrium approach, the interaction of actors on markets of the economy is described in a closed circular flow of income (Figure 1). This allows capturing both direct effects in individual sectors (e.g. energy) as well as indirect effects (feedback effects) across the economy that are caused by price-induced supply and demand shifts in response to the political intervention. Figure 1 illustrates the concept and structure of the NEWAGE model. Several applications were illustrated in Beestermöller 2016, Geres et al. 2016, Beestermöller et al. 2013, Beestermüller & Fahl 2013, Zürn 2010, Küster et al. 2009, Küster 2009 and Küster et al. 2007. Underlying modeling strategies are described in Böhringer 1996, Rutherford 1999, Rutherford & Paltsev 2000, Abrell 2009 and Rutherford 2010. The central external data sources are IEA 2009 and Fouré et al. 2012.

 

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Figure 1: NEWWAGE Concept and composition

The model builds upon neoclassical theory, has solid micro-foundations and solves for an equilibrium that maximizes welfare subject to technology and policy constraints. The basic assumption of the general equilibrium approach is perfect competition on all factor and goods markets. The equilibrium conditions are formulated as a system of mixed-complementary equations (MCP) based on the work of Arrow-Debreu (1954) and Matthiesen (1985). In this regard, the equilibrium system is solved for the variables prices, production levels and income. The demand of the representative agent is made up of household demand, government demand and investment demand. The disposable income of the representative agent is used to cover the demand for goods and services, thus maximizing the agent’s utility or welfare.

The assumption of perfect competition may be waived in special markets, as is done for the labor market in NEWAGE to reflect imbalances existing on real labor markets. Therefore, the model considers unemployment, wage rigidities and different grades of labor qualifications (skilled, unskilled).

Foreign trade is illustrated by bilateral trade flows. For every good there is an import/export matrix, which shows the flow from countries of origin to countries of destination.

The data base is formed by the global input-output database GTAP (Global Trade Analysis Project - Version 9, base year 2011, Aguiar et al. 2016), which covers 140 countries and regions and 57 economy sectors. In addition, energy specific data from the International Energy Agency (IEA) and similar sources are used to represent the energy sector in more technological detail.

The specific model resolution can be adjusted depending on the analytical purpose. The current aggregation version covers 18 countries and world regions, 18 production sectors and 4 input factors, as shown on Table 1. The EU-28 is composed by Germany, France, Italy, Poland and Great Britain as single countries and the country groups of Benelux, Spain and Portugal, North Europe and Southeast Europe. In addition to Europe, the USA and the developing countries of Brazil, Russian, India, China and South Africa, members of the BRICS group, are also modeled as single countries. The remaining countries are divided in three groups, “Remaining OECD”, “Middle-East and OPEC” and “Rest of the World”.

Table 1: Regional and sectoral mapping

The 18 production sectors can be divided into five energy sectors (coal, gas, crude oil, mineral oil and electricity including district heating), nine manufacturing industries, and four sectors of the rest of the economy, including agriculture and transport. The manufacturing industry includes the consuming goods industry (mechanical engineering, the rest of the manufacturing industry) and the energy-intensive industry. The latter describes the production of chemical products, iron and steel, non-ferrous metals (such as aluminum, copper), nonmetallic minerals (such as glass, ceramics, cement) as well as paper, cardboard & printing.

The equilibrium model is built as recursive-dynamic and the time spam is from 2011 to 2050 on five-years steps. The production of goods in the 18 sectors is modeled with CES (constant elasticity of substitution) production functions (Figure 2), where output is produced as a combination of the input factors capital, labor, energy and materials. The degree to which inputs can be substituted for each other is exogenously determined by the respective elasticities of substitution, which are based on technical assumptions or taken from the literature. CO2 allowances are an additional input if fossil fuels are used. In the case where an emissions trading system is applied, then the CO2 emissions certificates are also considered as a production factor. The transport costs associated with international trade are taken into account in the CES function.
 

Figure 2: Production output (CES-nesting)

A special focus of the NEWAGE model is the technology based representation of the electricity generation sector. The production of electricity is differentiated into 16 electricity generation technologies in 3 load segments (Figure 3). Each generation technology is modeled as a CES-production function with the inputs capital, labor, energy and materials. Technological improvements are modeled via an autonomous energy efficiency index (AEEI) which reflects sector specific technological changes, i.e. changes in the energy use per unit output of an industry through time.  As the NEWAGE model includes such level of details for energy generation technologies in a general equilibrium framework, it is also known as a Hybrid Model (Hourcade et al. 2006) and, thus, it can can also be regarded as a hybrid general equilibrium model.

 

Figure 3: Electricity generation (CES-Nesting)

A further characteristic of the NEWAGE model is the technology-based presentation of the energy demand of private households in Germany. For this purpose, the energy demand of private households is differentiated in terms of energy services (such as space heating and mobility). In addition, demand for electricity and other consuming goods are, as well, differentiated in a technology-oriented manner. This includes various vehicle and building types with different specific energy requirements and associated capital costs. This can be used to describe the technology-specific composition of the energy demand of private households and the resulting CO2 emissions, including the associated energy and capital costs, and ultimately the overall economic impact of climate-related instruments in the household sector, such as energy standards, CO2 taxes, subsidies or different implementation forms of European emissions trading system. Figure 4 illustrates the technology-based modeling of the energy demand of private households in Germany.

 

Figure 4: Household energy demand (CES-Nesting)

By means of the NEWAGE model, detailed analyzes of the economic effects of energy and climate policies, such as the promotion of renewable energies, European CO2 emissions trading, purchase premiums or energy standards, can ultimately be carried out. The model results allow quantitative conclusions to be drawn about the policy-induced change in macroeconomic indicators, such as gross domestic product, gross added value, employment and competitiveness.

The current development stage of the NEWAGE model is to expand the final consumer by adding different household types. This is to be done according to income classes, in order achieve a statement on the distribution impacts of energy and climate policy instruments on the different households.

 

References

Abrell (2009) Abrell, J.: „Transport under Emission Trading - A Computable General Equilibrium Assessment“, Fakultät Wirtschaftswissenschaften der Technischen Universität Dresden, Dissertation, (November 2009).

Aguiar et al. (2016) Aguiar, A.; Narayanan, B.; McDougall, R.: „An Overview of the GTAP 9 Data Base“, In: Journal of Global Economic Analysis 1 (June 3, 2016), Nr. 1, S. 181–208.

Arrow & Debreu (1954) Arrow, K. J.; Debreu, G.: „Existence of an equilibrium for a competitive economy“, In: Econometrica 22 (1954), Nr. 3, S. 265–290.

Beestermöller et al. (2013) Beestermöller, R.; Blesl, M.; Kuder, R.; Fahl, U.: „Energie- und gesamtwirtschaftliche Auswirkungen veränderter Rahmenbedingungen auf die Nutzung von Erdgas in Deutschland“, eine Studie für das Zentrum für Energieforschung Stuttgart (ZfES) Projekt 24 (IER), (August 2013).

Beestermöller (2016) Beestermöller, R.: „Die Energienachfrage privater Haushalte und ihre Bedeutung für den Klimaschutz - Volkswirtschaftliche Analysen zur deutschen und europäischen Klimapolitik mit einem technologiefundierten Allgemeinen Gleichgewichtsmodell“, 2016 (in Bearbeitung).

Beestermöller & Fahl (2013) Beestermöller, R.; Fahl, U.: „Impacts of German energy policies on the competitiveness of national energy intensive industries“, Fullpaper at the EcoMod2013 International Conference on Economic Modeling, Czech University of Life Sciences, Prague (1-3 July 2013).

Böhringer (1996) Böhringer, C.: „Allgemeine Gleichgewichtsmodelle als Instrument der energie- und umweltpolitischen Analyse - Theoretische Grundlagen und empirische Anwendung“, Frankfurt am Main [u.a.] : Lang, 1996.

Fouré et al. (2012) Fouré, J.; Bénassy-Quéré, A.; Fontagné, L.: „The Great Shift: Macroeconomic projections for the world economy at the 2050 horizon“, CEPII working paper 2012-03, (March 2012).

Geres et al. (2016) Geres, R.; Kohn, A.; Nickel, F.; Scholz, D.; Mühlpointner, T.; Sternhardt, M.; Beestermöller, R.; Fahl, U.; Blesl, M.; Haasz, T.; Brunke, J.-C.: „Ausgestaltung des EU-Emissionshandels nach 2020 und seine Auswirkungen – insbesondere auf die industrielle Wettbewerbsfähigkeit und die Energiewirtschaft – unter Berücksichtigung von Optionen zur Vermeidung von Carbon Leakage“, FutureCamp Holding GmbH; FutureCamp Climate GmbH; Institut für Energiewirtschaft und Rationelle Energieanwendung (IER) der Universität Stuttgart, Studie im Auftrag des Bundesministeriums für Wirtschaft und Energie (BMWi) , Schlussbericht zum Vorhaben 06/15, (2016).

Hourcade et al. (2006) Hourcade, J.-C.; Jaccard, M.; Bataille, C.; Ghersi, F.: „Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of "The Energy Journal"“, In: The Energy Journal 27 (2006), S. 1–11., Überprüfungsdatum 30.11.2015.

IEA (2009) International Energy Agency (IEA): „Electricity Information 2009“, Paris : OECD Publishing, 2009.

Küster et al. (2007) Küster, R.; Ellersdorfer, I.; Fahl, U.: „A CGE-Analysis of Energy Policies Considering Labor Market Imperfections and Technology Specifications“, Fondazione Eni Enrico Mattei (FEEM), Nota di Lavoro, 7.2007, CCMP – Climate Change Modelling and Policy, Milano (January 2007).

Küster et al. (2009) Küster, R.; Ellersdorfer, I.; Voß, A.: „Economic Impacts of EU Climate Policy Targets Accounting for No-Regret Options – Scenario Analyses with NEWAGE-W“, eine Studie für die BASF AG, Stuttgart (2009).

Küster (2009) Küster, R.: „Klimaschutz, Volkswirtschaft und Beschäftigung - Analysen zur deutschen und europäischen Klimaschutzpolitik mit einem berechenbaren allgemeinen Gleichgewichtsmodell“, Berlin : Mensch und Buch Verl., 2009 (Climate protection).

Mathiesen (1985) Mathiesen, L.: „Computation of economic equilibria by a sequence of linear complementarity problems“. In: Manne, Alan S. (Hrsg.): Economic Equilibrium: Model Formulation and Solution, Berlin, Heidelberg : Springer, 1985 (Mathematical Programming Studies, 23), S. 144–162.

Rutherford (1999) Rutherford, T. F.: „Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem: An Overview of the Modeling Framework and Syntax“, In: Computational Economics 14 (1999), 1-2, S. 1–46.

Rutherford (2010) Rutherford, T. F.: „GTAP7inGAMS“, Center for Energy Policy and Economics, Department of Management, Technology and Economics ETH Zurich, Working paper, (April 2010).

Rutherford & Paltsev (2000) Rutherford, T. F.; Paltsev, S.: „GTAPinGAMS and GTAP-EG: Global Datasets for Economic Research and Illustrative Models“, Department of Economics, University of Colorado, Working paper, (September 2000).

Zürn (2010) Zürn, M.: „Auswirkungen des technologischen Fortschritts und des Klimaschutzes auf die Stromerzeugung - Analysen mit einem allgemeinen Gleichgewichtsmodell“, 1. Aufl, Lohmar, Köln : Eul, 2010 (Reihe: Industrieökonomik 7).

 

Current projects

  • REEEM: Role of technologies in an energy efficient economy – model-based analysis of policy measures and transformation pathways to a sustainable energy system (Horizon 2020, LCE21). Contracting Authority: EU. Contract Period: 2016-2019.