This introductory paper to the special issue on shaping long-term baselines with Computable General Equilibrium (CGE) models presents the main challenges and opportunities in constructing numerical scenarios of future economic activity using CGE models. Better understanding the role of socioeconomic drivers in baseline scenarios allows for better understanding of policy scenarios. The combined set of papers in this special issue provides three key contributions to the literature. First, it highlights the need and room for improved transparency and possibly harmonisation of baseline assumptions, while avoiding herding behaviour where all models make identical assumptions. Secondly, it raises awareness of the crucial role of the baseline in quantitative dynamic CGE analysis. Thirdly, it provides the means and incentives to modelling teams to construct more sophisticated baselines by showing practices used in advanced large-scale models and highlighting the role of different drivers. It is the objective of this special issue to set a research agenda, encouraging greater attention to baseline scenarios in the research literature.

There are increasing numbers of published articles in the field of input–output analysis and modelling that use the GTAP input–output database; particularly, in relation to the estimation of carbon, energy and water footprints and the analysis of global value chains and international trade. The policy relevance of those topics is also increasing, thus calling for consistently linking these databases with official statistics. Although, so far, GTAP has been using their own classification and reconciliation methods, this paper develops a new conversion method for the EU that guarantees that the EU-GTAP database respects the new statistical standards and Eurostat official statistics. We recommend for future updates, a shift of the current GTAP classification of industries to the new official standard classifications to which countries are progressively moving to. Otherwise, the lack of matching official data would jeopardize the usefulness of such database. This method can be extended to other similar input–output databases with different classification schemes from the original input data sources.

This paper examines the way trade and other economic interactions between countries are modelled in the construction of baseline projections with recursive dynamic computable general equilibrium (CGE) models. Simulations are conducted on the size of trade elasticities, the way the trade balance is modelled (macroeconomic closure), trade growth, and energy prices. Other topics scrutinized are the modelling of zeros, modelling of new technologies and new types of trade policies (trade in data and digitalization), phasing in of future trade policies, and migration and remittances. We conclude that there is relative consensus about the use of nested Armington preferences, whereas different scholars model the trade balance very differently. The discrepancy between baseline trade growth and historical trade growth is not considered in most models though highly relevant. Research efforts, both in terms of modelling and data collection, should be allocated to a better coverage of other items on the current account (capital income, remittances) and the inclusion of net foreign debt and asset positions, projecting trade growth based on historical patterns, and better tools to model the rapidly growing digital economy.

This technical report describes a multi-regional generalized RAS (MR-GRAS) procedure to update/project input-output tables or social accounting matrices. The method is able to incorporate a number of constraints on row and columns sums as well as specific flows between economic sectors and specific taxes in an input-output table. This feature is particularly useful to reconcile information coming from different data sets. In the application described in this report, the method is tailored towards constraints with regard to the energy system. Specifically, we specify constraints in the updating/projecting algorithm that are able to reproduce the economic values reflected in an energy balance from an energy system model. Here, we show that the method is able to generate input-output tables that are forward projected until 2050 and can be used as a baseline in a computable general equilibrium model like JRC-GEM-E3.

Many countries are formulating a long-term climate strategy to be submitted to the United Nations Framework Convention on Climate Change by 2020. Model-based, multi-disciplinary assessments can be a key ingredient for informing policy makers and engaging stakeholders in this process.

Economic models with global and economy-wide coverage can be useful tools to assess the impact of energy and environmental policies, but often disregard finer technological details of emission abatement measures. We present a framework for integrating and preserving detailed bottom-up information for end-of-pipe abatement technologies into a large-scale numerical model. Using an activity analysis approach, we capture non-linearities that typically characterise bottom-up abatement cost curves derived from discrete technology options. The model framework is flexible and can accommodate greenhouse gas and air pollution abatement, as well as modelling carbon capture and storage (CCS). Here, we illustrate this approach for non-CO2 greenhouse gases in a large-scale Computable General Equilibrium (CGE) model and compare results with a fitted marginal abatement curve and with completely excluding non-CO2 greenhouse gases. Results show that excluding non-CO2 abatement options leads to an overestimation of the total abatement cost. When the detailed bottom-up technology implementation is replaced by a fitted smooth marginal abatement cost curve, significant over- or underestimations of abatement levels and costs can emerge for particular pollutant-sector-region combinations.

A transition towards Autonomous, Connected and Electric (ACE) Vehicles on the road is likely to have significant socio-economic implications beyond the impacts foreseen in the passenger and freight transport sectors. This paper explores how the deployment of these technologies may impact the European Union's economy, employment and emissions. A number of impacts are in focus for this analysis. First, as new technologies for cars and trucks develop, the manufacturing of vehicles will change, with ramifications throughout the entire supply chain. Second, as these new vehicles penetrate the passenger and freight transport markets and the vehicle stock is renewed, further socio-economic shifts will result from their use on the road: the fuel mix and fuel efficiency will gradually evolve, together with emission intensity, triggering changes across energy extraction, production and distribution sectors. Their deployment will also affect demand for other goods and services, such as repair and maintenance, spare components, costs of freight and passenger transport services. These issues are analysed through scenario analysis using a multi-sectoral computable general equilibrium model: the JRC-GEM-E3. As a global economy-energy-environment CGE model, the JRC-GEM-E3 is extended to identify key sectors (e.g. vehicle manufacturing) and relationships of interest between road transport activity, fuel consumption, emissions and the rest of the economy. Three key scenarios – varying in terms of technology deployment and vehicle use – are modelled against a baseline scenario, to identify and disentangle the potential impacts of ACE trends on the EU economy, employment and the environment.

This report analyses global transition pathways to a low Greenhouse Gas (GHG) emissions economy. The main scenarios presented have been designed to be compatible with the 2°C and 1.5°C temperature targets put forward in the UNFCCC Paris Agreement, in order to minimise irreversible climate damages. Reaching these targets requires action from all world countries and in all economic sectors. Global net GHG emissions would have to drop to zero by around 2080 to limit temperature increase to 2°C with respect to pre-industrial times (by around 2065 for the 1.5°C limit). The analysis shows that this ambitious low-carbon transition can be achieved with robust economic growth, implying small mitigation costs. Results furthermore highlight that the combination of climate and air policies can contribute to improving air quality across the globe, thus enabling progress on the UN Sustainable Development Goals for climate action, clean energy and good health. Key uncertainties in future pathways related to the availability of future technological options have been assessed for Carbon Capture and Sequestration (CCS) and bioenergy. If CCS technologies would not develop, a 2°C pathway would have a similar mitigation trajectory in the first half of the century as a 1.5°C scenario with CCS.

This paper provides an overview of the different approaches to model trade in dynamic computable general equilibrium models. It will address the theoretical structures used, the trade baselines implemented in the projections, and the challenges for dynamic trade modelling. On the theory side we study the import demand specifications employed (Armington, monopolistic competition, and the use of nested preferences) and the export structure (perfect or imperfect transformation between domestic and exported goods). We also provide an in-depth discussion of the approaches to model the trade balance. On the trade structure most models converge on the use of nested Armington preferences with domestic goods and exports being homogeneous. Approaches to modelling the trade balance diverge between constant trade balances, trade balances based on a macro model, trade balances determined by rates of return, and converging trade balances. On projections the main questions are whether and how trade to income ratios are modelled given historical trends in this ratio. The way structural change is modelled also affects trade projections as it impacts the sectoral composition of trade and the possibility to generate Balassa-Samuelson effects (higher price levels in richer countries). Challenges for dynamic trade modelling consist among others of capturing changes in the extensive margin, exploring the impact of new technologies and digitalization on the size and composition of trade, including affiliate sales in projections, creating a database for trade cost trajectories related to the numerous FTAs in place, the appropriateness for dynamic modelling of the theoretical structures and parameters developed for static models, and the role of changes in energy use and energy efficiency in the development of trade balances.

From a price range between 100 and 120 USD (U.S. dollars) per barrel in 2011–2014, the crude oil price fell from mid-2014 onwards, reaching a level of 26 USD per barrel in January 2016. Here we assess the economic consequences of this strong decrease in the oil price. A retrospective analysis based on data of the past 25 years sheds light on the vulnerability of oil-producing regions to the oil price volatility. Gross domestic product (GDP) and government revenues in many Gulf countries exhibit a strong dependence on oil, while more diversified economies improve resilience to oil price shocks. The lack of a sovereign wealth fund, in combination with limited oil reserves, makes parts of Sub-Saharan Africa particularly vulnerable to sustained periods of low oil prices. Next, we estimate the macroeconomic impacts of a 60% oil price drop for all regions in the world. A numerical simulation yields a global GDP increase of roughly 1% and illustrates how the regional impact on GDP relates to oil export dependence. Finally, we reflect on the broader implications (such as migration flows) of macroeconomic responses to oil prices and look ahead to the challenge of structural change in a world committed to limiting global warming.

This report analyses global transition pathways to a low Greenhouse Gas (GHG) emissions economy The main scenarios presented have been designed to be compatible with the 2°C and 1.5°C temperature targets put forward in the UNFCCC Paris Agreement, in order to minimise irreversible climate damages. Reaching these targets requires action from all world countries and in all economic sectors. Global net GHG emissions would have to drop to zero by around 2080 to limit temperature increase to 2°C above pre-industrial levels (by around 2065 for the 1.5°C limit). The analysis shows that this ambitious low-carbon transition can be achieved with robust economic growth, implying small mitigation costs. Results furthermore highlight that the combination of climate and air policies can contribute to improving air quality across the globe, thus enabling progress on the UN Sustainable Development Goals for climate action, clean energy and good health. Key uncertainties in future pathways related to the availability of future technological options have been assessed for Carbon Capture and Sequestration (CCS) and bioenergy. If CCS technologies would not develop, a 2°C pathway would have a similar mitigation trajectory in the first half of the century as a 1.5°C scenario with CCS.

The Paris Agreement—which is aimed at holding global warming well below 2 °C while pursuing efforts to limit it below 1.5 °C—has initiated a bottom-up process of iteratively updating nationally determined contributions to reach these long-term goals. Achieving these goals implies a tight limit on cumulative net CO2 emissions, of which residual CO2 emissions from fossil fuels are the greatest impediment. Here, using an ensemble of seven integrated assessment models (IAMs), we explore the determinants of these residual emissions, focusing on sector-level contributions. Even when strengthened pre-2030 mitigation action is combined with very stringent long-term policies, cumulative residual CO2 emissions from fossil fuels remain at 850–1,150 GtCO2 during 2016–2100, despite carbon prices of US$130–420 per tCO2 by 2030. Thus, 640–950 GtCO2 removal is required for a likely chance of limiting end-of-century warming to 1.5 °C. In the absence of strengthened pre-2030 pledges, long-term CO2 commitments are increased by 160–330 GtCO2, further jeopardizing achievement of the 1.5 °C goal and increasing dependence on CO2 removal. Residual CO2 emissions from fossil fuels limit the likelihood of meeting the goals of the Paris Agreement. A sector-level assessment of residual emissions using an ensemble of IAMs indicates that 640–950 GtCO2 removal will be required to constrain warming to 1.5 °C.

Local air quality co-benefits can provide complementary support for ambitious climate action and can enable progress on related Sustainable Development Goals. Here we show that the transformation of the energy system implied by the emission reduction pledges brought forward in the context of the Paris Agreement on climate change (Nationally Determined Contributions or NDCs) substantially reduces local air pollution across the globe. The NDCs could avoid between 71 and 99 thousand premature deaths annually in 2030 compared to a reference case, depending on the stringency of direct air pollution controls. A more ambitious 2 °C-compatible pathway raises the number of avoided premature deaths from air pollution to 178–346 thousand annually in 2030, and up to 0.7–1.5 million in the year 2050. Air quality co-benefits on morbidity, mortality, and agriculture could globally offset the costs of climate policy. An integrated policy perspective is needed to maximise benefits for climate and health.

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

This paper describes the so called EU-GTAP conversion method developed by the European Commission to produce a set of Input-Output Tables for the 28 Member States for the reference year 2010 under the new European System of Accounts methodology (ESA2010, complying with UN SNA2008) and in compliance with GTAP submission requirements. Such conversion method allows the transformation of the ESTAT Input-Output Tables from NACE Rev.2/ISIC Rev.4 into the GTAP sectorial classification by means of several steps. The resulting EU GTAP IO tables fully comply with Eurostat aggregates and subtotals at a certain common level of aggregation as well as with other official statistics on gross output, value added and foreign trade statistics.

This paper presents a model-based assessment of the United Nations-led round of international climate change negotiations in Paris in December 2015 (COP21). We combine a technology-rich bottom-up energy system model with a top-down economic model that captures economy-wide interactions. We analyse the impact of the Intended Nationally Determined Contributions (INDCs) by the individual countries put forward in the run-up to COP21 on greenhouse gas emissions, energy demand and supply, and the wider economic effects, including the implications for trade flows and employment levels. We also illustrate how the gap between the Paris pledges and a pathway that is likely to restrict global warming to 2°C can be bridged, taking into account both equity and efficiency considerations. Results indicate that energy demand reduction and a decarbonisation of the power sector are important contributors to overall emission reductions up to 2050. Further, the analysis shows that global action to cut emissions is consistent with robust economic growth. Emerging and lowest-income economies will maintain high rates of economic growth. The analysis also provides evidence that the use of smart fiscal policies tailored to each region, i.e. increasing emission auctions and taxes, reducing indirect taxes to consumption and investment, and/or lowering labour taxes, can further increase GDP growth.

Concise introductions to the main issues in energy policy and their interaction with environmental policies in the EU. The European Union (EU) faces critical challenges in energy policy making, the most pressing of which are how to achieve the deep greenhouse gas reductions promised at the December 2015 UN Conference of the Parties in Paris, and how this effort can be coordinated with already existing policies. Energy policy is primarily a member state responsibility, and policy makers need an overarching view of the main issues in energy policy and their interaction with environmental policies. This volume aims to fill this need, offering concise introductions to some of the major issues as well as practical suggestions for policy making. The contributors discuss reforms to the EU Emissions Trading System (ETS), the world's largest carbon market; ways to improve the operation and integration of the EU's power grids, in terms of both supply and demand; changes to the EU's Energy Tax Directive, which sets tax floors for fuels outside the ETS; the coordination of climate policies with policies to promote renewables and energy efficiency; research into clean technology; challenges to shale gas development; and transportation policy and the need for action on such externalities as traffic congestion. Finally, contributors consider obstacles to reform, including its potential effects on vulnerable households and energy-intensive industries. Contributors Mikael Skou Andersen, Niels Anger, Bruno De Borger, Antoine Dechezleprêtre, Jos Delbeke, Ottmar Edenhofer, Christian Flachsland, Beatriz Gaitan, Polona Gregorin, Cameron Hepburn, Alan Krupnick …

The European Commission’s DG JRC IPTS undertook the task of updating/transforming the GTAP database's Input-Output tables for the 28 EU countries using the 2010 EUROSTAT Supply, Use and IO Tables (SUIOTs) and 'Taxes less subsidies on products' (TLS) matrices and auxiliary data, notably the MacMap for import duties, the 'Excise Revenue Tables' and 'National Tax List' data of DG TAXUD, the Eurostat's national accounts database and various publications of the national statistical offices. The first task was the decomposition of the TLS matrix to its VAT, excise tax, custom duty, 'other taxes on products' and subsidy components. This decomposition is not required for a GTAP data update, but a higher degree of detail makes the EU data more suitable for tax policy analysis. In the decomposition we exploited fully that the different taxes/subsidies usually affect only a limited number of users or products. The estimation process consists of the following main phases: 1. Estimating the row-totals (totals by products) for the component matrices (TLS layers), 2. Estimating satisfactory priors for each TLS layers, 3. Elaborating an entropy-model to simultaneously and consistently estimate the TLS layers. Since data availability, accounting methods and the tax system are heterogeneous across the EU countries, the general entropy model had to take into account country-specific constraints and adjustments. A partly different pilot-entropy model for Hungary was elaborated to take into account the very specific characteristics of its tax system. The entropy model seems to produce reasonable results for the decomposition. Then the TLS layers have been transformed to GTAP-sectors and split to domestic and import related parts. The transformed IOTs in GTAP format had to be consistent with the official statistics figures for value added, output and total imports too. We developed and used an other entropy model which represented all consistency criteria and other constraints.