Renewable Energy Targets in the Context of the EU ETS: Whom do They Benefit Exactly?

Author:Landis, Florian

    The climate policy of the EU has distributional consequences across households, industries, and countries. In order for the EU to be able to continue to pursue ambitious targets in climate policy, policy implementation needs to keep these distributional consequences in check: In order to facilitate unanimous agreement on targets, it must be avoided that some, especially less affluent, member states bear disproportionately big shares of the overall policy cost. However, unevenly distributed impacts have to be expected in the context of C[O.sub.2] taxes or emission trading systems, as low-income households usually spend a larger share of their income on energy services when compared to wealthier households.

    The EU'S policy design shows recognition of this problem by allocating auction revenues from the European Emission Trading System (EU ETS) to member states based on their economic abilities (viz. 'expectations for economic growth, the energy mix, and the industrial structure of the respective Member State' according to the EU council's decision 2002/358/CE). EU rules further encourage member states to use their allocated permit auction revenue for counteracting unintended distributional impacts of climate policies (among other recommended uses of the revenue). (1)

    This paper analyses the effectiveness of the EU'S distribution of permit auction revenues against the backdrop of pre-existing inequality in/across the member states and analyses the interaction of EU targets for renewable power generation with this redistribution mechanism. Mandatory targets on the member state level for renewable energy sources (RES) in the power sector increase emissions abatement under the ETS within the member states that adopt such targets. (2) By doing so, they reduce the emission reductions required from other member states. (3) At the same time, they reduce the market price for emission allowances under the ETS and thus revenues from auctioning the emission allowances, because increased renewable energy production reduces the demand for conventional power generation and consequently emissions allowances (while supply of allowances remains constant). The overall effect of RES targets on the distribution of climate policy cost is a priori unknown. We approach the analysis of the distributional effects and interactions of climate policies in the context of the EU'S 20 percent emission reduction target for the year 2020 and apply the computable general equilibrium (CGE) model PACE in order to examine costs and distributional effects across and within EU member states under different policy scenarios.

    There is a large body of literature on the distributional effects of climate policy. Most studies analysing expenditure patterns suggest that direct carbon taxation will cause regressive effects if the prices of necessities, such as electricity or space heating, are affected. In contrast, direct taxation of the carbon content of transport fuels tends to be neutral or even progressive (Sterner, 2012). However, restricting the analysis to expenditure patterns ignores important effects on the income side. The analysis by Fullerton and Heutel (2007) and a survey by Boccanfuso et al. (2011) emphasise the importance of general equilibrium effects in this context. If climate policy causes important changes for factor income (land rents, capital income, labour income) CGE models are a valuable tool for keeping track of these effects. Rausch et al. (2011) confirm this argument in their analysis of a hypothetical cap-and-trade scheme in the United States, assuming a carbon price of approximately USD 20 per ton of C[O.sub.2] equivalent. Buddelmeyer et al. (2012) combine a CGE model with a micro-simulation model to assess the impact of carbon emission reductions by cap-and-trade in Australia. The authors find a moderately progressive distribution of costs after revenue recycling by lump-sum transfers. However, progressivity diminishes over the course of time as recycled permit revenues eventually become too small to compensate households in the second income quintile.

    Distributional effects of renewable energy standards in the United States are examined in a CGE model by Rausch and Mowers (2014). They find that a renewable energy standard would be about four times more costly than a "comprehensive market-based carbon pricing policy" [p. 582]. A renewable energy standard would further cause regressive distributional effects [p. 574]. Since the policy does not raise revenues, options for mitigating distributional effects through revenue recycling do not exist. Several ways in which promotion of RES interacts with the ETS in unintended ways have been highlighted in the literature: Flues et al. (2014) show how the combination of policies make ETS permit prices more sensitive to economic activity and that policy costs increase in particular in the presence of negative electricity demand shocks. Bohringer and Rosendahl (2010) show that the lower permit prices implied by binding RES targets may prove most advantageous for those fossil generation technologies that pollute the most. But an analysis of how national RES policies may affect the distribution of policy cost of the ETS across countries seems to be missing.

    Our results indicate that the EU'S efforts to redistribute policy costs through allocating permit auction revenues succeed in protecting the least wealthy member states in Eastern Europe from negative impacts of the ETS. In fact, most of those countries appear to profit from the current ETS design. Binding minimum requirements for RES in national power generation shift abatement costs from countries without such ancillary targets to countries that implement them but at the same time reduce revenues from permit auctions, which affects countries in proportion to the shares of auction revenues that are allocated to them. We find the latter effect to dominate the former, if several net permit importing member states adopt binding RES targets. That is, a country will tend to gain (lose) from the ancillary RES targets if it receives auction revenues from fewer (more) emission permits than its industries require under the cap. This holds almost irrespective of whether the country itself is subject to a binding RES target or not. Also, in the absence of revenue recycling, observed distributional effects within countries show regressive patterns for most EU member states. If revenues are fully or partly recycled in accordance with existing tax and transfer schemes, the resulting patterns of distribution become progressive. In some member states, the lowest income quintiles even profit in absolute terms.

    The remainder of this paper is organised as follows. The model is presented in Section 2, including a data description, the procedure of disaggregation of households along the quintiles of the income distribution, and the policy scenarios. Results are discussed in Section 3. Section 4 discusses the newly introduced MSR and Section 5 concludes.

  2. MODEL

    Our study employs the PACE model and extends it by splitting the EU member states' representative households into income quintiles. Realistic accounting of ETS permit auctioning revenues and how they are distributed among member states allows for the analysis of distributional impacts of climate policy targets. The PACE model is well suited for the analysis of international climate policy, due to its sectoral resolution of energy production, its representation of trade patterns, physical energy flows and its calibration to the EU'S scenarios for economic growth and energy use under continuation of the currently enacted climate policy. This section provides a brief overview of the model. The model is described in detail in Appendix A.

    2.1 The PACE model

    The PACE model is a GTAPinGAMS CGE model (4) with extensions that make it suitable for the analysis of climate and energy policies at a global scale. Besides the 28 member states of the EU, the model includes the world regions China, Japan, South Korea, Indonesia, India, Canada, USA, Mexico, Brazil, Russia, Australia, and New Zealand, Rest of Annex I (5), Rest of World. In each region, representative households own (region specific) production factors that are employed by the regional sectors for producing globally traded commodities. For each European member state, consumers are segmented into five households which represent income quintiles and both their expenditure and their income are calibrated by using survey data from European member states.

    The production factors owned by the representative households are labour, capital, and resources (viz. the fossil fuels crude oil, gas, and coal). The demand for consumption goods of the representative households are given by household specific demand functions and the investment good is demanded by households in fixed amounts. Labour and capital are mobile between sectors within countries. Technology specific capital for power generation is an exception to this and is in fixed supply. Governments in each region levy taxes, issue subsidies, make transfers to households, and demand fixed amounts of government services. Taxes in PACE are levied on production factors and final products. Countries levy tariffs on imports and subsidise exports.

    The production factors are employed by industrial sectors to produce sector specific outputs which are traded between regions and used as intermediate inputs by other sectors or consumed by representative agents. PACE uses nested constant elasticity of substitution (CES) production functions to represent production in different economic sectors, trade, and final consumption. The standard production function (see also Fig. 5 in the Appendix) combines the use of intermediates with a value added-energy composite at the top level.

    In the case of power generation, the model distinguishes the five generation technologies 'oil', 'gas', 'coal'...

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