Are Carbon Prices Redundant in the 2030 EU Climate and Energy Policy Package?

• Author: Aune, Finn Roar

1. INTRODUCTION

   In 2018, an agreement between the key EU institutions--the Commission, the European Parliament, and the European Council--was reached after a long-lasting discourse over the 2030 EU climate and energy policy package. While there had been disagreement over the types of energy targets and how ambitious the targets should be, the parties agreed to an EU-wide renewable share in final energy consumption of 32 percent (Eur-lex (2018a)), to improve EU energy efficiency by 32.5 percent (relative to 2005) (Eur-lex (2018b)), and also to reduce greenhouse gas (GHG) emissions by (at least) 40 percent (relative to 1990) (Europa (2019a)). The aim of this paper is to offer a comprehensive assessment of the approved EU 2030 climate and energy package. As there have been intense debates on which targets the EU should reach, we also analyze the 2030 outcome if, hypothetically, alternative energy policy targets had been agreed upon (or the EU energy targets are changed in the future).

   The motivation of this paper is that the EU 2030 policy package is probably the single most important factor with respect to the development of the European energy markets and it also has powerful implications for policy design. The package is complex as it contains three types of targets: GHG emissions, renewables, and energy efficiency. Each target will contribute to decreased GHG emissions, although the partial effects of reaching each target differ: standard economic theory suggests that if a higher share of renewables in energy consumption is obtained through producing more renewable electricity, the price of electricity is pushed down. Then units such as fossil-fuel power plants with high operating costs will be phased out. With less fossil-based electricity, GHG emissions drop. (1) Economic theory also suggests that improved energy efficiency tends to lower the demand for fossil energy. Therefore, the price of fossil energy declines and fossil fuel-based energy production is phased out.

   While standard economic theory predicts the main effects of reaching each of the targets in the EU 2030 package, the net effects of reaching all targets, as well as the magnitude of the effects, cannot be predicted from theory; a numerical model is needed. In this study, we will use the numerical model LIBEMOD to find the equilibrium effects of the EU 2030 climate and energy package, see LIBEMOD (2015).

   LIBEMOD is a multigood, multiperiod model covering the entire value chain in the energy markets in 30 European countries from investment, extraction, and production via trade to consumption. In LIBEMOD, emissions reductions in the electricity generation sector are accomplished through a different mix and scale of electricity technologies; a higher price of emissions triggers less investment in, and production of, fossil fuel-based electricity. In the end-user sectors, emissions reductions require higher end-user prices. LIBEMOD determines all energy prices and quantities in the European energy markets. Because renewable electricity plays a critical role in reaching the 2030 EU targets, investment in hydro, bio, wind, and solar power is endogenous in LIBEMOD. The model finds the combination of policy instruments that is consistent with reaching all policy goals.

   This paper makes three contributions to the literature. Whereas the 2030 EU climate and energy policy package was analyzed in a commissioned work by the EU Commission, see PRIMES (2019), the present paper is the first "external" study of the 2030 package. Our first contribution is to characterize the outcome when all EU climate and energy targets are required to be met. We find that the targets for renewables and improved energy efficiency have been set so high that the implied GHG emissions reduction is 50 percent, which is higher than the agreed-upon 40 percent target. This result is in line with PRIMES (2019), which found that the 2030 package will lower GHG emissions by 46 percent. We compare our results to PRIMES (2019) as well as to other studies that have imposed some of the targets in the 2030 package.

   The EU climate target of a 40 percent emissions reduction by 2030 should, according to EU decisions, be reached by cutting emissions in the ETS sectors (electricity generation, carbon-intensive manufacturing firms, petroleum extraction and most of aviation) by 43 percent relative to 2005, whereas emissions in the remaining sectors (non-ETS) should be reduced by 30 percent relative to 2005. We find that by achieving the renewable and energy efficiency targets, both the ETS and non-ETS emissions targets are met (see Section 5). Hence, there is no need for a climate policy. However, while an efficient emissions reduction is characterized by equal marginal cost of emissions reduction in the ETS and non-ETS sectors, there is no reason to believe that cost efficiency will be reached when the emissions reduction is obtained through achieving the renewable and energy efficiency targets. In fact, we demonstrate that if a 50 percent GHG emissions reduction is reached cost-efficiently, then annual welfare increases (relative to the Reference scenario above) by an amount corresponding to 0.6 percent of GDP in Europe (see Section 6.3).

   For years there has been a heated debate in the EU on whether there should be policy targets for renewables and improvement in energy efficiency, and if so, how ambitious these should be (see Section 3). Our second contribution is to examine how a renewable share in final energy consumption other than 32 percent, as well as an improvement in energy efficiency other than 32.5 percent, will affect emissions in the ETS and non-ETS sectors (see Section 6.1). We also show how the policy instruments imposed to reach the two energy policy targets need to be adjusted when the energy targets take alternative values. For example, we examine by how much the renewable share can be reduced below 32 percent (or the improvement in energy efficiency can be reduced below 32.5 percent) before either the ETS or the non-ETS emissions reduction target bites. We find that if the renewable share is 23 percent (and the improvement in energy efficiency is 32.5 percent), then ETS emissions are exactly 43 percent below their 2005 value. Hence, if the renewable share is below 23 percent (and the improvement in energy efficiency is 32.5 percent), it is necessary to have a positive price on C[O.sub.2] emissions in the ETS sector in 2030 in order to meet the requirement that ETS emissions should be 43 percent lower than in 2005.

   Our third contribution is to the energy modeling literature. Here, our main contribution is to offer a framework for endogenizing investment in intermittent power (wind and solar power) and to present a calibration strategy that quantifies structural wind and solar parameters. We derive first-order conditions for investment in and production of intermittent power by solving an optimization problem with the same structure as for any other electricity technology. However, we take into account that production sites differ with respect to wind conditions and solar irradiance. This is captured by a structural relationship between a measure for generated wind (or solar) power in a country and installed wind (or solar) capacity. We calibrate these relationships by utilizing detailed, spatial information about hourly wind speed, solar irradiance, reflection, and air temperature. For calibration, we have to make assumptions about the share of grid cells that will be available for the development of wind and solar power. We can, however, easily test how alternative land-availability assumptions affect energy markets (Section 6.2).

   The remainder of the paper is structured as follows. Section 2 provides a short review of two strands of the literature that are related to the present paper, namely achieving climate and energy targets, and efficiency of electricity markets. In Section 3, we give a summary of the debate that culminated in 2018 when the key EU institutions agreed upon the 2030 policy package. The numerical model LIBEMOD, which is used to analyze the 2030 climate and energy package, is presented in Section 4, whereas the resulting 2030 equilibrium is described in Section 5. In Section 6, we provide two types of robustness analysis: alternative policy targets and alternative parameter values. Section 7 concludes.

2. RELATED LITERATURE

   Our paper is linked to two strands of the energy economics literature: policy instruments used to reach climate and energy targets, and the efficiency of electricity markets with a high share of intermittent supply.

   2.1 Climate and energy policy targets

   Our paper contributes to the empirical literature on how climate and energy targets have impacted European energy markets. (2) This literature covers the following: (i) the 2020 EU climate and energy package with its three 20 percent targets (GHG emissions, renewables, and energy efficiency); (ii) the 2030 EU climate and energy targets; and (iii) the European energy market in 2050, in particular, how the way the EU intends to reduce GHG emissions by at least 80 percent by 2050 affects the energy sector.

   EU 2020

   Bohringer et al. (2009) provide an economic impact assessment of the 2020 EU goal to reduce emissions by at least 20 percent relative to 1990. To identify the impacts of the EU climate policy, they use a computable general equilibrium model of international trade and energy and simulate alternative scenarios. Boeters and Koornneef (2011) examine the cost of imposing a 20 percent renewable target in addition to the climate target of a 20 percent emissions reduction by 2020. Using the computable general equilibrium model WorldScan, they find that the renewable target increases costs by 6 percent; however, this estimate is sensitive to a number of key assumptions. Landis and Heindl (2019) study distributional effects of the 2020 EU climate and energy policy. Using the...