Abstract
The lack of equal globally binding GHG’s emission reduction targets is currently leading to a set of diverging GHG’s emission prices across the world (or even no price for GHG’s emission in some regions). This may result in distortions with direct implications on competitiveness of the industries in regions with strict climate policies (as the European Union) and can cause the issue of carbon leakage. Carbon leakage is defined as ‘the increase in emission outside a region as a direct result of the policy to cap emission in this region’.
This paper is the first part of the set of two analysis aiming at the carbon leakage assessment. In the following paper (aimed to be published this year), we will assess the impact of free allowances for emission intensive trade exposed industries (EITE) and the NDCs in the rest of the world countries – for the sake of brevity, we decided to remove these results from the current paper, but they will be presented later this year. The purpose of this paper is to assess the possible scale of the carbon leakage using different assumptions and policy scenarios and identify channels to efficiently prevent the carbon leakage phenomenon. The analysis has been carried out using the computable general equilibrium d-PLACE model developed within the Centre for Climate and Policy Analysis (CAKE).
See: http://climatecake.pl/?lang=en
Our model is a recursive dynamic multi-regional and multi-commodity tool in which emissions are modelled in great detail, for example, the process and each fossil fuel combustion related emission are modelled separately. Furthermore, the big advantage of the applied model is a very detailed modelling of EU ETS as well as non-ETS emission targets. In the paper, the simulations using two versions of model was presented – with and without endogenous technical change to elaborate on how the assumptions on technical change affect the modelling results and consequent scale of the carbon leakage. Moreover, this paper aims mainly at the assessment of different channels of carbon leakage; therefore, we do not take into account either NDCs in the rest of the world or free allowances for emission intensive trade exposed sectors. These problems will be handled in the next paper, aimed to be published later this year.
Using the above mentioned CGE (computable general equilibrium model, we captured the main factors, that determine the carbon leakage rates. We assessed the contribution of three channels – demand channel, competitiveness channel and carbon intensity channel to the risk of carbon leakage. It turned out that carbon intensity channel and competitiveness channel are the most important, while demand channel contributes to changes in GHG’s emission only in the most restrictive scenario. Moreover, energy channel was further decomposed to the impact of sectoral structure and influence in emission intensity within each sector – the impact of these two channels is also similar, but dependent on the analysed scenario. Such a decomposition allowed us to determine the main channels through which the carbon leakage occur and pursue relevant policy recommendations.
Market-induced carbon leakage in China’s certified emission reduction projects
