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Economic Change and Restructuring

Published in:

07-01-2022

COVID-19, recovery policies and the resilience of EU ETS

Authors: Hanmin Dong, Xiujie Tan, Si Cheng, Yishuang Liu

Published in: Economic Change and Restructuring | Issue 5/2023

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Abstract

COVID-19 pandemic and its recovery bring opportunities and threats for global climate governance and further challenge climate related assets. In this study, we analyze the efficiency of government response policies and fiscal policies on green recovery by observing the variation characteristics of carbon allowance prices in the EU emission trading system (EU ETS). Using the OLS and threshold methods in the original time scales, we find that: (1) The EUA prices had an inverted U-shaped relationship with the number of new confirmed cases and deaths. (2) Government response policies had a better effect than fiscal policies when mitigating the negative impact of the pandemic. After decomposing and reconstructing the time series, the multiscale analysis indicates that: (3) The carbon price fluctuated in the short term with the increasing number of newly confirmed cases (or deaths) but gradually recovered due to the recovery policies. (4) Government response policies had a “stop-loss” effect in the short term, and then working alongside fiscal policies, sustained and promoted the development of the EU ETS and green recovery. In the post-COVID-19 era, we suggest the combination of various policies to convert the current health crisis into opportunities for climate change mitigation.

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Based on the experience of the 2008 financial crisis, when the wave of recession affected the EU ETS, the price of the EUA fell to very low levels as the supply–demand imbalance increased (Elkerbout and Zetterberg 2020). However, in the post-financial-crisis era, even though the economic activities started to recover, the EUA price remained below €10/ton for approximately the next 9 years. Faced with the current COVID-19 outbreak, the EUA price fell from €24/ton at the beginning of 2020 to €16/ton on March 20 with a total decrease of more than 30%. Compare with the fluctuations in the 2008 financial crisis, the decline in the EUA price was smaller, and the subsequent price recovery was relatively fast (Gerlagh et al. 2020). For example, the EUA price rose to €22/ton by June 2020 (Azarova and Mier 2020), indicating that it was well regulated and protected during the COVID-19 pandemic.

These measures included the introduction of the Market Stability Reserve mechanism and improved Linear Reduction Factor (Azarova and Mier 2020; Bocklet 2020; Elkerbout and Zetterberg 2020; Gerlagh et al. 2020).

Retrieved from International Energy Agency. The impacts of the COVID-19 crisis on global energy demand and CO₂ emissions. https://www.iea.org/reports/global-energy-review-2020. Last accessed October 20, 2021.

During the COVID-19 pandemic, carbon emissions in EU ETS were 38 Mt CO₂/month lower than usual (Bruninx and Ovaere 2020).

Examples include economic shocks, policy regulation, market fundamentals, climatic conditions, production activity, energy prices, and stock markets (Alberola et al. 2008; Boersen and Scholtens 2014; Christiansen et al. 2005; Creti et al. 2012; Deeney et al. 2016; Dutta et al. 2018; Keppler and Mansanet-Bataller 2010; Mansanet-Bataller et al. 2007; Ye and Xue 2021; Zhu et al. 2019).

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WIND is a financial data and analytic tools provider in China, covering domestic and foreign stocks, funds, bonds, foreign exchange, insurance, futures, financial derivatives, spot trading, macroeconomics, financial news, and other fields. WIND is frequently cited by the Chinese and English media, research reports, and academic papers. Retrieved from https://www.wind.com.cn/Default.html. Last accessed October 20, 2021.

The Oxford COVID-19 Government Response Tracker Database (OxCGRT) extensively quantifies government responses to COVID-19 from 3 dimensions and 13 indictors based on news reports, government announcements, and public information. To be specific, Stringency Indicator records information on social distancing policies and is coded from 8 indicators including the closure of school or workplace, cancellation of public events, restrictions on gathering, stay-at-home requirement, restrictions on internal movements; Containment and Health Indicator is coded from3 indicators representing public information campaigns, testing policy, and extent of contact tracing. Economic Support Indicator is constructed from 2 indicators including government income support and household debt/ contract relief. This database is widely used by academic research and its providers-Hale et al (2020)’s paper has been cited more than 800 times by October 2021. Retrieved from https://data.humdata.org/dataset/oxford-covid-19-government-response-tracker. Last accessed October 20, 2021.

Here, we do not consider the supply of EUA, as it depends entirely on the cap on emissions set by the European Commission and quantities allocated to individual firms (Batten et al. 2021).

If the Government Response Stringency Index is added to Eq. (1) directly, multicollinearity among the number of confirmed cases and deaths may occur. Therefore, this study uses a threshold model to determine the point at which the government measures against the pandemic became more stringent (or measures against the pandemic became more effective).

Empirical Mode Decomposition (EMD): \(x\left(t\right)=\sum_{i-1}^{n}{IMF}_{I}\left(t\right)+{r}_{n}\).

The NA-MEMD method applies the noise-assisted analysis method into MEMD, a dyadic filter bank on each channel while adding certain multi-dimensional White Gaussian Noises (WGNs) together with the original signals which are decomposed by using MEMD. For mode-alignment and mode mixing, the NA-MEMD is optimal compared with MEMD and EEMD (Zhang et al. 2017a; Zhang et al. 2017b).

Retrieved from http://www.tanjiaoyi.com/article-30814-1.html. Last accessed October 20, 2021.

In general, when fossil energy prices rise, power plants will reduce their use of these fossil energy sources and increase the use of cleaner energy sources. Hence, carbon emissions will decrease, and the carbon market will consequently reduce the demand for carbon allowances, leading to a decrease in the price of carbon. Conversely, when the price of clean energy increases, power plants will use cheaper fossil energy sources, which increases the price of carbon (Chevallier 2011).

We also use the death/ confirmed ratio (\({dc}_{t}\)) to conduct a robustness estimation. After consider \({dc}_{t}\) as the explanatory variable in Eq. (2), a threshold of 0.3943 could be obtained and matched to 25 February, which is close to our selected threshold day (3 March).

The calculation of abnormal prices refers to the principle of event study.

Considering the time overlap, we set the fiscal policies (\({fiscal}_{t}\)) as 0.5 when government responses (\({govern}_{t}\)) equals to 1 (hereinafter same).

Considering that the trend term of the carbon price reflects the long-term equilibrium of the carbon market, we do not include the short-term variable (\({case}_{t}\)) in the explanatory variables.

Retrieved from https://www.climatechangenews.com/2021/03/24/carbon-markets-proved-resilient-coronavirus-pandemic/. Last accessed October 20, 2021.

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Title: COVID-19, recovery policies and the resilience of EU ETS
Authors: Hanmin Dong
Xiujie Tan
Si Cheng
Yishuang Liu
Publication date: 07-01-2022
Publisher: Springer US
Published in: Economic Change and Restructuring / Issue 5/2023
Print ISSN: 1573-9414
Electronic ISSN: 1574-0277
DOI: https://doi.org/10.1007/s10644-021-09372-2

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