Introduction

The worldwide community is deeply concerned about the global issue of climate warming, which poses a severe danger to society’s long-term development (Adedoyin et al. 2020; Chen et al. 2021a, b; Zheng et al. 2022a, d). As the increase in carbon dioxide concentration is an important factor leading to climate change (Pachauri et al. 2014), many countries have targeted greenhouse gas (GHG) emission reduction through global agreements. Starting from the entry into force of the Kyoto Protocol, a carbon emissions trading (CET) system has been set up by significant economic entities, including the European Union and the USA (Omonijo and Yunsheng 2022; Maiti 2022; Jiang et al. 2022; Feng and Zheng 2022; Wang et al. 2022b, c; Lee and Hussain 2022; Hao et al. 2022, Yang et al. 2022a; Dey et al. 2022). At present, there are 24 carbon emission trading systems in the world, covering 16% of global GHG. The most effective political weapon for reducing CO2 emissions and preventing climate change has traditionally been considered the carbon market (Chai et al. 2022; Hao et al. 2023; Luo et al. 2022; Ren et al. 2022; Xue et al. 2022; Zhao et al. 2021). China is the world’s largest emitter of carbon dioxide, and therefore its efforts to reduce emissions have garnered interest on a global scale (Abbasi et al. 2021a).

China is likewise actively pursuing a low-carbon economy and lowering carbon emissions, but its carbon emission trading industry is still in the early stages (Zhang 2015). Since 2011, the country has implemented carbon emission trading as a pilot program in Shenzhen, Shanghai, Beijing, Guangdong, Tianjin, Hubei, Chongqing, and Fujian, as well as built and developed the carbon emission trading market. This serves to encourage corporate emission reduction and to fulfill the “Double Carbon” objective. China assured the world community in September 2020 that its carbon dioxide emissions will peak by 2030, and the nation will become carbon neutral by 2060 (Mallapaty 2020). There is no question that the healthy growth of China’s carbon emission trading market is critical for it to meet international carbon emission targets while also supporting a green and low-carbon transition. During the operation of the carbon emission trading market, restricted enterprises can use the carbon quota obtained for their own offset, trade additional carbon emissions in the carbon market, and sell them to enterprises that need carbon emission rights. Therefore, maintaining a stable carbon price is crucial for China’s carbon market.

As of July 27, 2022, COVID-19 had spread to more than 200 countries since the end of 2019, infected almost 570 million individuals, and claimed the lives of more than 6 million people.Footnote 1 To curb the further its spread, in addition to medical treatments, governments in many countries have taken restrictive measures on the movement of people, including closures of cities, jobs, businesses, and schools (Alfano and Ercolano 2020). Although these policies might control the epidemic’s development to a certain extent, they also have had an unprecedented impact on economic development (Tisdell 2020; Chang et al. 2021; Norouzi et al. 2020; Feng et al. 2021). The National Bureau of Statistics reports that China’s GDP decreased 6.8% year over year in the first quarter of 2020. In late December 2019, its PPI began to decline and the economy suffered heavy losses. In terms of its effect on equities, the circuit breaker mechanism was activated four times in the U.S. stock market in March 2020, and the Dow Jones index fell for several consecutive days with the largest drop reaching 37.1%. China’s financial market was also hit hard. February 3, 2020 was the first day of the opening of Shanghai and Shenzhen markets after the outbreak of the epidemic, and 3188 individual shares fell by their down-limit, making this the largest decline since 2015.

COVID-19’s serious impact both economically and financially has naturally spread to the carbon markets. This is mainly because, on the one hand, carbon emission quotas are like financial assets and closely relate to the financial market. On the other hand, the supply and demand of an enterprise’s carbon emission quotas play a significant role in the development of carbon prices, and the amount of supply and demand is strongly tied to enterprises’ production, particularly those that rely on fossil fuels (Fu et al. 2020; Wen et al. 2021; Zhao et al. 2022b; Zheng et al. 2022b, c, 2023; Wang et al. 2021b, 2022a). The global energy demand model was obviously altered at the start of the pandemic, which caused carbon emissions to shift, the carbon emission trading system to suffer significantly, and the carbon market to swing wildly. Therefore, to ensure the stability of carbon emission trading markets under the “Double Carbon” strategy, we thus concentrate on the pandemic’s effects on China’s carbon markets.

The COVID-19 epidemic’s influence upon the carbon market can theoretically be linked by the market’s supply and demand as well as investor expectations. To begin with, the COVID-19 pandemic altered the supply and demand therein by affecting carbon price volatility. From the perspective of carbon markets’ demand, the outbreak of the epidemic caused the global economy to slump, industrial production to shrink, construction activities to slow down, and traffic usage to decline, resulting in lower social demand for energy and putting the energy industry under great pressure (Chakraborty and Maity 2020). In the first 3 months of 2020, thermal power generation fell over 9% year-on-year. However, fossil energy consumption is the main reason for the rise in greenhouse gas emissions, and so with the reduction of global fossil energy use, carbon dioxide emissions will also drop (Li et al. 2021). Due to the lower resultant production and business activities, the carbon emissions generated by the production of control and emission enterprises markedly dropped. Naturally, they do not need to purchase carbon quotas to complete their emission reduction target. The demand for carbon emission caps also decreased, which had an immediate influence on the supply and demand curve of the carbon markets, resulting in instability and a drop in carbon prices (Yang et al. 2022b; Wang et al. 2021a; Long et al. 2022; Peng et al. 2022; Yin et al. 2022a, b; Wen et al. 2023). Once the situation of epidemic prevention and control improved, the economy gradually recovered, and the resumption of production proceeded. As such, enterprises need more carbon emission quotas, which will weaken the negative impact of the pandemic on the carbon price.

The relationship between the pandemic and the carbon market can be linked by increased volatility in the carbon market. According to the emotion theory, negative news in the financial markets is prone to panic and turbulence (Iyke and Ho 2019). This is mainly because once the government adopts stricter prevention and control policies, the pandemic situation may become more severe. In order to attract viewers, the news media may publish negative news, sending investors into a frenzy and increasing uncertainty in the carbon market. China’s carbon markets started late and encountered many problems, such as low market participation, inadequate government regulation, and a trading system that needed to be improved, and so investors have shown a wait-and-see attitude (Aihua et al. 2022). As a result, investors may have reallocated their portfolios to minimize risks when the COVID-19 pandemic broke out and spurred uncertainty in the carbon markets. This may have resulted in a short-term decrease in carbon market activity and a subsequent drop in carbon prices. In the long run and given the economic recovery, investors’ negative attitude towards the market will likely turn better. They may even reinvest in the carbon market, and the downward trend of carbon prices should disappear. It would appear that the COVID-19 pandemic’s negative impact on the market for carbon emission trading will only last a short while.

To more clearly demonstrate how China’s carbon market responded to the pandemic, this paper takes eight carbon emission trading markets in China, Beijing, Shenzhen, Guangdong, Shanghai, Hubei, Tianjin, Fujian, and Chongqing, as the research objects and presents the event study approach, which examines their responses to the pandemic. The decision to use the event research methodology is because, first, it is forward-looking and can timely obtain the returns brought to investors by events. Second, the method uses high-frequency data (daily data) to overcome the difficulty of low-frequency data not being able to separate the returns brought by time from the overall performance of carbon markets.

The study selects two incident dates. One is January 8, 2020, which is the initial stage of the epidemic’s outbreak—that is, COVID-19 was the cause of the outbreak, according to the National Health Commission’s experts on that day. The other is April 8, 2020, which was the end of the first wave of the massive outbreak or when Wuhan reopened. In addition to the Fujian carbon market, our empirical research findings indicate that the COVID-19 pandemic negatively impacted the other seven carbon markets as well. However, given the ongoing domestic control of the epidemic, this negative effect is gradually decreasing.

Our research contributes to the literature in three ways. First, scholars have gradually focused on the economic influence of the COVID-19 pandemic and growth (or lack of it) in the global economy, its impact on the securities market (Baker et al. 2020), and its impact on the energy market (Chen et al. 2021a, b). However, as an important means to solve the global climate problem, the response of carbon emission trading on COVID-19 has rarely been paid attention to by existing studies. Therefore, compared to others, this paper presents eight carbon trading markets in China and discusses how COVID-19 affects them.

Second, unlike previous discussions on the factors affecting the carbon market from the perspective of the energy market (Ji et al. 2018; Han et al. 2019), weather (Batten et al. 2021), and the macroeconomy (Wen et al. 2022), we believe that the carbon market’s stability is also linked to extreme events. Our study takes the COVID-19 pandemic as a factor affecting China’s carbon markets and expands research on the influencing factors of the carbon markets. Overall, it gives a fresh viewpoint for government departments to stabilize the healthy operation of carbon markets and to enhance the building of its essential mechanisms.

Third, contrast to prior research that focused on the COVID-19 pandemic’s impact on the EU carbon market, our study looks at the carbon market in China, because it can more accurately depict how developing nations’ carbon markets have responded to the pandemic. It can also guide development and investment in the carbon markets of developing countries, as represented by China.

The remainder of this paper runs as follows: the “Literature review” section introduces the literature review. The “Methodology and data” section describes the research methods and data sources. The “Empirical results” section presents the empirical findings. The “Conclusion and policy implications” section offers conclusions and some policy recommendations.

Literature review

Scientifically comprehending the effects of the COVID-19 pandemic is one of many important tasks in the post-epidemic phase. In this regard, its impact on macroeconomic performance and financial markets has attracted broad attention from scholars, who have focused on the interaction between it and macroeconomic variables. In this regard, the academic community has targeted the pandemic’s impact on macroeconomic variables including macroeconomic performance and securities markets as well as their correlations. Shen et al. (2020) stressed that the main reason for the global economic recession is mandatory lockdown policies after the pandemic erupted. Additionally, some academics looked into how the pandemic affected the securities market (Baker et al. 2020; Narayan et al. 2021; Engelhardt et al. 2021; Chang et al. 2021). Al Awadhi et al. (2020) discovered an inverse correlation between the quantity of confirmed COVID-19 cases and deaths and stock returns for Chinese-listed businesses. In contrast, Mazur et al (2021) examined the stock market performance of different industries in the USA, presenting that the response of their stock returns was inconsistent with the pandemic. Mazur et al. (2021), in contrast, concentrated on the stock market performance of several industries in the USA, showing that their stock returns reacted inconsistently with the pandemic. For example, the stock returns of healthcare, food, software, and other industries increased, while the stock returns of oil, entertainment, hotels, real estate, and other industries declined.

The pandemic’s impact on the energy market, especially on energy usage, energy pricing, and stock price performances of energy companies, has been established by several scholars (Devpura and Narayan 2020; Chen et al. 2021a, b; Fu and Shen 2020; Jiang et al. 2021). Sui et al (2021) found that crude oil prices were negatively affected by global epidemic disasters spanning from 1976 to 2018. According to Hu et al. (2022), the stock values of global energy companies fell along with the escalating severity of the government’s response to the COVID-19 epidemic. Unfortunately, there are scant studies on carbon markets, despite the fact that these studies have proved the COVID-19 pandemic’s enormous impact on a variety of social and economic systems.

To enable the proper operation and healthy growth of the carbon trading system, an appropriate carbon price must be established in the carbon market trading (Duan et al. 2021). Therefore, studies on the influencing factors of carbon emission trading price (carbon price) have increasingly gained popularity among researchers, with a particular emphasis on the energy market (Ji et al. 2018; Han et al. 2019; Zhao et al. 2022a; Abbasi et al. 2021b; Zheng et al. 2022a, b; Zhang et al. 2022; Abbasi et al. 2022a). According to Abbasi et al. (2022b), the usage of renewable energy only adversely affects carbon dioxide emissions over a relatively short time period. In contrast, increasing the consumption of fossil fuels will result in higher carbon emissions. However, using data from 10 emerging economies from 1996 to 2015, Awan et al. (2022) demonstrated that renewable energy lowered CO2 emissions at all quantile levels.

Several academics have also studied the connection between carbon markets and the macroeconomy or financial markets (Bandyopadhyay et al. 2022; Wen et al. 2022). Enterprises increase production when the macroeconomy is booming, which will lead to a rise in the demand for carbon emission quotas and a consequent rise in the carbon price. In contrast, when the economy is depressed, businesses’ output levels will decline, resulting in a drop in carbon emissions and a subsequent drop in the price of carbon (Wen et al. 2022). Some studies have discussed the impact of weather on the carbon market (Batten et al. 2021). Alberola et al. (2008) found that carbon price changes only in extremely cold weather. As a result, we see that while there have been many significant advances in the study of the factors that drive carbon prices (such as weather, energy, and macroeconomics); there are still few studies that consider extreme events, especially pandemics, as pre-factors to carbon prices. Although Feng et al. the COVID-19 pandemic affects carbon prices; they targeted the EU carbon market. The carbon markets in developing countries, as represented by China, had a late start and are less mature than the EU carbon market. There is clearly a gap in the literature covering the response of China’s carbon markets to the COVID-19 pandemic. This paper aims to fill this gap through our investigation.

Methodology and data

Fama et al. (1969) proposed an event study, which is a common method utilized in economic and financial research. It is able to understand the impact of an event by comparing the abnormal changes of sample yields before and after the event—that is, the abnormal rate of return. It excludes normal income from the actual income of the market, so as to evaluate the degree of the market’s abnormal reaction to a specific event. Using this method allows investors in a timely manner to obtain the expected value from events that have just occurred before obtaining the real income, which is forward-looking. At the same time, this method uses high-frequency data (daily data), while other low-frequency data (quarterly or annual) make it difficult to separate the income from the company’s overall performance (Sorescu et al. 2017). Therefore, we apply the event study approach to more clearly understand how COVID-19 will affect China’s individual carbon markets in the immediate future.

Methodology

This paper mainly presents the response of China’s carbon markets to COVID-19 by calculating and analyzing the daily abnormal rate of return (AR) and daily cumulative abnormal rate of return (CAR) of each carbon market, including the following specific steps.

(1) Determination of the event window

The COVID-19 pandemic event day, the event window period, and the estimation window period must first be established. This paper first sets the occurrence date of the event as day 0 (t = 0). The 20 trading days before and following the event day (i.e., [− 20, 20]) are chosen as the event window period based on past academic research. Second, determining the estimated window period is extremely important. The closer it is to the event day, the stronger is the interpretation of its data. However, the study findings are unreliable and skewed if the estimating window is too short. Therefore, we take 150 trading days to the first 21 trading days before the event day (that is, [− 150, − 20] (t =  − 150, t =  − 21)) as the estimation window period.

(2) Determination of abnormal rate of return

It is clear that the value of AR relies on how far the actual rate of return deviates from the normal rate of return E(R). Therefore, calculating the value of E(R) is the first step in calculating AR. The normal rate of return may now be calculated using a number of different approaches, including the market model method, market index adjustment model, and constant return model. If a bull market or bear market is on-going for a specific trading day, then there will be a great deviation between the mean value adjustment model and the constant return model (Klein and Rosenfeld 1987). High requirements for relationship assumptions are necessary for the development of the market index adjustment model, and so it is generally not applicable. Therefore, this paper selects the market model in the calculation process, because most studies have selected it, and it is very common. The idea behind the calculation is to estimate E(R) when there is no event based on the sample data in the estimation window period. This study develops a regression model in which we use the rate of return of China’s carbon market and of EU’s carbon market during the window period as explained variable and explanatory variable, respectively

$${R}_{it}={\alpha }_{i}+{\beta }_{i}{R}_{mt}+{\varepsilon }_{it}$$
(1)

In Eq. (1), Rit represents the daily yield of carbon market i on trading day t; Rmt represents the daily yield of the EU carbon market on trading day t; βi represents the systematic risk of carbon market i; and εit is a random error term. We assume ɑi and βi is stable in the inspection period. The expected normal rate of return is

$$E\left(R\right)={\alpha }_{i}+{\beta }_{i}{R}_{mt}$$
(2)

The variable \({AR}_{it}\) of carbon market i on trading day t can be obtained as

$${AR}_{it}={R}_{it}-E\left(R\right)$$
(3)

(3) Determination of the cumulative abnormal rate of return

In order to calculate CAR and determine the average response of the carbon market’s rate of return to the pandemic, this paper superimposes the daily abnormal rate of return during the event window. The calculation formula is

$${CAR}_{t}=\sum_{j=-20}^{t}{AAR}_{T}$$
(4)

(4) T-test of the cumulative abnormal rate of return

To judge whether \({AR}_{it}\) and \({CAR}_{it}\) calculated above are caused by the pandemic, this paper conducts a statistical significance test and constructs t-statistics as:

$${t}_{{CAR}_{t}=\frac{{CAR}_{t}}{S\left(CAR\right)/\sqrt{N}}}$$
(5)

If the t-test result is significant, then it can be inferred that the COVID-19 pandemic has a considerable impact on each carbon market and that the fluctuation of the carbon market over the event period is not due by random variables, as well as vice versa.

Sample selection and data

This paper examines COVID-19’s impact on China’s carbon markets. Since 2011, China has conducted carbon emissions trading pilots in Beijing, Shenzhen, Guangdong, Shanghai, Hubei, Tianjin, Fujian, and Chongqing, as well as created carbon markets. Therefore, our research focuses on these eight pilot carbon markets. The Wind database is where the transaction pricing information for each carbon market is derived.

According to the information disclosure and development of the COVID-19 pandemic in China, in December 2019 many patients with unexplained pneumonia symptoms began to appear in Wuhan. National Health Commission experts verified on January 8, 2020 that the new coronavirus was the cause of the pandemic. After that, COVID-19 developed rapidly, with the absolute closure of Wuhan and the establishment of a shelter hospital, which seriously hurt China’s economy. Therefore, in this paper, January 8, 2020 is regarded as the event day in the research process, and the window period is 20 trading days before and after the event day.

Empirical results

Empirical results based on event day of January 8, 2020

To obtain \({AR}_{it}\), this study first establishes a regression equation based on the samples in the estimation window period, calculates \(E\left(R\right)\) of the eight carbon markets in the event window period according to the regression equation, and then subtracts Rit in the event window period. Table 1 reports the calculation results of Rit, \(E\left(R\right)\), and \({AR}_{it}\) of the eight carbon markets at nine main time points (t =  − 20, t =  − 15, t =  − 10, t =  − 5, t = 0, t = 5, t = 10, t = 15, t = 20) at the initial stage of the pandemic.Footnote 2

Table 1 Results of the actual rate of return, normal rate of return, and abnormal rate of return of the eight carbon markets
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Table 1 reports the daily excess abnormal rate of return of the eight carbon markets. Following formula (4), this paper calculates the cumulative abnormal rate of return CAR of each carbon market in different event window periods. Table 2 presents the results.

Table 2 Results of the abnormal rate of return of the eight carbon markets (based on event day of January 8, 2020)
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From the calculation results of CAR, first, except for the Chongqing carbon market, the cumulative excess returns of the other carbon markets in any event window period are negative and pass the t-test, indicating that the COVID-19 pandemic is to blame for the abnormal rate of return. Second, apart from the carbon markets in Shenzhen and Fujian, the value of CAR gradually decreases with an increase in the time window, especially after the event day—that is, after the event day the rate of return of the carbon market shows a downward trend in the short term. Therefore, we preliminarily judge that China’s carbon market reacted negatively to the pandemic. Table 2 lists CAR of the eight carbon markets in each event window period, but the statistics in the table do not directly represent the changing trend of the carbon market rate of return. Therefore, to more clearly reflect the change trend of the rate of return in Table 2, we build a time series diagram of the anomalous rate of return based on the daily AR and daily CAR of each carbon market on trading day t of the event window period, as shown in Fig. 1.

Fig. 1
figure 1

Trend charts of AR and CAR of the 8 carbon markets

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Figure 1a illustrates the AR and CAR trend change charts of the Hebei carbon market. For AR, during the event window period [− 20, 20], the trading days with a positive abnormal rate of return AR account for 34% of all trading days during the event window period. Overall, AR fluctuates greatly. In the first half of the event window period (that is, [− 20, 0]), the abnormal rate of return is negative in 13 trading days, such as t =  − 20, t =  − 16, and t =  − 12. Among them, before t =  − 6, the abnormal rate of return AR fluctuates around 0, and the floating range is small, while between t =  − 6 and t = 0 the fluctuation of AR increases. In the second half of the event window period (that is, between [0, 20]), the AR value of 14 trading days is negative, and its change fluctuates greatly. Therefore, through the change trend of AR, we may consider that the rate of return of the Hubei carbon market fluctuated significantly from the pandemic. There are positive and negative returns, but what changes eventually come to the carbon markets and whether they are led to by the pandemic are still yet unknown.

We next analyze the calculation result of CAR. On the whole, throughout the full event window time, the CAR value of the Hubei carbon market exhibits a stable variation at first, followed by a negative trend. In the period [− 20, 0], the cumulative abnormal rate of return CAR value for 8 trading days is greater than 0. From t =  − 12, the CAR value is negative, starts to show a downward trend, and reaches the minimum value of − 0.3388 when t = 20. Combined with the results in Table 2, after the event day, as the range of the time window increases, the value of CAR becomes smaller and smaller and decreases by 66.48% from − 0.1295 to − 0.2156, passing the 99% significant level. This means that Hubei’s carbon market has been adversely affected by COVID-19.

Figure 1b shows the trend changes of AR and CAR in the Beijing carbon market. Similar to Fig. 1a, during the whole event window period the AR value of this carbon market fluctuates up and down around the 0 axis, while CAR shows a downward trend. Specifically, before t = 5, the change trends of AR and CAR are relatively consistent and then deviate gradually. This is mainly because before t = 5, the value of AR is positive and negative, and so it will not change in one direction. However, after t = 5, the value of AR is basically negative, which leads to the negative fluctuation of cumulative excess return CAR. When t = 15, CAR reaches the minimum value of 0.6957. However, after t = 5, the value of AR is basically negative, which leads to the negative fluctuation of CAR, and when t = 15, CAR reaches the minimum value of 0.6957. This result is also reflected in Table 2. In the event window period [0, 5], the average CAR value is − 0.2438, and then with the range of the time window increasing, the CAR value becomes smaller and smaller. In the event window period [0, 20] it reaches − 0.4255, which is a significant drop of 74.5%. The above analysis state that the Beijing carbon market also negatively responded to the COVID-19 pandemic.

Figure 1c shows the AR and CAR trend change charts of the Shenzhen carbon market. In the entire event window period [− 20, 20], AR fluctuates around the 0 axis, and after t = 5, the fluctuation range is large. CAR shows a downward trend. In the first half of the event window period (− 20, 0), only four trading days’ AR is positive. From t =  − 16, AR and CAR show a gradual deviation, and after t = 8, CAR shows a stable trend. Table 2 describes after the event day that with the expansion of the event window range, the average CAR value in each event window period gradually decreases, from − 2.4424 in the window period [0, 5] to − 2.5493 in the window period [0, 20], or a drop of 4.38%, which passes the 1% significance level. Arguably the Shenzhen carbon market negatively responded to the pandemic.

Figure 1d illustrates the AR and CAR trend change charts of the Shanghai carbon market. In the figure, throughout the event window, AR varies about the 0 axis. Especially in the second half of the event window period [0, 20], the fluctuation range of AR becomes larger. From the perspective of the relationship between AR and CAR, in the first half of the event window period [− 20, 0] the change trends of AR and CAR are consistent, while after t = 0 there is a deviation between them. Specifically, in the event window [0, 16] there are 14 trading days with negative AR, which leads to a straight downward trend of CAR even though AR fluctuates around the 0 axis. At the end of the whole event window period, after t = 16, AR gradually becomes positive, and CAR shows an upward trend. According to Table 2, after the event day with the expansion of the time window range, the average value of CAR decreases from − 0.4287 in the window period [0, 5] to − 0.8088 in the window period [0, 20], or a fall of 88.66%. The t-test of CAR in each event window period is significant. From the results of the preceding analysis, the more severe the pandemic situation is, the more negative impact the Shanghai carbon market will suffer.

Figure 1e presents the AR and CAR trend change charts of the Tianjin carbon market, where AR fluctuates up and down around the 0 axis. Before t = 4, the change trends of AR and CAR are similar, but in the next 17 trading days, AR is negative in 13 trading days, resulting in a gradual deviation between AR and CAR and showing a downward trend. According to Table 2, after the event day, the average CAR gradually decreases with an increase of the event window range. The CAR value falls 137% from − 0.0951 in the event window [0, 5] to − 0.2255 in the event window [0, 20]. The CAR value is still significant, which means the abnormal rate of return still belongs to the range of abnormal fluctuations. Thus, the Tianjin carbon market negatively responded to the pandemic over the short run.

Figure 1f depicts the AR and CAR trend change charts of the Guangdong carbon market. The figure illustrates that AR fluctuates up and down around the 0 axis and fluctuates greatly in the second half of the event window [0, 20]. Before t = 5, the change trends of AR and CAR are similar. After t = 5, AR and CAR show a deviation, and CAR begins to decline, reaching the minimum value of − 0.2514 on t = 19. According to Table 2, with an increase in the range of the event window period, CAR falls from − 0.0978 in the window period [0, 5] to − 0.1623 in the window period [0, 20], or a drop of 66%. The CAR of each event window period is significant at the 99% level—that is, the abnormal rate of return of the Guangdong carbon market just after the COVID-19 pandemic is very significant. Therefore, we consider that the Tianjin carbon market negatively responded to the pandemic over the short run.

Figure 1g shows the trend changes of AR and CAR in the Fujian carbon market, where AR fluctuates up and down around the 0 axis, while unlike other carbon markets, CAR shows a W-shape trend. This is mainly because there are 11 trading days with negative AR between t =  − 20 and t =  − 8, and so CAR shows a downward trend in this event window. From t =  − 5 to t =  − 1, the market’s AR is positive, and so CAR quickly rises. However, AR is negative for five consecutive trading days, and then CAR shows a downward trend. In the 13 trading days after t = 8, AR is almost always positive, and then CAR starts to rise. Overall, CAR shows a W-shape trend. According to Table 2, which presents the statistical results, with the increase in the range of the event window period, the CAR value goes from − 0.7874 in the window period [0.5] to − 0.5787 in the window period [0.20] and passes the 1% significance level. The reason for this result mainly relates to data selection. The Fujian carbon market is the last one to start among the eight carbon markets, being established on December 22, 2016. As a result, it lags behind the other carbon markets for trading mechanism maturity, trading frequency, and degree of market information reaction.

When collecting data, we find after the COVID-19 pandemic that the Fujian carbon market has only six trading days in February 2020, as it closed from March to June and resumed trading in July. Due to data acquisition, 6 trading days in the event window period [0, 20] are in February, and the rest are in July and August, during which the epidemic was being basically controlled. Therefore, it can be assumed that the COVID-19 had a short-term detrimental shock on the carbon market in Fujian. However, over time, as the epidemic’s spread was contained, the negative impact was progressively eradicated, and a positive influence on the carbon market gradually appeared.

Figure 1h shows the trend changes of AR and CAR in the Chongqing carbon market, where AR fluctuates up and down around the 0 axis. In the first half of the event window period [− 20, 0], there are 4 trading days with negative AR, and so CAR shows an upward trend during this period. In the second half of the event window period [0, 20], AR fluctuates greatly and is mostly negative. Therefore, CAR in this period shows a downward trend and reaches the minimum value of − 0.575 at t = 20. It means that the COVID-19 pandemic had a negative impact to the Chongqing carbon market. Simultaneously, when taken with the statistical data in Table 2, after the event day with the expansion of the event window range, the CAR value decreases from 0.07223 in the window period [0, 5] to − 0.2147 in the window period [0, 20], or a drop of 397%. The statistical significance of CAR is on the 10th trading day after the event day. It further demonstrates that the Chongqing carbon market’s reaction to COVID-19 was unusually slow, which relates to the market’s recent inception and its relatively immature market mechanism. In conclusion, China’s carbon markets have seen a brief negative shock as a result of the COVID-19 outbreak.

Empirical results based on event day of April 8, 2020

In the “Empirical results based on event day of January 8, 2020” section, we analyze the changes of AR and CAR of the eight carbon markets and come to the conclusion that the pandemic negatively influenced the carbon market within a short time. For further investigation, this paper changes the date of the event day and selects Wuhan’s lockdown being lifted on April 8, 2020 as the event day to explore how the COVID-19 event affected China’s carbon markets. The reason why we choose this date as the event day is that January 8, 2020, which is the day when the National Health Commission expert group confirmed the novel coronavirus as the coronavirus source, can be regarded as the initial stage of the COVID-19 pandemic outbreak and prevention. After that, the government took various epidemic prevention and protection measures, such as lockdowns, production suspensions, and school closures. Wuhan lifted its lockdown on April 8, indicating that the epidemic prevention and control had achieved certain results. To further explore the responses of the 8 carbon markets to COVID-19, this study uses April 8 as the event day.

Table 3 reports the CAR values and its t-test results of the 8 carbon markets in different event windows with April 8 as the event day. First, from the results of CAR, apart from the Chongqing carbon market, the CAR values of the other carbon markets in each event window are negative and significant at the 99% or 95% level. The CAR value of the Chongqing carbon market in the event window period of [0, 10], [0, 15], [0, 20] is negative, and its significance is gradually enhanced. This shows that the CAR values belong to the range of abnormal fluctuations. Carbon markets in China have clearly been significantly shocked by the COVID-19 outbreak.

Table 3 Results of the abnormal rate of return of the eight carbon markets (based on event day of April 8, 2020)
Full size table

Second, we observe the CAR value of each event window period after the event day (t = 0) and find in addition to the Fujian carbon market that, with the increase of the scope of the event window period, the CAR value of each carbon market also decreases, indicating that China’s carbon markets incurred a short-term negative effect from the COVID-19 pandemic outbreak. This is mainly because although the domestic COVID-19 pandemic was initially controlled, the pandemic then spread over several nations throughout the world. The World Health Organization declared COVID-19 a pandemic on March 11, 2020, demonstrating its severity. The USA, UK, and the European continent and other regions with serious outbreaks took up strict epidemic prevention measures, such as traffic restrictions and forced isolation, to curb its spread.

Third, carbon emission reduction is an important means to handle the problem of global climate change. Under the serious situation of the pandemic, the global economy became depressed and production dropped, which delayed the path of China’s economic resumption to some extent. Reduced trading volume appeared in the carbon market, and carbon prices dropped. With results similar to those in Table 2, the CAR value of the Fujian carbon market gradually increased during each event window period after the event day, which relates to data selection. Due to the inactivity of carbon market trading in Fujian, the carbon market did not start trading until July during the pandemic, and so available data appeared only in July and August. At that time, the domestic and international epidemic had been controlled to some extent, productivity gradually recovered, and demand for carbon emissions had progressively grown, resulting in a rise in carbon pricing. This also implies that the COVID-19 pandemic’s detrimental effects on the carbon market may reverse in the long run.

Finally, the short-term effects of COVID-19 are clearly detrimental to the carbon market. Compared with the results in Table 2, after the date of the event, the CAR value of each event window period with April 8 as the event day is greater than that of each event window period with January 8 as the event day. This result shows with the control of the epidemic that the negative impact on the carbon market is gradually decreasing.

Discussion of research results

Through the analysis of the above statistical results, this study demonstrates that the COVID-19 epidemic had a short-term detrimental influence on China’s carbon trading market, driving carbon prices lower, but this negative impact progressively subsided over time. Our research result is basically similar to that of Feng et al. (2022), who noted that the emergence of the pandemic negatively shocked the EU carbon market, but with the introduction of green funds in the later stage the carbon price began to rise.

Ray et al. (2022) found that when the COVID-19 epidemic first began, the implementation of blockade measures adopted by government departments reduced CO2 emissions in the air. The demand for carbon quotas fell as a result of the drop in CO2 emissions, which also caused a decrease in carbon pricing. However, their studies also stressed that the decreases were only temporary. With the gradual relaxation of containment measures and economic recovery, the reduction of carbon emissions brought by COVID-19 was not sustainable. These studies also provide support for the conclusions of this study. From this viewpoint, COVID-19 negatively affected the global carbon market at the early stage. With the economic recovery, this negative impact gradually was eliminated.

This research result is also consistent with reality. First, from the perspective of economics, the outbreak of the epidemic reduced market demand for carbon emissions’ trading rights, thereby lowering carbon prices. The epidemic also posed a major threat to human life, and the consequences of the implementation of these restrictive measures temporarily disjointed the whole society, which is not conducive to economic development. According to statistics, China’s national economic production shrank 6.8% year over year in the first quarter of 2020. At the same time, governments of various countries issued their own epidemic prevention and control policies, meaning global growth suffered a huge shock. Energy demand decreased, and the energy market experienced a serious downturn. China adopted significant production reduction measures under the pandemic from the beginning of it through the first ten days of April 2020, which is the key concentration time for carbon emission reduction. This undoubtedly reduced market demand for carbon emissions trading, affected the supply and demand curves of carbon emissions trading price, and pushed the carbon price toward a downward trend (Wen et al. 2022). However, when the pandemic was brought under control, business production activities grew, and economic activity warmed up. This led to a steady increase in demand for carbon quotas and a subsequent slow recovery in the carbon price.

Second, the finding that the COVID-19 pandemic had a detrimental effect on China’s carbon markets is also in line with the emotion theory. The high infection rate and mortality during the pandemic as well as the temporary inability to produce drugs that could effectively treat the virus generated fear in investors and increased their negative emotions. At the same time, the summit on climate change was unable to proceed as planned owing to the outbreak, and it was impossible to predict how the carbon market would develop in the future. As a result, the uncertainty surrounding the carbon market increased. China’s carbon markets have been undergoing further development, and their trading activities are not very large. In this case, investors may have had a negative attitude towards their development, which could have also led to a downward trend in the carbon price. After the outbreak was progressively brought under control and the economy began to recover, investors’ panic gradually subsided and investment in the carbon market rose.

Conclusion and policy implications

This paper connects the COVID-19 pandemic and China’s carbon markets into the same research framework to explore how the epidemic affected these markets. The event study approach is used herein to thoroughly examine the effects of the COVID-19 pandemic’s first outbreak and the prevention and control period on each of China’s eight carbon markets in great detail. The results of our study show that, in addition to the carbon market in Fujian, the COVID-19 pandemic outbreak caused a rapid decrease in carbon prices in China, indicating that the carbon market was negatively impacted by the severity of the epidemic crisis. However, under the prevention and control policies of the epidemic, the negative influence gradually subsided.

Policy implications of this study are as follows. The first finding is that the carbon market was negatively impacted by the initial COVID-19 outbreak. In this respect, the China government should aggressively establish pertinent regulations, react to the national strategic demand for green and low-carbon growth, and offer policy support for the resumption of production and low-carbon development of companies in the post-COVID-19 global job landscape. To stabilize the carbon market and advance the “Double Carbon” objective, it is especially important to give emphasis to supporting clean enterprises. To reduce the negative impact generated from the pandemic, China’s carbon markets should formulate reasonable emission reduction targets according to economic development in the post-epidemic era. This can help prevent enterprises from being overloaded with emission reduction at the initial stage of work resumption and also ensure that the goals of “Double Carbon” can be achieved as scheduled.

Second, this study believes that COVID-19’s detrimental effects on China’s carbon market will only last temporarily, due to the impacts of the mandatory blockade and isolation policy. However, this temporary impact has also highlighted the construction of China’s carbon emission trading market. It is challenging to rely on current mechanisms to address emergencies once more because the carbon emission trading market system in China is not ideal and market efficacy is not great. Therefore, in the future, the government should speed up and improve the construction system of the national carbon trading market as soon as possible. At the same time, traders, investors, and regulators in the carbon markets should pay attention to carbon price fluctuations and build a carbon financial risk early warning index system. Carbon markets need to maintain their support for the quick growth of the carbon finance sector, create more innovative carbon financial products, and enrich investors’ investment choices in order to help them hedge risks and improve the stable growth of these markets.

The limitations of our research are twofold. First, this research only considers China’s carbon emission trading market. Future research can collect data from the EU carbon market or other developing countries’ carbon markets to expand scenarios for analysis. Second, the influence of COVID-19 on the carbon market in the year it first emerged is the main focus of this paper. Future studies may broaden the time horizon and examine how carbon markets have reacted over a longer time horizon to COVID-19.