Cap setting and allowance allocation in China's emissions trading pilot programmes: special issues and innovative solutions

Abstract

Seven emissions trading scheme (ETS) pilots have been established in China. They have introduced some unique methods to set emissions caps and allocate allowances, different from textbook models and their counterparts in the EU, California, and many other regions. This article provides a detailed introduction to the methods for cap setting and allowance allocation adopted by the pilots, and presents detailed comparisons of these methods. In terms of cap setting, the pilots adopt flexible caps that can be adjusted where necessary, which primarily depends on the outcomes of the bottom-up approach, namely aggregating the allowances allocated to participants. As for allowance allocation, the pilots not only adopt such methods as grandfathering and benchmarking, which are also widely applied in other existing schemes, but also some special methods that require ex post adjustment, such as those based on enterprises’ historical emissions intensity (including both physical quantity and added-value intensity) and current production/output. The factors influencing the design are further analysed, including the impacts of theory and experience from foreign systems, concerns about economic development, traditions regarding intensity targets and policy, constraints from data availability and preparation time, tight regulation of the electricity and heat generation sector, and concerns regarding price stability. The practice of pilots presents an improvement opportunity and a challenge for China to further balance the theoretical and practical requirements in ETS design in establishing its national system.

Policy relevance

China is piloting emissions trading in seven regions, as part of efforts to try to rely more on market-based instruments to achieve GHG emissions control targets. All seven pilots have been confronted with special issues in the design process when compared with existing foreign schemes. This article analyses in depth the special issues related to cap setting and allowance allocation and the approaches adopted to address these issues. Flexible cap setting through a bottom-up approach and different types of allocation methods with or without ex post adjustment are adopted in the pilots. The flexible and innovative approaches the pilots have developed could provide useful experience for designing the nationwide ETS in China and promoting emissions trading policy in other parts of the world.

Keywords:

• allowance allocation
• cap and trade
• China
• emissions trading
• pilot

1. Introduction

China is now piloting emissions trading in seven regions: Beijing, Tianjin, Shanghai, Chongqing, Hubei, Guangdong, and Shenzhen. By June 2014, the seven regions had all launched their emissions trading schemes (ETSs).

As the largest CO₂ emitter in the world, China's attempt to control CO₂ emissions with a market mechanism is attracting strong interest from both political and academic fields. The design features of the seven pilots are described generally in the literature (Duan, Pang, & Zhang, 2014; Jotzo & Löschel, 2014; Zhang, Karplus, Cassisa, & Zhang, 2014), and some individual pilot schemes are presented in detail, e.g. for Hubei (Qi, Wang, & Zhang, 2014), Shanghai (Wu, Qian, & Li, 2014), and Shenzhen (Jiang, Ye, & Ma, 2014).

When designing an ETS, setting an emissions cap and allocating allowances to the entities covered are two closely interconnected core issues. Compared with some other operating ETSs throughout the world, these pilot programmes are confronted by certain special issues that affect cap setting and allowance allocation, such as fast but very uncertain economic development, no absolute carbon targets for the whole economy, tight regulation of the electricity market, and so on (Jotzo & Löschel, 2014; Qi et al., 2014; Zhang et al., 2014). To address these issues, the pilot programmes diverge greatly from the ‘cap and trade’ model in textbooks and their counterparts in foreign countries in terms of the methods they use for cap setting and allowance allocation, and there are also marked differences among the pilot programmes. The pilots ‘generally do not have clearly defined emissions targets’ (Jotzo & Löschel, 2014), and adopt various allocation methods (both ex ante and ex post, based on both emissions and productions) (Duan et al., 2014). The experience from the pilot programmes is of great reference value to China in establishing a nationwide ETS and may also be relevant to other regions.

This article intends to systematically and comparatively present the designs of the pilots in terms of cap setting and allowance allocation, and to analyse the underlying reasons for these choices. The article is presented in the following order. The next section identifies the special issues confronting the programmes in cap setting and allowance allocation. Section 3 presents the cap setting approaches used in each and every individual pilot programme and the theoretical rationality for a flexible cap. Section 4 discusses the methods used in the pilot programmes to allocate allowances, the characteristics of these methods, and the major reasons behind them. Section 5 analyses the practical factors affecting the pilots’ design.

2. Special issues confronting China's ETS programmes

2.1. Great uncertainty over growth of the economy and emissions

Future emissions projections provide an important basis for ETS cap setting and allowance allocation (Buchner, Carraro, & Ellerman, 2006), and are closely related to economic growth and energy consumption. China is now undergoing an economic transformational process with rapid but uncertain economic growth, known as the ‘new normal'. Figure 1 presents the gross domestic product (GDP) and energy consumption growth rates of the seven regions implementing pilot programmes between 2006 and 2012, which are observed to vary significantly.

FIGURE 1 GDP and energy consumption growth rates of seven ETS pilot regions (2006–2012)

Source: National Bureau of Statistics of China.

2.2. Absence of an absolute economy-wide emissions cap

Economy-wide emissions control targets provide an important basis for cap setting, despite the fact that their relationship cannot be expressed simply in the form of a proportion. For instance, the emissions reduction targets for EU Member States prescribed in the Kyoto Protocol and the EU Burden-Sharing Agreement can be used as a basis for EU ETS cap setting (Ellerman, Buchner, & Carraro, 2007). China has not established any quantitative emissions control targets until recently, and these targets are GDP-based intensity ones at both national and local levels. The absence of an economy-wide absolute emissions target thus makes it more difficult for the pilots to set emissions caps.

2.3. Tight regulation of the electricity and heat generation sector

The electricity and heat generation sector has been included in all seven pilot programmes. However, it is subject to stringent government regulation in China in terms of pricing and output (Baron et al., 2012). This means that China's electricity and heat generation companies can neither transfer the cost arising from emissions control to consumers nor adjust their output. It is difficult for them to withstand allowance shortage, unlike their counterparts in the EU ETS (Buchner et al., 2006).

2.4. Corporate influence

Corporate influence is another issue affecting allowance allocation decisions in the pilot programmes. In some regions, the vast majority of emissions in certain sectors originate from a few very large enterprises, which play a significant role in local employment and taxation. Some are state-owned, and their managers enjoy even higher administrative rankings than the local Development and Reform Commissions, the pilot authorities, and may become high-level government officials at any time. These enterprises therefore sway the decision-making processes in their regions (e.g. several corporations in Hubei Province) (Qi & Wang, 2013).

3. Cap setting

Two approaches are used in setting ETS caps: top-down and bottom-up (Betz, Eichhammer, & Schleich, 2004; Dian, Ann, Tana, & Monique, 2006; Ellerman et al., 2007). With a top-down approach, the cap can be identified based on an emissions target across the whole economy or at the sector level. With a bottom-up approach, the cap is determined by aggregating the allowances allocated to all the market participants, which are determined according to certain allocation rules.

It is more difficult to set a cap with a top-down approach than a bottom-up approach in these pilot programmes due to the lack of an economy-wide absolute emissions control target and great uncertainty about economic and CO₂ emissions growth, as well the need for ex post adjustment of free allowance allocation. So, although both top-down and bottom-up approaches are adopted by the pilots, they mainly rely on the results of the latter for cap setting. The caps of the pilot programmes are characterized by flexibility or adjustment, namely flexible caps. Among the seven pilot programmes, some have predetermined caps, while others do not.

3.1. Bottom-up approach adopted by the pilot programmes

Only Hubei and Guangdong have published definitive emissions caps (Guangdong DRC, 2013, 2014; Hubei DRC, 2014). In the meantime, a certain number of allowances have been set aside in the two pilots for auctioning and market intervention¹. There is a possibility that some of these reserved allowances will not enter the market. Thus, the ‘predetermined caps’ are only nominal, and the ‘actual caps’, which comprise the allowances that actually enter the market and thus influence market scarcity, are decided by the bottom-up approach. The ‘actual caps’ may only constitute part of the nominal caps.

For the other five pilot programmes (without definitive caps), the ‘actual caps’ are naturally regarded as the results of bottom-up aggregation.

The bottom-up approach makes the actual caps for the pilot programmes flexible, mainly for two reasons. First, ex post adjustments are adopted for allowance allocation for different covered entities (see Section 4). Second, many pilot programmes set aside a certain number of allowances for possible market interventions, all or part of which may not be allocated later.

3.2. Top-down approach adopted by the pilot programmes

The top-down approach was adopted by the pilot programmes for two purposes: to determine the ‘nominal cap’ and to serve as a reference for coordination when a bottom-up approach is used in determining the cap.² The specific methods used by the pilots can be divided into four types.

1. 

First, the emissions of a region up to 2015 are estimated based on local GDP forecasts and the GDP emissions intensity reduction target issued by the Chinese Central Government for the 12th Five-Year Plan period. Second, the cap is calculated according to the percentage of historical emissions from covered enterprises in the entire region.

2.  

There are two different processes to determine the . In the first, the variable can be worked out directly based on historical emissions, growth forecasts, and emissions control responsibilities of the covered enterprises in different sectors. In the second, the total emissions caps for all covered sectors are determined based on their targets for growth and emissions intensity reduction. Then, is calculated based on the percentage of covered enterprises’ historical emissions.

3. 

Chongqing follows this method. The maximum annual emissions from all existing production facilities in covered enterprises between 2008 and 2012 are summed up as the reference cap. The annual cap before 2015 is calculated based on a decrease of 4.13% per year on the basis of the reference cap (Chongqing DRC, 2014).

4. Shenzhen sets an intensity cap rather than an absolute cap. Considering emissions reduction potentials and other factors, it breaks down its carbon intensity (i.e. emissions per GDP) reduction target into ETS and non-ETS sectors (Jiang et al., 2014).

3.3. Rationality of a flexible cap

A flexible cap is a practically feasible choice for the pilot programmes, but its theoretical rationality needs to be assessed. The flexible caps used by pilot programmes are not intensity-based targets, but can be considered as such for the convenience of analysis because they are linked to the regional overall intensity targets and the enterprise- or industry-specific emissions intensities. The debate regarding intensity targets and absolute targets primarily focuses on their influences on the uncertainty in emissions reductions and the costs thereof (Ellerman & Wing, 2003; Jotzo, 2006; Jotzo & Pezzey, 2007; Marschinski & Edenhofer, 2010; Sue Wing, Ellerman, & Song, 2006). Ellerman and Wing (2003) and Jotzo and Pezzey (2007) analysed the conditions under which the uncertainty regarding emissions reductions and the costs thereof would be lower if an intensity target was set. The discussion below focuses on whether these conditions could be met in the pilot programmes, namely, whether adopting a flexible cap can reduce the uncertainty regarding emissions reductions and the price of allowances.

Following the analysis of Sue Wing et al. (2006), if Q is carbon emissions, Y is GDP, and γ is the emissions intensity per unit of GDP, we can derive the following equations:(1)

Generally, the uncertainty regarding GDP and carbon emissions can be reflected by their annual growth rates (Jotzo, 2006). Additionally, growth rates of recent years have been an important basis on which the government has set related targets. To simplify analysis, this article assumes that GDP and emissions are forecast based on data from the previous year. In a business-as-usual (BAU) scenario, the forecast growth rates of GDP and emissions in year i are the same as the actual growth rates in year (i – 1), τ_i and ϵ_i , respectively, leading to the following:(2) (3)

and refer to emissions and GDP in year i in a BAU scenario. Based on these equations, we can calculate the emissions reductions required to achieve the absolute target and intensity target, respectively:(4) (5)

where is the absolute emission target and is the emissions intensity target per unit of GDP.

Accordingly, the variances in emissions reductions required to achieve the absolute target and intensity target are given by(6) (7)

If the uncertainty regarding emissions reductions with an intensity target is the lower of the two, namely, , we have(8)

where is the emissions intensity per unit of GDP in year (i – 1).

Currently, the binding target China sets for emissions control is the decrease in the emissions intensity per unit of GDP. If the target is , we have(9)

Therefore, the condition for lower uncertainty with an intensity target is(10)

Because no emissions data from the pilot regions are available, Table 1 shows the M values in the seven pilot regions calculated with data on the growth rates of GDP and energy consumption³ from 2006 to 2012.

TABLE 1 Annual growth rates of GDP and energy consumption (as percentages), and corresponding M values for seven pilot programmes

Year		2006	2007	2008	2009	2010	2011	2012	M
Beijing	τ	13.0	14.5	9.1	10.2	10.3	8.1	7.7	1.7680
	ϵ	6.9	6.5	0.7	3.8	5.8	0.6	2.6
Tianjin	τ	14.7	15.5	16.5	16.5	17.4	16.4	–	3.2432
	ϵ	10.3	10.4	9.5	9.5	16.3	11.7	–
Shanghai	τ	12.7	15.2	9.7	8.2	10.3	8.2	7.5	2.3128
	ϵ	7.9	9.0	5.6	1.6	8.0	0.6	0.8
Chongqing	τ	12.4	15.9	14.5	14.9	17.1	16.4	13.6	2.1971
	ϵ	9.3	12.9	6.9	9.1	10.7	11.7	4.2
Hubei	τ	13.2	14.6	13.4	13.5	14.8	13.8	11.3	2.1412
	ϵ	9.6	9.9	5.8	6.7	10.4	9.5	6.6
Guangdong	τ	14.8	14.9	10.4	9.7	12.4	10.0	8.2	4.2515
	ϵ	16.8	13.5	1.9	8.8	16.0	8.1	−0.2
Shenzhen	τ	16.6	14.8	12.1	10.7	12.2	10.0	–	2.9112
	ϵ	13.2	11.6	8.9	7.6	8.8	1.3	–

The results suggest that the M value is larger than 1 in all seven pilots. In reality, the intensity reduction target per unit of GDP in every pilot region is a positive number (), so ‘ '. Therefore, in all the pilots, the uncertainty regarding emissions reductions and the costs thereof are lower with an intensity target than with an absolute target. In other words, from the perspective of uncertainty, a flexible cap is more suitable and practical. It should be noted that this conclusion is drawn based on an analysis of the whole economy, but the ETS covers only part of the economic sectors. More detailed analysis can be conducted when data are available.

4. Allowance allocation

The methods for free allowance allocations and auctions used by pilot programmes are introduced below, with a summary of their characteristics.

4.1. Allocation of free allowances

Most allowances are allocated free in the seven pilots, for three different types of allowance recipient: existing installations operated by existing enterprises, new installations operated by existing enterprises, and new enterprises.

4.1.1. Free allocation methods for existing installations

Free allocation methods can be categorized according to various standards. For instance, according to different data timescales, they can be grouped into grandfathering and updating. With grandfathering, allowances are allocated based on fixed historical data, whereas with updating, allowances are allocated in accordance with regularly updated data. According to the different sources of data used for free allocation, there are input-based, output-based, and emission-based methods (Harrison & Radov, 2002). Additionally, benchmarking refers to free allocation based on a sector-wide intensity standard, rather than an enterprise-specific intensity. Based on the time point when the quantity of free allowances for entities are finally determined, free allocation methods can also be divided into ex ante and ex post allocation (Ellerman et al., 2007). To facilitate analysis, this article divides the free allocation methods used by the pilot programmes into five groups (see Table 2).

TABLE 2 Free allowance allocation methods used in China's ETS pilot programmes

	Method	Formula	Application
Without ex post adjustment	Emission-based grandfathering		Beijing: industrial sector (power and heat generation sector excluded) and service sector Shanghai: industrial sector (electricity and heat generation sector excluded) and large public buildings Tianjin: all industries excluding electricity and heat generation sector Guangdong: co-generation unit in the power sector, short processes in the iron and steel sector, and mining in the cement sector (2013, 2014) Hubei: all sectors excluding the power sector and pre-allocated allowances for the power sector
	Historical production based benchmarking		Guangdong: pure power generation units in the power sector, long processes in the iron and steel sector, and clinker production and grinding in the cement sector (2013)
With ex post adjustment	Current production and historical intensity-based grandfathering		Beijing: electricity and heat generation sector Tianjin: electricity and heat generation sector Shenzhen: all covered enterprises excluding 9E gas-turbine power plants
	Current production based benchmarking		Shanghai: electricity and heat generation sector, aviation, airport, port and other sectors Hubei: adjusted allowances of the power sector Guangdong: pure power generation units in the power sector, long processes in the iron and steel sector, and clinker production and grinding in the cement sector (2014) Shenzhen: 9E gas-turbine power plants
	Current emission-based updating		Chongqing: all sectors

Notes: EA: emissions allowances, i.e. the amount of free allowances for the enterprise. HE: historical emissions, i.e. enterprise's verified historical emissions. AF: allocation factor, reflecting allowance shortage compared to historical emissions/intensities. CF: correction factor, used for coordinating the results of cap setting and allowance allocation. HP: historical production, i.e. enterprise's actual productions in the historical years. BM: benchmark, i.e. carbon emission intensity at the level of sector used for allocation. CP: current production, i.e. enterprise's actual production in the compliance year. HI: historical intensity, i.e. enterprise's historical emissions intensity of output (physical quantity/added value). RE: reported emissions, i.e. annual emissions reported to the government by enterprises in the compliance period. Δ: allowance adjustment, used to adjust the amount of free allowances an enterprise can get in the case where the difference between the verified and reported emissions of that enterprise exceeds a certain threshold.

4.1.1.1. Allocation without ex post adjustment

The two ex ante allocation methods used in the pilot programmes can also be found in in the EU ETS (Betz, Rogge, & Schleich, 2006; Ellerman et al., 2007; Stenqvist & Åhman, 2014).

1. Emission-based grandfathering

Emission-based grandfathering has been the most widely used among the pilot programmes. The scope of its application and the formula for calculating the free allowances are shown in Table 2.

HE refers to the verified average annual historical emissions. However, Guangdong allocated allowances for 2013 based on enterprises’ averaged annual emissions from 2010 to 2012, and allowances for 2014 based on enterprises’ average annual emissions from 2011 to 2013. Therefore, it cannot be considered a conventional grandfathering method because it includes some features of updating. It may be termed dynamic grandfathering.

The AF values selected by different pilots are different, which reflects the varying expectations of local governments regarding allowance scarcity. Shanghai, Hubei, and Guangdong set AF to 1 (Guangdong DRC, 2014; Guangdong Emissions Management and Trading Taskforce, 2013; Hubei DRC, 2014; Shanghai DRC, 2013), whereas in Beijing, AF is required to be smaller than 1, and declines yearly from 2013 to 2015 and varies from sector to sector (Beijing DRC, 2013a). Beijing, Shanghai, Hubei and Guangdong have used the same AF for all enterprises in the same sector. In Tianjin, however, AF varies among enterprises in the same sector because enterprises’ technology levels and previous mitigation actions are considered in the determination of the AF to avoid the phenomenon of ‘whipping the fast ox’ (Tianjin DRC, 2013). The other pilot programmes used other methods to prevent the fast from being whipped.

2. Historical production-based benchmarking

This method is only used by Guangdong in the 2013 allowance allocation for production processes where the benchmark is easy to determine. In its allowance calculation formula, BM is the average emissions intensity of the sector in a specific historical year, and the yearly decline in BM is prescribed, namely, AF ≤ 1.

4.1.1.2. Allocation with ex post adjustment

Allocation with ex post adjustment for existing installations is an important feature of the pilots in China, particularly for the electricity and heat generation sectors. Moreover, to encourage trading of allowances by enterprises, increase market liquidity, and promote the formation of a market price, ETS authorities have pre-allocated free allowances to enterprises before the compliance period begins (Table 3). Excessive allowances will be taken back, and shortfall will be made up for covered enterprises when the compliance period ends.

TABLE 3 Pre-allocation basis and percentage in pilot programmes with ex post adjustment

	Pre-allocation basis	Pre-allocation percentage
Beijing	Electricity and heat supply in the previous year	100
Tianjin (Tianjin DRC, 2013)	Average electricity/heat supply during base years	90
Shanghai (Shanghai DRC, 2013)	Average business volume during base years	100
Chongqing (Chongqing DRC, 2014)	Reported emissions by the enterprises and adjustment factor	100
Hubei (Hubei DRC, 2014)	Average emissions during base years and adjustment factor	50
Shenzhen (Jiang et al., 2014)	Reported added value and emission intensity	100
Guangdong (2014)	Production in the previous year	100

1. Current production and historical intensity-based grandfathering

The application scope and allowance calculation formula for this are shown in Table 2. For each electricity and heat generation enterprise in Beijing and Tianjin, HI refers to its average emissions intensity during the base years, 2009–2012 (Beijing DRC, 2013a; Tianjin DRC, 2013), and AF reflects the government's expectation of reducing emissions intensity by enterprises (Table 4). However, the AF values in Beijing and Tianjin are very small, supporting the notion that the pilot governments have no intention of asking electricity and heat generation enterprises to take great responsibility for emissions reductions.

TABLE 4 AF values (given as percentages) for electricity and heat generation enterprises in Beijing and Tianjin

		2013	2014	2015
Beijing	Gas-turbine power plants	100	100	100
	Coal-fired units power plants	99.9	99.7	99.5
	Gas-turbine heating plants	100	100	100
	Coal-fired units heating plants	99.8	99.5	99.0
Tianjin	Power and heating plants	100	99.8	99.6

Shenzhen has eight power plants, of which one coal-fired power plant and two 9F gas-turbine power plants receive their free allowances based on this method (Wang, Xu, & Ma, 2013). For other sectors, Shenzhen has introduced a special method for free allocation, which requires enterprises to go through a gaming process (Jiang et al., 2014). The allocation result is closely related to each enterprise's historical intensity and current production.

The allocation process is as follows. (1) Covered enterprises are divided into groups according to their products and production scale. (2) They are required to report their estimated output and allowance demands to the ETS authority, based on which their emissions intensities, or HI values, can be calculated. (3) Afterwards, the authority will set a reference benchmark and a nominal cap of allowances for each group. (4) The HI of every enterprise will be compared with the reference benchmark of the group to determine its AF value. The higher the reported intensity is, the smaller the AF will be, and vice versa. (5) The amount of pre-allocated allowance is determined according to enterprises’ estimated output and the HI and AF. (6) Following this, the gaming rounds begin. In each round, enterprises satisfied with the pre-allocation result can get the corresponding allowances, while enterprises not satisfied with the result can report their demands again in an attempt to acquire their allowances from the remaining resources in the next round. (7) When the compliance period ends, the amount of allowances will be adjusted according to the actual output of the enterprises.

The added-value output is used for allocation and not product output in Shenzhen, because many sectors with a great variety of products in each sector are covered and it is difficult to compare product-based emissions intensities.

2. Current production-based benchmarking

The application scope and allowance calculation formula for this are shown in Table 2. Shanghai adopts this method for airlines, airports, and ports (Wu et al., 2014). Setting benchmarks for these sectors is relatively simple because there are not many enterprises and there is a high degree of similarity between enterprises in terms of the products or service provided. Additionally, due to the fast growth of these sectors, it is fair and more acceptable to these enterprises if allowances are adjusted according to their actual business volume.

In 2014, Guangdong changed its free allocation method for production processes using historical production-based benchmarking in 2013 (see Section 4.1.1.1, list item 2) to current production-based benchmarking. Experience from the previous year shows that free allocation based on historical production fails to reflect the current state of the enterprises and can easily lead to excesses or shortages of allowances, which makes it more difficult for the enterprises or governmental agencies to accept the allocation results. For example, because of the decline in electricity generation in 2013, most electricity enterprises received excessive allowances.

This method is used for the electricity and heat generation sector in the four pilot programmes in Shanghai, Hubei, Guangdong, and Shenzhen, but they differ in both the method for setting benchmarks and the benchmarks themselves. Shanghai divides the sector into six categories according to unit type and installed capacity, namely ultra-supercritical (1000 MW, 660 MW), supercritical (900 MW, 600 MW), subcritical (600 MW, 300 MW), and gas-turbine, and sets a benchmark for each category according to local units’ product energy consumption limits and advanced energy efficiency values. Guangdong also divides the sector into six categories, including coal-fuelled (1000 MW, 600 WM, 300 MW, <300 MW) and gas-turbine (390 MW, <390 MW), and takes the average emissions intensity of units within a category as the benchmark. Hubei adopts the emissions intensity of the thermal power plant ranking in the middle of all covered plants in terms of emissions intensity in 2011 (i.e. the median) as the benchmark for all types of unit. Shenzhen takes the average emissions intensity of the five 9E gas-turbine power plants as their benchmark. Figure 2 compares the benchmarks used in the four pilot programmes (Guangdong DRC, 2013, 2014; Hubei DRC, 2014; Shanghai DRC, 2013; Wang et al., 2013). Guangdong's benchmarks for various units in 2014 are different from those in 2013, demonstrating that the policy continues to change, and it is difficult to set a proper benchmark once and for all.

FIGURE 2 Benchmarks for thermal power plants in four pilot programmes

The benchmark differences among the pilot programmes are related to the technological level of local enterprises and the method of setting the benchmark. Such subtle differences demonstrate how the pilot programmes differ from each other in determining the same parameter and indicate, to some extent, the difficulty that would be faced in benchmarking if a nationwide ETS were to be established in China.

3. Current emission-based updating

Chongqing uses this method to allocate free allowances for all sectors (Chongqing DRC, 2014), and the formula for calculating the allowances is shown in Table 2. The ETS authority pre-allocates free allowances according to the emissions of the year reported by the enterprises, or RE. There are two different scenarios: (1) if the sum of reported emissions is below the ETS cap, free allowances will be allocated according to the reported emissions, and (2) if the sum exceeds the cap, a base allowance for each enterprise will be determined first. As for the base allowance, if an enterprise's RE is higher than its maximum historical annual emissions, the average of the two will be used as its base allowance; otherwise, the RE will be considered its base allowance. If the sum of all enterprises’ base allowances is below the ETS cap, the amount of free allowances allocated to an enterprise will be its base allowance; if the sum exceeds the cap, the amount of free allowances allocated to each enterprise will be its base allowance multiplied by an identical correction factor. When the compliance period ends, if the difference between an enterprise's verified and reported emissions is over 8%, an allowance adjustment () will be determined according to the principle of taking back excessive allowances and filling shortfalls; otherwise, there will be no adjustment.

Both Chongqing and Shenzhen allocate allowances based on enterprises’ reported data. To a certain extent, such a method leaves the challenge of handling uncertainty to enterprises. However, enterprises have an incentive to report more than the actual estimate to get more free allowances, and the actual data quality could be poor, which may prevent the authorities from making informed decisions.

4.1.2. Methods of allocating free allowances to new installations

All the pilots except Chongqing have considered new installations built by existing enterprises in free allowance allocation, and allow qualified new installations to apply for extra allowances. New installations are provided with free allowances to ensure the normal production needs of covered enterprises. Two methods are used in the pilot programmes: production-based allocation and emission-based allocation.

1. Production-based allocation

Beijing and Tianjin employ current production-based benchmarking for new installations (Beijing DRC, 2013a; Tianjin DRC, 2013). Beijing takes the advanced industrial performance values published by the Beijing DRC as benchmarks (2014a), but Tianjin has not made their benchmarks public. Shenzhen adopts the method of ‘reporting by enterprises + ex post adjustment', so enterprises factor in new installations when reporting their estimated outputs (Jiang et al., 2014).

Guangdong's allocation methods for new installations in 2013 and 2014 are the same. For production processes in which the benchmark is easy to determine, the allowances for new installations are calculated as the designed capacity multiplied by the benchmark. For production processes in which the benchmark is difficult to determine, the allowances for new installations are calculated as the amount of estimated energy consumption multiplied by a conversion coefficient (Guangdong DRC, 2013, 2014).

2. Emission-based allocation

In Shanghai and Hubei, enterprises with new installations whose capacities extend beyond a certain threshold may apply for extra free allowances according to expected or actual emissions. In Shanghai, new installations that consume more than 2000 tonnes of coal equivalent annually can apply for extra free allowances: allowances amount = estimated annual emissions under designed capacity × production load factor × production months/12 (Shanghai DRC, 2013). In Hubei, if the difference between an enterprise's actual emissions and its initial free allowance is greater than 20% or 200,000 tonnes due to changes in installations or production, the enterprise shall report this difference to the ETS authority; the authority will then adjust the free allowance amount. Only the difference greater than 20% or 200,000 tonnes will be adjusted (Hubei DRC, 2014).

4.1.3. Methods of allocating free allowances to new enterprises

Beijing, Guangdong, and Shenzhen adopt the same free allocation methods for new enterprises as for new installations (Beijing DRC, 2013a; General Office of Shenzhen Municipal Government, 2014; Guangdong DRC, 2013, 2014). Shanghai, Chongqing, and Hubei, however, do not cover new enterprises in their systems; i.e. the coverages of these three pilot programmes do not change once determined based on historical data (Chongqing DRC, 2014; Hubei Provincial Government, 2013; Shanghai Municipal Government, 2012).

4.2. Auction

To date, Hubei, Guangdong, Shanghai, and Shenzhen have conducted allowance auctions, while some others have established auction rules, with different purposes and approaches.

4.2.1. Purpose of auction

Auctions are adopted in pilot programmes for two major purposes: to allocate a small portion of allowances, and to implement market intervention (Beijing DRC, 2013b; General Office of Shenzhen Municipal Government, 2014; General Office of Tianjin Municipal Government, 2013; Guangdong Provincial Government, 2014; Hubei DRC, 2014; Shanghai Municipal Government, 2013; Standing Committee of Beijing Municipal People's Congress, 2013). Interventions in pilot programmes are introduced in two scenarios: the allowances prices are too high, which may have significant negative impacts on the regional economy, and enterprises are not willing to sell, causing a lack of market liquidity and compliance failure risk.

4.2.2. Methods of auction

Beijing has two types of auction, temporary auctions triggered by the price ceiling of allowances and regular auctions. The government decides according to market conditions whether to hold auctions. The auction is conducted with a single round of closed bidding and a uniform settlement price. The number of auctioned allowances shall not exceed 5% of the ‘actual cap’ (Beijing DRC, 2014b).

Hubei sets aside 8% of its total allowances, 70% of which are used for market interventions and 30% are auctioned to increase market liquidity and promote price discovery (General Office of Hubei Provincial Government, 2014; Hubei DRC, 2014). Besides ETS-covered enterprises, institutional investors can also bid for allowances (China Hubei Emissions Exchange, 2014).

Guangdong used a special method of auctioning in 2013. The government set aside 3% of enterprises’ allowances, calculated according to the method prescribed in Section 4.1, and made a mandatory requirement that only if enterprises purchase the 3% of allowances through auction could they receive the remainder for free (Guangdong DRC, 2013). A reserve price of RMB yuan 60/tonne was set for the auction (Guangdong DRC, 2013). As the government also decided that the covered enterprises could only buy 3% of allowances through the auction, rational enterprises purchased at the reserve price, so the auction in fact had a fixed amount and price. In 2014, Guangdong no longer required enterprises to obtain a portion of the allowances through auctioning before receiving free allowances (Guangdong DRC, 2014). Auctions in 2014 were characterized by voluntary participation and competitive bidding. However, enterprises could still receive only a proportion of the allowances for free, as determined according to the method in Section 4.1 (e.g. 95% for power plants and 97% for iron and steel, petrochemical, and cement plants).

To help enterprises fulfil their compliance obligation, Shanghai and Shenzhen have introduced special auctions for enterprises whose annual emissions exceed their allowances. These auctioned allowances can be used only for compliance and not for trading. A ceiling is also set for the number of allowances on which an enterprise can bid (15% and 100% of an individual enterprise's allowance shortage in Shenzhen and in Shanghai, respectively) (China Shenzhen Emissions Exchange, 2014; Shanghai DRC, 2014).

4.3. Characteristics of allowance allocation in pilot programmes

Based on the above analysis, the characteristics of allowance allocation in the pilot programmes can be summarized as follows.

1. Allowances are mainly allocated free of charge, and the demands of enterprises are more favoured.

2. Multiple allocation methods are used with noticeable differences among the pilot programmes (Table 2), even within a sector. Additionally, even when the same method is used, the basic data and adjustment factors are selected or determined differently.

3. Innovative solutions are proposed in response to special realities, including different allocation methods with ex post adjustment.

4. The purposes and methods of auctioning are diversified.

5. Almost all the pilot programmes adopt ex post allocation for new enterprises and new installations.

5. Discussion about factors affecting the development of allocation plans

The development of an allocation plan is a process of balancing many factors, including environmental integrity, economic efficiency, equity, industry competitiveness, political acceptance, and so on (Sijm, Berk, den Elzen, & van den Wijngaart, 2007). This section will touch on the practical factors affecting the development of allocation plans in the pilot programmes.

5.1. Impacts of theory and experience from foreign countries

There has been an abundance of theoretical research on and experience with emissions trading (Betz et al., 2004, 2006; Buchner et al., 2006; Burtraw, Palmer, Bharvirkar, & Paul, 2001; Ellerman et al., 2007; Ellerman & Joskow, 2008; Fischer, 2001; Grubb, Azar, & Persson, 2005; Grubb & Neuhoff, 2006; Harrison & Radov, 2002), and the knowledge gained from this has had some influence on the development of allocation plans in the pilot programmes. For example, theoretically, auctioning is considered to be the most economically efficient allocation method (Burtraw et al., 2001; Cramton & Kerr, 2002). Most pilot programmes have set up auction rules and some have implemented auctions. Furthermore, as emission-based grandfathering may lead to some unfavourable issues, such as ‘whipping the fast ox’, historical production-based benchmarking is considered fairer and is widely adopted in the foreign schemes. Guangdong, Beijing, and Shanghai have also made attempts to design and use benchmarking, but they have all adjusted the design according to their own circumstances.

5.2. Concerns about economic development

Political acceptance has a decisive influence on the smooth implementation of the allocation plan, and the economy is a dominant factor for political acceptance. If the emissions control policy significantly negatively affects the economy, the ETS authority will have to cope with pressure from enterprises, the general public, and higher authorities regarding their performance appraisal. Therefore, in either cap setting or allowance allocation, consideration should be given to economic impacts.

In terms of cap setting, due to the great uncertainty regarding the growth of the economy and carbon emissions, most pilot regions prefer the bottom-up approach to the top-down approach and adopt a flexible cap. Such a demand-based design not only helps to address uncertainty in the growth of the economy and emissions and avoids the impact of an improperly set target on the local economy, but is also better accepted by enterprises and easier for the government to put into practice.

The pilot programmes also consider the needs of enterprises in allowance allocation and aim to provide them with the allowances they need for normal operation. The output of some enterprises in the ETS fluctuates violently; quite a number of enterprises are in the output growth phase, and it is even harder to predict the output of new enterprises or installations. Ex ante allocation methods may hinder the development of enterprises, which will undermine the political acceptance of the allocation method and perhaps the entire ETS. This is one of the reasons why allocation methods with ex post adjustment are used more in pilots than in foreign schemes.

Additionally, auctioning is used much less, because enterprises will have to bear the costs of both emissions control and allowances in the case of auctions and its political acceptance is not high. Theoretically, auctioning is a good way of allocating allowances to new installations or enterprises because they have no stranded costs and there are no historical data on them. In the pilot programmes, however, because new installations need to go through energy efficiency and environmental impact assessments and usually adopt advanced technologies, free allocation is still adopted for them to avoid great impacts on the investment and economic development.

5.3. Tradition regarding intensity targets and policy

China is a developing country with a long and strong tradition of setting intensity targets in the fields of energy and climate change. During the 12th Five-Year Plan period, the Chinese Government sets the goal of reducing the emissions intensity per unit of GDP by 17% and breaks down the intensity targets for all provinces (State Council, 2011). These intensity targets are the basis for governments at all levels to formulate their emissions control policies. Without direct external political stimulation, it is very difficult for local governments to set an absolute quantitative target for regional carbon emissions control, which makes it harder to set an ETS cap through a top-down approach. Therefore, many pilot programmes do not set a definitive cap but adopt a bottom-up approach to set a flexible cap allowing for ex post adjustment. However, the adjustment is not made according to an intensity target but rather to enterprises’ actual production or emissions changes and the amount of allowances for new installations. This characteristic appears to violate the textbook ‘cap and trade’ model, which aims to achieve a predetermined absolute emissions control target at the lowest economic costs.

5.4. Constraints from basic data and preparation time

The preparation time for the pilot programmes is approximately 1.5 to 2.5 years, which is too tight to adopt certain allocation methods. For example, although benchmarking attracted much interest in the pilot programmes, it is not widely used. This is partly because enterprises in the same sector differ greatly in size and technology level and because of limited available data regarding enterprises’ emissions and production, which are necessary for designing the benchmarks.

5.5. Tight regulation of the electricity and heat generation sector

Most pilot programmes adopt allocation methods with ex post adjustment for the electricity and heat generation sector in response to the tight market regulation. It is a feasible way to ensure that enterprises obtain the allowances they need for normal operation, which means that the amount of free allowances is determined according to enterprises’ current production and pre-set intensity. There are two ways to calculate the intensity. One is to set a sector-based benchmark, and the other is to set it by reducing each and every enterprise's historical emissions intensity by a certain percentage. The reduction is very limited for two reasons. First, electricity and heat generation companies have to bear high stranded costs because their installations can be used for many years once put into operation. Second, the pilot may not last long enough to motivate the enterprises to upgrade technology or choose alternative energy.

5.6. Concerns regarding price stability

Piloting of an ETS is the first market-based policy tool China has used widely in the climate field. Therefore, pilot regions all hope to stabilize the price of allowances to help replicate the ETS in more regions. Price is determined by supply and demand. Supply in the carbon market is the emissions cap set by the government. A flexible cap allows the government to adjust supply according to demand and helps to form a more stable allowance price, which is what the government would like to see. Additionally, emissions trading is still new in China. Enterprises have not yet established a mature carbon asset management system, and their reluctance to sell will lead to insufficient market liquidity. When the compliance period is coming to an end, special auctions are held in some pilot programmes to help enterprises in need obtain limited extra allowances to reduce their compliance costs. This is further evidence for the concerns raised by the pilot regions regarding market stability. However, as a practically feasible mechanism, price stabilization may sacrifice the schemes’ environmental integrity and economic efficiency.

6. Conclusions

This article describes some special issues regarding pilot emissions trading schemes (ETSs) in seven regions of China, introduces in detail the methods of cap setting and allowance allocation in the pilot programmes, summarizes their characteristics, and analyses the rationality of adopting a flexible cap and the practical factors affecting the design of pilot programmes.

In terms of cap setting, not all the pilots have set a definitive cap, and they tend to use a bottom-up approach in setting the ‘actual cap’, while reserving room for ex post adjustment. Such a flexible cap favours the allowance demands of the covered enterprises. The main reason for this choice is to address uncertainty in the growth of the economy and emissions. The empirical analysis based on energy consumption and gross domestic product (GDP) data from the pilot regions between 2006 and 2012 demonstrates that adopting a flexible cap is also theoretically rational, because an intensity target could provide less uncertainty in emissions reductions and the costs thereof than an absolute target. At the same time, the outcome of four types of top-down approach are referred to by pilot programmes during cap setting and allowance allocation.

Regarding allowance allocation, the pilot programmes use auctions and five free allocation methods with or without ex post adjustment for existing installations. Allocation with ex post adjustment is used more often in these pilot programmes than in foreign systems because it is more politically acceptable and practically feasible when addressing the special issues in China. Additionally, most pilot programmes allow new installations and enterprises covered by the ETS to apply for extra allowances, which will be allocated based on their production or emissions.

Given China's realities, a flexible cap and allocation with ex post adjustment are better accepted by enterprises and the economic authorities than a fixed cap and pre-determined allocation. Admittedly, however, they are compromised choices that deviate from the textbook model of ‘cap and trade’ as they cannot provide a predefined emissions level and will lead to social abatement costs higher than the theoretically optimal level. This presents both an improvement opportunity and a challenge for China to further balance the theoretical and practical requirements in ETS design.

The seven ETS pilot programmes in China have just begun, and their success is yet to be determined by their future performance in the market. The flexible and innovative approaches the pilot programmes have developed to address both common issues in building ETSs throughout China and their unique regional issues could provide useful experience or lessons for the design of a nationwide ETS in China and may also be relevant to ETS design in other parts of the world.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Ministry of Science and Technology of China, under a Grant of the National Key Technology R&D Program during the 12th Five-year Plan Period (no. 2012BAC20B11], and the Ministry of Education of China, under a Grant of the Key Project for the Research Base of Humanities and Social Sciences (no. 13JJD630007).

Notes

1. Hubei has set aside approximately 30% of its cap in 2014 (Hubei DRC, 2014) and Guangdong approximately 10% and 9% in 2013 and 2014, respectively (Guangdong DRC, 2013, 2014).

2. Because not all ETS cap-setting methods used by these pilot programmes are public, some information in this section is from interviews with experts involved in programme design.

3. Energy consumption data are used here because emissions data for the year are not available, while there is short-run bidirectional causality between the carbon emissions and energy consumption at the provincial level in China (Wang, Zhou, Zhou, & Wang, 2011).