• No results found

Sharing Emission Responsibility. An Approach to Accrue Emission Shares to Both Producers and Consumers Globally

N/A
N/A
Protected

Academic year: 2021

Share "Sharing Emission Responsibility. An Approach to Accrue Emission Shares to Both Producers and Consumers Globally"

Copied!
34
0
0

Bezig met laden.... (Bekijk nu de volledige tekst)

Hele tekst

(1)

Sharing Emission Responsibility. An Approach to Accrue Emission

Shares to Both Producers and Consumers Globally

Master’s thesis

Author: Frank de Gorter

Student number: s2020289

Email: f.de.gorter@student.rug.nl

Supervisor: Erik H.W.A. Dietzenbacher

Period of research: 01-09-2015 – 05-01-2016

Rijksuniversiteit Groningen

Faculty of Economics & Business

Department: Economics

Nettelbosje 2

(2)

2

Sharing Emission Responsibility. An Approach to Accrue Emission Shares to Both Producers and Consumers Globally

Frank de Gorter and Erik H.W.A. Dietzenbacher

Abstract

(3)

3 Index 1. Introduction ... 4 2. Literature review ... 5 3. Method ... 10 3.1 Design ... 11

3.2 Leontief inverse with emissions on a national level ... 11

3.3 National shared responsibility ... 13

3.4 Global shared, producer and consumer responsibility ... 16

(4)

4

1. Introduction

Since the industrial revolution there has been a significant increase of greenhouse gasses

(GHGs) released into the earth’s atmosphere. This increase is one of the causes of global warming (Lashof and Ahuja 1990). Ninety nine point nine percent of peer-reviewed articles studying global warming tell us that global warming is man-made (Powell 2015). GHGs are released with the production of goods and services, but mostly with the production of goods. In 1996, in Kyoto, a treaty was signed with the aim of decreasing GHGs (IPCC 1996). Nowadays, the Kyoto protocol is still something that is being endorsed by many nations. The latest update to the Kyoto Protocol was in 2012, a result of negotiations in Doha (UNFCCC 2012). Large polluting nations, such as China, India and the United States were reluctant to follow the most recent treaty requirements. Under the first Kyoto protocol of 1996, the Intergovernmental Panel for Climate Change (IPCC) emission measurement of a nation included all GHG emissions released within that nation and over the areas where it has jurisdiction (IPCC 1996). Since 1996, all nations that endorse the protocol, report their annual amount of GHGs generated to the Intergovernmental Panel for Climate Change. The territorial boundary the IPCC uses for emission measurements is problematic for assigning emission responsibility. Although there is a large abundance of international trade of emissions the territorial boundary restriction makes importers of emissions not liable for any of the emissions (Peters 2008). The international trade of emissions is defined as “foreign emissions that are embodied in imported goods and services as a result of the production processes that made the goods and services” Peters and Hertwich (2008). As an example of the enormous quantities involved results show that in 2001, 5.3 Gt of CO2 was traded, which moved from developing nations to developed nations. A more recent

study of Davis and Caldeira (2010), shows that in 2004, 6.2 Gt of CO2was traded internationally.

(5)

5

responsibility of the designated group to deal with them. In practice, when producers are held responsible, higher costs for a producer due to emission taxes can be a consequence. An example is carbon tax. Nowadays, carbon tax is used by many nations, with the aim of decreasing GHGs, in particular that of CO2 (World Bank 2015). Although producers generate all emissions with their production, it is the consumers that are satisfying their needs by consuming the goods and services. Therefore, consumers are responsible for the demand of goods and services. When consumer responsibility is used, they become responsible for the generated emissions during the production of goods and services. A pitfall of CR is that producers are conclusively responsible for offering their goods and services that embody emissions, so in the absence of these goods that embody emissions, consumers cannot consume goods that embody emissions. Nevertheless, when consumers are held responsible, it can imply higher costs of goods for consumption due to carbon tax.

Given the flaws that are present in both the PR and CR approaches, we address a third

approach for emission responsibility. This approach is shared responsibility (SR). Shared responsibility accrues emission responsibility shares to both producers and the consumers of goods and services. So the consumers that are responsible for demand have to carry an emission burden. At the same time the relevant producers carry part of the emission burden also. Therefore, SR addresses the fact that there is more than one actor in the supply chain; namely producers and consumers. Using shared responsibility of emissions is very much unchartered territory. There have been scant attempts in applying the shared responsibility method, as opposed to the widespread use of PR and CR of emissions. Given the possible benefit that SR of emissions has over PR and CR, and its unexplored nature, we will describe in the next chapter, the existing literature regarding the SR approach for assigning emission responsibility.

2. Literature review

As we mentioned in the introduction, there is a vast amount of internationally traded

(6)

6

consumption of the United States, 10.8 percent of that total was generated in other nations. The imported emissions are coming from developing nations, such as China. For example, China, exports 22.5 percent of all its emissions generated with the production of goods and services.

The main reason that caused the international trade of emissions to develop, is the rise of

international supply chains (IDE-JETRO and WTO 2011). A supply chain can be defined as follows: “the full production cycle, starting with the supplier and that ends with buyer.” With the

rise of international supply chains came the fragmentation of the domestic supply chains. This

resulted in geographical changes of the supply chain (Hummels, Ishii and Yi 1999). Now parts of the production process that were taking place domestically, were moved to a foreign nation.

Rent-seekingwas an important motive to move a certain part of the production process abroad, as

there was a large abundance of cheap foreign labor. It resulted in an immense increase in the global trade of intermediaries. This meant that a portion of the emissions generated domestically were now embodied in exports to a foreign nation giving rise to the international trade of emissions.

As explained earlier, the UNFCCC mandate of 1996 puts full responsibility on the

producers of emissions (IPCC 1996; Steininger et al. 2014). The PR definition we use is: “the responsibility or accounting of emissions released during production processes only lies at the point of production.” This means that when emissions are released during production, this will only be the responsibility of producers and this might have negative consequences for them. A consequence can be that emissions taxes are enforced by the government on producers that release emissions with their production. Additionally, the government might force them to reduce the amount of emissions generated with their production. An example of this is the purchase of more sustainable technology. However, not every producer will have sufficient capital to do this.

More recently, organizations responsible for developing policies and decision-making for

(7)

7

we use is: “the responsibility of emissions released during production processes of services and goods lies with the consumers that buy the goods or services and consume them.” In other words the embodied emissions are accounted at the point of consumption. This can result in government policy focusing on the consumer side of the supply chain, with the aim to decrease the emissions generated at the point of production. We will illustrate this situation with an example. In this example CR is only used to assign emission responsibility. So consumers pay the costs that are a result of emissions released at the point of production. We assume that with the production of a good emissions were released, and that for every extra emission released the price of the good will increase (e.g. due to emission taxes on consumer goods). In this case the production of this good results in a higher price compared to a similar good in which its production process does not generate emissions. Therefore, due to the higher price of the good, consumers will most likely buy less of it, thus decreasing their consumption of the pricier good. As a result, the production quantity of the good will drop due to lower demand. This can lead to a decrease in the total amount of emissions generated with the production of goods. An advantage that CR has over PR is that the emission responsibility can be with a consumer in a foreign nation. Therefore the responsibility measurement no longer depends on a territorial boundary as with PR. It depends on the consumption bundle of consumers globally.

We explained that a weakness of PR and CR is that it only assigns emission responsibility

(8)

8

down or forward in the supply chain. Conversely, upstream translates to going up, or backwards, in the direction of the start of the supply chain. Using the same logic, the CR does not incorporate the fact that the upstream producers are essentially the origin of the emissions released. Without these upstream producers of goods that release emissions, there would not be any emissions in the first place. Moreover, Gallego and Lenzen (2005) argue that the PR and CR do not account for the responsibility of producers that use intermediaries for their production. As they state: “In fact even though enabling car manufacturing, the steel sector is not responsible for any waste at all, neither under producer nor under worker/investor responsibility.” (Gallego and Lenzen 2005, p. 374).1

A third novel approach in assigning emission responsibility, is the shared responsibility method of Gallego and Lenzen (2005). The intuition of Gallego and Lenzen (2005) that lead to the SR was, that it was unclear what actors in the supply chain should be held responsible for their contributions and on what grounds. As a result, they derived a new method as an attempt to solve this problem. Their method came with one major flaw, namely, there was no formula for the value that divides the emission shares between producers and consumers. Therefore, it was a subjective value. In a follow-up study Lenzen et al. (2007) designed a formula for the value. The definition of SR we use is: “Allocating the emissions released at the point of production, to producers based on their intermediary sales and to consumers based on their consumption of goods and services, in the same nation or region.” In other words, it is a redistribution of territorial emissions to both producers and consumers within the same nation or region. When shared responsibility is used, the total amount of emissions does not actually change in comparison to when PR and CR are used, only the distribution of emissions changes. There are several benefits of sharing responsibility of emissions. SR results in shared responsibility among all actors in the supply chain. Subsequently this will stimulate actors to work together in improving or streamlining their supply chain. Furthermore, Lenzen et al. (2007, p.36) state that in comparison to CR, SR differs so that it “provides an incentive for producers and consumers to enter into a dialogue about what to do to improve the profile of consumer products.” Additionally, Bastianoni, Pulselli and Tiezzi (2004) state that under CR, producers have no

(9)

9

incentive to reduce emissions. Consumers do so with CR, but only with proper incentives and policies, enforced by for example its national government.

Despite the evidence that shows that SR has benefits over PR and CR, there is little

literature available on what the outcomes are when it is used to measure emission responsibilities. Hence, there is little empirical support to back the alleged benefits that SR has. Zhang (2013; 2015) is one of the very few researchers that studied SR. Zhang (2013) used the SR method of Lenzen et al. (2007) to simultaneously evaluate the responsibilities/multipliers of each sector and producer in China. In his evaluation Zhang derived several SR methods from the SR approach of Gallego and Lenzen (2005). The method that showed the most promising results was the weighted comprehensive SR, as it was the only method that included all interactions among actors. His key results showed that the shared responsibility values differ in all sectors in China. Subsequently, on this study, Zhang (2015) conducted a follow-up that focused on several responsibility approaches, including SR, used on specific sectors in Chinese provinces. One result was that the emission responsibility increased with the economic size of provinces. More importantly, Zhang found that there was a disparity in producer and consumer shares of emissions between the Chinese provinces. Zhang’s policy advice for China and its regions is: “All provinces must implement a series of policies or policy systems that are related to the production, consumption and circulation of products to reduce their carbon emissions even if their key policies are different from one another.” (Zhang 2015, p.152).

To the best of our knowledge, the literature has not expanded the application of SR

(10)

10

the downstream Japanese and US consumers will all accrue emission shares. Their emission shares will be based upon their production and consumption respectively. More specifically, the upstream Chinese producers will be responsible for a share of emissions due to their production. Similarly, the Japanese and US consumers will be responsible for a share of emissions generated at the point of production that are embodied in their consumption bundle. It is important to accentuate once again, that with PR and CR only one actor will be held responsible for all emissions released during the production of services and goods. Mainly, given the unexplored nature of SR, its benefits over PR and CR and its appropriateness within a global setting, lead to the following research question:

“What share of the emission responsibilities accrues to producers and what to consumers in developed and developing nations with a shared responsibility approach on a global scale.”

The aim of is this paper is to explore shared responsibility of emissions on a sample of

developed and developing nations in a global setting. The originality of this paper lies in the fact that SR of emissions has never been applied on more than one nation at a time. With the use of our method, we will acquire the first results of shared responsibility of emissions on a global scale. This new information will contribute to the debate on who should be held accountable for the emissions generated by the production of services and goods, with particular emphasis on sharing the emission responsibility.

3. Method

The method is divided into four sections. In section 3.1 we explain the design of the

(11)

11

3.1 Design

For the analyses we use the World-Input-Output Database (WIOD) (Dietzenbacher et al. 2013). This is an input-output (I-O) database that includes transactions of 35 sectors between 40 nations plus the rest of the world (RoW). The RoW incorporates all nations that are not included in the WIOD. Additionally, the WIOD gives information on the sector transaction to final demand of households, non-profit organizations and governments. It also gives capital formations and changes in inventories and valuables. Furthermore, the WIOD includes emissions released during production of sectors. We will use 2009 as our period for analysis, since the latest emissions data emanates from this year. The labels of the variables, are mostly consistent with the labelled variables of Gallego and Lenzen (2005), Lenzen et al. (2007) and Zhang (2013; 2015). In our sample there are n sectors and w nations.

3.2 Leontief inverse with emissions on a national level

The following describes the first part of our framework, namely the Leontief model. The Leontief model is based on the structure of I-O matrices. The gross output of a nation is given by the sum of the final demand and the sum of the inter-industry sales.

This is described by the equation: 𝒙 = 𝒚 + 𝑻𝒆 2

𝒙 denotes the gross output, 𝒚 indicates the final demand of a nation, 𝑻 indicates the inter-industry sales matrix with its element 𝑡𝑖𝑗 that denotes a sale from industry i to industry j, 𝒆 denotes a

summation vector of ones. Using 𝑻 and 𝒙 we can calculate the inter-industry sales per gross

output matrix 𝑨.

2 A small italic bold letter, e.g. 𝒙, denotes vector 𝑥. A capital italic bold letter, e.g. 𝑨, denotes matrix 𝐴. A small italic

letter, e.g. 𝑦𝑖 denotes a scalar, in this case element i in vector 𝑦. A letter with a circumflex, e.g. 𝒙̂, denotes the

(12)

12 𝑨 = 𝑻(𝒙̂)−1

In 𝑨, element 𝑎𝑖𝑗 indicates the sales from sector i to sector j per unit of gross output of sector j.

The equation that gives 𝑨 can be rewritten into:

𝑻 = 𝑨 𝒙̂ ˅ 𝑻𝒆 = 𝑨 𝒙

Subsequently, we can replace 𝑻𝒆 with 𝑨 𝒙 in 𝒙 = 𝒚 + 𝑻𝒆. Then we get

𝒙 = 𝑨 𝒙 + 𝒚

and

𝒙 = (𝑰 − 𝑨)−𝟏 y ˅ 𝒙 = 𝑳 𝒚

In which (𝑰 − 𝑨)−𝟏 is the Leontief inverse or 𝑳. Element 𝑙𝑖𝑗 gives the additional output of sector i

that is required to satisfy one unit of extra final demand for good j. The emission intensities are calculated with the use of the emissions released with the production of goods and services and the gross output.

𝝓 = 𝒇(𝒙̂)−1

𝒇 is the emissions vector and 𝝓 the vector of emissions intensities. 𝝓𝑗 gives the emission

intensity of sector j. Let us assume that there is a sector that incorporates all agriculture within a

nation, with emission intensity 𝝓𝒂𝒈𝒓𝒊𝒄𝒖𝒍𝒕𝒖𝒓𝒆. 𝝓𝒂𝒈𝒓𝒊𝒄𝒖𝒍𝒕𝒖𝒓𝒆 will indicate how many emissions are

(13)

13 𝒖𝒕 = 𝝓𝒕 𝑳 = [𝜙1 … 𝜙𝑛] [ 𝑙11 ⋯ 𝑙1𝑛 ⋮ ⋮ 𝑙𝑛1 ⋯ 𝑙𝑛𝑛 ]

𝒖𝒕 is a vector of emission multipliers. 𝑢𝑗 gives the total emissions generated (i.e. in all sectors

together) per unit of final demand for good j. The matrix structure above indicates the structure of the vectors and matrix on a national scale

3.3 National shared responsibility

The second part of our framework comprises shared responsibility measures on a nation scale, which is an extension of the previous section. The first fundament of the SR framework was provided by Gallego and Lenzen (2005) by quantifying shared responsibility on a national level. Their method accrues responsibility to a sector, based upon the contributions that their actors have in the supply chain. The contributions are the final demand of the sector and a fraction of the inter-industry sales of the sector.

𝑦̅𝑖 = 𝑦𝑖 + (1 − 𝛼𝑖)(𝑥𝑖 − 𝑦𝑖)

(1 − 𝛼𝑖)(𝑥𝑖 − 𝑦𝑖) indicates the responsibility share due to inter-industry sales, in which 𝛼𝑖 is a

responsibility fraction specifically for sector i. The sum of the contribution that sector i has, is

given by 𝑦̅𝑖. The Leontief inverse depicted in section 3.2, does not account for the responsibility

fraction 𝜶. This lead to an adjustment to the equation that gives the Leontief inverse (Gallego and Lenzen 2005; Lenzen et al. 2007).

𝑳̅ = (𝑰 − (𝜶̂)𝑨)−13

The difference with the former Leontief inverse calculation is that 𝜶̂ is included. The inclusion of

𝜶̂ leads to to an adjustment that affects matrix 𝑨, i.e. the inter-industry sales per unit of gross

(14)

14

output matrix. Consequently, the adjusted Leontief inverse indicated by 𝑳̅. Now the total

emission responsibility of a nation can be calculated.

𝜇 = 𝝓𝒕 𝑳̅ 𝒚̅ = [𝜙1 … 𝜙𝑛] [ 𝑙̅11 ⋯ 𝑙̅1𝑛 ⋮ ⋮ 𝑙̅𝑛1 ⋯ 𝑙̅𝑛𝑛 ] [ 𝑦̅1 … 𝑦̅𝑛 ]

𝜇 is the total emissions generated with all production processes in a nation, adjusted for the responsibility fractions. The vector of the emission multipliers under shared responsibility is given by: 𝜽̅𝒕 = 𝝓𝒕 𝑳̅ = [𝜙 1 … 𝜙𝑛] [ 𝑙̅11 ⋯ 𝑙̅1𝑛 ⋮ ⋮ 𝑙̅𝑛1 ⋯ 𝑙̅𝑛𝑛 ] in which 𝜃̅𝑖 = ∑ 𝜙𝑖 𝑙̅𝑖𝑗 𝑗

This implies that:

𝜇 = 𝜽̅𝒕 𝒚̅ = [𝜃̅ 1 … 𝜃̅𝑛] [ 𝑦̅1 … 𝑦̅𝑛 ]

The sum of the emission responsibility allocated to producers and consumers of sector i under shared responsibility is:

(15)

15

𝑠𝑖 denotes the sum of the producers’ and consumers’ emission responsibility under the shared

responsibility. The producers’ emission share is:

𝑝𝑖 = 𝜃̅𝑖 [(1 − 𝛼𝑖)(𝑥𝑖 − 𝑦𝑖)]

in which 𝑝𝑖 indicates the producers’ responsibility share in sector i. The consumers’ emission

share is given by:

𝑐𝑖 = 𝜃̅𝑖𝑦𝑖

where 𝑐𝑖 denotes the consumers’ responsibility share in sector i. The maximum and minimum of

𝜶 are 1 and 0 respectively. When 𝛼𝑖 is 0 the 𝑠𝑖 will coincide with producer responsibility. When

𝛼𝑖 is 1 the 𝑠𝑖 will coincide with consumer responsibility. According to Lenzen et al. (2007) 𝛼𝑖 is

given by:

𝛼𝑖 = 1 −

𝑣𝑖 𝑥𝑖 − 𝑡𝑖𝑖

When a supply chain is disaggregated and responsibility shares of emissions are fixed, there will be inconsistency in the final amount of emissions when the supply chain is extended, e.g. when an actor (i.e. a sector) is added. According to Lenzen et al. (2007) the inconsistency can be solved by deriving 𝜶 from a variable that is invariant to the amount of actors included in the supply chain. One variable that is invariant to the amount of actors included in the supply chain is value-added. The amount of value-added will always be the same for every specific sector, regardless of whether the sector is the first actor or the last actor in the supply chain. The responsibility

share 𝛼𝑖 for sector i is a function of the value-added 𝑣𝑖 of sector i, divided by the gross output of

(16)

16

3.4 Global shared, producer and consumer responsibility

Now we will extend the national framework of shared responsibility measures to a global scale. The total emission responsibility of producers and consumers in all nations is calculated with 𝜇̅ = 𝝓𝒕 𝑳̅ 𝒚̅ = [((𝝓𝟏)𝑡 … (𝝓𝒘)𝑡)] [𝑳̅ 𝟏𝟏 𝑳̅𝟏𝒘 ⋮ ⋮ 𝑳̅𝒘𝟏 ⋯ 𝑳̅𝒘𝒘 ] [ 𝒚 ̅𝟏𝟏+ ⋯ 𝒚 ̅𝟏𝒘 ⋮ 𝒚 ̅𝒘𝟏+ ⋯ 𝒚 ̅𝒘𝒘 ]

𝜇̅ denotes the total emission responsibility of all nations. The emission responsibility under shared responsibility for producers and consumer on a global scale is measured through a similar method as shared responsibility on a national scale. The producer responsibility on a national scale is given by:

(1 − 𝛼𝑖)(𝑥𝑖 − 𝑦𝑖) ˅ (𝑰 − 𝜶̂)(𝒙 − 𝒀𝒆)

Given

𝒙 − 𝒀𝒆 = 𝑻𝒆

We can use 𝑻 to calculate the producer responsibility shares on a global scale. We sum 𝑻 over n sectors in w nations that receive the intermediary good. As a result, we get matrix 𝑯. 𝑯 is a

matrix of inter-industry transactions of n sectors in w nations to w nations. An element of 𝑯 is

denoted by:

𝑖𝑟𝑠 = ∑𝑗𝑡𝑖𝑗𝑟𝑠

𝑖𝑟𝑠 gives the inter-industry transaction from sector i in nation r to nation s. The matrix structure

(17)

17 𝑯 = [ 𝒉𝟏𝟏 ⋯ 𝒉𝟏𝒘 ⋮ ⋮ 𝒉𝒘𝟏 ⋯ 𝒉𝒘𝒘 ]

Now we can measure the producer responsibility emission shares of n sectors in w nations that sell intermediaries to w nations, as given by:

𝑷 = 𝝓̂ 𝑳̅ (𝑰 − 𝜶̂)𝑯

When we sum 𝑷 over its sectors that produce intermediaries, we acquire the producer

responsibility emissions shares matrix 𝑷̅ of w nations selling intermediaries to w nations. Its matrix structure is:

𝑷̅ = [

𝑝̅11 𝑝̅1𝑤

⋮ ⋮

𝑝̅𝑤1 𝑝̅𝑤𝑤

]

in which 𝑝̅𝑟𝑠 denotes the emission responsibility share of producers in nation r that sell their intermediaries to producers in nation s. The consumer responsibility emissions shares of consumers in w nations that purchase goods from n sectors in w nations are given by:

𝑪 = 𝝓̂ 𝑳̅ [𝒀] = [ 𝝓̂𝟏 ⋱ 𝝓̂𝒘 ] [ 𝑳̅𝟏𝟏 ⋯ 𝑳̅𝟏𝒘 ⋮ ⋮ 𝑳̅𝒘𝟏 𝑳̅𝒘𝒘 ] [ 𝒚𝟏𝟏 𝒚𝟏𝒘 ⋮ ⋮ 𝒚𝒘𝟏 𝒚𝒘𝒘 ]

in which 𝒀 is a final demand matrix. The matrix structure of 𝑪 is:

𝑪 = [

𝒄𝟏𝟏 𝒄𝟏𝒘

⋮ ⋮

𝒄𝒘𝟏 ⋯ 𝒄𝒘𝒘

(18)

18

When we sum 𝑪 over its sectors n in w nations that produced goods, which are sold to consumers in w nations, we acquire 𝑪̅. 𝑪̅ is a matrix that gives the responsibility emissions shares of consumers in w nations that consume goods that are purchased from w nations. The matrix structure of 𝑪̅ is: 𝑪̅ = [ 𝑐̅11 𝑐̅1𝑤 ⋮ ⋮ 𝑐̅𝑤1 ⋯ 𝑐̅𝑤𝑤 ],

𝒄̅𝑟𝑠 denotes the emission responsibility shares of consumers in nation s that purchased goods

from nation r. Since we have acquired both the producers and consumers shares we can calculate the total shared responsibility.

𝑺 = 𝑷̅ + 𝑪̅ = 𝜽𝒕[ 𝒀𝒆 + (𝑰 − 𝜶̂)(𝐱 − 𝒀𝒆)].

𝑺 is a matrix that gives the total responsibility shares of all nations. Essentially, the measurements to calculate producer responsibility and consumer responsibility on a national scale are very similar to that on a global scale. Though, we briefly shed light on two differences between the two. Firstly, the matrix structure on a global scale is different. This is caused by including more than one nation in the analyses and therefore the equations had to be adjusted accordingly. Secondly, our methodology on the national scale focuses on shared responsibility of emissions in

n sectors. On the global scale our aim is to avoid the sector scope, and look at shared

responsibility of emissions between w nations.

We also calculated emission responsibilities using the classical producer and classical

consumer responsibility approaches. The classical producer responsibility is calculated with

(19)

19

𝒑𝒓 is a vector of producer responsibilities of n sectors in w nations. When we sum 𝒑𝒓 over n sectors we get a vector 𝒑𝒓̅̅̅̅ of producer responsibilities in w nations. The classical consumer responsibility is calculated with:

𝒄𝒓 = 𝝓̂ 𝑳 𝒚 = 𝜽̂ 𝒚 = [𝜽 ̂𝟏 ⋱ 𝜽 ̂𝒘 ] [ 𝒚𝟏 … 𝒚𝒘 ]

𝒄𝒓 is a vector of consumer responsibilities of n sectors in w nations. When we sum 𝒄𝒓 over n

sectors we get a vector 𝒄𝒓̅̅̅ of consumer responsibilities in w nations. When using the method to

calculate the total emission responsibility on a global scale − as described in this last section − the

values of 𝜇̅ should coincide with the sum of 𝒑𝒓̅̅̅̅ and the with the sum of 𝒄𝒓̅̅̅.

4. Results

After applying the methodology, as described in the previous chapter, we acquired results

on shared responsibility, producer responsibility and consumer responsibility of emissions of 40 nations and the RoW. We grouped the 40 nations and the RoW in several regions. As a result, shown in table 1, six regions emerged, namely, EU-27, NAFTA, Southeast Asia, RoW+ABT (Australia, Brazil, RoW and Turkey), Russia and Southeast Asia. Our analyses on total emission responsibility showed a total of 24.87 billion tonnes of CO2 for all regions combined when using the SR. The total shared responsibility is interpreted as follows: “the emission responsibility of a nation combines the responsibility of production by upstream producers and the final demand of consumers.” The total emissions generated with the production of goods and services measured with CR and PR was in both instances 24.87 billion tonnes of CO2 in 2009. Therefore, the total SR of all nations coincides with the corresponding CR and PR, indicating that all emissions were incorporated into the measurements of the total SR. This supports the validity of the SR as a measure of emission responsibility.

In this section we will describe the PR and CR results. When the emissions embodied in

(20)

20

own consumption (i.e. imports of emissions) are larger than zero, there are net exports. In other words, PR – CR > 0. Otherwise, there are net imports. We will distinguish the sample between two groups, namely, the net exporters and net importers. A net exporting nation is China and a net importing nation is Germany. An important note to make is that net exporters are generally developing nations and net importers are mostly developed nations (Davis and Caldeira 2010; Hertwich 2008). We will elaborate on our SR results with the support of the corresponding PR and CR results. It is important to keep this distinction between net exporters and net importers in mind. That being said, we find that the total SR of all nations is almost always between the corresponding PR and CR. To explain why this is the case, we have to refer back to section 3.3 in the methodology. As we explain there, 𝜶 is a value between the minimum zero and the maximum

one. When 𝜶 is zero the total SR is equal to PR. If 𝜶 is one the total SR is equal to PR. Due to

these two conditions it is expected that the total SR will always hover between the PR and CR values. We find that these conditions hold for 35 nations and RoW (Appendix A, table 3), thus

supporting the design of the SR approach and the use of 𝜶 as designed by Lenzen et al. (2007).

This result also tells us that the SR can be used as an independent measure in calculating the emission responsibility of a nation as a whole. There are however five total SRs that were lower than both the PR and CR. The corresponding nations with those SRs are Bulgaria, Denmark, Mexico, Netherlands and Poland. We believe that the explanation should be found within the methodology and not within the database we used for our calculations. However, we could not find such an explanation for these five odd SR values from analyzing the methodology in more detail. We still have the belief that the underlying reason is methodological, but we acknowledge that our method is insufficient in explaining or accounting for it.

(21)

21

Table 1. Shared Responsibility, Producer Responsibility and Consumer Responsibility

Producer share Consumer share Total shared responsibility CS/PS Producer responsibility Consumer responsibility CR/PR 𝜶 EU-27 EU-27 1,238,389 2,282,708 3,521,097 1.84 3,161,905 4,460,732 1.41 0.70 France 83,789 235,170 318,959 2.81 260,360 465,847 1.79 0.68 Germany 253,828 465,544 719,372 1.83 636,309 869,297 1.37 0.70 Great Britain 157,019 298,323 455,342 1.90 422,297 538,857 1.28 0.68 Italy 118,836 253,534 372,371 2.13 329,336 522,251 1.59 0.63 Poland 109,266 165,094 274,360 1.51 275,037 292,087 1.06 0.69 NAFTA NAFTA 2,016,180 3,164,441 5,180,620 1.57 4,978,060 5,477,265 1.10 0.68 Canada 196,134 240,395 436,529 1.23 439,065 424,049 0.97 0.67 Mexico 123,521 224,276 347,797 1.82 351,280 348,207 0.99 0.72 United States 1,696,525 2,699,770 4,396,295 1.59 4,187,715 4,705,010 1.12 0.66 Southeast Asia Southeast Asia 4,678,452 3,637,121 8,315,573 0.78 8,321,552 8,356,306 1.00 0.61 China 3,711,016 2,161,547 5,872,563 0.58 6,213,385 5,163,681 0.83 0.47 Japan 436,258 557,966 994,223 1.28 953,737 1,100,978 1.15 0.63 South Korea 261,872 231,415 493,287 0.88 532,878 448,456 0.84 0.63

Australia, Brazil, RoW and

Turkey 2,622,972 2,591,869 5,214,840 0.99 5,496,216 4,341,608 0.79 0.64

India 693,626 769,740 1,463,366 1.11 1,501,808 1,410,093 0.94 0.64

Russia 636,142 538,388 1,174,529 0.85 1,410,486 824,022 0.58 0.72

Total emissions 11,885,760 12,984,266 24,870,026 24,870,026 24,870,026

Source: Authors’ calculations based on the World Input-Output Database (revised November 2013 release).

Notes: First and second column give the producer and consumer shares using shared responsibility in Kilotonnes of CO2. The third column gives the total shared

shared responsibility in Kilotonnes of CO2. The fourth column gives the ratio of consumer shares to producer shares. The fifth and the sixth column give producer responsibility and consumer responsibility respectively in Kilotonnes of CO2. The seventh column gives the ratio of consumer responsibility to producer responsibility. The last column denotes the weighted averages of 𝜶. The last row denotes the total emissions of the three approaches that are used. The data is comprised of 35 sectors that produce goods and services in 40 nations and in the rest of the world in 2009. The six regions are EU-27 (Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Germany, Denmark, Spain, Estonia, Finland, France, Great Britain, Greece, Hungary, Ireland, Italy, Lithuania, Luxembourg, Latvia, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia and Sweden), NAFTA (Canada, Mexico and the United States), Southeast Asia (China, Indonesia, Japan, South Korea and Taiwan), Australia, Brazil, the rest of the world, Turkey, India and Russia.

(22)

22

services that embody emissions and have larger consumer than producer shares. The result indicates that for these 28 nations, the shared responsibility method distributes more of the emission responsibility to consumers than to producers. This is in line with the larger consumption than production that is present in these nations. At the other end of the CS/PS spectrum we find similar results. For five nations, the CS/PS ratio < 1 coincides with the CR/PR ratio < 1. This indicates that when a nation is producing more than it consumes, the producers are allocated with a larger responsibility share of emissions when shared responsibility is used. This result is in agreement with the larger production than consumption that is present in the nation.

There are some nations that have ratios of CS/PS and CR/PR that are not in line with our

intuition. For example Canada and India both have a CS/PS ratio > 1 and a CR/PR ratio < 1. The latter indicating that these nations are net exporters of goods and services that embody emissions. Intuitively, we would expect that especially Canada to have a CR/PR ratio > 1, given it is a developed nation. Additionally, we would expect a CS/PS ratio < 1 for India, given its global role as a producer of goods and services. India’s CR/PR ratio is in line with this reasoning. We can explain a component of these results by looking closer at the consumer shares of the nations. As explained in the methodology, 𝜶 is given by

1 − 𝑣𝑖

𝑥𝑖 − 𝑡𝑖𝑖

𝜶 is a function of the profit margin (value-added, 𝑣𝑖) and the costs of intermediaries (𝑥𝑖− 𝑡𝑖𝑖). 𝜶

will increase when either the profit margin increases or the costs of intermediaries decreases. In our method there is an apparent relationship between the value of 𝜶 and the CS. Given that 𝜶 is only incorporated once in the formula that measures the consumer shares on a global scale, namely in 𝑳̅ where 𝑳̅ is given by

𝑳̅ = (𝑰 − (𝜶̂)𝑨)−1

Therefore, when 𝜶 increases, the CS will always increase and when 𝜶 decreases the CS will

(23)

23

not imply a lower producer share and a lower 𝜶 does not imply a higher producer share.

Therefore, there is no relation between 𝜶 and PS. Given this knowledge, let us look closer at Canada. Canada has a CS/PS > 1. In this case we expect a large 𝜶 that as a result will skew upwards the consumer share in comparison to the producer share. The same logic applies to any nation with a CS/PS > 1 and not just to Canada and India. We calculated the weighted average of all 𝜶 values to look further into this. The weighted average 𝜶 of all 40 nations and the RoW was 0.68. The value of Canada’s 𝜶 is 0.67, which is just below average. This implies that for Canada, the profit margin is roughly one third of the cost of the intermediaries. India has an 𝜶 of 0.64. So

in comparison to the entire sample Canada and India do not have a very large 𝜶. However, it is

possible that the sample has a large average 𝜶 that generally skews upwards the CS/PS shares.

The lowest 𝜶 is found in China, which is 0.47. A lower 𝜶 implies a lower CS/PS ratio since it

skews the CS share downwards. Given that China has the lowest CS/PS ratio, it indicates that China’s low 𝜶 decreases its CS/PS ratio. Two other components that directly influence the CS/PS ratio are the industry sales of producers and the consumption of consumers. If the inter-industry sales increase, the PS will increase and the CS/PS ratio will decrease. When the consumption of consumers increases, the CS share will increase and the CS/PS will increase.

In this last section we will discuss the results shown in table 2. In table 2 we describe the matrices of consumer and producer shares of the aggregated regions. The disaggregated version of this matrix has 41 rows and columns, one row and column for every nation and RoW

(Appendix B, table 4 and table 5). The producer share, 𝑝̅ 𝐸𝑈−27𝑁𝐴𝐹𝑇𝐴, indicated by the row

header EU-27 and the column header NAFTA, is 132,581 million tonnes of CO2. The interpretation of this value is: ”the emission responsibility of producers in the NAFTA region is 132,581 million tonnes of CO2 in inter-industry sales to the EU-27.” The consumer share, 𝑐̅ 𝐸𝑈−27𝑁𝐴𝐹𝑇𝐴, indicated by the row header EU-27 and the column header, is 152,813 million

(24)

24

Table 2. Aggregated Producer and Consumer Shares

Region EU-27 NAFTA Southeast Asia

Australia, Brazil,

RoW and Turkey India Russia

Region Producer shares

EU-27 1,080,993 132,581 61,821 236,914 11,934 146,217 NAFTA 93,662 1,612,814 131,549 231,264 21,802 20,823 Southeast Asia 44,919 225,064 4,446,736 140,839 17,053 7,017 Australia, Brazil,

RoW and Turkey 13,401 29,205 27,753 1,999,005 2,288 9,406

India 3,031 15,546 9,896.05 7,307 640,499 411 Russia 2,384 970 696.28 7,643 50 452,268 Total emissions 1,238,389 2,016,180 4,678,452 2,622,972 693,626 636,142 Consumer shares EU-27 1,666,477 152,813 70,834 26,111 4,176 3,104 NAFTA 143,970 2,583,613 183,883 34,896 14,080 1,438 Southeast Asia 130,839 202,068 3,240,831 49,858 18,447 1,057 Australia, Brazil,

RoW and Turkey 144,912 157,792 101,366 2,459,879 7,238 2,058

India 22,812 28,584 26,803 4,812 725,087 85

Russia 173,697 39,572 13,404 16,314 713 530,645

Total emissions 2,282,708 3,164,441 3,637,121 2,591,869 769,740 538,388

Source: Authors’ calculations based on the World Input-Output Database (revised November 2013 release).

Notes: The upper half of the table denotes the producer share responsibility that regions have in their own regions as in all other regions. The column headers indicate

the origin of the producers. The bottom half of the table denotes the consumer share responsibility that regions have in their own regions as in all other regions. The column headers indicate the origin of the consumers. The data is comprised of 35 sectors that produce goods and services in 40 nations and in the rest of the world in 2009. All producer and consumer shares are measured in Kilotonnes of CO2.

supplied by the region itself. If we reflect this on the trade of emissions, it indicates that most of the emissions released during the production of services and goods are actually staying within the borders of the region, with only a fraction of the emissions embodied in goods and services being traded.

When we compare the producer and consumer shares of table 2, we find two things. Firstly, given that the EU-27 and NAFTA region are net importers, we expect larger consumer than producer shares. For these two regions we find that almost all consumer shares are larger

than the corresponding producer shares. The exception is 𝑐̅ 𝑆𝑜𝑢𝑡ℎ𝑒𝑎𝑠𝑡 𝐴𝑠𝑖𝑎𝑁𝐴𝐹𝑇𝐴. For the other four

regions that are net exporters we expect larger producer shares than corresponding consumer shares. For these four regions we find four cases that have a larger consumer share than

corresponding producer share. These cases are 𝑝̅ 𝑅𝑜𝑊+𝐴𝐵𝑇𝑅𝑜𝑊+𝐴𝐵𝑇 , 𝑝̅ 𝐸𝑈−27𝐼𝑛𝑑𝑖𝑎, 𝑝̅ 𝑁𝐴𝐹𝑇𝐴𝐼𝑛𝑑𝑖𝑎

(25)

25

frequently producers get larger responsibility shares than consumers when the nation is a net exporter. Both results are independent of the geographical origin of both the buyer of intermediaries and of the vendor selling goods to consume.

5. Discussion

This paper presents the first study that applies the shared responsibility of emissions

methodology at a global level on a sample of developing and developed nations . With the results we acquired, based on the application of our methodology, we will give an answer to the research question in this chapter. Our research question again is: “What share of the emission

responsibilities accrues to producers and what to consumers in developed and developing nations with a shared responsibility approach on a global scale.”

As expected, shared responsibility accrues emission responsibility to both upstream

producers and downstream consumers. The results showed that the producer and consumer shares of emission responsibilities were allocated in a way that coincides very much with whether a nation is a net importer or net exporter. When a nation is a net importer it generally indicates it is a developed nation. Also when a nation is a net exporter then it is most likely that it is a developing nation. Since there were a few exceptions, we cannot say that net importers are always developed nations, and that net exporters are always developing nations.

An important result was that most net importers have larger consumer shares than

(26)

26

exactly the same if we would have treated them as individual nations. If we apply this to an emission policy, it would imply that nations should focus on their own producers and consumers regarding decreasing emissions, given that is where most of the responsibility is accrued. This is why we believe that SR should be taken into account for emission policies.

We see several windows of opportunities for improvement with regard to further research

involving shared responsibilities. Our results are derived from two producer and consumer share matrices. In table 2, we depicted an aggregated version of the exhaustive matrices (Appendix B, table 4 and table 5). It would be valuable to look at the origins of consumer and producer share emissions of nations’. This will confirm whether the results found on a regional level are indeed similar to that on a national level.

Another line of research would be to look at the trends of producer and consumer shares over the last decade. It could tell us whether the responsibility for the increase of total emissions lies with the producers or consumers. It could indicate for which specific group, intervention would be beneficial, with the aim to decrease the total emissions released by production. We discussed some of the influence of the responsibility fraction 𝜶 in the results section. We found a

clear relationship between the consumer shares and 𝜶, whereas such a relation remained absent

for producer shares. It would be beneficial to study this topic and see whether such a relationship can be found for producer shares too.

We were not able to explain why five nations had seemingly odd SR values. We believe it would be important to find the methodological reasons behind this.

One restriction of the WIOD database is that the RoW incorporates all the nations that are not included in the WIOD. This offers an opportunity to apply the SR on a different database of nations that are not included in our sample. For example apply SR on only developing nations that are not present in the WIOD and compare the results with our study.

The main question that arises from our study is: “should policy makers now use the SR

(27)

27

literature available on SR results and more specifically on the interpretation of them. When it comes to looking at emissions policies, we illustrated the benefits of SR over PR and CR. If policy makers want to look at the origin of emissions and at the extent to which actors are responsible, the shared responsibility approach is particularly suitable.

6. Conclusion

The results of this SR study open up the debate on who should be held responsible for the

(28)

28

7. References

Bastianoni, Simone, Pulselli Federico M., and Enzo Tiezzi (2004) The problem of assigning responsibility of greenhouse gas emissions. Ecological Economics, 49, 253-257.

Davis, Stephen J., and Ken Caldeira (2010) Consumption-based accounting of CO2

emissions. Proceedings of the National Academy of Sciences, 107(12), 5687-5692. Dietzenbacher, Erik, Los, Bart, Robert Stehrer, Timmer Marcel, and Gaaitzen de Vries (2013)

THE CONSTRUCTION OF WORLD INPUT-OUTPUT TABLES IN THE WIOD PROJECT. Economics Systems Research, 25(1), 71-98.

Gallego, Blanca and Manfred Lenzen (2005) A Consistent Input-Output Formulation of Formulation of Shared Producer and Consumer Responsibility. Economic Systems

Research, 17(4), 365-391.

Hummels, David, Ishii, Jun, and Kei-Mu Yi (1999) The Nature and Growth of Vertical Specialization in World Trade. Journal of International Economics, 54, 75-96.

IDE-JETRO and WTO (2011) Trade patterns and global value chains in East Asia: from trade in goods to trade in tasks. Technical Report. IDE-JETRO, World Trade Organization, Geneva, Switzerland.

IPCC. (1996) Revised 1966 IPCC Guidelines for National Greenhouse Gas Inventories (3 volumes). Intergovernmental Panel on Climate Change.

Lashof, Daniel A., and Dilip R. Ahuja (1990) Relative contributions of greenhouse gas emissions to global warming. Nature, 344, 529-531.

Lenzen, Manfred, Murray, Joy, Sack, Fabian, and Thomas Wiedmann (2007). Shared producer and consumer responsibility – theory and practice. Ecological Economics, 61, 27-42.

Peters, Glen P. (2008) From production-based to consumption-based of national emissions inventories. Ecological Economics, 65(1), 13-23.

Peters, Glen P., and Hertwich, Edgar G. (2008) CO2 embodied in international trade with

implications for global climate policy. Environmental Science & Technology, 42(5), 1401-1407.

(29)

29

Steininger, Karl, Lininger, Christian, Droege, Susanne, Roser, Dominic, Tomlinson, Luke, and Lukas Meyer (2014) Justice and cost effectiveness of consumption-based versus production-based approaches in the case of unilateral climate policies. Global

Environmental Change, 24(4), 75-87.

UNFCCC (2012) Doha Amendment to the Kyoto Protocol. Article 1. Framework Convention on Climate Change.

Wiedmann, Thomas (2009) EDITORIAL: CARBON FOOTPRING AND INPUT-OUTPUT = ANALYSIS – AN INTRODUCTION. Economic Systems Research, 21(3), 175-186. World Bank (2015) Pricing Carbon. The World Bank.

http://www.worldbank.org/en/programs/pricing-carbon. Accessed: December 2015. Zhang, Youguo (2013) The responsibility for carbon emissions and carbon efficiency at the

sectoral level: Evidence from China. Energy Economics, 40, 967-975. Zhang, Youguo (2015) Provincial responsibility for carbon emissions in China under

(30)

30 Appendix A

Table 3. Shared Responsibility, Producer Responsibility and Consumer Responsibility

Producer share Consumer share Total responsibility CS/PS Producer responsibility Consumer responsibility CR/PR 𝜶 Nation Australia 158,513 226,455 384,968 1.43 364,325 406,188 1.11 0.62 Austria 21,533 56,972 78,505 2.65 47,928 119,773 2.50 0.72 Belgium 36,265 63,258 99,522 1.74 91,053 125,340 1.38 0.74 Bulgaria 17,376 20,038 37,414 1.15 41,684 38,142 0.92 0.62 Brazil 107,240 157,733 264,974 1.47 251,288 297,653 1.67 0.64 Canada 196,134 240,395 436,529 1.23 439,065 424,049 1.53 0.67 China 3,711,016 2,161,547 5,872,563 0.58 6,213,385 5,163,681 1.37 0.47 Cyprus 2,271 6,036 8,308 2.66 6,713 11,187 0.75 0.74 Czech Republic 43,151 76,772 119,923 1.78 96,801 147,628 1.38 0.66 Germany 253,828 465,544 719,372 1.83 636,309 869,297 0.89 0.70 Denmark 25,531 30,719 56,251 1.20 78,220 59,016 1.35 0.71 Spain 102,186 147,874 250,061 1.45 230,728 318,263 1.79 0.65 Estonia 5,951 7,265 13,216 1.22 14,245 12,637 1.28 0.69 Finland 26,156 33,941 60,098 1.30 55,188 74,521 1.41 0.65 France 83,789 235,170 318,959 2.81 260,360 465,847 1.92 0.68 Great Britain 157,019 298,323 455,342 1.90 422,297 538,857 2.50 0.68 Greece 46,174 59,979 106,153 1.30 93,776 132,221 1.38 0.76 Hungary 14,192 43,231 57,423 3.05 41,606 79,900 0.92 0.71 Indonesia 155,534 173,109 328,643 1.11 331,193 317,095 0.96 0.63 India 693,626 769,740 1,463,366 1.11 1,501,808 1,410,093 0.94 0.64 Ireland 12,067 22,008 34,074 1.82 27,569 44,146 1.60 0.80 Italy 118,836 253,534 372,371 2.13 329,336 522,251 1.59 0.63 Japan 436,258 557,966 994,223 1.28 953,737 1,100,978 1.15 0.63 South Korea 261,872 231,415 493,287 0.88 532,878 448,456 0.84 0.63 Lithuania 4,226 11,593 15,820 2.74 11,527 24,039 2.09 0.76 Luxembourg 1,210 3,264 4,473 2.70 3,039 6,956 2.29 0.86 Latvia 2,753 6,554 9,307 2.38 7,181 13,245 1.84 0.69 Mexico 123,521 224,276 347,797 1.82 351,280 348,207 0.99 0.72 Malta 974 2,003 2,977 2.06 2,514 3,545 1.41 0.74 Netherlands 60,245 93,355 153,600 1.55 166,194 185,846 1.12 0.73 Poland 109,266 165,094 274,360 1.51 275,037 292,087 1.06 0.65 Portugal 21,855 32,845 54,701 1.50 52,180 64,361 1.23 0.69 Romania 30,979 51,879 82,858 1.67 76,798 96,546 1.26 0.71 Rest of the World 2,273,070 2,079,429 4,352,499 0.91 4,640,995 3,444,615 0.74 0.59 Russia 636,142 538,388 1,174,529 0.85 1,410,486 824,022 0.58 0.72 Slovakia 13,202 12,739 25,942 0.96 33,232 24,058 0.72 0.71 Slovenia 6,210 27,721 33,931 4.46 13,038 65,793 5.05 0.68 Sweden 21,142 54,994 76,136 2.60 47,351 125,229 2.64 0.65 Turkey 84,149 128,251 212,399 1.52 239,608 193,152 0.81 0.69 Taiwan 113,773 513,084 626,857 4.51 290,360 1,326,096 4.57 0.67 United States 1,696,525 2,699,770 4,396,295 1.59 4,187,715 4,705,010 1.12 0.66 Total emissions 11,885,760 12,984,266 24,870,026 24,870,026 24,870,026

Source: Authors’ calculations based on the World Input-Output Database (revised November 2013 release).

Notes: First and second column give the producer and consumer shares using shared responsibility in Kilotonnes of CO2. The third column gives the total

(31)

31 Appendix B

Table 4. Producer Responsibility Shares

Table 4 continuous on the next page.

Nation Australia Austria Belgium Bulgaria Brazil Canada China Cyprus Czech

Republic Germany Denmark Spain Estonia Finland France Great

Britain Greece Hungary Indonesia India Ireland Nation Australia 125,013 50 93 10 86 855 8,414 1 28 549 109 54 4 61 289 2,090 24 17 1,255 922 16 Austria 73 12,388 473 194 80 223 1,088 13 1,025 3,426 73 128 39 56 227 314 30 724 61 230 26 Belgium 164 201 16,537 1,451 183 1,240 2,123 2 1,163 6,267 221 632 76 243 1,077 1,302 246 198 147 751 81 Bulgaria 5 38 22 11,595 12 24 203 2 50 133 13 33 1 6 29 34 57 39 7 31 2 Brazil 144 77 392 25 89,697 1,354 2,408 0 54 1,535 105 186 12 53 218 334 25 21 219 495 7 Canada 720 69 308 54 389 130,446 5,936 1 62 1,124 92 232 5 101 378 885 200 29 185 8,915 41 China 9,153 273 858 84 4,026 4,914 3,513,626 6 243 3,753 576 420 24 373 1,587 1,657 177 112 4,995 7,253 69 Cyprus 3 6 12 7 3 6 63 2,008 94 36 11 16 1 5 14 29 36 11 8 87 1 Czech Republic 39 311 240 66 24 101 1,165 3 29,839 1,861 46 132 6 48 258 237 21 178 83 186 20 Germany 680 2,224 2,869 719 1,191 3,268 10,169 32 3,641 180,831 972 1,256 106 664 2,076 3,591 323 909 806 2,529 190 Denmark 130 50 260 20 82 113 997 1 88 1,101 8,612 93 90 127 111 636 27 37 286 226 17 Spain 94 165 915 128 336 498 2,298 2 268 2,198 156 85,435 63 209 1,332 1,870 45 204 1,064 666 133 Estonia 2 4 12 3 3 8 68 1 13 61 13 7 3,955 103 10 14 1 3 6 10 1 Finland 91 39 207 26 212 216 651 0 78 759 234 78 277 19,055 120 246 14 37 30 303 33 France 439 330 2,145 182 378 982 4,417 4 439 5,150 239 1,995 63 226 60,094 2,301 93 236 460 871 227 Great Britain 673 208 874 115 252 2,990 4,453 10 352 3,071 381 917 83 287 1,173 107,604 171 178 367 1,955 498 Greece 25 38 137 259 73 124 452 41 37 482 37 124 3 21 132 143 41,389 30 60 119 6 Hungary 13 342 262 81 15 73 662 2 414 896 27 60 6 34 122 113 7 8,294 19 126 14 Indonesia 616 18 88 11 115 184 3,923 1 16 208 99 28 2 16 131 260 9 17 118,048 559 7 India 1,667 70 580 25 169 1,266 7,470 2 70 585 185 105 8 72 153 505 12 16 1,052 640,499 14 Ireland 115 33 209 88 16 362 1,109 1 106 802 61 198 8 39 261 1,925 18 86 81 134 8,946 Italy 201 915 1,052 327 368 601 3,553 8 567 4,549 242 918 23 151 1,564 1,685 178 374 541 1,444 299 Japan 5,050 123 139 26 641 2,347 21,691 2 78 1,039 360 142 14 181 457 837 43 41 7,397 2,653 45 South Korea 2,513 78 141 24 517 1,029 15,267 4 63 1,027 184 124 6 95 290 544 132 71 3,768 1,062 19 Lithuania 2 6 17 4 2 3 56 1 21 70 27 8 107 28 9 23 4 4 6 7 1 Luxembourg 11 15 359 12 5 103 89 0 24 407 8 40 4 11 84 196 11 15 6 20 30 Latvia 1 7 12 6 1 6 35 3 12 63 10 7 103 20 14 12 7 5 2 7 2 Mexico 74 35 72 9 193 789 3,346 0 40 510 34 227 18 24 125 215 8 12 99 319 15 Malta 1 2 4 1 0 5 38 1 1 19 2 8 1 6 14 42 5 2 1 11 0 Netherlands 152 138 1,859 107 447 428 3,638 8 290 3,290 269 446 304 287 698 2,709 69 112 308 948 92 Poland 45 212 353 80 55 126 1,607 3 835 2,254 126 214 26 219 395 428 32 345 82 199 27 Portugal 11 26 239 22 167 59 278 0 43 513 45 1,122 3 26 244 255 12 15 38 91 28 Romania 13 117 81 263 30 191 338 6 153 485 18 84 3 13 117 110 43 272 15 153 8

Rest of the World 103 111 134 186 44 50 1,933 18 232 772 73 137 68 209 201 197 19 106 50 173 18

(32)

32

Nation Italy Japan South Korea Lithuania Luxembourg Latvia Mexico Malta Netherlands Poland Portugal Romania Rest of

the World

Russia Slovakia Slovenia Sweden Turkey Taiwan United States Nation Australia 180 660 739 10 1 2 63 2 402 51 15 13 1,626 319 15 8 19 402 218 8,150 Austria 453 126 108 35 10 26 34 4 265 699 66 583 4,616 13,355 1,146 12 91 134 77 3,380 Belgium 503 333 275 63 86 12 92 8 2,869 1,178 161 276 4,574 2,632 218 60 101 176 142 6,530 Bulgaria 81 13 20 2 0 1 3 9 29 100 5 209 5,748 591 61 1 72 16 4 580 Brazil 221 369 416 4 1 2 218 1 136 93 125 22 4,507 647 18 9 19 229 287 7,205 Canada 264 583 565 16 5 3 714 1 304 127 40 133 2,421 1,033 31 13 28 318 1,683 4,970 China 742 10,520 14,510 26 10 21 718 10 1,140 744 78 116 45,274 2,451 84 68 136 8,705 1,223 51,909 Cyprus 37 4 5 2 0 3 4 1 14 10 4 13 552 363 2 1 1 4 8 124 Czech Republic 779 231 169 169 14 5 6 42 1 197 1,155 28 109 3,967 29,098 202 8 24 123 30 Germany 2,037 1,412 1,206 176 154 58 835 17 3,946 4,660 364 702 30,373 28,809 1,060 126 426 1,090 512 19,042 Denmark 125 99 129 54 3 39 108 9 784 343 34 28 1,313 902 32 65 24 112 86 2,501 Spain 1,219 222 337 47 15 10 993 4 963 492 1,062 174 8,566 3,334 92 22 93 194 148 10,056 Estonia 12 8 6 47 0 30 2 0 16 60 1 2 921 108 7 4 4 8 2 172 Finland 96 82 97 16 4 23 33 2 290 263 49 27 12,271 621 21 62 20 72 35 1,637 France 1,973 528 597 88 93 16 438 15 1,517 1,045 450 296 22,750 7,362 234 40 132 303 340 13,851 Great Britain 1,964 764 765 594 40 23 30 142 56 1,767 936 200 191 9,029 3,492 126 56 146 353 379 Greece 339 43 113 3 1 11 25 1 136 69 14 83 6,854 525 26 4 63 39 59 2,406 Hungary 152 103 131 5 5 2 23 1 217 380 8 228 5,827 11,304 213 7 17 46 24 831 Indonesia 57 1,022 981 3 1 3 19 0 97 41 4 18 1,567 190 12 5 12 352 64 6,182 India 200 484 734 17 3 8 151 1 162 89 14 52 5,193 411 36 9 38 277 156 14,129 Ireland 156 110 80 9 8 3 19 3 236 328 34 19 1,332 380 15 9 9 46 115 2,161 Italy 98,381 396 538 28 34 11 202 27 1,175 863 176 527 45,792 14,089 821 34 237 363 196 18,773 Japan 294 373,148 4,314 9 3 9 274 4 310 131 28 29 14,400 684 27 16 26 5,033 936 31,886 South Korea 855 238 6,071 202,402 7 2 5 151 21 212 115 15 37 9,575 684 38 10 27 958 417 Lithuania 21 3 5 2,101 0 37 1 3 17 229 2 3 8,007 388 9 3 2 4 1 260 Luxembourg 39 49 13 37 3 527 1 9 1 113 63 7 8 159 293 6 2 11 9 8 Latvia 14 2 5 116 0 1,765 0 0 19 121 2 3 1,425 207 13 3 2 5 2 261 Mexico 164 619 693 7 1 1 98,034 3 140 44 26 15 1,476 328 17 4 9 276 1,039 2,163 Malta 47 2 5 1 0 1 1 678 8 4 1 3 79 21 2 0 2 2 1 84 Netherlands 2,462 378 505 352 25 22 12 176 3 33,309 637 126 184 18,355 3,600 81 43 54 231 182 Poland 440 151 409 169 9 19 30 8 387 87,485 29 138 15,621 14,959 144 20 46 103 84 2,276 Portugal 143 31 65 6 2 1 19 1 150 49 17,186 22 883 420 12 3 14 17 25 1,760 Romania 294 28 92 3 2 1 6 3 109 364 9 24,233 3,860 4,093 165 2 127 29 10 1,071

Rest of the World 17,960 228 252 407 292 3 40 17 2 168 721 12 112 1,718,670 8,198 129 10 45 73 38

Russia 109 41 261 3 1 4 5 1 77 315 5 30 7,579 452,268 55 2 11 45 13 945 Slovakia 194 15 20 3 1 1 3 0 32 62 3 27 666 1,555 6,753 1 13 18 6 669 Slovenia 159 150 150 71 5 39 33 3 483 622 83 113 5,672 1,589 44 5,003 43 87 92 3,635 Sweden 507 116 495 9 8 4 19 3 159 182 27 346 6,619 2,129 70 11 17,238 145 36 2,275 Turkey 91 2,667 1,104 3 1 2 32 0 121 72 8 24 4,237 241 12 5 15 53,021 160 8,377 Taiwan 1,473 4,482 4,257 72 11 16 16,995 16 1,861 574 285 151 23,846 3,008 133 52 166 3,964 99,172 56,853 United States 15,097 5,769 29,911 24,450 622 149 476 2,836 49 5,906 3,751 1,069 1,680 206,868 19,462 1,019 398 1,582 6,766 5,761 Total emissions 202,225 118,836 436,258 261,872 4,226 1,210 2,753 123,521 974 60,245 109,266 21,855 30,979 2,273,070 636,142 13,202 6,210 21,142 84,149 113,773 Source: Authors’ calculations based on the World Input-Output Database (revised November 2013 release).

Notes: Responsibility shares in Kilotonnes of CO2. The column headers indicate the producers responsibility shares in the specific nation. The row header indicates to which nation the inter-industry sales was. The data is comprised

(33)

33

Table 5. Consumer Responsibility Shares

Table 5 continuous on the next page.

(34)

34

Nation Italy Japan South Korea Lithuania Luxembourg Latvia Mexico Malta Netherlands Poland Portugal Romania Rest of the

World Russia Slovakia Slovenia Sweden Turkey Taiwan United States Nation Australia 208 2.775 807 3 3 2 113 2 173 47 19 17 173 18 7 89 64 461 3.795 7.016 Austria 892 146 72 12 13 9 57 3 173 227 51 184 244 149 138 181 142 35 692 2.457 Belgium 1.771 316 117 46 479 21 119 11 2.496 430 333 134 356 69 78 558 456 86 1.944 3.679 Bulgaria 489 46 29 15 15 11 21 2 153 132 29 481 485 35 40 61 382 12 228 2.067 Brazil 292 438 171 5 4 2 291 2 361 69 123 29 261 14 10 113 91 77 2.235 5.461 Canada 415 1.260 325 7 29 5 1.012 8 339 92 63 155 231 21 15 146 111 189 28.634 5.542 China 8.635 40.915 13.782 151 130 85 6.572 76 6.418 3.506 640 740 9.818 696 308 1.617 5.725 4.773 105.973 100.091 Cyprus 14 8 6 1 2 2 1 1 9 5 1 12 26 2 1 3 12 1 9 115 Czech Republic 779 138 69 45 33 23 71 3 358 997 71 240 595 988 83 203 181 29 660 2.373 Germany 6.263 1.808 951 158 367 107 893 39 4.006 2.524 848 724 2.277 463 322 1.628 1.212 471 8.846 23.693 Denmark 377 539 149 56 7 25 73 5 312 242 68 32 285 38 16 1.477 400 58 1.303 23.777 Spain 1.922 322 133 35 27 18 667 25 627 384 2.289 159 440 52 87 304 684 57 2.685 7.913 Estonia 34 19 6 340 3 145 37 1 355 28 6 6 139 2 2 167 18 9 119 353 Finland 192 186 74 51 8 30 32 8 244 291 48 17 326 14 7 1.438 62 31 702 1.959 France 2.815 1.109 321 31 121 27 274 23 1.150 576 556 231 725 134 75 644 695 184 4.575 10.899 Great Britain 1.964 1.119 410 41 41 22 324 75 2.014 620 407 154 589 88 42 775 806 250 8.592 17.741 Greece 275 49 62 3 5 8 11 7 70 40 16 62 61 9 10 39 147 14 941 1.693 Hungary 521 81 72 16 12 12 26 2 158 468 34 427 387 173 56 132 155 16 359 1.853 Indonesia 391 2.308 605 17 5 3 190 2 314 129 50 23 548 35 16 71 783 299 4.744 7.424 India 1.833 2.031 749 16 17 14 616 22 1.196 401 154 406 1.461 85 70 384 1.901 529 18.448 24.546 Ireland 269 68 21 1 9 3 19 2 119 39 36 9 35 8 5 69 20 12 455 884 Italy 166.666 932 338 60 46 29 355 139 558 737 339 463 1.306 138 396 301 1.062 178 3.741 12.850 Japan 624 452.560 3.370 7 10 4 724 5 552 215 55 39 734 54 24 188 259 2.247 8.464 27.919 South Korea 855 5.106 191.986 12 11 9 1.049 7 452 559 99 123 1.313 259 41 225 875 902 9.173 31.335 Lithuania 47 15 7 4.599 4 210 20 1 37 163 11 5 243 4 10 80 15 3 181 687 Luxembourg 39 5 2 1 982 0 2 0 25 9 3 3 7 1 1 6 11 1 23 226 Latvia 14 9 4 83 1 3.251 1 1 14 17 1 3 69 4 1 35 5 1 33 554 Mexico 160 384 94 3 6 1 201.744 1 136 39 26 9 68 7 5 31 50 35 17.803 2.642 Malta 41 10 30 2 0 0 3 1.146 3 7 2 3 3 5 0 3 3 1 21 49 Netherlands 2.462 614 264 119 140 52 347 32 52.305 676 421 244 549 116 64 1.143 340 219 3.820 11.302 Poland 2.071 218 132 741 52 228 103 11 1.040 128.828 157 575 1.877 430 123 908 571 63 1.297 6.658 Portugal 293 57 15 3 9 3 81 2 201 46 22.731 14 83 8 4 85 76 8 575 1.727 Romania 685 51 36 6 5 4 22 2 171 153 29 38.106 292 29 27 89 327 15 234 1.908

Rest of the World 17.960 9.691 4.884 3.121 174 1.468 1.867 160 5.246 5.662 834 1.821 2.029.828 1.961 525 2.873 6.395 1.838 25.627 126.850 Russia 13.978 1.166 754 748 244 358 642 50 4.073 13.231 710 4.761 13.976 530.645 1.351 2.243 2.994 326 6.863 37.125 Slovakia 963 49 33 26 6 25 35 4 104 555 32 235 805 131 7.706 72 99 15 489 2.467 Slovenia 42 20 10 4 2 4 7 0 37 22 8 3 23 3 2 5.416 12 5 98 458 Sweden 332 39 23 4 2 3 15 3 64 67 20 128 127 13 12 39 20.988 10 254 2.035 Turkey 599 6.872 735 10 8 8 539 4 384 190 38 49 435 66 26 151 508 109.552 9.476 9.882 Taiwan 250 881 261 3 5 3 1.120 2 188 78 32 13 122 13 10 87 77 151 161.099 5.974 United States 15.097 23.608 9.505 992 223 323 4.182 116 6.721 2.594 1.456 1.043 8.108 1.411 1.023 3.646 6.281 5.090 67.874 2.165.589 Total emissions 253.534 557.966 231.415 11.593 3.264 6.554 224.276 2.003 93.355 165.094 32.845 51.879 2.079.429 538.388 12.739 27.721 54.994 128.251 513.084 2.699.770 Source: Authors’ calculations based on the World Input-Output Database (revised November 2013 release).

Notes: Responsibility shares in Kilotonnes of CO2. The column headers indicate the consumer responsibility share in the specific nation. The row header indicates the nation from which the good or service is purchased. The data is

Referenties

GERELATEERDE DOCUMENTEN

Gedurende de groeiseizoenen 1988 t/m 1990 werden vele Nederlandse graantelers geconfronteerd met een aantasting van hun gewas door het gerstevergelingsvirus (Barley Yellow

(lower panel) Average amplitude of central (Cz) EEG deflection prior to myoclonic jerks from 500 prior to jerk to jerk onset in cortical myoclonus (CM), functional jerks with absent

• Voorbereidend gesprek met gespreksleiding over: aanleiding voor de KlantArena, de belangrijkste thema’s voor de discussie. • Opstellen van een checklist met gespreksthema’s voor

Methods: To simultaneously decompose depression heterogeneity on the person-, symptom and time-level, three-mode Principal Component Analysis (3MPCA) was applied to data of 219

De docenten zijn redelijk te spreken over de schooladviezen van de basisscholen, toch is er een aantal scholen dat duidelijk nauwkeuriger adviseert dan anderen, en daar

Upon assignment, Ban made the advancement of RtP one of his central agenda items for the coming years of his term(s) in office. He reinforced this commitment by creating two

By comparing the ICISS and Ban Ki-moon interpretation of JWT with the English School perspectives of solidarism and pluralism (Table 4.3), we can conclude that

Deze onduidelijkheden zullen, naar mijn idee, zeker van belang zijn voor de rest van het onderzoek omdat het gebrek aan een duidelijk en scherp afgebakend principe invloed