This document summarizes a study that quantifies CO2 emissions according to the control criterion of enterprises on a global scale. The study develops a new approach to allocate emissions based on the "span of control" or ultimate controlling institute of an enterprise. The results show that Dutch controlled emissions total 242 million tons, with 57% emitted abroad. Emissions in the EU are largely from Germany, Spain, and Poland in chemical, basic metals, and warehousing industries. Non-EU emissions are highest in the US, Canada, China, and Brazil in mining, chemicals, and food. Foreign control accounts for 38% of Dutch emissions, largely from energy and chemicals. The study is still developing but provides insight into allocating emissions according to

1. Quantifying CO2-emissions according to the
control-criterion in a globalizing world
Maarten van Rossum, Cor Graveland, Sjoerd Schenau and Bram Edens
Presentation and discussion by Abdul A Erumban
Rotterdam, August 2014, IARIW conference
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2. Introduction and background
 Globalisation; effects on the environment
 Different ways to attributing CO2 emissions
 Production approach, consumption approach, Kyoto reporting
 From a GDP perspective to a national income perspective
 Resident controlled and foreign controlled emissions
 Develop a new approach to monitor CO2 responsibility
 Allocate emissions according to span of control
– By means of the Ultimate Controlling Institute: indicator for span of control
 Question: How to asses CO2 –emissions according to the control criterion
‘span of control’ by enterprises and to what extent do these emissions
deviate from emissions based on alternative approaches?
 Which countries have ‘control’ over Dutch residents?
 Which countries are ‘controlled’ by Dutch residents?
 Which industries are important in bilateral control relationships?
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3. Data and methodology (1)
Methodology used for foreign control in the Dutch economy
1. First allocate the available stationary emissions on micro level
2. Secondly, add mobile emissions based on meso-level info
3. Allocate rest of emissions based on employment-key (key of
Ultimate Controlling Institute (1,0))
Data used for foreign control in the Dutch economy:
1. Micro information on CO2 emissions at statistical unit level (Energy
Statistics & Environmental Statistics)
2. UCI information (0 or 1) on micro level (statistical unit)
3. Employment data on micro-level (statistical unit)
4. Emission accounts data at meso-level (stationairy emissions and
emissions from mobile sources)
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4. Data and methodology (2)
Methodology used for Dutch control in foreign economies:
1. Calculate emission per number of employees (including self-employed)
 emission-intensity (X)
2. Multiply FATS employment data with ‘emission-intensity ‘at meso
level
3. Control for differences in emission-intensity in different countries
(index (emissions/production; NL=100)
Data used for Dutch control in foreign economies:
1. Foreign Affiliates Statistics data of European countries (inward FATS
European countries) and FATS data of non European countries
(outward FATS NL)
2. Emission accounts data at meso-level (stationairy emissions and
mobile emissions)
3. Labour accounts data at meso-level
4. WIOD data on differences in emission-intensity (emission/production)
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5. Results (1)
Domestic emissions related to Dutch and foreign control, 2008
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• Firms in the
Netherlands emitted
168Mton CO2, 62%
being from Dutch
controlled
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• Most of the emissions
(1/3) are from electricity
and gas
• Other high emission
intensive industries have
more foreign emissions
than Dutch

6. Results (2A)
Emissions in the European Union related to Dutch span of
control
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• 28Mton CO2 emissions in EU by
Dutch controlled firms (using Dutch
coefficients).
• Germany had the highest Dutch
emission, and Slovakia the lowest.
• Substantial difference between
using Dutch emission coefficients
vs. Foreign emission coefficients
(e.g. Germany, Poland, Bulgaria)
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7. Results (2B)
Emissions in the European Union related to Dutch span of
control
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• Most of Dutch emissions
in EU are in chemicals,
followed by basic metals
• Again differences between
Dutch coefficients and
foreign coefficients
(foreign is high in all
industries except in
chemicals)
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8. Results (3A)
Emissions outside the European Union related to Dutch span of
control
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• 49Mton CO2 emissions in outside
EU by Dutch controlled firms
(using Dutch coefficients)
• U.S and Canada had the highest
Dutch emission, followed by China
and Brazil.
• Substantial difference between
Dutch coefficients vs. Foreign
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9. Results (3B)
Emissions outside the European Union related to Dutch span of
control
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• Almost all non-EU emissions from
Dutch controlled firms are in
chemical, and mining sector.
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10. Results (4):Total emissions of Dutch controlled enterprises in the Netherlands and abroad
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• 43% (104 Mton) of Dutch controlled
emissions (242 Mton) are emitted by
Dutch residents, and 57% (138 Mton) by
foreign residents abroad.
• Total emissions by Dutch controlled
firms (242 Mton) are higher by 44% than
production approach (168 Mton)
[excluding households].
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11. Conclusions and recommendations (1)
Conclusions
 EU:Dutch control in Germany, Spain and Poland goes along with a lot of
emissions (chemical industry, basic metal industry and warehousing)
 Non EU: Dutch control in USA, Canada, China and Brazil goes along
with a lot of emissions (mining and quarring, chemical sector and food
industry)
 Foreign control in Dutch economy: especially relevant in energy sector,
air transport and chemical sector
 38 percent of resident emissions (production approach) are foreign
controlled
 Dutch controlled emissions are 44 percent larger than what the
production approach would produce
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12. Conclusions and recommendations (2)
Recommendations:
 Study is still in the learning phase
 Quality of data on emissions of residents is better than data on
emissions of non-residents.
 In modelling emissions of non-residents: from a 2 digit level to a 3 or a 4
digit level if possible (because aggregation level matters!)
 NACE classification in FATS matters a lot! NACE classification not
always perfect in FATS
 In depth study of some eye catching enterprises could be worthwhile
 Ambition: Time series! In order to monitor carbon leakage over time and
to test the pollution haven hypothesis
 Compare ‘control emissions’ with national income statistics in stead of
with GDP!
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13. Comments
 Interesting paper, and important step in improving our understanding of who is
responsible for CO2 emission and how much
 Instead of taking employment as proxy for size of economy (in measuring
emission intensity as emission/employment), why not use GDP. Since GDP is a
good measure of production, and will also take care of labor productivity effect
(employment can still be lower (hence high emission intensity), if labor
productivity is high.
 A better definition of how you define UCI
 Assumption of emission intensity of Dutch firms in the Netherlands is same for
a similar industry abroad
 How realistic is this: can you say Phillips’s emission intensity in the Netherlands is
same as in China or India
 This is also against your intution that companies, for instance, engaged in mining are
involved in exploration activities abroad, which is less emission intensive
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14.  In general, the use of Dutch coefficients produce lower emissions
 What does this mean, does it implicitly state that Dutch industries within the Netherlands are more
environmentally efficient, hence their coefficients are lower?
 This distinction has important consequences for total emissions and its distribution (figure)
• If you use Dutch coefficients, 27% of total Dutch
controlled emissions is in non EU countries, and
57% within the Netherlands
• But if we use foreign coefficients, Dutch controlled
emissions abroad is much higher than within the
Netherlands, and its magnitude in non-EU is as
high as it is in the Netherlands
• The choice of the coefficient has important
implications, and you may want to pay more
attention to this
 It is hard to argue that the differences are because Dutch enterprises in an industry have different
specialization than its foreign counterpart, because, in almost all industries Dutch coefficients produce
lower emission
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Total Emissions by Dutch controlled

15. Thank you for your attention!
Questions, remarks?
m.vanrossum@cbs.nl
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