Tales from the Tails:
Sector-level carbon intensity distribution
Baran Doda
IAERE, Rome, 17.02.2017
Motivation and overview
Tails of the carbon intensity distribution key to decarbonisation eorts:
• High carbon intensity (HCI) sectors to clean-up or shrink
• Low carbon intensity (LCI) sectors to expand
One-sentence overview:
Propose stylized facts describing economic sectors with exceptionally high
and low carbon intensity using data from 34 sectors in 39 countries
covering 1995-2009
Who lives in the tails? How have they been doing?
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Motivation and overview
Decompose changes in a country's carbon emissions to changes in
• (sector level carbon intensity) + (sector share in GDP) + (GDP)
Characteristics of HCI and LCI sectors/sets?
•
•
Are the sets of HCI and LCI sectors the same across countries?
Does a given HCI (LCI) sector look the same across countries?
Changes in HCI and LCI sectors's input use and productivity over time?
•
•
Where are the signicant dierences?
Are advanced and developing countries the same?
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Data
WIOD Database @ www.wiod.org
•
•
•
35 sectors
40 countries and several key economic aggregates
1995-2009
Tab 1
Tab 2
Notes:
1
2
3
Advanced/developing country sub-samples based on median output
per worker in 2009. The 20 developing countries by this denition:
BGR, BRA, CHN, CYP, CZE, EST, HUN, IDN, IND, LTU,
LVA, MEX, MLT, POL, PRT, ROU, RUS, SVK, SVN, TUR
Some data missing for some countries in 2008-9.
New version of the database expected in summer 2017:
(43 countries; 56 sectors; 2000-2014; 2008 SNA; ISIC Rev 4)
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Decomposition and counterfactual scenarios
Sector carbon intensity & value-added share
cicit =
ecit
vacit
& scit =
vacit
Yct
Aggregate carbon emissions
Ect =
Index Decomposition
X
[cicit × scit × Yct ]
i
∆Et = ∆Eint,t + ∆Estr ,t + ∆Eact,t
where int =intensity; str =structure; act =activity
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Decomposition and counterfactual scenarios
Counterfactual Scenario (S) Formula for computing emissions
No Intensity Change (NIC )
EtNIC = E0 +
Pt
+ ∆Eact,s ]
No Structure Change (NSC )
EtNSC = E0 +
Pt
+ ∆Eact,s ]
No Activity Change (NAC )
EtNAC = E0 +
Pt
+ ∆Estr ,s ]
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s=1 [∆Estr ,s
s=1 [∆Eint,s
s=1 [∆Eint,s
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Decomposition and counterfactual scenarios
Counterfactual Scenario (S) Formula for computing emissions
No Intensity Change (NIC )
EtNIC = E0 +
Pt
+ ∆Eact,s ]
No Structure Change (NSC )
EtNSC = E0 +
Pt
+ ∆Eact,s ]
No Activity Change (NAC )
EtNAC = E0 +
Pt
+ ∆Estr ,s ]
s=1 [∆Estr ,s
s=1 [∆Eint,s
s=1 [∆Eint,s
Relative cumulative emissions of S :
P S
E
rce = Pt t − 1
t Et
S
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Decomposition and counterfactual scenarios
Country rceNIC
rceNSC
rceNAC
c
c
c
USA
CHN
RUS
0.054
0.338
-0.033
0.148
-0.101
0.203
-0.258
-0.534
-0.168
AVGfull
AVGadv
AVGdev
0.095
0.062
0.125
0.072
0.061
0.083
-0.246
-0.214
-0.277
Fact 1: Intensity and structure channels both constrained emissions in
most countries. In contrast, the activity channel increased emissions for all
countries in the sample.
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Identifying HCI & LCI sectors
Denition of HCI & LCI sectors
Order sectors in decreasing order of cicit in each country and year, so
the sector with the highest carbon intensity is ranked rst, the sector
with second highest is ranked second etc.
Calculate the average rank of each sector over all years and order
sectors in increasing order of average rank for each country.
Dene the set containing the top (bottom) ve sectors as the HCIc
(LCIc ) set.
1
2
3
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HCI & LCI sectors in select countries
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Heterogeneity in HCI & LCI sectors
Fact 2: There is substantial cross-country variation in the average carbon
intensity of HCI and LCI sets, and of individual HCI and LCI sectors.
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Intensity and key economic characteristics
Fact 3: HCI
sectors in advanced and developing countries tend to (i) account for
a smaller share of employment; (ii) be more capital intensive; and (iii) employ a
workforce with a lower average skill level.
USA example:
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Tab 6
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Tab 7
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Evolution of HCI & LCI sectors (1995-2009)
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Evolution of HCI & LCI sectors (1995-2009)
Fact 4: Labour supply declined in HCI sectors and increased in LCI
sectors with its composition shifting towards high-skilled workers in both.
Capital intensity growth was faster in HCI sectors but their multifactor
productivity growth was lower.
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Evolution of HCI & LCI sectors (1995-2009)
Fact 4: Labour supply declined in HCI sectors and increased in LCI
sectors with its composition shifting towards high-skilled workers in both.
Capital intensity growth was faster in HCI sectors but their multifactor
productivity growth was lower.
Fact 5: In developing countries the average growth rates of factor inputs
and productivity indicators were greater than or equal to those in advanced
countries. Moreover, the hours supplied by low-skilled workers in LCI
sectors did not decline in developing countries.
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What is all this good for?
•
Change in the composition of output can be as important as changes
in technology
→ Industrial and climate change policies interact
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What is all this good for?
•
•
Change in the composition of output can be as important as changes
in technology
→ Industrial and climate change policies interact
Target structure? Ban on new fossil-based plants without CCS
Target intensity? Subsidies to R&D and deployment of CCS
Target activity? "Prosperity without growth"
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What is all this good for?
•
•
Change in the composition of output can be as important as changes
in technology
→ Industrial and climate change policies interact
Target structure? Ban on new fossil-based plants without CCS
Target intensity? Subsidies to R&D and deployment of CCS
•
Target activity? "Prosperity without growth"
For most countries and sectors data precede the introduction of
stringent climate change policies. The paper establishes pre-policy
sector characteristics and trends.
→ Useful in formulating policies and evaluating their performance
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Thank you!
Comments, suggestions and questions most welcome
.
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