IV. RESULTADOS Y DISCUSIÓN
4.8 Ecuación de cointegración
Carbon Damage Ratio With 3% Discounting
R 8 8 Key: Cons 1.03 = Fankl.03 = aiConsUat 1-1997 » (1.03) ^Fankhauser (1.03)1-1997 » Nordl.03 = FankLI.03 = aNordhaus -C onsl.03 ■Nordl .03 RBck1.03 Fankl .03 FankLI .03 FankH1.03 a (1.03) ,-1997 ; Peckl.03 = JW) ;FankH1.03 =
aPeck & Teitberg (1.03) Fankhauser (Low) , i-1997 > a (1.03)' Fankhauser Çtâek) (1.03)i-1997 a,
Finally, we multiply by the amount of carbon emission reduction / carbon
sequestration achieved in each year/C^ to arrive at J ] ” C . a (1-Fry-
Carbon emission reduction achieved per year is thus adjusted by the carbon damage ratio applied to that year and the level of discounting applied from that year back to 1997. Notice that discounting was involved in creating the carbon damage costs from which the carbon damage ratios were derived.
The three damage cost studies examined here (Fankhauser, Peck and Teisberg and Nordhaus) all discount from the time at which global warming damage occurs back to the when the carbon was emitted. We introduce a second stage of discounting by discounting these damages from the date of emission back to today.^
Peck and Teisberg and Nordhaus used 3% discount rates. A 3% discount rate is used to discount their damage cost ratios back to 1997. Fankhauser used a randomly varying discount rate that would be complex to reproduce here (and may bring no really different result), so one is forced to use a different discount rate to the one used by Fankhauser.
If one believed a discount rate different to 3% should be used, one would not only have to use this from the date of the emission back to today, but one should really introduce this higher discount rate into the Fankhauser, Peck and Teisberg or Nordhaus studies. (These matters are discussed further in the sensitivity analysis section). Alternatively one could discount back to 1997 with a different discount rate to the one used in the damage cost study.
i
Diagrams 3.1 and 3.2 tell us a great deal. Diagram 3.1 shows us the relative value of carbon emission reduction per year, measured at the time of emission reduction. We see in diagram 3.1 that if we do not discount from the date o f emission reduction back to today, carbon damage rises over time. In the Fankhauser model, this rising damage phenomenon is due to the feet that, as time passes, the greater number o f people living on the earth and their increased wealth means the value of emission reduction is valued more highly.
^ Fankhauser’s cost of $27.8/tC for 2025 means that the damage to be caused by a tC emitted in 2025 has a value of $ 27.8/tC in that year. To produce the 1997 value of the $27.8/tC figure we discount fi-om 2025 back to 1997.
In diagram 3.2 there is discounting at 3% from the date of the emission reduction back to today. Diagram 3.2 shows us that if we discount at a 3% rate from the date of emission reduction back to today, there is a felling value of damage as the unit of emission reduction is achieved further into the future. In this scenario, the feet that we prefer benefits sooner outweighs the rising damage phenomena found in the preceding diagram.
The different damage studies tell us different stories about how emission reduction achieved in the future should be valued against emission reduction achieved today. Whether a 0% or a 3% discount rate is used, the Nordhaus study gives more relative weight to emission reduction achieved in the future compared to the present than any of the other studies.
The ‘constant carbon damage ratio’ profile is defined as follows: when there is a 0% discount rate between the date of emission reduction and today, this profile gives emission reduction in any year has the same value (in a manner similar to Nordhaus’ constant $7.3/tC result 1991b,c). We see in both diagrams that the value of emission reduction in the future compared to emission reduction at present is greater in the Fankhauser high discounting case than in the Fankhauser low discounting case.
3.5.4 Equivalent Damage
One of the USIJI projects (Rusagas) does not reduce carbon dioxide emissions but methane emissions. A method o f conq)aring the value of methane emissions with carbon dioxide emissions is needed; this method must also take account of the feet that the relationship between emissions and damage is not linear. One method used to compare methane and carbon dioxide is the Global Warming Potential (GWP) figure. GWPs are a measure of the relative radiative forcing capability o f gases, but this method does not take into account the non linear relationship between emissions and damage. An alternative approach is to use an ‘equivalent damage’ ratio . Global warming potential and equivalent
^ Vinson and Kolchugia (1996) writing about the methane emissions in the Rusagas project, incorrectly use the global warming potential approach instead of equivalent damage.
damage are only the same when the relationship between radiative forcing and damage is linearly related.
Fankhauser produces shadow prices for the marginal damage caused by methane that can be used as damage equivalent figures. These figures are adapted here to give ratios not absolute values; the methane shadow prices are set as ratios to the damage caused by 1 tC emitted between 1991 and 2000. This gives us methane damage ratios of:
Table 3.13: Methane Damage Ratios
1991-2000 5.32
2001-2010 6.35
2011-2020 7.49
2021-2030 8.67
(Source: adapted from Fankhauser 1993)
1991 1992 1991 1994 1995 1996 1997 1998 1999 2000 4.91 5.01 5.11 5.22 5.32 5.42 5.53 5.63 5.73 5.84 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 5.94 6.04 6.14 6.25 6.35 6.46 6.58 6.64 6.81 6.92 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 7.03 7.15 7.26 7.38 7.49 7.61 7.73 7.85 7.97 8.09 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 8.20 8.32 8.44 8.56 8.67 8.80 8.92 9.04 9.16 9.28 3.6 Results
The results, conq)uted using a discount rate of 3% and Fankhauser’s carbon ratio are presented below in table 3.15. The USIJI projects are identified by their project letters set out in appendix 3 B.
The average cost of carbon capture for these twenty projects is $64.9/tC. The average forestry project cost is $18.5/tC (eleven projects), the average fuel switching cost is $136.6/tC (eight projects). Carbon capture in forestry projects ranges in price fi-om $2.8/tC to $81.0/tC (in the Netherlands), fuel switching fiom $35.6/tC to $376.3/tC.
I
Cf;
L 1 % (0 U a i) (5 0 10 T ab le 3.15: R esults Number: Table 3.2 Letter: Appendix 3B Method Country Cqst $/tCFACE 4 Carbon planting Malaysia ê 4.0
FACE 5 Carbon planting Czech Republic < A I J
FACE 6 Carbon planting Ecuador ^
FACE 7 Carbon planting Uganda 4.4 T-'
FACE 8 Carbon planting Netherlands 81.CU.
A Carbon planting Russia 4.6
B Carbon plant & protect Costa Rica 13.4
Rio Bravo C Carbon plant & protect Belize 2.8
D Carbon protecting Costa Rica 3.2 _
E Fuel switching (Wind) Costa Rica 120.5
F Fuel switching (Gas) Czech R 62.0
G Fuel switching (Solar) Honduras 35.6
Biodiversifix H Carbon planting Costa Rica 24.4
I Carbon planting Costa Rica 15.5
J Fuel switching (Wind) Costa Rica 157.7
K Fuel switching (Hydro) Costa Rica 173.1 - -
L Fuel switching (Wind) Costa Rica 120.5
M Fuel switching (Biomass) Honduras 47.3
N Fuel switching (Geothermal) Nicaragua 376.3 .
0 Supply side energy efficiency Russia ^
,^5
^ i/'J c%if\ A(A
The Rusagas supply side energy efficiency project (project O) achieves by far the cheapest carbon equivalent emission reduction at $ 0.07/tC: this is forty times cheaper than the next cheapest option and five hundred times cheaper than the least expensive fuel switching project.
No single fuel switching project achieved a cost of carbon emission reduction less than $35. Not all forestry projects achieved carbon emission reduction less than $20, the benchmark used here as the cost of carbon damage.
Regression analysis was used to explain the variation in the cost of carbon capture. Four independent variables were considered for significance in explaining the variation in cost:
‘wealth’, ‘type’, ‘region’ and ‘organisation’. Wealth is the GNP per capita in 1992 of each host country. Type, region and organisation are dummy variables. By ‘type’, a project is either a fuel switching project or a non fuel switching project; for ‘region’ a project either takes place in Europe or in the rest of the world; and for ‘organisation’ a project is either a FACE project or not. These dummy variables were introduced to test respectively if fuel switching projects, projects in Europe and USIJI projects were more expensive than projects that did not fall within these categories.
^ ;
When one observation, projectj^Uwas omitted from the sample, the dummy variables ‘type’ and the variable ‘wealth’ proved statistically significant in a linear regression of the
c,
=
Pi+PsT.+PsW.+e.
(6)
where Pi is a constant, the T, the ‘type’ dummy variable, where T, = 1 if fuel switching project
0 if not a fuel switching project W, the ‘wealth’ variable and e, the error term, with the resul
1
C, = 2.82 + 92.7 T. + 0.00418
\
This result is obtained with an r squared of 0.67, an adjusted r squared of 0.63 and t statistics for the ‘type’ and ‘wealth’ variables of 5.6 and 2.2. This equation tells us that switching from a non fuel switching project to a fuel switching project involves an increase in cost of carbon emission reduction of $92.7/tC. In addition, the cost of carbon emission reduction is found to increase by $4.18/tC for every increase of $1000 in the GNP per capita of the host nation.
The ‘type’ variable is picking up the fact that emission reduction by fuel switching is m o re / expensive than emission reduction by carbon sequestration and demand side e n e ^ efiBciency. The ‘wealth’ variable presents evidence that emission reduction is more
L i s t w i s e D e l e t i o n o f M i s s i n g D a t a