Climate Policy’s
Policy s Uncertain Outcomes:
The Role of Complex Allocation Schemes
in Cap
Cap-and-Trade
and Trade
Josh Blonz, Dallas Burtraw, and Margaret Walls
Resources for the Future
January 15, 2010
Energy Policy Symposium:
Distributional Aspects
p
of Energy
gy and Climate Policy
y
Outline
• Extant literature on allocation of CO2 value
– Grandfathering, reducing preexisting taxes (e.g., income,
payroll),
p
y ), “cap-and-dividend”,
p
, EITC
•
•
•
•
Simple vs. complex allocation schemes
H.R. 2454 (Waxman-Markey) – a complex scheme
Our data and methodology
Optimistic and pessimistic characterizations of the bill
in our model; the dividend alternative
– Two drivers:
1) LDCs and consumer behavior; 2) “policy investments”
• Results
– Average consumer surplus loss
– Distribution across income quintiles
– The political economy: What might voters care about?
Findings from the Literature on Allocation
• Simple schemes: grandfathering, reductions in
preexisting taxes, lump-sum dividends, etc.
– Distributional
Di t ib ti
l iimpacts
t
• Dinan and Rogers 2002; Parry 2004; Burtraw, Sweeney, and
Walls 2009; Metcalf 2009; Hassett, Mathur, and Metcalf
2009; Rausch et al. 2009; Boyce and Riddle 2009 and others
– Efficiency
• Goulder et al. 1999; Parry 2003; Golder et al. 2009 and
others
• Complex schemes
– H.R. 2454 has 22 separate provisions
• Potential efficiency effects: allocation to electricity LDCs
LDCs, to
energy efficiency programs, to clean technology programs
• Distributional impacts on households: uncertain
• Analyses: CBO, EPA, EIA
• Only CBO looks at distributional impacts
H.R. 2454 Allocation of Allowances in 2016
Household Energy
Consumption
Low Income Consumers
Industry
Adaptation & Adjustment
International
Energy Efficiency,
Technology Development,
Development
Renewables
TOTAL
Description
Electricity LDCs
Percent
30 00
30.00
Natural gas LDCs; home heating oil
10.50
Energy refunds for low-income
consumers
Merchant coal; Trade-vulnerable, energyintensive industries; refineries
Various funds
International adaptation; clean tech
development; forestry
Various electricity efficiency provisions
Various technology development and
renewable energy provisions
15.00
21.69
2.64
7.00
5.80
8 14
8.14
100.77
Data and Method
•
•
•
•
Partial equilibrium framework
Consumer Expenditure Survey 2004-06
Direct and indirect energy consumption
Electricity sector MAC solved from Haiku;
other MAC data from EIA
• Fixed offsets
• Government’s own costs recovered through
g taxes
• CO2 emissions scaled to match Haiku and EIA
• Allowance price solved for in model for 2016
=> We examine three scenarios in which we vary two types
of assumptions about (1) allocation to LDCs and (2)
policy-created investments in technology and energy
efficiency.
Partial Equilibrium Costs in Cap-and-Trade
Dolllars
Marginal Cost Schedule
Area of Triangle
= Resource Cost
Area of Rectangle
= Allowance Value
Percent of Emissions
0
10
5
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
PA
– With
With allocation to LDCs, electric and natural gas bills allocation to LDCs electric and natural gas bills
will not rise by as much as in a full auction
What if electricity prices do rise? That is….
LDCs reduce fixed charge on monthly bills, to reflect value of allowances, but increase variable charge to reflect higher wholesale power prices
reflect higher wholesale power prices. Feasible? How will customers behave?
Example
bill from
Maryland
(Pepco)
2
Pessimistic - Reduce variable prices ($26.90)
Optimistic - Reduce fixed charges
Op
g ($
($22.72))
Cap-and-Dividend ($20.91)
$300
$250
$200
$150
$100
$50
$0
2) Estimates on Policy Investments
Energy Efficiency, Energy R&D, Technology Development, Renewables
Program Description
CCS Clean Vehicle Technology
S
Supplemental Renewable Energy
l
t lR
bl E
Investment in EE and RE
Optimistic Section of Abatement Percent
Bill
Outcome
Energy Innovation Hubs
Advanced Energy Research
d
d
h
EE and RE
EE and RE ‐ Small LDCs
1.75
3.00
0 14
0.14
3.25
3.25
0.45
10
1.05
0.05
0.50
Sub Total
Investment Outcomes Held Constant Across Scenarios
Total EE, R&D, RE and Technology Percentage
13.44
4.25
17.69
782(f)
782(I)(1)
782( )
782(u)
782(g)(1)
782(g)(1)
782(h)(1)
782(h)(2)
82(h)(2)
782(g)(3)
782(a)(2)
$50/ton
$75/ton
$34/t
$34/ton
$34/ton
$54/
‐> $54/ton
For the Pessimistic Outcome, the above 13.44 percent of allocations constitutes revenue lost.
Modeling H.R. 2454
LDC Provisions and Energy
Efficiency/Technology Development in 2016
El t i it LDC
Electricity
Various electricity efficiency
provisions
Development of CCS technology
Renewable energy
OPTIMISTIC CASE
All t d th
Allocated
through
h fi
fixed
d
charge on electricity bills
Electricity consumption
reduced at 2.8
2 8 cents/kwh
maps into $54/ton*
Abatement at $50/ton**
Abatement at $34/ton**
PESSIMISTIC CASE
All t d through
Allocated
th
h
variable charge on
electricity bills
Revenue lost
Percent
30 00
30.00
5.30
Revenue lost
Revenue lost
1.75
3.39
Clean vehicle
Cl
hi l technology
h l
Ab
Abatement
at $75/ton
$75/ **
R
Revenue
llost
SUBTOTAL
*
Affects households through both lower electricity bills and lower allowance price.
**
Affects households through lower allowance price.
3.00
3
00
43.44
Modeling H.R. 2454:
Remaining Provisions Held Constant
Percent
Natural gas LDCs, home heating
oil, some energy efficiency, trade
vulnerable industries
L i
Low-income
consumers
Merchant coal, refiners
Adaptation provisions
International provisions
SUB-TOTAL
Captured in MAC curve
25.44
P
Per-capita
it di
dividend
id d tto llow iincome hhouseholds
h ld
Shareholders
Per-capita dividend to all households
Lost revenue overseas
15.00
15
00
7.25
2.64
7 00
7.00
57.33
Results: Household Burden and Allowance Price
Net Avg CS Allowance
Loss per hh
Price
OPTIMISTIC
WAXMAN-MARKEY
$137
$13.20
PESSIMISTIC
WAXMAN-MARKEY
$421
$23.43
75% CAP-ANDDIVIDEND
$228
$17.37
What Drives the Difference Between
Optimistic & Pessimistic Outcomes?
• Allowance price driven by LDC allocations.
• Electricity efficiency provisions have bigger
effect on CS (even though they receive only
5.3% of allowances).
)
– Household electricity cost savings alone ($97/household)
account for 34% of difference in CS loss across scenarios
– Reduction in allowance price that these provisions bring
about adds to this
• This highlights the critical importance of these
provisions but their effectiveness is highly
uncertain.
perspective?
p
To whom is the
• Household p
energy efficiency benefit going to accrue?
CS Loss by Income Quintile
Avg
Conclusion
• Climate change poses an extraordinary coordination
and cost-sharing challenge.
• That
Th t challenge
h ll
iis amplified
lifi d b
by th
the ffundamental
d
t l
uncertainty about climate science.
• Economic response and technological change add
additional uncertainty about costs.
• We find that policy implementation adds further
uncertainty with respect to the effects on households.
• The more complex the policy, likely, the greater will
be the uncertainty.