ESA Roma 2007 CO 2 TAXES AND TRADABLE QUOTAS, EXPERIMENTAL EVIDENCE OF BIASED DECISIONS Carla Susana...
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ESA Roma 2007 CO 2 TAXES AND TRADABLE QUOTAS, EXPERIMENTAL EVIDENCE OF BIASED DECISIONS Carla Susana Assuad Erling Moxnes System Dynamics Group University of Bergen, Norway
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Transcript of ESA Roma 2007 CO 2 TAXES AND TRADABLE QUOTAS, EXPERIMENTAL EVIDENCE OF BIASED DECISIONS Carla Susana...
ESA Roma 2007
CO2 TAXES AND TRADABLE QUOTAS, EXPERIMENTAL EVIDENCE OF BIASED DECISIONS
Carla Susana AssuadErling Moxnes
System Dynamics GroupUniversity of Bergen, Norway
ESA Roma 2007
Problem• Kyoto targets for GHG emissions in 2012
– Domestic reductions?
– Quota trade?
• Democratic decisions –misperceptions?– Domestic: Tax policy – too late?
– Quota trade: Also cost increasing?
ESA Roma 2007
Laboratory Experiment
• Objective: Reach national Kyoto target with
minimal costs
– from 4000 to 3000 Mt/y
• Time horizon: 2000 to 2012• Task
– T1: Set CO2 taxes every year, no trade of quotas– T2: Set CO2 taxes and trade quotas every year
(symmetric 5 player game)
ESA Roma 2007
Underlying model
• Dynamics - Lecocq et al (1998) – Replacements (20 year lifetime, wide distr.)– Retrofits (3 year delay, more costly)
• No economic growth
• No technological improvement
• Punishment: 200 $/ton in 2012
• Cost curve
Info.
v
v
v
v
ESA Roma 2007
Information • Marginal cost curve:
Estimate Marginal Cost Curve of Different Total Emission Reduction by 2012
0
20
40
60
80
100
120
0 100 200 300 400 500 600 700 800 900 1000 1100
Total Emission Reductions in 2012 [Million tones of CO2 equivalents]
Fu
ture
val
ue
of
co
st
ESA Roma 2007
Interface T1
ESA Roma 2007
Interface T2
ESA Roma 2007
Benchmarks
0
20
40
60
80
100
120
140
2000 2002 2004 2006 2008 2010
Optimal price
Optimal tax
Optimal quota price and tax, $/t CO2
ESA Roma 2007
Feedback strategy
• Complex dynamic optimisation problem with lack of precise information
• With a proper mental model including delays, a simple and efficient feedback strategy exists
ESA Roma 2007
Data
• 30 economics students in Norway
• 38 economics students in Colombia– after 1 outlier removed (market with 5 subjects)
• Data are pooled
ESA Roma 2007
T1: Only tax policy
0
20
40
60
80
100
120
140
2000 2002 2004 2006 2008 2010
0.00
0.05
0.10
0.15
0.20
Optimal
Median
p-value
Tax $/t p-value
ESA Roma 2007
T2: Tax with trade option
0
20
40
60
80
100
120
140
2000 2002 2004 2006 2008 2010
0.00
0.05
0.10
0.15
0.20
Median
Optimal
p-value
Tax $/t p-value
ESA Roma 2007
T2: Quota price
0
40
80
120
160
2000 2002 2004 2006 2008 2010
0.00
0.20
0.40
0.60Optimal Median p-value
Quota price $/t p-value
ESA Roma 2007
T2: Price minus tax
0
20
40
60
80
100
120
140
160
2000 2002 2004 2006 2008 2010
0.00
0.05
0.10
0.15
0.20
Optimal price Optimal taxMedian price Median taxp-value
Quota price $/t p-value
ESA Roma 2007
Emissions in 2012
Compared to target of 3000 Mt/y
Treatment Average p-value
T1 3114 0.0001
T2 3118 0.04
ESA Roma 2007
Quotas vs. dom.reductions (2012)
-5000
-2500
0
2500
5000
0 500 1 000 1 500 2 000
Quota Holding
Needed quota
Regression
Quota, Mt/y
Domestic reduction, Mt/y
ESA Roma 2007
Costs
Treatment Total
costs
Costs minus
punishments
Punishments
with perfect
arbitrage
Costs
with
perfect
arbitrage
T1 70825 47013 23813 69871
+59 % +5 % 53 % +56 %
T2 136756 55186 23549 78735
+206 % +24 % 53 % 76 %
Compared to benchmark costs of 44674 M$
ESA Roma 2007
Conclusions
• Excess costs in T1– Misperception of delays– Tax aversion– Field data (quota price minus tax)
• Excess costs in T2– quota trade stimulates tax differences– different taxes motivate quota trade– all trade does not signal efficiency improvement– profit potential for quota sellers– lack of arbitrage
ESA Roma 2007
Thanks
