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CIES 2013
Prices versus Quantities versus Shares
CIES 2013
Elisabetta Cornago, Renaud Foucart, Antonio Estache
Université Libre de Bruxelles
October 29, 2013
CIES 2013
Introduction
A piece of EU policy
The Renewable Energy Directive 2009/28/EC [...]established a European framework for the promotion ofrenewable energy, setting mandatory national renewableenergy targets for achieving a 20% share of renewable
energy in the �nal energy consumption [...] by 2020.These goals are headline targets of the European 2020
strategy for growth, since they contribute to Europe'sindustrial innovation and technological leadership as wellas reducing emissions, improving the security of ourenergy supply and reducing our energy importdependence. [European Commission, 2013, p.2]
CIES 2013
Introduction
�Prices vs. Quantities�, M. Weitzman, 1974
One of current interest is the question of whether itwould be better to control certain forms of pollution
by setting emission standards or by charging theappropriate pollution taxes.
When quantities are employed as planninginstruments, the basic operating rules from the centretake the form of quotas, targets or commands to producea certain level of output. With prices as instruments, therules specify either explicitly or implicitly that pro�ts areto be maximized at the given parametric prices.
CIES 2013
Introduction
Q-based instruments: shares vs. levels
Assumption: uncertainty on the production costs of RES-E, i.e.electricity produced from renewable energy sources.
sshare ofRES-E
;qr
level ofRES-E
;ψ(qf )level ofpollution
CIES 2013
Introduction
A bit of intuition
Imagine the policy-maker underestimates production costs ofrenewable-based electricity:
I with a Q-based mandatory share...
I with a P-based feed-in tari�...
CIES 2013
Introduction
The paper in one slide
I Framework: partial equilibrium model of the perfectly competitiveretail electricity market,
I Policy tools: two alternative incentive schemes for RES-E:
1. price-based feed-in tari�s,2. quantity-based mandatory share.
I Assumption: uncertainty on the production costs ofrenewable-based electricity.
I Conclusion: an identical estimation error leads to opposite e�ectsdepending on the policy tool used in terms of:
1. equilibrium P and Q of electricity,2. equilibrium level of pollution,3. cost of subsidizing green electricity producers.
CIES 2013
Introduction
Literature
I Weitzman [1974]: prices versus quantities.
I Analysis of RES-E incentive schemesMenanteau et al. [2003]
I Instrument choice in climate change policyMontero [2002], Rohling and Ohndorf [2012], Pizer [1999, 2002], Hoel and Karp
[2001, 2002]
→ what about prices versus quantities versus shares, when costsare uncertain?
CIES 2013
The model
The model: roadmap
I Setting: retail electricity market.
I Setup of the model:I supply side ,I demand side ,I government objectives and tools .
I Scenarios.
CIES 2013
The model
Setup
Notation
I x∗ = optimal level of x (in perfect information)
I x = expected equilibrium level of x (in imperfect information)
I x = realized equilibrium level of x.
CIES 2013
The model
Setup
Supply side: Technologies
I Electricity can be produced through fossil and renewableenergy:
Q = qf + qr
I Production costs of renewable-based electricity qr are assumedto be
a) subject to uncertainty.b) structurally higher than those of qf .
I Why such assumptions?
CIES 2013
The model
Setup
Green vs conventional electricity: stylized facts
Figure: Levelized cost of electricity. Fraunhofer ISE, 2012.
CIES 2013
The model
Setup
Demand side
I qr and qf are perfect substitutes to consumers.
I Aggregate demand:Q = K − γP
CIES 2013
The model
Setup
Government objectives
The government aims at keeping pollution below the critical levelat the lowest possible cost:
ψ ≤ ψ∗(q∗f )
His two alternative policy handles are:
I feed-in tari� h,
I mandatory share of RES-E s.
CIES 2013
The model
Setup
The model: roadmap
Scenarios: instrument choice when production costs ofrenewable-based electricity are...
1. certain: P and Q yield same outcomes. 4 ,
2. uncertain: P vs. Q vs. shares.
CIES 2013
The model
Setup
Timeline of the problem
t = 1 : uncertain production cost of renewable-based electricityc 6= c
I government chooses FIT vs. mandatory share ,I MCr = 1+ cqr .
t = 2 : production cost of renewable-based electricity c is observedI electricity producers take their production decision.
CIES 2013
The model
Equilibrium in uncertainty: Q-based vs. P-based policy tools
Q-based instruments: a mandatory share
I Government �xes a mandatory share of RES-E s given c ,expected production cost of renewable-based electricity :s = s(c, q∗f )
I expected fossil-based electricity production: qf .I expected pollution is ψ(qf ).
CIES 2013
The model
Equilibrium in uncertainty: Q-based vs. P-based policy tools
Retail electricity market: a mandatory share s
The case of cost underestimation c > c
Q
P
D
P = 1+ cs2Q
Q
P
(1− s)Q
P = 1+ cs2Q
Q
P
(1− s)Q
ψ(qf )<ψ(qf )
CIES 2013
The model
Equilibrium in uncertainty: Q-based vs. P-based policy tools
P-based instruments: a feed-in tari�
I Government yields to producers a per-unit subsidy h per eachunit of qr produced:
h = c qr
⇔ h = c
(K − γ
1+ γc s2− q∗f
)I The producer picks qr according to the rule
MCf = MCr − h
⇔ qr =c
cqr
I The subsidy is �nanced through a per-unit tax on electricityconsumption: P = 1+ s · h.
CIES 2013
The model
Equilibrium in uncertainty: Q-based vs. P-based policy tools
Retail electricity market: a FIT h
The case of cost underestimation c > c
Q
P
D
P
1
tax = s · h
(1− s)Q
S
Q = Q
P = P
1
(1− s)Q
ψ(qf )>ψ(qf )
CIES 2013
Conclusions
The risks of underestimating the cost of renewables
Benchmark: perfect information setting
Criteria Q-based
mandatory
share s
P-based
feed-in tari�
h
Share of RES-E attained higher lower
Retail market price higher lower
Pollution lower higher
Cost of transfers to �rms n.a. lower
CIES 2013
Conclusions
To wrap up...
If the regulator tends to underestimate production costs ofrenewable-based electricity...
I Quantity-based tool: lower pollution; higher market price.
I Price-based tool: higher pollution; lower market price;taxation distortion to �nance FITs.
If the regulator tends to overestimate production costs ofrenewable-based electricity, results are exactly symmetric.
CIES 2013
Conclusions
Conclusions
I A �scally-constrained, risk-averse government could tend topick more cautious incentive schemes for RES-E and end upwith a relatively more polluting electricity sector.
I Potential of hybrid instruments.
