Transcript Exploring mechanisms for treaty formation in an energy

Exploring mechanisms for treaty
formation in an energy-climate
economy model
Markus Brede1, Bert de Vries2, Nicky Grigg1
and John Finnigan1
1CSIRO
2
Centre for Complex Systems Science, CMAR
The Netherlands Environmental Assessment Agency
(PBL) and Utrecht University (UCAD)
Outline

Introduction

A simple energy-economy-climate model

Competition for CPRs


Static and renegotiated (dynamic) Climate
Agreements
Conclusions
Why does it matter?

Integrated Assessment Models

Difficult to include human decision making explicitly
but some insights can be gained from Game Theory
(What can rough assumptions about the degree of competitiveness in world
management tell us about scenario outcomes?)

Often: optimization of “world utilities” which are
globally optimal but involve potential sacrifices by
some actors; such a fully cooperative world is
unrealistic

Issues of rather arbitrary lumping of economic
regions; numbers of actors, etc.

We want to link assumptions about competition in
world management and scenarios about resource
Economy-Energy-Climate Model
(GDP Y)
( T)
Economy
Climate
damages
emissions
investments
investments
energy supply
Consumption
red = common pool resources
Energy
(fossil fuel/renewables)
atmosphere
damages
Managing the economy as an
optimal control problem
Production
Economic
Growth
Energy
Energy
(carbon-based)
(carbon-free)
Consumptio
n
Optimize investment allocations to maximize
consumption (discounted utility)!
Competition for the Atmosphere


Countries make decisions about investment
allocations (considering actions of other
countries as constraints)
Iteration of mutual decision making (“if you do
this ... then I'll do that!”) till convergence is
reached
Competitive management of the
atmosphere
N Identical countries
 Developed economies

low damages
large damages
N<Nc energy transition
N>Nc no energy transition
Competitive management of the
atmosphere: Energy systems
Climate Agreements




Agreement = emissions cap C for the world and
allocation rule for emissions caps for countries
Emission allocations Ci proportional to
weights Wi= Pi+(1-) Yi (Pi Population, Yi
GDP)
Static agreement: fix allocations Ci at one
instant t0 in time
Dynamic (renegotiated agreement): assign
quotas according to present and future
developments
(“every unborn citizen receives a
carbon quota”)
Static vs Dynamic Agreements (1)

Static agreement


Country maximizes its growth path
subject to a fixed carbon quota
Dynamic agreement

Country maximizes its growth path
subject to a carbon quota

Growth path influences the carbon quota
a country receives
Static vs Dynamic Agreements (2)
quotas reached in dynamic agreements
ratio of sizes of the economies reached when
agreements are dynamic and static
(Emissions caps C are relative to the maximum emissions of the world without climate agree
ments)
(Illustrative experiment: 3 developed countries (D) and 3 developing countries (U) in a world
with low climate damages and a purely population-based sharing rule, i.e. =1)
Static vs Dynamic Agreements (3)


Static agreements: countries strive to optimize
their growth path to maximize utility subject to
fixed carbon allocations
Dynamic agreements: countries strive to
optimize growth paths and agreements to
maximize utilities

competition for quotas

leads to larger economies, faster phasing out of
fossil fuels, less early and more late consumption
Conclusions



Caveat: This is an idealised “economic world”:
agents are omniscient optimizers with perfect
knowledge
Simple EEC models highlight that including
competition effects into IAMs matters
Comparison shows difference between static
and renegotiated agreements:

Competition for carbon quotas can significantly
alter optimal growth trajectories!