Transcript carbon price only - Centre International de Recherche

Domestic and international drivers
of urban dynamics
Urbanization and low-carbon growth pathways
Modeling the interactions
between energy and real estate prices
Henri WAISMAN
([email protected])
International Research Network for Low‐Carbon Societies
Third Researchers Meeting - Paris, 13/14 October 2011
1
20 years of a surprising absence
in energy-economy modeling
 What was “obvious” in the early nineties
 Large competitive advantage of oil-based motor and fuels over substitutes
(biofuels, electricity, hydrogen)
 Apparent low price elasticity of mobility and energy demand for transportation
 Mobility and transportation are driven by other “signals” than energy prices
 What should have been done
A strong collaboration between energy, transportation and urban economists
(Hourcade ,1993)
 What happened :
A methodological lock-in due to three converging intellectual dynamics:
 The ‘Elephant and rabbit stew metaphor’ legitimates to treat the energy sector
independently from the rest of the economy (Hogan & Manne 1977)
 The TD/BU controversy about the energy efficiency gap focused the debate on
technological efficiency
 Extrapolating electricity optimization models to the entire energy system
 The overwhelming majority of energy-economy models adopt carbon price as the
only driver of decarbonizing economies.
The Impasse of the « carbon price only » frameworks
 A carbon price at 50$/tCO2
 doubles the cost of cement in India and hurts segments of the steel industry in the EU
 …but hardly affects mobility demand (low price-elasticity)
 Consequences for cost assessment of climate policies
o Underestimated : an often ignored caveat of energy-economy modeling
« Most models use a global least cost approach to mitigation portfolios with universal
emissions trading, assuming transparent markets, no transaction cost, and thus perfect
implementation of mitigation measures throughout the 21st century. » (IPCC, AR4, WGIII )
o Overestimated : in absence of complementary policies in the transport sector
• very high carbon prices are needed to curve down transport emissions
(low elasticity of mobility demand to energy prices)
• other determinants : non-energy prices and non price signals
(real estate prices, risk-adjusted capital cost, infrastructure policies)
 Economic rationale behind the difficulties in making a deal around policy
architectures built around a “pure” pricing of carbon
Intertwined methodological issues to be solved
 Modeling second- best economies with
 Imperfect foresight
 Inertia of capital stocks
 Market imperfections (underutilization of production factors)
 Representing structural change driving the decoupling between growth and energy
 Beyond pure energy efficiency, the fundamentals of the material content of the
economy C-T-L (Hourcade 1993):
 Consumption styles (preferences)
 Technical potentials (resource and technology availability, asymptotes)
 Location patterns
 Capturing the interplay between energy prices, land prices and the growth engine
(productivity, demography, savings) in an opened economy
 Endogenizing the urbanization process and location decisions in urban/rural areas
IMACLIM, a tool to investigate the interplay between
Systems of Cities in Interaction and growth patterns
Transport
Transport
Economic signals
(prices, quantities,
Investments)
Static Equilibrium (t+1)
(reduced forms of BU models)
Oil
under constraints
Dynamic sub-modules
Industry
Agricolture
...
Systems
UrbanElectricity
Energy
Static Equilibrium (t)
under updated constraints
Technical and structural
parameters
(i-o coefficients, population,
productivity)
 Long term growth drivers vs. transitory disequilibrium
 Demography + Labor productivity growth
 Imperfect markets & Partial use of production factors (unemployment, idle capacities)
 Investments under imperfect foresight
 Trade and capital flows under exogenous assumption about debts
 A dialogue between engineering-based and economic analyses
 Hybrid matrixes in values, energy and « physical » content (Mtoe, pkm)
 Explicit accounting of inertias on equipements, technical asymptotes and basic needs
IMACLIM, a tool to investigate the interplay between
Systems of Cities in Interaction and growth patterns
3.
Capture the feedbacks on growth patterns
Aggregate
Economic
variables:
Price, Wage,
Profit,
Production
Spatial disaggregation
into a system of cities in interaction
2
3
Migration of firms
and population
Re-aggregation
of technical coefficients
Static Equilibrium t+1
Static Equilibrium t
1
Oil
Represent the spatial dynamics among a number of urban agglomerations
Transport
Transport
2.
Systems
UrbanElectricity
Energy
Disaggregate the national economy into a System of Cities in Interaction
Industry
Agricolture
...
1.
Transport basic needs, productivity,
investment costs
The system of cities in interaction

Spatial structure of cities
 Monocentric and axisymmetrical
 Firms clustered into the adimensionnal centre
 Spatial distribution of households
 tradeoff on housing/commuting costs
Households/ Workers
Firms
x
0
Calibration in 2001: 74 OECD agglomerations
« Empirical data » : Population, Density, Production, Wage

Multi-level interactions
 Inter-city trade (iceberg structure)
 Monopolistic competition & imperfect substitution among varieties
 Agglomeration effect on production
 Spatial dynamics
 Differentiated attractiveness of cities (investment profitability)
 Migration of investments towards the most attractive cities
 Migration of firms and associated labor force
dj
A consistent view of macreconomic and urban dynamics
Unitary urban commuting cost
(index 1=2010)
World oil price
(index 1= 2010)
5
2
1,8
4
1,6
3
1,4
2
1,2
1
1
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2010
2020
2030
Average urban density
(index 1= 2010)
2040
2050
2060
2070
2080
2090
2100
2070
2080
2090
2100
Urban land price
(index 1=2010)
1,2
2
1,8
1
1,6
1,4
0,8
1,2
0,6
2010
1
2020
2030
2040
2050
2060
2070
2080
2090
2100
2010
2020
2030
2040
2050
2060
Climate policy (450ppm-CO2) and urban dynamics
Relative variation of unitary commuting cost
under climate policy (index 1= baseline)
Carbon price
($/tC02 )
1000
1,6
800
1,5
1,4
600
1,3
400
1,2
200
1,1
0
2010
1
2020
2030
2040
2050
2060
2070
2080
2090
2100
2010
2020
Relative variation of urban density
under climate policy (index 1= baseline)
2030
2040
2050
2060
2070
2080
2090
2100
2090
2100
Relative variation of urban land price
under climate policy (index 1= baseline)
1,3
1,5
1,4
1,2
1,3
1,1
1,2
1,1
1
1
0,9
2010
0,9
2020
2030
2040
2050
2060
2070
2080
2090
2100
2010
2020
2030
2040
2050
2060
2070
2080
Urban policy and CO2 emissions
Spatial policy at the city level to limit urban sprawl and constrained mobility
= 0.1% of OECD GDP
Kaya decomposition of CO2 emissions
from automobile
Variation of CO2 emissions from transport
under urban policy (GtCO2)
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
0,05
2%
0
0%
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
-0,05
-2%
-4%
-6%
-0,1
-8%
-10%
-0,15
-12%
-14%
-0,2
mobility demand
Automobile
Public transport
unitary energy consumption
Air transport
TOTAL transport
carbon content of fuels
Urban densification policy and costs of climate policies
discount rate = 7%
carbon price
carbon price &
only
urban policy
Carbon price
($/tCO2)
Oil price
($/Barrel)
Land price
(index 1
=baseline)
Total surplus
variations
(Billion $)
discount rate = 1%
carbon price
carbon price &
only
urban policy
56.2
55.8
225.0
219.8
69.4
69.2
61.2
60.0
1.31
1.37
1.70
1.93
-4.30
-4.27
-4.08
-3.46
Conclusion
IMACLIM, a methodological tool for consistency checks between expertises
 material content of economic growth
 transport, infrastructure policies and mitigation
 endogenizing urban systems in a global energy-economy model
Quantification of the impact of urban policies on carbon and real estate prices
 important complement to carbon pricing for ambitious mitigation objectives
 not only for carbon mitigation : political implementation, social dimensions
(welfare effects, distributional issues)
On-going research:
 real estate markets and scarcity rents
 interplay between transport infrastructure, modal choice and the dynamics of
real estate at the local level
linkages between labor productivity and agglomeration effects