Nic Rivers Presentation - The Porter Hypothesis at 20: Can Environmental Regulation Enhance Innovation and Competitiveness? June 2010
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The document discusses the use of computable general equilibrium (CGE) models to analyze the impact of climate change policies on competitiveness and economic leakage. It provides examples of studies using CGE models to estimate the effects of policies like the Waxman-Markey bill in the US and emissions reductions in Canada. Typical findings from these models are that climate policies increase costs for energy-intensive industries, reducing their international competitiveness. The models also show non-energy industries may see reduced costs from lower input prices. However, most CGE models do not fully represent induced innovation from climate policies.
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networks
h i g h l i g h t s
A mathematical–statistical model for designing Pareto optimal CO2 cap-and-trade policies.
The model fills a gap in the current literature that primarily supports cap-and-trade policy evaluation but not policy design.
Pareto optimal policies accommodate conflicting goals of the market constituents.
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Higher demand-price sensitivity increases the influence of penalty and social cost of carbon on reducing carbon emissions.
a r t i c l e i n f o a b s t r a c t
Article history:
Received 15 August 2013
Received in revised form 2 January 2014
Accepted 4 January 2014
Keywords:
Electricity networks
Cap-and-trade
Game theory
MPEC/EPEC
Among the CO2 emission reduction programs, cap-and-trade (C&T) is one of the most used policies. Economic studies have
shown that C&T policies for electricity networks, while reducing emissions, will likely increase price and decrease consumption
of electricity. This paper presents a two layer mathematical– statistical model to develop Pareto optimal designs for CO2 cap-
and-trade policies. The bottom layer finds, for a given C&T policy, equilibrium bidding strategies of the competing generators
while maximizing social welfare via a DC optimal power flow (DC-OPF) model. We refer to this layer as policy evaluation.
The top layer (called policy optimization) involves design of Pareto optimal C&T policies over a planning horizon. The
performance measures that are considered for the purpose of design are social welfare and the corresponding system marginal
price (MP), CO2 emissions, and electricity consumption level.
2014 Elsevier Ltd. All rights reserved.
1. Introduction
A major part of the total CO2 emissions come from the electricity
production sector, e.g., 40% in the U.S. ([1]). In 2009, 70% of the electricity
was produced from fossil fuel such as gas, coal, and petroleum ([2]). In 2005,
the European Union Emissions Trading System (EU ETS) launched a cap-
and-trade system that seeks to reduce the greenhouse gas (GHG) emissions
by 21% by 2020 from the 2005 level. Currently, the EU ETS is the largest
emission market in the world [3], and according to the European Commission
[4], at least 20% of its budget for 2014–2020 will be spent on climate-related
projects and policies. In the United States, as well as in the EU, different
regulations have been discussed to cut CO2 emissions such as carbon tax,
renewable portfolio standards (RPS), and capand-trade programs (C&T). In
the northeastern U.S., the Regional Greenhouse Gas Initiative (RGGI) has
already implemented a C&T program through a nine state collaborative effort,
which seeks to cut the CO2 emissions by 10% by 2018. Recently the
California Air Resources Board .
Policy directions to 2050
This document discusses policy options for transitioning to a low-carbon economy by 2050. It explores sustaining economic growth while transforming energy production and consumption. The presentation builds on previous publications by identifying policy ideas without prescribing specific approaches. It discusses challenges like uncertain development pathways and high/low carbon scenarios. Milestones by 2025 include efficiency gains, commercializing carbon capture and storage, renewable deployment, and vehicle efficiency. National policy frameworks and international cooperation on technology and emissions management can help achieve long-term climate goals.
The Impacts of EnvironmentalRegulations on Competitiveness.docx
The Impacts of Environmental
Regulations on Competitiveness
Antoine Dechezleprêtre* and Misato Sato
†
Introduction
Ever since the first major environmental regulations were enacted in the 1970s, there has been
much debate about their potential impacts on the competitiveness of affected firms. Businesses
and policy makers fear that in a world that is increasingly characterized by the integration of trade
and capital flows, large asymmetries in the stringency of environmental policies could shift
pollution-intensive production capacity toward countries or regions with less stringent regula-
tion, altering the spatial distribution of industrial production and the subsequent international
trade flows. This has caused concern, particularly among countries that are leading the action
against climate change, because their efforts to achieve deep emission reductions could put their
own pollution-intensive producers at a competitive disadvantage in the global economy.
There are two different views in the environmental economics literature on the effects of
asymmetric policies on the performance of companies competing in the same market: the
pollution haven hypothesis and the Porter hypothesis. The pollution haven hypothesis, which
is based on trade theory, predicts that more stringent environmental policies will increase
compliance costs and, over time, shift pollution-intensive production toward low abatement
cost regions, creating pollution havens and causing policy-induced pollution leakage
(e.g., Levinson and Taylor, 2008). This is a particularly troubling problem for global pollutants
such as carbon dioxide, because it means that on top of the economic impacts on domestic
firms, abatement efforts will be offset to some extent by increasing emissions in other regions.
*Grantham Research Institute on Climate Change and the Environment, London School of Economics,
Houghton Street, London WC2A 2AE, United Kingdom. Tel:þ44 (0)207 852 3626; e-mail: [email protected]
lse.ac.uk.
†
Grantham Research Institute on Climate Change and the Environment, London School of Economics,
Houghton Street, London WC2A 2AE, United Kingdom. Tel: þ44 (0)207 107 5412; e-mail: [email protected]
lse.ac.uk.
We would like to thank Milan Brahmbhatt, Raphael Calel, Baran Doda, Damien Dussaux, Carolyn Fischer,
Matthieu Glachant, Colin McCormick, and Dimitri Zenghelis for helpful comments on an earlier version of
this article. We are grateful to three anonymous referees for very constructive comments and suggestions.
Financial support has come from the Global Green Growth Institute, the Grantham Foundation for the
Protection of the Environment, the European Union Seventh Framework Programme (FP7/2007-2013)
under grant agreement no. 308481 (ENTRACTE), and the UK Economic and Social Research Council
through the Centre for Climate Change Economics and Policy.
Review of Environmental Economics and Policy, volume 11, issue 2, Summer 2017, pp. 183–206
doi: 10.109.
The Impacts of EnvironmentalRegulations on Competitiveness.docx
The Impacts of Environmental
Regulations on Competitiveness
Antoine Dechezleprêtre* and Misato Sato
†
Introduction
Ever since the first major environmental regulations were enacted in the 1970s, there has been
much debate about their potential impacts on the competitiveness of affected firms. Businesses
and policy makers fear that in a world that is increasingly characterized by the integration of trade
and capital flows, large asymmetries in the stringency of environmental policies could shift
pollution-intensive production capacity toward countries or regions with less stringent regula-
tion, altering the spatial distribution of industrial production and the subsequent international
trade flows. This has caused concern, particularly among countries that are leading the action
against climate change, because their efforts to achieve deep emission reductions could put their
own pollution-intensive producers at a competitive disadvantage in the global economy.
There are two different views in the environmental economics literature on the effects of
asymmetric policies on the performance of companies competing in the same market: the
pollution haven hypothesis and the Porter hypothesis. The pollution haven hypothesis, which
is based on trade theory, predicts that more stringent environmental policies will increase
compliance costs and, over time, shift pollution-intensive production toward low abatement
cost regions, creating pollution havens and causing policy-induced pollution leakage
(e.g., Levinson and Taylor, 2008). This is a particularly troubling problem for global pollutants
such as carbon dioxide, because it means that on top of the economic impacts on domestic
firms, abatement efforts will be offset to some extent by increasing emissions in other regions.
*Grantham Research Institute on Climate Change and the Environment, London School of Economics,
Houghton Street, London WC2A 2AE, United Kingdom. Tel:þ44 (0)207 852 3626; e-mail: [email protected]
lse.ac.uk.
†
Grantham Research Institute on Climate Change and the Environment, London School of Economics,
Houghton Street, London WC2A 2AE, United Kingdom. Tel: þ44 (0)207 107 5412; e-mail: [email protected]
lse.ac.uk.
We would like to thank Milan Brahmbhatt, Raphael Calel, Baran Doda, Damien Dussaux, Carolyn Fischer,
Matthieu Glachant, Colin McCormick, and Dimitri Zenghelis for helpful comments on an earlier version of
this article. We are grateful to three anonymous referees for very constructive comments and suggestions.
Financial support has come from the Global Green Growth Institute, the Grantham Foundation for the
Protection of the Environment, the European Union Seventh Framework Programme (FP7/2007-2013)
under grant agreement no. 308481 (ENTRACTE), and the UK Economic and Social Research Council
through the Centre for Climate Change Economics and Policy.
Review of Environmental Economics and Policy, volume 11, issue 2, Summer 2017, pp. 183–206
doi: 10.109.
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