207
3
Social, Economic, and Ethical
Concepts and Methods
Coordinating Lead Authors:
Charles Kolstad (USA), Kevin Urama (Nigeria / UK / Kenya)
Lead Authors:
John Broome (UK), Annegrete Bruvoll (Norway), Micheline Cariño Olvera (Mexico), Don
Fullerton (USA), Christian Gollier (France), William Michael Hanemann (USA), Rashid Hassan
(Sudan / South Africa), Frank Jotzo (Germany / Australia), Mizan R. Khan (Bangladesh), Lukas Meyer
(Germany / Austria), Luis Mundaca (Chile / Sweden)
Contributing Authors:
Philippe Aghion (USA), Hunt Allcott (USA), Gregor Betz (Germany), Severin Borenstein (USA),
Andrew Brennan (Australia), Simon Caney (UK), Dan Farber (USA), Adam Jaffe (USA / New
Zealand), Gunnar Luderer (Germany), Axel Ockenfels (Germany), David Popp (USA)
Review Editors:
Marlene Attzs (Trinidad and Tobago), Daniel Bouille (Argentina), Snorre Kverndokk (Norway)
Chapter Science Assistants:
Sheena Katai (USA), Katy Maher (USA), Lindsey Sarquilla (USA)
This chapter should be cited as:
Kolstad C., K. Urama, J. Broome, A. Bruvoll, M. Cariño Olvera, D. Fullerton, C. Gollier, W. M. Hanemann, R. Hassan, F. Jotzo,
M. R. Khan, L. Meyer, and L. Mundaca, 2014: Social, Economic and Ethical Concepts and Methods. In: Climate Change
2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovern-
mental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler,
I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)].
Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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3
Chapter 3
Contents
Executive Summary � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 211
3�1 Introduction � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 213
3�2 Ethical and socio-economic concepts and principles � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 214
3�3 Justice, equity and responsibility � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 215
3�3�1 Causal and moral responsibility
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 215
3�3�2 Intergenerational justice and rights of future people
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 216
3�3�3 Intergenerational justice: distributive justice
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 216
3�3�4 Historical responsibility and distributive justice
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 217
3�3�5 Intra-generational justice: compensatory justice and historical responsibility
� � � � � � � � � � � � � � � � � � � � � � � � � � � � 217
3�3�6 Legal concepts of historical responsibility
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 218
3�3�7 Geoengineering, ethics, and justice
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 219
3�4 Values and wellbeing � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 220
3�4�1 Non-human values
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 220
3�4�2 Cultural and social values
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 221
3�4�3 Wellbeing
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 221
3�4�4 Aggregation of wellbeing
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 221
3�4�5 Lifetime wellbeing
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 222
3�4�6 Social welfare functions
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 222
3�4�7 Valuing population
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 223
3�5 Economics, rights, and duties � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 223
3�5�1 Limits of economics in guiding decision making
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 224
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Chapter 3
3�6 Aggregation of costs and benefits � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 225
3�6�1 Aggregating individual wellbeing
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 225
3.6.1.1 Monetary values
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
3�6�2 Aggregating costs and benefits across time
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 228
3�6�3 Co-benefits and adverse side-effects
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 232
3.6.3.1 A general framework for evaluation of co-benefits and adverse side-effects
. . . . . . . . . . . . . . . . . . . . . . . . 232
3.6.3.2 The valuation of co-benefits and adverse side-effects
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
3.6.3.3 The double dividend hypothesis
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
3�7 Assessing methods of policy choice � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 235
3�7�1 Policy objectives and evaluation criteria
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 235
3.7.1.1 Economic objectives
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
3.7.1.2 Distributional objectives
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
3.7.1.3 Environmental objectives
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
3.7.1.4 Institutional and political feasibility
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
3�7�2 Analytical methods for decision support
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 238
3.7.2.1 Quantitative-oriented approaches
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
3.7.2.2 Qualitative approaches
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
3�8 Policy instruments and regulations � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 239
3�8�1 Economic incentives
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 239
3.8.1.1 Emissions taxes and permit trading
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
3.8.1.2 Subsidies
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
3�8�2 Direct regulatory approaches
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 240
3�8�3 Information programmes
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 241
3�8�4 Government provision of public goods and services, and procurement
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 241
3�8�5 Voluntary actions
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 241
3�8�6 Policy interactions and complementarity
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 241
3�8�7 Government failure and policy failure
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 241
3.8.7.1 Rent-seeking
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
3.8.7.2 Policy uncertainty
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
3�9 Metrics of costs and benefits � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 242
3�9�1 The damages from climate change
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 243
3�9�2 Aggregate climate damages
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 245
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3�9�3 The aggregate costs of mitigation � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 247
3�9�4 Social cost of carbon
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 249
3�9�5 The rebound effect
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 249
3�9�6 Greenhouse gas emissions metrics
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 250
3�10 Behavioural economics and culture � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 252
3�10�1 Behavioural economics and the cost of emissions reduction
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 252
3.10.1.1 Consumer undervaluation of energy costs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
3.10.1.2 Firm behaviour
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
3.10.1.3 Non-price interventions to induce behavioural change
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
3.10.1.4 Altruistic reductions of carbon emissions
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
3.10.1.5 Human ability to understand climate change
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
3�10�2 Social and cultural issues
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 254
3.10.2.1 Customs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
3.10.2.2 Indigenous peoples
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
3.10.2.3 Women and climate change
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
3.10.2.4 Social institutions for collective action
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
3�11 Technological change � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 256
3�11�1 Market provision of TC
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 256
3�11�2 Induced innovation
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 256
3�11�3 Learning-by-doing and other structural models of TC
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 257
3�11�4 Endogenous and exogenous TC and growth
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 257
3�11�5 Policy measures for inducing R&D
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 257
3�11�6 Technology transfer (TT)
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 257
3�12 Gaps in knowledge and data � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 258
3�13 Frequently Asked Questions � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 259
References � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 260
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Chapter 3
Executive Summary
This framing chapter describes the strengths and limitations of the
most widely used concepts and methods in economics, ethics, and
other social sciences that are relevant to climate change. It also pro-
vides a reference resource for the other chapters in the Intergovern-
mental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5),
as well as for decision makers.
The significance of the social dimension and the role of ethics and
economics is underscored by Article 2 of the United Nations Frame-
work Convention on Climate Change, which indicates that an ultimate
objective of the Convention is to avoid dangerous anthropogenic inter-
ference with the climate system. Two main issues confronting society
(and the IPCC) are: what constitutes ‘dangerous interference’ with the
climate system and how to deal with that interference. Determining
what is dangerous is not a matter for natural science alone; it also
involves value judgements — a subject matter of the theory of value,
which is treated in several disciplines, including ethics, economics, and
other social sciences.
Ethics involves questions of justice and value. Justice is concerned with
equity and fairness, and, in general, with the rights to which people
are entitled. Value is a matter of worth, benefit, or good. Value can
sometimes be measured quantitatively, for instance, through a social
welfare function or an index of human development.
Economic tools and methods can be used in assessing the positive
and negative values that result from particular decisions, policies, and
measures. They can also be essential in determining the mitigation
and adaptation actions to be undertaken as public policy, as well as
the consequences of different mitigation and adaptation strategies.
Economic tools and methods have strengths and limitations, both of
which are detailed in this chapter.
Economic tools can be useful in designing climate change miti-
gation policies (very high confidence). While the limitations of eco-
nomics and social welfare analysis, including cost-benefit analysis, are
widely documented, economics nevertheless provides useful tools for
assessing the pros and cons of taking, or not taking, action on climate
change mitigation, as well as of adaptation measures, in achieving
competing societal goals. Understanding these pros and cons can help
in making policy decisions on climate change mitigation and can influ-
ence the actions taken by countries, institutions and individuals. [Sec-
tion 3.2]
Mitigation is a public good; climate change is a case of ‘the
tragedy of the commons’ (high confidence). Effective climate change
mitigation will not be achieved if each agent (individual, institution or
country) acts independently in its own selfish interest, suggesting the
need for collective action. Some adaptation actions, on the other hand,
have characteristics of a private good as benefits of actions may accrue
more directly to the individuals, regions, or countries that undertake
them, at least in the short term. Nevertheless, financing such adaptive
activities remains an issue, particularly for poor individuals and coun-
tries. [3.1, 3.2]
Analysis contained in the literature of moral and political phi-
losophy can contribute to resolving ethical questions that are
raised by climate change (medium confidence). These questions
include how much overall climate mitigation is needed to avoid ‘dan-
gerous interference’, how the effort or cost of mitigating climate
change should be shared among countries and between the present
and future, how to account for such factors as historical responsibility
for emissions, and how to choose among alternative policies for miti-
gation and adaptation. Ethical issues of wellbeing, justice, fairness, and
rights are all involved. [3.2, 3.3, 3.4]
Duties to pay for some climate damages can be grounded in
compensatory justice and distributive justice (medium confi-
dence). If compensatory duties to pay for climate damages and adap-
tation costs are not due from agents who have acted blamelessly,
then principles of compensatory justice will apply to only some of
the harmful emissions [3.3.5]. This finding is also reflected in the pre-
dominant global legal practice of attributing liability for harmful emis-
sions [3.3.6]. Duties to pay for climate damages can, however, also be
grounded in distributive justice [3.3.4, 3.3.5].
Distributional weights may be advisable in cost-benefit analysis
(medium confidence). Ethical theories of value commonly imply that
distributional weights should be applied to monetary measures of ben-
efits and harms when they are aggregated to derive ethical conclu-
sions [3.6.1]. Such weighting contrasts with much of the practice of
cost-benefit analysis.
The use of a temporal discount rate has a crucial impact on the
evaluation of mitigation policies and measures� The social dis-
count rate is the minimum rate of expected social return that com-
pensates for the increased intergenerational inequalities and the
potential increased collective risk that an action generates. Even with
disagreement on the level of the discount rate, a consensus favours
using declining risk-free discount rates over longer time horizons (high
confidence). [3.6.2]
An appropriate social risk-free discount rate for consumption
is between one and three times the anticipated growth rate in
real per capita consumption (medium confidence). This judgement
is based on an application of the Ramsey rule using typical values in
the literature of normative parameters in the rule. Ultimately, however,
these are normative choices. [3.6.2]
Co-benefits may complement the direct benefits of mitigation
(medium confidence). While some direct benefits of mitigation are
reductions in adverse climate change impacts, co-benefits can include
a broad range of environmental, economic, and social effects, such as
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Chapter 3
reductions in local air pollution, less acid rain, and increased energy
security. However, whether co-benefits are net positive or negative in
terms of wellbeing (welfare) can be difficult to determine because of
interaction between climate policies and pre-existing non-climate poli-
cies. The same results apply to adverse side-effects. [3.6.3]
Tax distortions change the cost of all abatement policies (high
confidence). A carbon tax or a tradable emissions permit system can
exacerbate tax distortions, or, in some cases, alleviate them; carbon tax
or permit revenue can be used to moderate adverse effects by cutting
other taxes. However, regulations that forgo revenue (e. g., by giving
permits away) implicitly have higher social costs because of the tax
interaction effect. [3.6.3]
Many different analytic methods are available for evaluating
policies� Methods may be quantitative (for example, cost-benefit
analysis, integrated assessment modelling, and multi-criteria analysis)
or qualitative (for example, sociological and participatory approaches).
However, no single-best method can provide a comprehensive analysis
of policies. A mix of methods is often needed to understand the broad
effects, attributes, trade-offs, and complexities of policy choices; more-
over, policies often address multiple objectives. [3.7]
Four main criteria are frequently used in evaluating and choos-
ing a mitigation policy (medium confidence). They are: cost-effec-
tiveness and economic efficiency (excluding environmental benefits,
but including transaction costs); environmental effectiveness (the
extent to which the environmental targets are achieved); distributional
effects (impact on different subgroups within society); and institutional
feasibility, including political feasibility. [3.7.1]
A broad range of policy instruments for climate change miti-
gation is available to policymakers� These include: economic
incentives, direct regulatory approaches, information programmes,
government provision, and voluntary actions. Interactions between
policy instruments can enhance or reduce the effectiveness and cost
of mitigation action. Economic incentives will generally be more
cost-effective than direct regulatory interventions. However, the
performance and suitability of policies depends on numerous con-
ditions, including institutional capacity, the influence of rent-seek-
ing, and predictability or uncertainty about future policy settings.
The enabling environment may differ between countries, including
between low-income and high-income countries. These differences
can have implications for the suitability and performance of policy
instruments. [3.8]
Impacts of extreme events may be more important economi-
cally than impacts of average climate change (high confidence).
Risks associated with the entire probability distribution of outcomes
in terms of climate response [WGI] and climate impacts [WGII] are
relevant to the assessment of mitigation. Impacts from more extreme
climate change may be more important economically (in terms of the
expected value of impacts) than impacts of average climate change,
particularly if the damage from extreme climate change increases more
rapidly than the probability of such change declines. This is important
in economic analysis, where the expected benefit of mitigation may be
traded off against mitigation costs. [3.9.2]
Impacts from climate change are both market and non-market�
Market effects (where market prices and quantities are observed)
include impacts of storm damage on infrastructure, tourism, and
increased energy demand. Non-market effects include many ecological
impacts, as well as changed cultural values, none of which are gen-
erally captured through market prices. The economic measure of the
value of either kind of impact is ‘willingness-to-pay’ to avoid damage,
which can be estimated using methods of revealed preference and
stated preference. [3.9]
Substitutability reduces the size of damages from climate
change (high confidence). The monetary damage from a change in the
climate will be lower if individuals can easily substitute for what is
damaged, compared to cases where such substitution is more difficult.
[3.9]
Damage functions in existing Integrated Assessment Models
(IAMs) are of low reliability (high confidence). The economic assess-
ments of damages from climate change as embodied in the damage
functions used by some existing IAMs (though not in the analysis
embodied in WGIII) are highly stylized with a weak empirical foun-
dation. The empirical literature on monetized impacts is growing but
remains limited and often geographically narrow. This suggests that
such damage functions should be used with caution and that there
may be significant value in undertaking research to improve the preci-
sion of damage estimates. [3.9, 3.12]
Negative private costs of mitigation arise in some cases,
although they are sometimes overstated in the literature
(medium confidence). Sometimes mitigation can lower the private
costs of production and thus raise profits; for individuals, mitigation
can raise wellbeing. Ex-post evidence suggests that such ‘negative cost
opportunities’ do indeed exist but are sometimes overstated in engi-
neering analyses. [3.9]
Exchange rates between GHGs with different atmospheric life-
times are very sensitive to the choice of emission metric� The
choice of an emission metric depends on the potential application and
involves explicit or implicit value judgements; no consensus surrounds
the question of which metric is both conceptually best and practical to
implement (high confidence). In terms of aggregate mitigation costs
alone, the Global Warming Potential (GWP), with a 100-year time hori-
zon, may perform similarly to selected other metrics (such as the time-
dependent Global Temperature Change Potential or the Global Cost
Potential) of reaching a prescribed climate target; however, various
metrics may differ significantly in terms of the implied distribution of
costs across sectors, regions, and over time (limited evidence, medium
agreement). [3.9]
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The behaviour of energy users and producers exhibits a variety
of anomalies (high confidence). Understanding climate change as a
physical phenomenon with links to societal causes and impacts is a
very complex process. To be fully effective, the conceptual frameworks
and methodological tools used in mitigation assessments need to take
into account cognitive limitations and other-regarding preferences that
frame the processes of economic decision making by people and firms.
[3.10]
Perceived fairness can facilitate cooperation among individu-
als (high confidence). Experimental evidence suggests that reciprocal
behaviour and perceptions of fair outcomes and procedures facilitate
voluntary cooperation among individual people in providing public
goods; this finding may have implications for the design of interna-
tional agreements to coordinate climate change mitigation. [3.10]
Social institutions and culture can facilitate mitigation and
adaptation (medium confidence). Social institutions and culture can
shape individual actions on mitigation and adaptation and be comple-
mentary to more conventional methods for inducing mitigation and
adaptation. They can promote trust and reciprocity and contribute to
the evolution of common rules. They also provide structures for acting
collectively to deal with common challenges. [3.10]
Technological change that reduces mitigation costs can be
encouraged by institutions and economic incentives (high con-
fidence). As pollution is not fully priced by the market, private indi-
viduals and firms lack incentives to invest sufficiently in the develop-
ment and use of emissions-reducing technologies in the absence of
appropriate policy interventions. Moreover, imperfect appropriability of
the benefits of innovation further reduces incentives to develop new
technologies. [3.11]
3.1 Introduction
This framing chapter has two primary purposes: to provide a frame-
work for viewing and understanding the human (social) perspective on
climate change, focusing on ethics and economics; and to define and
discuss key concepts used in other chapters. It complements the two
other framing chapters: Chapter 2 on risk and uncertainty and Chapter
4 on sustainability. The audience for this chapter (indeed for this entire
volume) is decision makers at many different levels.
The significance of the social dimension and the role of ethics and eco-
nomics is underscored by Article 2 of the United Nations Framework
Convention on Climate Change (UNFCCC), which indicates that the
ultimate objective of the Convention is to avoid dangerous anthropo-
genic interference with the climate system. Two main issues confront-
ing society are: what constitutes ‘dangerous interference’ with the
climate system and how to deal with that interference (see box 3.1).
Providing information to answer these inter-related questions is a pri-
mary purpose of the IPCC. Although natural science helps us under-
stand how emissions can change the climate, and, in turn, generate
physical impacts on ecosystems, people, and the physical environment,
determining what is dangerous involves judging the level of adverse
consequences, the steps necessary to mitigate these consequences,
and the risk that humanity is willing to tolerate. These are questions
requiring value judgement. Although economics is essential to evaluat-
ing the consequences and trade-offs associating with climate change,
how society interprets and values them is an ethical question.
Our discussion of ethics centres on two main considerations: justice
and value. Justice requires that people and nations should receive
what they are due, or have a right to. For some, an outcome is just
if the process that generated it is just. Others view justice in terms
of the actual outcomes enjoyed by different people and groups and
the values they place on those outcomes. Outcome-based justice can
range from maximizing economic measures of aggregate welfare to
rights-based views of justice, for example, believing that all countries
have a right to clean air. Different views have been expressed about
what is valuable. All values may be anthropocentric or there may be
non-human values. Economic analysis can help to guide policy action,
provided that appropriate, adequate, and transparent ethical assump-
tions are built into the economic methods.
The significance of economics in tackling climate change is widely rec-
ognized. For instance, central to the politics of taking action on climate
change are disagreements over how much mitigation the world should
undertake, and the economic costs of action (the costs of mitigation)
and inaction (the costs of adaptation and residual damage from a
changed climate). Uncertainty remains about (1) the costs of reducing
emissions of greenhouse gases (GHGs), (2) the damage caused by a
change in the climate, and (3) the cost, practicality, and effectiveness
of adaptation measures (and, potentially, geoengineering). Prioritiz-
ing action on climate change over other significant social goals with
more near-term payoffs is particularly difficult in developing countries.
Because social concerns and objectives, such as the preservation of
traditional values, cannot always be easily quantified or monetized,
economic costs and benefits are not the only input into decision mak-
ing about climate change. But even where costs and benefits can be
quantified and monetized, using methods of economic analysis to
steer social action implicitly involves significant ethical assumptions.
This chapter explains the ethical assumptions that must be made for
economic methods, including cost-benefit analysis (CBA), to be valid,
as well as the ethical assumptions that are implicitly being made
where economic analysis is used to inform a policy choice.
The perspective of economics can improve our understanding of the
challenges of acting on mitigation. For an individual or firm, mitigation
involves real costs, while the benefits to themselves of their own miti-
gation efforts are small and intangible. This reduces the incentives for
individuals or countries to unilaterally reduce emissions; free-riding on
the actions of others is a dominant strategy. Mitigating greenhouse
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gas (GHG) emissions is a public good, which inhibits mitigation. This
also partly explains the failure of nations to agree on how to solve the
problem.
In contrast, adaptation tends not to suffer from free-riding. Gains to
climate change from adaptation, such as planting more heat tolerant
crops, are mainly realized by the parties who incur the costs. Associated
externalities tend to be more localized and contemporaneous than for
GHG mitigation. From a public goods perspective, global coordination
may be less important for many forms of adaptation than for mitiga-
tion. For autonomous adaptation in particular, the gains from adapta-
tion accrue to the party incurring the cost. However, public adaptation
requires local or regional coordination. Financial and other constraints
may restrict the pursuit of attractive adaptation opportunities, particu-
larly in developing countries and for poorer individuals.
This chapter addresses two questions: what should be done about
action to mitigate climate change (a normative issue) and how the
world works in the multifaceted context of climate change (a descrip-
tive or positive issue). Typically, ethics deals with normative questions
and economics with descriptive or normative questions. Descriptive
questions are primarily value-neutral, for example, how firms have
reacted to cap-and-trade programmes to limit emissions, or how soci-
eties have dealt with responsibility for actions that were not known to
be harmful when they were taken. Normative questions use economics
and ethics to decide what should be done, for example, determining
the appropriate level of burden sharing among countries for current
and future mitigation. In making decisions about issues with norma-
tive dimensions, it is important to understand the implicit assumptions
involved. Most normative analyses of solutions to the climate problem
implicitly involve contestable ethical assumptions.
This chapter does not attempt to answer ethical questions, but rather
provides policymakers with the tools (concepts, principles, arguments,
and methods) to make decisions. Summarizing the role of economics
and ethics in climate change in a single chapter necessitates several
caveats. While recognizing the importance of certain non-economic
social dimensions of the climate change problem and solutions to it,
space limitations and our mandate necessitated focusing primarily on
ethics and economics. Furthermore, many of the issues raised have
already been addressed in previous IPCC assessments, particularly AR2
(published in 1995). In the past, ethics has received less attention than
economics, although aspects of both subjects are covered in AR2. The
literature reviewed here includes pre-AR4 literature in order to pro-
vide a more comprehensive understanding of the concepts and meth-
ods. We highlight ‘new’ developments in the field since the last IPCC
assessment in 2007.
3.2 Ethical and socio-economic
concepts and principles
When a country emits GHGs, its emissions cause harm around the
globe. The country itself suffers only a part of the harm it causes. It is
therefore rarely in the interests of a single country to reduce its own
emissions, even though a reduction in global emissions could benefit
every country. That is to say, the problem of climate change is a “trag-
edy of the commons” (Hardin, 1968). Effective mitigation of climate
change will not be achieved if each person or country acts indepen-
dently in its own interest.
Consequently, efforts are continuing to reach effective international
agreement on mitigation. They raise an ethical question that is widely
recognized and much debated, namely, ‘burden-sharing’ or ‘effort-
sharing’. How should the burden of mitigating climate change be
divided among countries? It raises difficult issues of justice, fairness,
and rights, all of which lie within the sphere of ethics.
Burden-sharing is only one of the ethical questions that climate change
raises.
1
Another is the question of how much overall mitigation should
1
A survey of the ethics of climate change is Gardiner (2004), pp. 555 – 600.
Box 3�1 | Dangerous interference with the climate system
Article 2 of the United Nations Framework Convention on Climate
Change states that “the ultimate objective of the Convention
[…] is to achieve […] stabilization of greenhouse gas concentra-
tions in the atmosphere at a level that would prevent dangerous
anthropogenic interference with the climate system.” Judging
whether our interference in the climate system is dangerous, i. e.,
risks causing a very bad outcome, involves two tasks: estimat-
ing the physical consequences of our interference and their
likelihood; and assessing their significance for people. The first
falls to science, but, as the Synthesis Report of the IPCC Fourth
Assessment Report (AR4) states, “Determining what constitutes
‘dangerous anthropogenic interference with the climate system’
in relation to Article 2 of the UNFCCC involves value judgements”
(IPCC, 2007, p.42). Value judgements are governed by the theory
of value. In particular, valuing risk is covered by decision theory
and is dealt with in Chapter 2. Central questions of value that
come within the scope of ethics, as well as economic methods for
measuring certain values are examined in this chapter.
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take place. UNFCCC sets the aim of “avoiding dangerous anthropo-
genic interference with the climate system”, and judging what is dan-
gerous is partly a task for ethics (see Box 3.1). Besides justice, fairness,
and rights, a central concern of ethics is value. Judgements of value
underlie the question of what interference with the climate system
would be dangerous.
Indeed, ethical judgements of value underlie almost every decision
that is connected with climate change, including decisions made by
individuals, public and private organizations, governments, and group-
ings of governments. Some of these decisions are deliberately aimed at
mitigating climate change or adapting to it. Many others influence the
progress of climate change or its impacts, so they need to take climate
change into account.
Ethics may be broadly divided into two branches: justice and value.
Justice is concerned with ensuring that people get what is due to them.
If justice requires that a person should not be treated in a particular
way — uprooted from her home by climate change, for example — then
the person has a right not to be treated that way. Justice and rights are
correlative concepts. On the other hand, criteria of value are concerned
with improving the world: making it a better place. Synonyms for
‘value’ in this context are ‘good’, ‘goodness’ and ‘benefit’. Antonyms
are ‘bad’, ‘harm’ and ‘cost’.
To see the difference between justice and value, think of a transfer of
wealth made by a rich country to a poor one. This may be an act of
restitution. For example, it may be intended to compensate the poor
country for harm that has been done to it by the rich country’s emis-
sions of GHG. In this case, the transfer is made on grounds of justice.
The payment is taken to be due to the poor country, and to satisfy a
right that the poor country has to compensation. Alternatively, the rich
country may make the transfer to support the poor country’s mitiga-
tion effort, because this is beneficial to people in the poor country,
the rich country, and elsewhere. The rich country may not believe the
poor country has a right to the support, but makes the payment simply
because it does ‘good’. This transfer is made on grounds of value. What
would be good to do is not necessarily required as a matter of justice.
Justice is concerned with what people are entitled to as a matter of
their rights.
The division between justice and value is contested within moral phi-
losophy, and so is the nature of the interaction between the two.
Some authors treat justice as inviolable (Nozick, 1974): justice sets
limits on what we may do and we may promote value only within
those limits. An opposite view — called ‘teleological’ by Rawls
(1971) — is that the right decision to make is always determined
by the value of the alternatives, so justice has no role. But despite
the complexity of their relationship and the controversies it raises,
the division between justice and value provides a useful basis for
organizing the discussion of ethical concepts and principles. We
have adopted it in this chapter: sections 3.3 and 3.4 cover justice
and value, respectively. One topic appears in both sections because
it bridges the divide: this topic is distributive justice viewed one way
and the value of equality viewed the other. Section 3.3.7 on geoen-
gineering is also in an intermediate position because it raises ethical
issues of both sorts. Section 3.6 explains how some ethical values
can be measured by economic methods of valuation. Section 3.5
describes the scope and limitations of these methods. Later sections
develop the concepts and methods of economics in more detail. Prac-
tical ways to take account of different values in policy-making are
discussed in Section 3.7.1.
3.3 Justice, equity and
responsibility
Justice, fairness, equity, and responsibility are important in interna-
tional climate negotiations, as well as in climate-related political deci-
sion making within countries and for individuals.
In this section we examine distributive justice, which, for the purpose
of this review, is about outcomes, and procedural justice or the way in
which outcomes are brought about. We also discuss compensation for
damage and historic responsibility for harm. In the context of climate
change, considerations of justice, equity, and responsibility concern the
relations between individuals, as well as groups of individuals (e. g.,
countries), both at a single point in time and across time. Accordingly,
we distinguish intra-generational from intergenerational justice. The
literature has no agreement on a correct answer to the question, what
is just? We indicate where opinions differ.
3�3�1 Causal and moral responsibility
From the perspective of countries rather than individuals or groups of
individuals, historic emissions can help determine causal responsibil-
ity for climate change (den Elzen etal., 2005; Lamarque etal., 2010;
Höhne etal., 2011). Many developed countries are expected to suf-
fer relatively modest physical damage and some are even expected to
realize benefits from future climate change (see Tol, 2002a; b). On the
other hand, some developing countries bear less causal responsibil-
ity, but could suffer significant physical damage from climate change
(IPCC, 2007, WG II AR4 SPM). This asymmetry gives rise to the follow-
ing questions of justice and moral responsibility: do considerations of
justice provide guidance in determining the appropriate level of pres-
ent and future global emissions; the distribution of emissions among
those presently living; and the role of historical emissions in distribut-
ing global obligations? The question also arises of who might be con-
sidered morally responsible for achieving justice, and, thus, a bearer of
duties towards others. The question of moral responsibility is also key
to determining whether anyone owes compensation for the damage
caused by emissions.
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3�3�2 Intergenerational justice and rights of
future people
Intergenerational justice encompasses some of the moral duties owed
by present to future people and the rights that future people hold
against present people.
2
A legitimate acknowledgment that future or
past generations have rights relative to present generations is indica-
tive of a broad understanding of justice.
3
While justice considerations
so understood are relevant, they cannot cover all our concerns regard-
ing future and past people, including the continued existence of
humankind and with a high level of wellbeing.
4
What duties do present generations owe future generations given that
current emissions will affect their quality of life? Some justice theo-
rists have offered the following argument to justify a cap on emissions
(Shue, 1993, 1999; Caney, 2006a; Meyer and Roser, 2009; Wolf, 2009).
If future people’s basic rights include the right to survival, health, and
subsistence, these basic rights are likely to be violated when tempera-
tures rise above a certain level. However, currently living people can
slow the rise in temperature by limiting their emissions at a reason-
able cost to themselves. Therefore, living people should reduce their
emissions in order to fulfil their minimal duties of justice to future
generations. Normative theorists dispute the standard of living that
corresponds to people’s basic rights (Page, 2007; Huseby, 2010). Also
in dispute is what level of harm imposed on future people is morally
objectionable. Some argue that currently living people wrongfully
harm future people if they cause them to have a lower level of well-
being than their own (e. g., Barry, 1999); others that currently living
people owe future people a decent level of wellbeing, which might be
lower than their own (Wolf, 2009). This argument raises objections on
grounds of justice since it presupposes that present people can violate
the rights of future people, and that the protection of future people’s
rights is practically relevant for how present people ought to act.
Some theorists claim that future people cannot hold rights against
present people, owing to special features of intergenerational rela-
tions: some claim that future people cannot have rights because they
cannot exercise them today (Steiner, 1983; Wellman, 1995, ch. 4). Oth-
ers point out that interaction between non-contemporaries is impos-
sible (Barry, 1977, pp. 243 – 244, 1989, p.189). However, some justice
theorists argue that neither the ability to, nor the possibility of, mutual
interaction are necessary in attributing rights to people (Barry, 1989;
Buchanan, 2004). They hold that rights are attributed to beings whose
interests are important enough to justify imposing duties on others.
2
In the philosophical literature, “justice between generations” typically refers to
the relations between people whose lifetimes do not overlap (Barry, 1977). In
contrast, “justice between age groups” refers to the relations of people whose
lifetimes do overlap (Laslett and Fishkin, 1992). See also Gardiner (2011),
pp.145 – 48.
3
See Rawls (1971, 1999), Barry (1977), Sikora and Barry (1978), Partridge (1981),
Parfit (1986), Birnbacher (1988), and Heyd (1992).
4
See Baier (1981), De-Shalit (1995), Meyer (2005), and for African philosophi-
cal perspectives see, Behrens (2012). See Section 3.4 on the wellbeing of future
people.
The main source of scepticism about the rights of future people and
the duties we owe them is the so-called ‘non-identity problem’. Actions
we take to reduce our emissions will change people’s way of life and
so affect new people born. They alter the identities of future people.
Consequently, our emissions do not make future people worse off than
they would otherwise have been, since those future people would not
exist if we took action to prevent our emissions. This makes it hard to
claim that our emissions harm future people, or that we owe it to them
as a matter of their rights to reduce our emissions.
5
It is often argued that the non-identity problem can be overcome
(McMahan, 1998; Shiffrin, 1999; Kumar, 2003; Meyer, 2003; Harman,
2004; Reiman, 2007; Shue, 2010). In any case, duties of justice do not
include all the moral concerns we should have for future people. Other
concerns are matters of value rather than justice, and they too can be
understood in such a way that they are not affected by the non-iden-
tity problem. They are considered in Section 3.4.
If present people have a duty to protect future people’s basic rights,
this duty is complicated by uncertainty. Present people’s actions or
omissions do not necessarily violate future people’s rights; they create
a risk of their rights being violated (Bell, 2011). To determine what cur-
rently living people owe future people, one has to weigh such uncer-
tain consequences against other consequences of their actions, includ-
ing the certain or likely violation of the rights of currently living people
(Oberdiek, 2012; Temkin, 2012). This is important in assessing many
long-term policies, including on geoengineering (see Section 3.3.7),
that risk violating the rights of many generations of people (Crutzen,
2006; Schneider, 2008; Victor etal., 2009; Baer, 2010; Ott, 2012).
3�3�3 Intergenerational justice: distributive
justice
Suppose that a global emissions ceiling that is intergenerationally just
has been determined (recognizing that a ceiling is not the only way to
deal with climate change), the question then arises of how the ceil-
ing ought to be divided among states (and, ultimately, their individ-
ual members) (Jamieson, 2001; Singer, 2002; Meyer and Roser, 2006;
Caney, 2006a). Distributing emission permits is a way of arriving at a
globally just division. Among the widely discussed views on distribu-
tive justice are strict egalitarianism (Temkin, 1993), indirect egalitarian
views including prioritarianism (Parfit, 1997), and sufficientarianism
(Frankfurt, 1999). Strict egalitarianism holds that equality has value
in itself. Prioritarianism gives greater weight to a person’s wellbeing
the less well off she is, as described in Section 3.4. Sufficientarianism
recommends that everyone should be able to enjoy a particular level
of wellbeing.
5
For an overview of the issue see Meyer (2010). See also Schwartz (1978), Parfit
(1986), and Heyd (1992). For a different perspective see Perrett (2003).
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For example, two options can help apply prioritarianism to the dis-
tribution of freely allocated and globally tradeable emission permits.
The first is to ignore the distribution of other goods. Then strict egali-
tarianism or prioritarianism will require emission permits to be distrib-
uted equally, since they will have one price and are thus equivalent
to income. The second is to take into account the unequal distribution
of other assets. Since people in the developing world are less well off
than in the developed world, strict egalitarianism or prioritarianism
would require most or all permits to go to the developing world. How-
ever, it is questionable whether it is appropriate to bring the overall
distribution of goods closer to the prioritarian ideal through the dis-
tribution of just one good (Wolff and de-Shalit, 2007; Caney, 2009,
2012).
3�3�4 Historical responsibility and distributive
justice
Historical responsibility for climate change depends on countries’ con-
tributions to the stock of GHGs. The UNFCCC refers to “common but
differentiated responsibilities” among countries of the world.
6
This is
sometimes taken to imply that current and historical causal responsi-
bility for climate change should play a role in determining the obliga-
tions of different countries in reducing emissions and paying for adap-
tation measures globally (Rajamani, 2000; Rive et al., 2006; Friman,
2007).
A number of objections have been raised against the view that his-
torical emissions should play a role (see, e. g., Gosseries, 2004; Caney,
2005; Meyer and Roser, 2006; Posner and Weisbach, 2010). First, as
currently living people had no influence over the actions of their ances-
tors, they cannot be held responsible for them. Second, previously liv-
ing people may be excused from responsibility on the grounds that
they could not be expected to know that their emissions would have
harmful consequences. Thirdly, present individuals with their particu-
lar identities are not worse or better off as a result of the emission-
generating activities of earlier generations because, owing to the non-
identity problem, they would not exist as the individuals they are had
earlier generations not acted as they did.
From the perspective of distributive justice, however, these objections
need not prevent past emissions and their consequences being taken
into account (Meyer and Roser, 2010; Meyer, 2013). If we are only
concerned with the distribution of benefits from emission-generating
activities during an individual’s lifespan, we should include the ben-
efits present people have received from their own emission-generating
activities. Furthermore, present people have benefited since birth or
conception from past people’s emission-producing actions. They are
6
Specifically, Article 3 of the UNFCCC includes the sentence: “The Parties should
protect the climate system for the benefit of present and future generations of
humankind, on the basis of equity and in accordance with their common but dif-
ferentiated responsibilities and respective capabilities.”
therefore better off as a result of past emissions, and any principle of
distributive justice should take that into account. Some suggest that
taking account of the consequences of some past emissions in this
way should not be subject to the objections mentioned in the previous
paragraph (see Shue, 2010). Other concepts associated with historical
responsibility are discussed in Chapter 4.
3�3�5 Intra-generational justice: compensatory
justice and historical responsibility
Do those who suffer disproportionately from the consequences of cli-
mate change have just claims to compensation against the main per-
petrators or beneficiaries of climate change (see, e. g., Neumayer, 2000;
Gosseries, 2004; Caney, 2006b)?
One way of distinguishing compensatory from distributive claims is to
rely on the idea of a just baseline distribution that is determined by
a criterion of distributive justice. Under this approach, compensation
for climate damage and adaptation costs is owed only by people who
have acted wrongfully according to normative theory (Feinberg, 1984;
Coleman, 1992; McKinnon, 2011). Other deviations from the baseline
may warrant redistributive measures to redress undeserved benefits or
harms, but not as compensation. Some deviations, such as those that
result from free choice, may not call for any redistribution at all.
The duty to make compensatory payments (Gosseries, 2004; Caney,
2006b) may fall on those who emit or benefit from wrongful emis-
sions or who belong to a community that produced such emissions.
Accordingly, three principles of compensatory justice have been sug-
gested: the polluter pays principle (PPP), the beneficiary pays princi-
ple (BPP), and the community pays principle (CPP) (Meyer and Roser,
2010; Meyer, 2013). None of the three measures is generally accepted,
though the PPP is more widely accepted than the others. The PPP
requires the emitter to pay compensation if the agent emitted more
than its fair share (determined as outlined in Section 3.3.2) and it
either knew, or could reasonably be expected to know, that its emis-
sions were harmful. The victim should be able to show that the emis-
sions either made the victim worse off than before or pushed below a
specified threshold of harm, or both.
The right to compensatory payments for wrongful emissions under PPP
has at least three basic limitations. Two have already been mentioned
in Section 3.3.4. Emissions that took place while it was permissible
to be ignorant of climate change (when people neither did know nor
could be reasonably be expected to know about the harmful conse-
quences of emissions) may be excused (Gosseries, 2004, pp. 39 – 41).
See also Section 3.3.6. The non-identity problem (see Section 3.3.2)
implies that earlier emissions do not harm many of the people who
come into existence later. Potential duty bearers may be dead and can-
not therefore have a duty to supply compensatory measures. It may
therefore be difficult to use PPP in ascribing compensatory duties and
identifying wronged persons. The first and third limitations restrict the
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Chapter 3
assignment of duties of compensation to currently living people for
their most recent emissions, even though many more people are caus-
ally responsible for the harmful effects of climate change. For future
emissions, the third limitation could be overcome through a climate
change compensation fund into which agents pay levies for imposing
the risk of harm on future people (McKinnon, 2011).
According to BPP, a person who is wrongfully better off relative to a
just baseline is required to compensate those who are worse off. Past
emissions benefit some and impose costs on others. If currently liv-
ing people accept the benefits of wrongful past emissions, it has been
argued that they take on some of the past wrongdoer’s duty of com-
pensation (Gosseries, 2004). Also, we have a duty to condemn injustice,
which may entail a duty not to benefit from an injustice that causes
harm to others (Butt, 2007). However, BPP is open to at least two
objections. First, duties of compensation arise only from past emissions
that have benefited present people; no compensation is owed for other
past emissions. Second, if voluntary acceptance of benefits is a con-
dition of their giving rise to compensatory duties, the bearers of the
duties must be able to forgo the benefits in question at a reasonable
cost.
Under CPP, moral duties can be attributed to people as members of
groups whose identity persists over generations (De-Shalit, 1995;
Thompson, 2009). The principle claims that members of a community,
including a country, can have collective responsibility for the wrongful
actions of other past and present members of the community, even
though they are not morally or causally responsible for those actions
(Thompson, 2001; Miller, 2004; Meyer, 2005). It is a matter of debate
under what conditions present people can be said to have inherited
compensatory duties. Although CPP purports to overcome the problem
that a polluter might be dead, it can justify compensatory measures
only for emissions that are made wrongfully. It does not cover emis-
sions caused by agents who were permissibly ignorant of their harm-
fulness. (The agent in this case may be the community or state).
The practical relevance of principles of compensatory justice is limited.
Insofar as the harms and benefits of climate change are undeserved,
distributive justice will require them to be evened out, independently
of compensatory justice. Duties of distributive justice do not presup-
pose any wrongdoing (see Section 3.3.4). For example, it has been
suggested on grounds of distributive justice that the duty to pay for
adaptation should be allocated on the basis of people’s ability to pay,
which partly reflects the benefit they have received from past emis-
sions (Jamieson, 1997; Shue, 1999; Caney, 2010; Gardiner, 2011).
However, present people and governments can be said to know about
both the seriously harmful consequences of their emission-generating
activities for future people and effective measures to prevent those
consequences. If so and if they can implement these measures at a rea-
sonable cost to themselves to protect future people’s basic rights (see,
e. g., Birnbacher, 2009; Gardiner, 2011), they might be viewed as owing
intergenerational duties of justice to future people (see Section 3.3.2).
3�3�6 Legal concepts of historical
responsibility
Legal systems have struggled to define the boundaries of responsibility
for harmful actions and are only now beginning to do so for climate
change. It remains unclear whether national courts will accept lawsuits
against GHG emitters, and legal scholars vigorously debate whether
liability exists under current law (Mank, 2007; Burns and Osofsky,
2009; Faure and Peeters, 2011; Haritz, 2011; Kosolapova, 2011; Kysar,
2011; Gerrard and Wannier, 2012). This section is concerned with moral
responsibility, which is not the same as legal responsibility. But moral
thinking can draw useful lessons from legal ideas.
Harmful conduct is generally a basis for liability only if it breaches
some legal norm (Tunc, 1983), such as negligence, or if it interferes
unreasonably with the rights of either the public or property owners
(Mank, 2007; Grossman, 2009; Kysar, 2011; Brunée etal., 2012; Gold-
berg and Lord, 2012; Koch etal., 2012). Liability for nuisance does not
exist if the agent did not know, or have reason to know, the effects
of its conduct (Antolini and Rechtschaffen, 2008). The law in connec-
tion with liability for environmental damage still has to be settled.
The European Union, but not the United States, recognizes exemption
from liability for lack of scientific knowledge (United States Congress,
1980; European Union, 2004). Under European law, and in some US
states, defendants are not responsible if a product defect had not yet
been discovered (European Commission, 1985; Dana, 2009). Some
legal scholars suggest that assigning blame for GHG emissions dates
back to 1990 when the harmfulness of such emissions was established
internationally, but others argue in favour of an earlier date (Faure and
Nollkaemper, 2007; Hunter and Salzman, 2007; Haritz, 2011). Legal
systems also require a causal link between a defendant’s conduct and
some identified harm to the plaintiff, in this case from climate change
(Tunc, 1983; Faure and Nollkaemper, 2007; Kosolapova, 2011; Kysar,
2011; Brunée etal., 2012; Ewing and Kysar, 2012; Goldberg and Lord,
2012). A causal link might be easier to establish between emissions
and adaptation costs (Farber, 2007). Legal systems generally also
require causal foreseeability or directness (Mank, 2007; Kosolapova,
2011; van Dijk, 2011; Ewing and Kysar, 2012), although some statutes
relax this requirement in specific cases (such as the US Comprehensive
Environmental Response, Compensation, and Liability Act (CERCLA),
commonly known as Superfund. Emitters might argue that their contri-
bution to GHG levels was too small and the harmful effects too indirect
and diffuse to satisfy the legal requirements (Sinnot-Armstrong, 2010;
Faure and Peeters, 2011; Hiller, 2011; Kysar, 2011; van Dijk, 2011; Ger-
rard and Wannier, 2012).
Climate change claims could also be classified as unjust enrichment
(Kull, 1995; Birks, 2005), but legal systems do not remedy all forms of
enrichment that might be regarded as ethically unjust (Zimmermann,
1995; American Law Institute, 2011; Laycock, 2012). Under some legal
systems, liability depends on whether benefits were conferred without
legal obligation or through a transaction with no clear change of own-
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ership (Zimmermann, 1995; American Law Institute, 2011; Laycock,
2012). It is not clear that these principles apply to climate change.
As indicated, legal systems do not recognize liability just because a
positive or negative externality exists. Their response depends on the
behaviour that caused the externality and the nature of the causal
link between the agent’s behaviour and the resulting gain or loss to
another.
3�3�7 Geoengineering, ethics, and justice
Geoengineering (also known as climate engineering [CE]), is large-
scale technical intervention in the climate system that aims to cancel
some of the effects of GHG emissions (for more details see Working
Group I (WGI) 6.5 and WGIII 6.9). Geoengineering represents a third
kind of response to climate change, besides mitigation and adaptation.
Various options for geoengineering have been proposed, including dif-
ferent types of solar radiation management (SRM) and carbon dioxide
removal (CDR). This section reviews the major moral arguments for and
against geoengineering technologies (for surveys see Robock, 2008;
Corner and Pidgeon, 2010; Gardiner, 2010; Ott, 2010; Betz and Cacean,
2012; Preston, 2013). These moral arguments do not apply equally to
all proposed geoengineering methods and have to be assessed on a
case-specific basis.
7
Three lines of argument support the view that geoengineering tech-
nologies might be desirable to deploy at some point in the future. First,
that humanity could end up in a situation where deploying geoengi-
neering, particularly SRM, appears as a lesser evil than unmitigated
climate change (Crutzen, 2006; Gardiner, 2010; Keith et al., 2010;
Svoboda, 2012a; Betz, 2012). Second, that geoengineering could be
a more cost-effective response to climate change than mitigation or
adaptation (Barrett, 2008). Such efficiency arguments have been criti-
cized in the ethical literature for neglecting issues such as side-effects,
uncertainties, or fairness (Gardiner, 2010, 2011; Buck, 2012). Third,
that some aggressive climate stabilization targets cannot be achieved
through mitigation measures alone and thus must be complemented
by either CDR or SRM (Greene etal., 2010; Sandler, 2012).
Geoengineering technologies face several distinct sets of objections.
Some authors have stressed the substantial uncertainties of large-
scale deployment (for overviews of geoengineering risks see also
7
While the literature typically associates some arguments with particular types of
methods (e. g., the termination problem with SRM), it is not clear that there are
two groups of moral arguments: those applicable to all SRM methods on the one
side and those applicable to all CDR methods on the other side. In other words,
the moral assessment hinges on aspects of geoengineering that are not connected
to the distinction between SRM and CDR.
Schneider (2008) and Sardemann and Grunwald (2010)), while others
have argued that some intended and unintended effects of both CDR
and SRM could be irreversible (Jamieson, 1996) and that some cur-
rent uncertainties are unresolvable (Bunzl, 2009). Furthermore, it has
been pointed out that geoengineering could make the situation worse
rather than better (Hegerl and Solomon, 2009; Fleming, 2010; Hamil-
ton, 2013) and that several technologies lack a viable exit option: SRM
in particular would have to be maintained as long as GHG concentra-
tions remain elevated (The Royal Society, 2009).
Arguments against geoengineering on the basis of fairness and jus-
tice deal with the intra-generational and intergenerational distribu-
tional effects. SRM schemes could aggravate some inequalities if, as
expected, they modify regional precipitation and temperature patterns
with unequal social impacts (Bunzl, 2008; The Royal Society, 2009;
Svoboda etal., 2011; Preston, 2012). Furthermore, some CDR methods
would require large-scale land transformations, potentially competing
with agricultural land-use, with uncertain distributive consequences.
Other arguments against geoengineering deal with issues including
the geopolitics of SRM, such as international conflicts that may arise
from the ability to control the “global thermostat” (e. g., Schelling,
1996; Hulme, 2009), ethics (Hale and Grundy, 2009; Preston, 2011;
Hale and Dilling, 2011; Svoboda, 2012b; Hale, 2012b), and a critical
assessment of technology and modern civilization in general (Fleming,
2010; Scott, 2012).
One of the most prominent arguments against geoengineering sug-
gests that geoengineering research activities might hamper mitigation
efforts (e. g., Jamieson, 1996; Keith, 2000; Gardiner, 2010), which pre-
sumes that geoengineering should not be considered an acceptable
substitute for mitigation. The central idea is that research increases the
prospect of geoengineering being regarded as a serious alternative to
emission reduction (for a discussion of different versions of this argu-
ment see Hale, 2012a; Hourdequin, 2012). Other authors have argued,
based on historical evidence and analogies to other technologies, that
geoengineering research might make deployment inevitable (Jamie-
son, 1996; Bunzl, 2009), or that large-scale field tests could amount to
full-fledged deployment (Robock etal., 2010). It has also been argued
that geoengineering would constitute an unjust imposition of risks
on future generations, because the underlying problem would not be
solved but only counteracted with risky technologies (Gardiner, 2010;
Ott, 2012; Smith, 2012). The latter argument is particularly relevant to
SRM technologies that would not affect greenhouse gas concentra-
tions, but it would also apply to some CDR methods, as there may be
issues of long-term safety and capacity of storage.
Arguments in favour of research on geoengineering point out that
research does not necessarily prepare for future deployment, but can,
on the contrary, uncover major flaws in proposed schemes, avoid pre-
mature CE deployment, and eventually foster mitigation efforts (e. g.
Keith etal., 2010). Another justification for Research and Development
(R&D) is that it is required to help decision-makers take informed deci-
sions (Leisner and Müller-Klieser, 2010).
220220
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
3.4 Values and wellbeing
One branch of ethics is the theory of value. Many different sorts of
value can arise, and climate change impinges on many of them. Value
affects nature and many aspects of human life. This section surveys
some of the values at stake in climate change, and examines how far
these values can be measured, combined, or weighed against each
other. Each value is subject to debate and disagreement. For example,
it is debatable whether nature has value in its own right, apart from
the benefit it brings to human beings. Decision-making about climate
change is therefore likely to be contentious.
Since values constitute only one part of ethics, if an action will increase
value overall it by no means follows that it should be done. Many
actions benefit some people at the cost of harming others. This raises
a question of justice even if the benefits in total exceed the costs.
Whereas a cost to a person can be compensated for by a benefit to
that same person, a cost to a person cannot be compensated for by
a benefit to someone else. To suppose it can is not to “take seriously
the distinction between persons”, as John Rawls puts it (1971, p.27).
Harming a person may infringe their rights, or it may be unfair to them.
For example, when a nation’s economic activities emit GHG, they may
benefit the nation itself, but may harm people in other nations. Even if
the benefits are greater in value than the harms, these activities may
infringe other nations’ rights. Other nations may therefore be entitled
to object to them on grounds of justice.
Any decision about climate change is likely to promote some values
and damage others. These may be values of very different sorts. In
decision making, different values must therefore be put together or
balanced against each other. Some pairs of values differ so radically
from each other that they cannot be determinately weighed together.
For example, it may be impossible to weigh the value of preserving a
traditional culture against the material income of the people whose
culture it is, or to weigh the value of biodiversity against human well-
being. Some economists claim that one person’s wellbeing cannot be
weighed against another’s (Robbins, 1937; Arrow, 1963). When values
cannot be determinately weighed, they are said to be ‘incommensu-
rable’ or ‘incomparable’ (Chang, 1997). Multi-Criteria Analysis (MCA)
(discussed in Section 3.7.2.1) is a technique that is designed to take
account of several incommensurable values (De Montis etal., 2005;
Zeleny and Cochrane, 1982).
3�4�1 Non-human values
Nature provides great benefits to human beings in ways that range
from absorbing our waste, to beautifying the world we inhabit. An
increasing number of philosophers have argued in recent years that
nature also has value in its own right, independently of its benefits to
human beings (Leopold, 1949; Palmer, 2011). They have argued that
we should recognize animal values, the value of life itself, and even the
value of natural systems and nature itself.
In moral theory, rational adult humans, who are self-conscious subjects
of a life, are often taken (following Kant, 1956) to have a kind of uncon-
ditional moral worth — sometimes called ‘dignity’ — that is not found
elsewhere on earth. Others believe that moral worth can be found else-
where (Dryzek, 1997). Many human beings themselves lack rationality
or subjectivity, yet still have moral worth — the very young, the very
old and people with various kinds of impairment among them. Given
that, why deny moral worth to those animals that are to some extent
subjects of a life, who show emotional sophistication (Regan, 2004),
and who experience pleasure, pain, suffering, and joy (Singer, 1993)?
An argument for recognizing value in plants as well as animals was
proposed by Richard Routley (1973). Routley gives the name ‘human
chauvinism’ to the view that humans are the sole possessors of intrin-
sic value. He asks us to imagine that the last man on earth sets out to
destroy every living thing, animal or plant. Most people believe this
would be wrong, but human chauvinists are unable to explain why.
Human chauvinism appears to be simply a prejudice in favour of the
human species (Routley and Routley, 1980). In contrast, some philoso-
phers argue that value exists in the lives of all organisms, to the extent
that they have the capacity to flourish (Taylor, 1986; Agar, 2001).
Going further, other philosophers have argued that biological com-
munities and holistic ecological entities also have value in their own
right. Some have argued that a species has more value than all of its
individuals have together, and that an ecosystem has still more value
(Rolston, 1988, 1999; compare discussion in Brennan and Lo, 2010).
It has further been proposed that, just as domination of one human
group by another is a moral evil, showing disrespect for the value of
others, then so is the domination of nature by humans in general.
If nature and its systems have moral worth, then the domination of
nature is also a kind of disrespect (Jamieson, 2010).
If animals, plants, species, and ecosystems do have value in their own
right, then the moral impact of climate change cannot be gauged by
its effects on human beings alone. If climate change leads to the loss
of environmental diversity, the extinction of plant and animal species,
and the suffering of animal populations, then it will cause great harms
beyond those it does to human beings. Its effects on species numbers,
biodiversity, and ecosystems may persist for a very long time, perhaps
even longer than the lifetime of the human species (Nolt, 2011).
It is very difficult to measure non-human values in a way that makes
them commensurate with human values. Economists address this
issue by dividing value into use value (associated with actual use of
nature — instrumental value) and nonuse or existence value (intrinsic
value of nature). As an example, biodiversity might have value because
of the medical drugs that might be discovered among the diverse
biota (use value). Or biodiversity might be valued by individuals sim-
221221
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
ply because they believe that biologic diversity is important, over and
above any use to people that might occur. The total amount people are
willing to pay has sometimes been used as an economic measure of
the total value (instrumental and intrinsic) of these features (Aldred,
1994). As the discussion of the past few paragraphs has suggested,
nature may have additional value, over and above the values placed by
individual humans (Broome, 2009; Spash etal., 2009).
3�4�2 Cultural and social values
The value of human wellbeing is considered in Section 3.4.3, but the
human world may also possess other values that do not form part of
the wellbeing of individual humans. Living in a flourishing culture and
society contributes to a person’s wellbeing (Kymlicka, 1995; Appiah,
2010), but some authors claim that cultures and societies also pos-
sess values in their own right, over and above the contribution they
make to wellbeing (Taylor, 1995). Climate change threatens damage to
cultural artefacts and to cultures themselves (Adger etal., 2012). Evi-
dence suggests that it may already be damaging the culture of Arctic
indigenous peoples (Ford etal., 2006, 2008; Crate, 2008; Hassol, 2004;
see also WGII Chapter 12). Cultural values and indigenous peoples are
discussed in Section 3.10.2.
The degree of equality in a society may also be treated as a value that
belongs to a society as a whole, rather than to any of the individu-
als who make up the society. Various measures of this value are avail-
able, including the Gini coefficient and the Atkinson measure (Gini,
1912; Atkinson, 1970); for an assessment see (Sen, 1973). Section 3.5
explains that the value of equality can alternatively be treated as a
feature of the aggregation of individual people’s wellbeings, rather
than as social value separate from wellbeing.
3�4�3 Wellbeing
Most policy concerned with climate change aims ultimately at making
the world better for people to live in. That is to say, it aims to promote
people’s wellbeing. A person’s wellbeing, as the term is used here,
includes everything that is good or bad for the person — everything
that contributes to making their life go well or badly. What things
are those — what constitutes a person’s wellbeing? This question has
been the subject of an extensive literature since ancient times.
8
One
view is that a person’s wellbeing is the satisfaction of their prefer-
ences. Another is that it consists in good feelings such as pleasure. A
third is that wellbeing consists in possessing the ordinary good things
of life, such as health, wealth, a long life, and participating well in a
8
For example: Aristotle, Nicomachean Ethics. Recent work includes: Griffin (1986);
Sumner (1999); Kraut (2007).
good community. The ‘capabilities approach’ in economics (Sen, 1999)
embodies this last view. It treats the good things of life as ‘function-
ings’ and ‘capabilities’ — things that a person does and things that
they have a real opportunity of doing, such as living to old age, having
a good job, and having freedom of choice.
A person’s wellbeing will be affected by many of the other values that
are mentioned above, and by many of the considerations of justice
mentioned in Section 3.3. It is bad for a person to have their rights
infringed or to be treated unfairly, and it is good for a person to live
within a healthy culture and society, surrounded by flourishing nature.
Various concrete measures of wellbeing are in use (Fleurbaey, 2009;
Stiglitz etal., 2009). Each reflects a particular view about what well-
being consists in. For example, many measures of ‘subjective wellbe-
ing’ (Oswald and Wu, 2010; Kahneman and Deaton, 2010) assume that
wellbeing consists in good feelings. Monetary measures of wellbeing,
which are considered in Section 3.6, assume that wellbeing consists
in the satisfaction of preferences. Other measures assume wellbeing
consists in possessing a number of specific good things. The Human
Development Index (HDI) is intended to be an approximate measure of
wellbeing understood as capabilities and functionings (UNDP, 2010). It
is based on three components: life expectancy, education, and income.
The capabilities approach has inspired other measures of wellbeing
too (Dervis and Klugman, 2011). In the context of climate change,
many different metrics of value are intended to measure particular
components of wellbeing: among them are the numbers of people at
risk from hunger, infectious diseases, coastal flooding, or water scar-
city. These metrics may be combined to create a more general measure.
Schneider etal. (2000) advocates the use of a suite of five metrics:
(1) monetary loss, (2) loss of life, (3) quality of life (taking account of
forced migration, conflict over resources, cultural diversity, and loss of
cultural heritage sites), (4) species or biodiversity loss, and (5) distribu-
tion and equity.
3�4�4 Aggregation of wellbeing
Whatever wellbeing consists of, policy-making must take into account
the wellbeing of everyone in the society. So the wellbeings of differ-
ent people have somehow to be aggregated together. How do they
combine to make up an aggregate value of wellbeing for a society as a
whole? Social choice theory takes up this problem (Arrow, 1963; Sen,
1970). Section 3.6 will explain that the aim of economic valuation is to
measure aggregate wellbeing.
Assume that each person has a level of wellbeing at each time they are
alive, and call this their ‘temporal wellbeing’ at that time. In a society,
temporal wellbeing is distributed across times and across the people.
When a choice is to be made, each of the options leads to a particular
distribution of wellbeing. Our aim is to assess the value of such distri-
butions. Doing so involves aggregating wellbeings across times and
across people, to arrive at an overall, social value for the distribution.
222222
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
3�4�5 Lifetime wellbeing
Next let us assume that each person’s temporal wellbeings can be
aggregated to determine a ‘lifetime wellbeing’ for the person, and that
the social value of the distribution of wellbeing depends only on these
lifetime wellbeings. This is the assumption that each person’s wellbe-
ing is “separable”, to use a technical term. It allows us to split aggre-
gation into two steps. First, we aggregate each person’s temporal well-
beings across the times in their life in order to determine their lifetime
wellbeing. The second step in the next section is to aggregate across
individuals using a social welfare function.
On one account, a person’s lifetime wellbeing is simply the total of
their temporal wellbeings at each time they are alive. If a person’s
wellbeing depended only on the state of their health, this formula
would be equivalent to ‘QALYs’ or ‘DALYs’ (quality-adjusted life years
or disability-adjusted life years), which are commonly used in the anal-
ysis of public health (Murray, 1994; Sassi, 2006). These measures take
a person’s lifetime wellbeing to be the total number of years they live,
adjusted for their health in each year. Since wellbeing actually depends
on other things as well as health, QALYs or DALYs provide at best an
approximate measure of lifetime wellbeing. If they are aggregated
across people by simple addition, it assumes implicitly that a year of
healthy life is equally as valuable to one person as it is to another.
That may be an acceptable approximation for the broad evaluation
of climate change impacts and policies, especially for evaluating their
effects on health (Nord etal., 1999; Mathers etal., 2009; but also see
Currie etal., 2008).
Other accounts give either increasing, (Velleman, 1991) or alternatively
decreasing, (Kaplow etal., 2010) weight to wellbeing that comes in
later years of life, in determining a person’s lifetime wellbeing.
3�4�6 Social welfare functions
Once we have a lifetime wellbeing for each person, the next step is
to aggregate these lifetime wellbeings across people, to determine an
overall value for society. This involves comparing one person’s wellbe-
ing with another’s. Many economists have claimed that interpersonal
comparisons of wellbeing are impossible.
9
If they are right, the wellbe-
ings of different people are incommensurable and cannot be aggre-
gated. In this section we set this view aside, and assume that temporal
wellbeings are measured in a way that is comparable across people.
10
This allows us to aggregate different people’s lifetime wellbeings
through a social welfare function (SWF) to arrive at an overall value or
‘social welfare’.
11
9
Examples are: Robbins (1937), Archibald (1959), Arrow (1963). A survey and
discussion of this sceptical view appears in Hammond (1993).
10
Potential bases of interpersonal comparisons are examined in: Fleurbaey and
Hammond (2004); Sen (1982); Elster and Roemer (1993); Mirrlees (1982);
Broome, (2004); Arrow (1977); Harsanyi (1977); Adler (2011).
11
A recent major study is Adler (2011).
We shall first consider SWFs under the simplifying but unrealistic
assumption that the decisions that are to be made do not affect how
many people exist or which people exist: all the options contain the
same people. A theorem of Harsanyi’s (1955) gives some grounds for
thinking that, given this assumption, the SWF is additively separable
between people. This means it has the form:
Equation 3�4�1 V = v
1
(w
1
) + v
2
(w
2
) + … + v
J
(w
J
)
Here w
i
is person i’s lifetime wellbeing. This formula says that each
person’s wellbeing can be assigned a value v
i
(w
i
), and all these val-
ues — one for each person — are added up to determine the social
value of the distribution.
The proof of Harsanyi’s Theorem depends on assumptions that can
be challenged (Diamond, 1967; Broome, 2004; Fleurbaey, 2010). So,
although the additively separable form shown in Equation 3.4.1 is
commonly assumed in economic valuations, it is not entirely secure.
In particular, this form makes it impossible to give any value to equal-
ity except indirectly through prioritarianism, which was introduced in
Section 3.3.2 and is defined below. The value of inequality cannot be
measured by the Gini coefficient, for example, since this measure is not
additively separable (Sen, 1973).
It is often assumed that the functions v
i
() all have the same form,
which means that each person’s wellbeing is valued in the same way:
Equation 3�4�2 V = v (w
1
) + v (w
2
) + … + v (w
J
)
Alternatively, the wellbeing of people who live later is sometimes
discounted relative to the wellbeing of people who live earlier; this
implies that the functional form of v
i
() varies according to the date
when people live. Discounting of later wellbeing is often called ‘pure’
discounting. It is discussed in Section 3.6.2.
Even if we accept Equation 3.4.2, different ethical theories imply dif-
ferent SWFs. Utilitarianism values only the total of people’s wellbeing.
The SWF may be written:
Equation 3�4�3 V = w
1
+ w
2
+ … + w
J
Utilitarianism gives no value to equality in the distribution of wellbe-
ing: a given total of wellbeing has the same value however unequally
it is distributed among people.
But the idea of distributive justice mentioned in Section 3.3.3 sug-
gests that equality of wellbeing does have value. Equation 3.4.2 will
give value to equality if the function v() is strictly concave. This
means the graph of v() curves downwards, as Figure 3.1 illustrates.
(Section 3.6.1.1 explains that a person’s wellbeing w
i
is commonly
assumed to be a strictly concave function of her consumption, but
this is a different point.) The resulting ethical theory is called priori-
tarianism. As Figure 3.1 shows, according to prioritarianism, improv-
Figure 3�1 | The prioritarian view of social welfare. The figure compares the social val-
ues of increases in wellbeing for a better-off and a worse-off person.
Wellbeing
Social Value of Wellbeing
Equal Increase
in Wellbeing
Increase in
Social Value
Lesser
Greater
223223
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
ing a person’s wellbeing contributes more to social welfare if the
person is badly off than if they are well off. The prioritarian slogan is
“priority to the worse off”. Prioritarianism indirectly gives value to
equality: it implies that a given total of wellbeing is more valuable
the more equally it is distributed (Sen, 1973; Weirich, 1983; Parfit,
1997). In judgements about climate change, a prioritarian function
will give relatively more importance to the interests of poorer people
and poorer countries.
3�4�7 Valuing population
The next problem in aggregating wellbeing is to take account of
changes in population. Climate change can be expected to affect the
world’s human population. Severe climate change might even lead to a
catastrophic collapse of the population (Weitzman, 2009), and even to
the extinction of human beings. Any valuation of the impact of climate
change and of policies to mitigate climate change should therefore
take changes in population into account.
The utilitarian and prioritarian SWFs for a fixed population may be
extended in a variety of ways to a variable population. For example,
the utilitarian function may be extended to ‘average utilitarianism’
(Hurka, 1982), whose SWF is the average of people’s wellbeing. Aver-
age utilitarianism gives no value to increasing numbers of people. The
implicit or explicit goal of a great deal of policy-making is to promote
per capita wellbeing (Hardin, 1968). This is to adopt average utilitari-
anism. This goal tends to favour anti-natalist policies, aimed at limiting
population. It would strongly favour population control as a means of
mitigating climate change, and it would not take a collapse of popula-
tion to be, in itself, a bad thing.
The utilitarian function may alternatively be extended to ‘critical-level
utilitarianism’, whose SWF is the total of the amount by which each
person’s wellbeing exceeds some fixed critical level. It is
Equation 3�4�4 V = (w
1
– c) + (w
2
– c) + … + (w
J
– c)
where c is the critical level (Broome, 2004; Blackorby et al., 2005).
Other things being equal, critical-level utilitarianism favours adding
people to the population if their wellbeing is above the critical level.
‘Total utilitarianism’ (Sidgwick, 1907) is critical-level utilitarianism
with the critical level set to zero. Its SWF is the total of people’s well-
being. Total utilitarianism is implicit in many Integrated Assessment
Models (IAMs) of climate change (e. g., Nordhaus, 2008). Its mean-
ing is indeterminate until it is settled which level of lifetime wellbeing
to count as zero. Many total utilitarians set the zero at the level of
a life that has no good or bad experiences — that is lived in a coma
throughout, for instance (Arrhenius, forthcoming). Since people on
average lead better lives than this, total utilitarianism with this zero
tends to be less anti-natalist than average utilitarianism. However, it
does not necessarily favour increasing population. Each new person
damages the wellbeing of existing people, through their emissions of
GHG, their other demands on Earth’s limited resources, and the emis-
sions of their progeny. If the damage an average person does to others
in total exceeds their own wellbeing, total utilitarianism, like average
utilitarianism, favours population control as a means of mitigating cli-
mate change.
12
Each of the existing ethical theories about the value of population has
intuitively unattractive implications (Parfit, 1986). Average utilitarian-
ism is subject to particularly severe objections. Arrhenius (forthcoming)
crystallizes the problems of population ethics in the form of impos-
sibility theorems. So far, no consensus has emerged about the value of
population. Yet climate change policies are expected to affect the size
of the world’s population, and different theories of value imply very
different conclusions about the value of these policies. This is a serious
difficulty for evaluating policies aimed at mitigating climate change,
which has largely been ignored in the literature (Broome, 2012).
3.5 Economics, rights,
and duties
Sections 3.2, 3.3 and 3.4 have outlined some of the ethical principles
that can guide decision making for climate change. The remainder of
this chapter is largely concerned with the concepts and methods of
12
Harford (1998) shows that an additional person causes damage from her own
emissions and the emissions of her children (and of their children, etc.). Kelly and
Kolstad (2001) examine this issue in the specific context of climate change.
We shall first consider SWFs under the simplifying but unrealistic
assumption that the decisions that are to be made do not affect how
many people exist or which people exist: all the options contain the
same people. A theorem of Harsanyi’s (1955) gives some grounds for
thinking that, given this assumption, the SWF is additively separable
between people. This means it has the form:
Equation 3�4�1 V = v
1
(w
1
) + v
2
(w
2
) + … + v
J
(w
J
)
Here w
i
is person i’s lifetime wellbeing. This formula says that each
person’s wellbeing can be assigned a value v
i
(w
i
), and all these val-
ues — one for each person — are added up to determine the social
value of the distribution.
The proof of Harsanyi’s Theorem depends on assumptions that can
be challenged (Diamond, 1967; Broome, 2004; Fleurbaey, 2010). So,
although the additively separable form shown in Equation 3.4.1 is
commonly assumed in economic valuations, it is not entirely secure.
In particular, this form makes it impossible to give any value to equal-
ity except indirectly through prioritarianism, which was introduced in
Section 3.3.2 and is defined below. The value of inequality cannot be
measured by the Gini coefficient, for example, since this measure is not
additively separable (Sen, 1973).
It is often assumed that the functions v
i
() all have the same form,
which means that each person’s wellbeing is valued in the same way:
Equation 3�4�2 V = v (w
1
) + v (w
2
) + … + v (w
J
)
Alternatively, the wellbeing of people who live later is sometimes
discounted relative to the wellbeing of people who live earlier; this
implies that the functional form of v
i
() varies according to the date
when people live. Discounting of later wellbeing is often called ‘pure’
discounting. It is discussed in Section 3.6.2.
Even if we accept Equation 3.4.2, different ethical theories imply dif-
ferent SWFs. Utilitarianism values only the total of people’s wellbeing.
The SWF may be written:
Equation 3�4�3 V = w
1
+ w
2
+ … + w
J
Utilitarianism gives no value to equality in the distribution of wellbe-
ing: a given total of wellbeing has the same value however unequally
it is distributed among people.
But the idea of distributive justice mentioned in Section 3.3.3 sug-
gests that equality of wellbeing does have value. Equation 3.4.2 will
give value to equality if the function v() is strictly concave. This
means the graph of v() curves downwards, as Figure 3.1 illustrates.
(Section 3.6.1.1 explains that a person’s wellbeing w
i
is commonly
assumed to be a strictly concave function of her consumption, but
this is a different point.) The resulting ethical theory is called priori-
tarianism. As Figure 3.1 shows, according to prioritarianism, improv-
Figure 3�1 | The prioritarian view of social welfare. The figure compares the social val-
ues of increases in wellbeing for a better-off and a worse-off person.
Wellbeing
Social Value of Wellbeing
Equal Increase
in Wellbeing
Increase in
Social Value
Lesser
Greater
224224
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
economics. They can be used to aggregate values at different times and
places, and weigh aggregate value for different policy actions. They can
also be used to draw information about value from the data provided
by prices and markets. Economics can measure diverse benefits and
harms, taking account of uncertainty, to arrive at overall judgements of
value. It also has much to contribute to the choice and design of policy
mechanisms, as Section 3.8 and later chapters show.
Valuations provided by economics can be used on a large scale: IAMs
can be used to simulate the evolution of the world’s economy under
different climate regimes and determine an economically efficient
reduction in GHG emissions. On a smaller scale, economic methods of
CBA can be used in choosing between particular policies and technolo-
gies for mitigation.
Economics is much more than a method of valuation. For example,
it shows how decision making can be decentralized through market
mechanisms. This has important applications in policy instruments for
mitigation with potential for cost-effectiveness and efficiency (Chap-
ters 6 and 15). Economic analysis can also give guidance on how
policy mechanisms for international cooperation on mitigation can
be designed to overcome free-rider problems (Chapters 13 and 14).
However, the methods of economics are limited in what they can do.
They can be based on ethical principles, as Section 3.6 explains. But
they cannot take account of every ethical principle. They are suited
to measuring and aggregating the wellbeing of humans, but not to
taking account of justice and rights (with the exception of distribu-
tive justice — see below), or other values apart from human wellbeing.
Moreover, even in measuring and aggregating wellbeing, they depend
on certain specific ethical assumptions. This section describes the limits
of economic methods.
Because of their limitations, economic valuations are often not on their
own a good basis for decision making. They frequently need to be sup-
plemented by other ethical considerations. It may then be appropriate
to apply techniques of multi-criteria analysis (MCA), discussed in Sec-
tion 3.7.2.1 (Zeleny and Cochrane, 1982; Keeney and Raiffa, 1993; De
Montis etal., 2005).
3�5�1 Limits of economics in guiding decision
making
Economics can measure and aggregate human wellbeing, but Sections
3.2, 3.3 and 3.4 explain that wellbeing may be only one of several
criteria for choosing among alternative mitigation policies. Other ethi-
cal considerations are not reflected in economic valuations, and those
considerations may be extremely important for particular decisions
that have to be made. For example, some have contended that coun-
tries that have emitted a great deal of GHG in the past owe restitution
to countries that have been harmed by their emissions. If so, this is an
important consideration in determining how much finance rich coun-
tries should provide to poorer countries to help with their mitigation
efforts. It suggests that economics alone cannot be used to determine
who should bear the burden of mitigation (also see Box 3.2).
What ethical considerations can economics cover satisfactorily? Since
the methods of economics are concerned with value, they do not take
account of justice and rights in general. However, distributive justice
can be accommodated within economics, because it can be under-
stood as a value: specifically the value of equality. The theory of fair-
ness within economics (Fleurbaey, 2008) is an account of distributive
justice. It assumes that the level of distributive justice within a soci-
ety is a function of the wellbeings of individuals, which means it can
be reflected in the aggregation of wellbeing. In particular, it may be
measured by the degree of inequality in wellbeing, using one of the
standard measures of inequality such as the Gini coefficient (Gini,
1912), as discussed in the previous section. The Atkinson measure of
inequality (Atkinson, 1970) is based on an additively separable SWF,
and is therefore particularly appropriate for representing the prioritar-
ian theory described in Section 3.4.6. Furthermore, distributive justice
can be reflected in weights incorporated into economic evaluations as
Section 3.6 explains.
Economics is not well suited to taking into account many other aspects
of justice, including compensatory justice. For example, a CBA might
not show the drowning of a Pacific island as a big loss, since the island
has few inhabitants and relatively little economic activity. It might con-
clude that more good would be done in total by allowing the island
to drown: the cost of the radical action that would be required to
save the island by mitigating climate change globally would be much
greater than the benefit of saving the island. This might be the correct
conclusion in terms of overall aggregation of costs and benefits. But
the island’s inhabitants might have a right not to have their homes
and livelihoods destroyed as a result of the GHG emissions of richer
nations far away. If that is so, their right may override the conclusions
of CBA. It may give those nations who emit GHG a duty to protect the
people who suffer from it, or at least to make restitution to them for
any harms they suffer.
Even in areas where the methods of economics can be applied in princi-
ple, they cannot be accepted without question (Jamieson, 1992; Sagoff,
2008). Particular simplifying assumptions are always required, as shown
throughout this chapter. These assumptions are not always accurate
or appropriate, and decision-makers need to keep in mind the result-
ing limitations of the economic analyses. For example, climate change
will shorten many people’s lives. This harm may in principle be included
within a CBA, but it remains highly contentious how that should be
done. Another problem is that, because economics can provide con-
crete, quantitative estimates of some but not all values, less quantifi-
able considerations may receive less attention than they deserve.
The extraordinary scope and scale of climate change raises particular
difficulties for economic methods (Stern, forthcoming). First, many of
the common methods of valuation in economics are best designed for
marginal changes, whereas some of the impacts of climate change and
225225
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
efforts at mitigation are not marginal (Howarth and Norgaard, 1992).
Second, the very long time scale of climate change makes the discount
rate crucial at the same time as it makes it highly controversial (see
Section 3.6.2). Third, the scope of the problem means it encompasses
the world’s extremes of wealth and poverty, so questions of distribu-
tion become especially important and especially difficult. Fourth, mea-
suring non-market values — such as the existence of species, natural
environments, or traditional ways of life of local societies — is fraught
with difficulty. Fifth, the uncertainty that surrounds climate change is
very great. It includes the likelihood of irreversible changes to societies
and to nature, and even a small chance of catastrophe. This degree of
uncertainty sets special problems for economics (Nelson, 2013).
3.6 Aggregation of costs
and benefits
3�6�1 Aggregating individual wellbeing
Policies that respond to climate change almost always have some good
and some bad effects; we say they have ‘benefits’ and ‘costs’. In choos-
ing a policy, we may treat one of the available options as a standard
of comparison — for instance, the status quo. Other options will have
costs and benefits relative to this standard. Most mitigation strategies
have costs in the present and yield benefits in the future. Policy-making
involves assessing the values of these benefits and costs and weigh-
ing them against each other. Chapter 6 contains an example in which
different mitigation strategies yielding different temporal allocations
of climate impacts are compared. The weighing of costs and benefits
need not be a precise process. Sections 3.2 and 3.4 explain that costs
and benefits may be values of very different sorts, which cannot be
precisely weighed against each other. They may also be very uncertain.
Nevertheless, the discipline of economics has developed methods for
measuring numerically values of one particular sort: human wellbeing.
In this section, we describe these methods; Section 3.5 explains their
serious limitations. Economists often use money as their unit of mea-
surement for values, but not always. In health economics, for example,
the unit of benefit for health care is often the ‘quality-adjusted life
year’ (QALY) (see Box 3.3). In economics, monetary measures of value
are used in cost-effectiveness analysis (see Weimer and Vining, 2010),
in estimating the social cost of carbon (see Section 3.9.4), in inter-tem-
poral optimization within IAMs (e. g., Stern, 2007; Nordhaus, 2008), in
CBA and elsewhere.
Generally the overall value of aggregate wellbeing needs to be mea-
sured, and not merely the wellbeing of each individual. A numerical
measure of overall wellbeing may be based on ethical analysis, through
a SWF of the sort introduced in Section 3.4. This basis of valuation is
described here. The literature contains a putative alternative basis built
on the ‘potential Pareto criterion’ (see Box 3.4), but this is subject to
severe objections (De Scitovszky, 1941; Gorman, 1955; Arrow, 1963,
Chapter 4; Boadway and Bruce, 1984; Blackorby and Donaldson, 1990).
We take as our point of departure the formulation of the SWF in Equa-
tion 3.4.2, which is based on assumptions described in Section 3.4.6.
To these we now add a further assumption that times are separable,
meaning that the distribution of wellbeing can be evaluated at each
time separately and its overall value is an aggregate of these separate
‘snap-shot’ values. A theorem of Gorman’s (1968) ensures that social
welfare then takes the fully additively separable form:
Equation 3�6�1 V = δ
1
V
1
+ δ
2
V
2
+ . . . + δ
T
V
T
Box 3�2 | Who mitigates versus who pays?
To mitigate climate change, emissions of GHG will need to be
reduced to varying degrees worldwide. Economic analysis tells
us that, for the sake of cost-effectiveness, the greatest reductions
should be made where they can be made most cheaply. Ideally,
emissions should be reduced in each place to just the extent that
makes the marginal cost of further reductions the same every-
where. One way of achieving this result is to have a carbon price
that is uniform across the world; or it might be approximated by a
mix of policy instruments (see Section 3.8).
Since, for efficiency, mitigation should take place where it is
cheapest, emissions of GHG should be reduced in many develop-
ing countries, as well as in rich ones. However, it does not follow
that mitigation must be paid for by those developing countries;
rich countries may pay for mitigation that takes place in poor
countries. Financial flows between countries make it possible to
separate the question of where mitigation should take place from
the question of who should pay for it. Because mitigating climate
change demands very large-scale action, if put in place these
transfers might become a significant factor in the international
distribution of wealth. Provided appropriate financial transfers
are made, the question of where mitigation should take place is
largely a matter for the economic theory of efficiency, tempered by
ethical considerations. But the distribution of wealth is a matter of
justice among countries, and a major issue in the politics of climate
change (Stanton, 2011). It is partly a matter of distributive justice,
which economics can take into account, but compensatory justice
may also be involved, which is an issue for ethics (Section 3.3).
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
where each V
t
is the value of wellbeing at time t and is the total of the
values of individual wellbeings at that time. That is:
Equation 3�6�2 V
t
= v (w
1t
) + v (w
2t
) + . . . + v (w
It
)
Each w
it
is the temporal wellbeing of person i at time t. Each δ
t
is a
‘discount factor’, which shows how wellbeing at time t is valued rela-
tive to wellbeing at other times.
The assumption that times are separable has some unsatisfactory
consequences. First, it cannot give value to equality between people’s
lives taken as a whole, but only to equality at each particular time.
Second, Equation 3.6.1 is inconsistent with average utilitarianism, or
with valuing per capita temporal wellbeing at any time, whereas per
capita wellbeing is a common object of climate-change policy. Third,
Equation 3.6.1 makes no distinction between discounting within
a single person’s life and intergenerational discounting. Yet a case
can be made for treating these two sorts of discounting differently
(Kaplow etal., 2010). Nevertheless, this assumption and the resulting
equation Equation 3.6.1 underlies the usual practice of economists
when making valuations. First they aggregate temporal wellbeing
across people at each time to determine a snapshot social value for
each time. Then all these values are aggregated across times. This sec-
tion and the next describe the usual practice based on these equa-
tions.
13
The second step — aggregation across time — is considered in
Section 3.6.1. The rest of this section considers the first step — aggre-
gation at time.
13
An alternative approach does not assume separability of times. First it determines
a lifetime wellbeing for each person in the way described in Section 3.4.5. For
instance, i’s lifetime wellbeing might be a discounted total of her temporal wellbe-
ings. Then this approach aggregates across people using Equation 3.4.2. See
Fullerton and Rogers (1993), Murphy and Topel (2006) and Kaplow et al. (2010).
Box 3�3 | The value of life
Climate change may shorten many people’s lives, and mitigat-
ing climate change may extend many people’s lives. Lives must
therefore be included in any CBA that is concerned with climate
change. The literature contains two different approaches to valu-
ing a person’s life. One is based on the length of time the person
gains if their life is saved, adjusted according to the quality of
their life during that time (QALY), an approach widely used to
value lives in health economics and public health. For assessing
the impact of climate on human health and longevity, the World
Health Organization uses the ‘disability-adjusted life year’ (DALY),
which is similar (Mathers etal., 2009; for DALYs see, Murray,
1994).
The other approach values the extension of a person’s life on the
basis of what they would be willing to pay for it. In practice, this
figure is usually derived from what the person would be willing
to pay for an increased chance of having an extended life. If, say,
a person is willing to pay $100 to reduce her chance of dying in a
road accident from 2 in 10,000 to 1 in 10,000, then her willing-
ness to pay (WTP) for extending her life is $100 x 10,000 = $1
million. A WTP measure of the value of life is widely used in envi-
ronmental economics (e. g., U. S. Environmental Protection Agency,
2010 Appendix B); it is often known as a ‘value of statistical life’
(Viscusi and Aldy, 2003).
The main differences between these approaches are:
1. Since WTP is measured in money, it is immediately compa-
rable with other values measured in money. QALYs need to be
assigned a monetary value to make them comparable (Mason
etal., 2009).
2. The use of QALYs implies a theoretical assumption about the
value of extending a life — that it is proportional to the length
of the extension, adjusted for quality — whereas WTP methods
generally leave it entirely to the individual to set a value on
extending their own life (Broome, 1994).
3. Each measure implies a different basis for interpersonal
comparisons of value. When QALYs are aggregated across
people by addition, the implicit assumption is that a year of
healthy life has the same value for each person. When WTP is
aggregated across people by addition (without distributional
weights), the implicit assumption is that a dollar has the same
value for each person. Neither assumption is accurate, but for
comparisons involving very rich countries and very poor ones,
the former assumption seems nearer the truth (Broome, 2012,
Chapter 9).
The two approaches can converge. The text explains that distribu-
tional weights should be applied to monetary values before they
are aggregated, and this is true of WTP for extending life. If appro-
priate weights are applied, WTP becomes more nearly propor-
tional to QALYs. Indeed, if we adopt the assumption that a QALY
has the same value for each person, we may use it to give us a
basis for calculating distributional weights to apply to money val-
ues (Somanathan, 2006). For example, suppose WTP for a 30-year
extension to healthy life in the United States is USD 5 million, and
in India it is USD 250,000; then, on this assumption, USD 1 to an
Indian has the same social value as USD 20 to an American.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
3�6�1�1 Monetary values
Climate policies affect the wellbeing of individuals by changing their
environment and their individual consumption. The first step in a prac-
tical economic valuation is to assign a monetary value to the costs and
benefits that come to each person at each time from the change. This
value may be either the amount of money the person is willing to pay
for the change, or the amount they are willing to accept as compensa-
tion for it. If the change is a marginal increase or decrease in the per-
son’s consumption of a marketed commodity, it will be equal to the
price of the commodity.
The effect of a change on the person’s wellbeing is the monetary value
of the change multiplied by the rate at which money contributes to the
person’s wellbeing. This rate is the marginal benefit of money or mar-
ginal utility of money to the person. It is generally assumed to dimin-
ish with increasing income (Marshall, 1890; Dalton, 1920; Pigou, 1932,
p.89; Atkinson, 1970).
The effects of the change on each person’s wellbeing at each time must
next be aggregated across people to determine the effect on social
value. Equation 3.6.2 shows how each person’s wellbeing contributes
to social value through the value function v(). The change in wellbeing
must therefore be multiplied by the marginal social value of wellbeing,
which is the first derivative of this function. It is an ethical parameter.
According to utilitarianism, that marginal social value is constant and
the same for everyone; according to prioritarianism, it diminishes with
increasing wellbeing.
Box 3�4 | Optimality versus Pareto improvement in climate change
The assessment of a change normally requires benefits to be
weighed against costs. An exception is a change − known as a
‘Pareto improvement’ − that benefits some people without harm-
ing anyone. Climate change provides one possible example. GHG
is an externality: a person whose activities emit GHG does not
bear the full cost of their activities; some of the costs are borne
by those who are harmed by the emissions. Consequently, climate
change causes Pareto inefficiency, which means that a Pareto
improvement would in principle be possible. Indeed it would be
possible to remove the inefficiency in a way that requires no sac-
rifice by anyone in any generation, compared to business-as-usual
(BAU). To achieve this result, the present generation must real-
locate investment towards projects that reduce emissions of GHG,
while maintaining its own consumption. Because it maintains
its own consumption, the present generation makes no sacrifice.
Because it reduces its conventional investment, this generation
bequeaths less conventional capital to future generations. Other
things being equal, this reallocation would make future genera-
tions less well off, but the reduction in emissions will more than
compensate them for that loss (Stern, forthcoming; Foley, 2009;
Rezai etal., 2011).
It is commonly assumed that climate change calls for sacrifices by
the present generation for the sake of future generations. Figure
3.2 illustrates why. The possibility frontier shows what combina-
tions of consumption are possible for present and future genera-
tions. Because of the externality, Business-as-usual lies below this
frontier. The frontier can be reached by a Pareto improvement.
Contours of two different SWFs are shown: one SWF places more
value than the other on future consumption relative to present
consumption. The two contours reflect in a purely illustrative
way SWFs that are implicit in Stern (2007) and Nordhaus (2008)
respectively. The point where a contour touches the possibility
frontier is the social optimum according to that function. Neither
optimum is a Pareto improvement on business-as-usual. Although
the inefficiency could be removed without any sacrifices, the best
outcomes described by both Stern and Nordhaus do require a
sacrifice by the present generation.
From an international rather than an intergenerational perspec-
tive, it is also true on the same grounds that the inefficiency of
climate change can be removed without any nation making a
sacrifice (Posner and Weisbach, 2010). But it does not follow that
this would be the best outcome.
Figure 3�2 | Illustrating optimality versus Pareto improvement in climate change.
Present Generation’s Consumption
Future Generation’s Consumption
Stern’s
Optimum
Nordhaus’s
Optimum
Business as Usual
Possibility Frontier
Pareto Improvement on
Business as Usual
Stern’s Value Contour
Nordhaus’s Value Contour
228228
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
In sum, the effect of a change in social value at a particular time is
calculated by aggregating the monetary value of the change to each
person, weighted by the social marginal value of money to the person,
which is the product of the marginal benefit of money to that per-
son and the marginal social value of their wellbeing (Fleurbaey, 2009).
Since the marginal benefit of money is generally assumed to dimin-
ish with increasing income, the marginal social value of money can be
assumed to do the same.
Many practical CBAs value costs and benefits according to aggregated
monetary values without any weighting. The implicit assumption is that
the marginal social value of money is the same for each person. The
consequence of omitting weights is particularly marked when applying
CBA to climate change, where extreme differences in wealth between
rich and poor countries need to be taken into account. An example
appeared in the Second Assessment Report of the IPCC (1995), where
it considered the value of human life. The report showed that the effect
of ignoring weighting factors would be to assign perhaps twenty times
more value to an American life than to an Indian life. (See also Box 3.3).
Even within a single country, weighting makes a big difference. Drèze
(1998) examined the benefits of reducing pollution in Delhi and con-
trasts New Delhi, which is relatively rich, with Delhi, which is relatively
poorer. If the criterion is reducing pollution for the greatest number
of people, then projects in Delhi will be favoured; whereas projects in
New Delhi will be favoured if the criterion is unweighted net benefits.
Another example of a monetary measure of value that does not incor-
porate distributional weights is Gross Domestic Product (GDP). To
evaluate changes by their effect on GDP is, once again, to assume that
the value of a dollar to a rich person is the same as its value to a poor
person (Schneider etal., 2000).
It is sometimes assumed that CBA is conducted against the back-
ground of efficient markets and an optimal redistributive taxation
system, so that the distribution of income can be taken as ideal from
society’s point of view. If that were true, it might reduce the need for
distributional weights. But this is not an acceptable assumption for
most projects aimed at climate change. Credit and risk-sharing mar-
kets are imperfect at the world level, global coordination is limited by
agency problems, information is asymmetric, and no supra-national tax
authority can reduce worldwide inequalities. Furthermore, intergen-
erational transfers are difficult. In any case, the power of taxation to
redistribute income is limited because redistributive taxes create inef-
ficiency (Mirrlees, 1971). Even optimal taxation would therefore not
remove the need for distributional weights. Thus, the assumption that
incomes are (second-best) optimally redistributed does not neutralize
the argument for welfare weights in aggregating costs and benefits.
The need for weights makes valuation more complicated in practice.
The data available for costs and benefits is generally aggregated across
people, rather than separated for particular individuals. This means that
weights cannot be applied directly to individuals’ costs and benefits, as
they ideally should be. This difficulty can be overcome by applying suit-
ably calculated weights to the prices of commodities, calculated on the
basis of income distribution of each commodity’s consumers.
14
3�6�2 Aggregating costs and benefits across
time
In climate change decisions, aggregating the pros and cons of alterna-
tive actions is particularly difficult because most benefits of mitigation
will materialize only in the distant future. On the other hand, the costs
of mitigation are borne today. Using a discount rate can therefore make
a big difference in evaluating long-term projects or investments for cli-
mate change mitigation. For example, a benefit of $1 million occurring
in 100 years has a present value of $369,000 if the discount rate is
1 %, $52,000 if it is 3 %, and $ 1,152 if it is 7 %. An important debate
in economics since AR4, spawned in part by the Stern (2007) Review,
has centred on the discount rate that should be applied in evaluating
climate change impacts and mitigation costs (Nordhaus, 2007; Stern,
2008; Dasgupta, 2008; Smith, 2010; see also Quiggin, 2008).
A descriptive approach to discounting examines how human beings
trade-off the present against their own futures. It focuses on how
individuals and markets make inter-temporal financial decisions, as
revealed by the market interest rate. A simple arbitrage argument
favours using the interest rate as the discount rate for climate policy
decisions: if one reallocates capital from a safe but marginal project
(whose return must be equal to the interest rate) to a safe project with
the same maturity whose return is smaller than the interest rate, the
net impact is null for the current generation, and is negative for future
generations. Thus, when projects are financed by a reallocation of capi-
tal rather than an increase in aggregate saving (reducing consump-
tion), the discount rate should be equal to the shadow cost of capital.
Table 3.1 documents real returns on different classes of assets in west-
ern countries, including government bonds, which are usually consid-
ered to be the safest, most risk-free assets. As can be seen, these rates
are close to zero.
The same arbitrage argument could be used to discount risky projects.
In that case, the discount rate should be equal to the expected rate of
return of traded assets with the same risk profile. For example, if the
project has the same risk profile as a diversified portfolio of equity,
one should use the expected rate of return of equity, as documented in
Table 3.1. It contains a relatively large equity premium.
This descriptive approach to the discount rate has many drawbacks.
First, we should not expect markets to aggregate preferences effi-
ciently when some agents are not able to trade, as is the case for
future generations (Diamond, 1977). Second, current interest rates
14
The method is presented in Drèze and Stern (1989, pp. 909 – 989). Applications of
distributional weights to climate change appear in Azar and Sterner (1996); and
Fankhauser et al. (1997).
Table 3�1 | Real returns of financial assets. Source: Updated data from (Dimson, 2002), in Gollier (2012).
Government Bills
(maturity <1 year)
Government Bonds
(maturity =10 years)
Equity
1900 – 2006 1971 – 2006 1900 – 2006 1971 – 2006 1900 – 2006 1971 – 2006
Australia 0.6 % 2.5 % 1.3 % 2.8 % 7.8 % 6.3 %
France – 2.9 % 1.2 % – 0.3 % 6.6 % 3.7 % 7.8 %
Japan – 2.0 % 0.4 % – 1.3 % 3.9 % 4.5 % 5.0 %
United Kingdom 1.0 % 1.9 % 1.3 % 3.9 % 5.6 % 7.1 %
USA 1.0 % 1.3 % 1.9 % 4.0 % 6.6 % 6.6 %
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
are driven by the potentially impatient attitude of current consumers
towards transferring their own consumption to the future. But climate
change is about transferring consumption across different people and
generations, so that determining the appropriate social discount rate
is mostly a normative problem. Thirdly, we do not observe safe assets
with maturities similar to those of climate impacts, so the arbitrage
argument cannot be applied.
We now examine the problem of a social policy-maker who must make
climate policy choices using a SWF discussed earlier. In aggregating
damages and costs over time, in order to make things comparable
across long periods we value consumption changes in the future by
equivalent changes in consumption today. These changes in the struc-
ture of consumption should be evaluated in monetary terms using
values described in Section 3.6.1.1. The incorporation of the intergen-
erational equity objective has challenged the traditional CBA approach
for the evaluation of climate change policies. Practitioners of CBA and
evaluators are expected to use discount rates that are consistent with
the pre-specified SWF that represents the society’s intergenerational
values, as in AR2 (1995). We simplify the model used in Section 3.6.1.1
by assuming only one generation per period and only one consumer
good. In an uncertain context, an action is socially desirable if it raises
the SWF given by 3.6.1:
Equation 3�6�3 V =
∑
t = 0
∞
e
−δt
Eu
(
c
t
)
where u
(
c
t
)
= v
(
w
(
c
t
)
)
= V
t
is the contribution to the SWF of genera-
tion t consuming c
t
. Because c
t
is uncertain, one should take the expec-
tation Eu (c
t
) of this uncertain contribution. The concavity of function u
combines prioritarism (inequality aversion) and risk aversion. Param-
eter δ measures our collective pure preference for the present, so that
the discount factor d
(
t
)
= e
−δt
decreases exponentially. δ is an ethical
parameter that is not related to the level of impatience shown by indi-
viduals in weighting their own future wellbeing (Frederick etal., 2002).
Many authors have argued for a rate of zero or near-zero (Ramsey,
1928; Pigou, 1932; Harrod, 1949; Parfit, 1986; Cowen, 1992; Schelling,
1995; Broome, 2004; Stern, 2008). Assuming δ > 0 would penalize
future generations just because they are born later. Many regard such
‘datism’ to be as ethically unacceptable as sexism or racism. Cowen
(1992) points out that discounting violates the Pareto principle for a
person who might live either at one time or at a later time. Some have
argued for a positive rate (Dasgupta and Heal, 1980; Arrow, 1999). A
traditional argument against a zero rate is that it places an extremely
heavy moral burden on the current generation (see, e. g., Dasgupta,
2007). But even when δ =0, as we see below, we still end up with a
discount rate of about 4 %, which is higher than it was during the last
century. Stern (2008) used δ =0.1 % to account for risk of extinction.
We conclude that a broad consensus is for a zero or near-zero pure
rate of time preference for the present.
In a growing economy ( c
t
> c
0
), investing for the future in a safe proj-
ect has the undesirable effect of transferring consumption from the
poor (current generations) to the wealthy (future generations). Thus,
investing in safe projects raises intergenerational inequalities. The
discount rate can then be interpreted as the minimum rate of return
that is necessary to compensate for this adverse effect on the SWF of
investing for the future. This is summarized by the Ramsey rule (i. e.,
the consumption approach to discounting) (Ramsey, 1928). Assuming
a standard constant elasticity in the consumption utility function (e. g.,
u(c)= c
1 – η
/ (1 – η)), and no uncertainty,
15
the minimum rate of return
ρ
t
of a project that marginally transfers consumption from 0 to t and
that guarantees an increase of intergenerational welfare V is defined
as follows:
Equation 3�6�4 ρ
t
= δ + ηg
t
where δ represents the pure rate at which society discounts the utility
of future generations, and g
t
is the annualized growth rate of mon-
etized consumption anticipated at date t, and η >0 measures inequal-
ity aversion. The greater the anticipated economic growth rate g
t
, the
higher the social discount rate ρ
t
. The growth rate g
t
is an empirical
variable that represents our collective beliefs about prospective eco-
nomic growth. In Box 3.5, we discuss plausible values for the inequal-
ity aversion parameter η.
15
For alternative assumptions, see Gollier (2002).
ably calculated weights to the prices of commodities, calculated on the
basis of income distribution of each commodity’s consumers.
14
3�6�2 Aggregating costs and benefits across
time
In climate change decisions, aggregating the pros and cons of alterna-
tive actions is particularly difficult because most benefits of mitigation
will materialize only in the distant future. On the other hand, the costs
of mitigation are borne today. Using a discount rate can therefore make
a big difference in evaluating long-term projects or investments for cli-
mate change mitigation. For example, a benefit of $1 million occurring
in 100 years has a present value of $369,000 if the discount rate is
1 %, $52,000 if it is 3 %, and $ 1,152 if it is 7 %. An important debate
in economics since AR4, spawned in part by the Stern (2007) Review,
has centred on the discount rate that should be applied in evaluating
climate change impacts and mitigation costs (Nordhaus, 2007; Stern,
2008; Dasgupta, 2008; Smith, 2010; see also Quiggin, 2008).
A descriptive approach to discounting examines how human beings
trade-off the present against their own futures. It focuses on how
individuals and markets make inter-temporal financial decisions, as
revealed by the market interest rate. A simple arbitrage argument
favours using the interest rate as the discount rate for climate policy
decisions: if one reallocates capital from a safe but marginal project
(whose return must be equal to the interest rate) to a safe project with
the same maturity whose return is smaller than the interest rate, the
net impact is null for the current generation, and is negative for future
generations. Thus, when projects are financed by a reallocation of capi-
tal rather than an increase in aggregate saving (reducing consump-
tion), the discount rate should be equal to the shadow cost of capital.
Table 3.1 documents real returns on different classes of assets in west-
ern countries, including government bonds, which are usually consid-
ered to be the safest, most risk-free assets. As can be seen, these rates
are close to zero.
The same arbitrage argument could be used to discount risky projects.
In that case, the discount rate should be equal to the expected rate of
return of traded assets with the same risk profile. For example, if the
project has the same risk profile as a diversified portfolio of equity,
one should use the expected rate of return of equity, as documented in
Table 3.1. It contains a relatively large equity premium.
This descriptive approach to the discount rate has many drawbacks.
First, we should not expect markets to aggregate preferences effi-
ciently when some agents are not able to trade, as is the case for
future generations (Diamond, 1977). Second, current interest rates
14
The method is presented in Drèze and Stern (1989, pp. 909 – 989). Applications of
distributional weights to climate change appear in Azar and Sterner (1996); and
Fankhauser et al. (1997).
Table 3�1 | Real returns of financial assets. Source: Updated data from (Dimson, 2002), in Gollier (2012).
Government Bills
(maturity <1 year)
Government Bonds
(maturity =10 years)
Equity
1900 – 2006 1971 – 2006 1900 – 2006 1971 – 2006 1900 – 2006 1971 – 2006
Australia 0.6 % 2.5 % 1.3 % 2.8 % 7.8 % 6.3 %
France – 2.9 % 1.2 % – 0.3 % 6.6 % 3.7 % 7.8 %
Japan – 2.0 % 0.4 % – 1.3 % 3.9 % 4.5 % 5.0 %
United Kingdom 1.0 % 1.9 % 1.3 % 3.9 % 5.6 % 7.1 %
USA 1.0 % 1.3 % 1.9 % 4.0 % 6.6 % 6.6 %
230230
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
By using a near-zero time discount rate, Stern (2007, see also 2008)
advanced the debate in the literature. Despite disagreement on the
empirical approach to estimating the discount rate, the literature sug-
gests consensus for using declining discount rates over time. Different
prominent authors and committees have taken different positions on
the values of δ, η and g, making different recommendations for the
social discount rate ρ. We summarize them in Table 3.2.
In Table 3.2, the Ramsey formula can be seen to yield a wide range of
discount rates, although most or all of the estimates reflect developed
country experience. From this table and Box 3.5, a relative consensus
emerges in favour of δ = 0 and η between 1 and 3, although they are
prescriptive parameters. This means that the normative Ramsey rule
leads to a recommendation for a social discount rate of between one
and three times the estimated growth rate in consumption between
today and the relevant safe benefit or cost to be discounted. The social
discount rate is normative because it relies on the intensity of our col-
lective inequality aversion. However, the practical coherence of our
ethical principles requires that if one has high inequality aversion, one
should also redistribute wealth more assiduously from the currently
rich to the currently poor. Furthermore, it is ultimately a judgement by
the policymaker on the appropriate value of the parameters of the
Ramsey rule, and thus the social discount rate.
The discount rate described here should be used to discount risk-free
costs and benefits (Anthoff etal., 2009). The rates that appear in Table
3.2 are higher than real interest rates observed on financial markets, as
documented in Table 3.1. This discrepancy defines the risk-free rate puz-
zle (Weil, 1989). The recent literature on discounting has tried to solve
this puzzle by taking into account the uncertainty surrounding economic
Box 3�5 | Plausible values for collective inequality aversion (η)
Consider the following thought experiment. A country has two
equally populated social groups. The wealthy group consumes
twice as many goods and services as the poor group. Consider
also an economic policy whose aim is to increase consumption by
1 unit for every person in the poor group. This implies a reduc-
tion of consumption for every wealthy person by x units, which
may not be equal to 1 owing to inherent inefficiencies in the
tax system. If one is neutral about inequalities, one would not
accept this policy if x is larger than 1. Inequality aversion justifies
accepting some productive inefficiency, so that an x larger than
1 may be allowed. What is the maximum value of x that one
would accept to implement the policy? Answering this question
tells us something about inequality aversion, with a large x being
associated with a larger η. If one is collectively ready to sacrifice
as much as x=2 units of consumption from the rich to provide
one unit of consumption to the poor, this is compatible with an
inequality aversion index η =1. An x of 4 or 8 would correspond
to an index of inequality aversion of 2 and 3, respectively.
Behind the veil of ignorance (Rawls, 1971), our collective prefer-
ences towards inequality should be identified as our individual risk
aversion. The economic literature in finance and macroeconomics
usually assumes a η between 1 and 5 to explain observed behav-
iours towards risk, as well as asset prices (Kocherlakota, 1996).
Table 3�2 | Calibration of the discount rate based on the Ramsey rule (Equation 3.6.4).
Author
Rate of pure preference
for present
Inequality aversion Anticipated Growth rate Implied social discount rate
Cline (1992) 0 % 1.5 1 % 1.5 %
IPCC (1996) 0 % 1.5 – 2 1.6 % – 8 % 2.4 % – 16 %
Arrow (1999) 0 % 2 2 % 4 %
UK: Green Book (HM Treasury, 2003) 1.5 % 1 2 % 3.5 %*
US UMB (2003)** 3 % – 7 %
France: Rapport Lebègue (2005) 0 % 2 2 % 4 %*
Stern (2007) 0.1 % 1 1.3 % 1.4 %
Arrow (2007) 2 – 3
Dasgupta (2007) 0.1 % 2 – 4
Weitzman (2007a) 2 % 2 2 % 6 %
Nordhaus (2008) 1 % 2 2 % 5 %
Notes:
*
Decreasing with the time horizon.
**
OMB uses a descriptive approach.
231231
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
growth. Prudent agents should care more about the future if the future
is more uncertain, in line with the concept of sustainable development.
Assuming a random walk for the growth rate of consumption per capita,
this argument applied to Equation 3.6.4 leads to an extended Ramsey
rule in which a negative precautionary effect is added:
Equation 3�6�5 ρ
t
= δ + ηg
t
– 0.5 η(η +1)σ
t
2
where σ
t
is the annualized volatility of the growth rate of GDP / cap,
and g
t
is now the expected annualized growth rate until time horizon t.
In Table 3.3, we calibrate this formula for different countries by using
the estimation of the trend and volatility parameters of observed
growth rates of consumption per capita over the period 1969 – 2010,
using η =2. We learn from this Table that the Ramsey rule (Equation
3.4.1) often provides a good approximation of the social discount rate
to be applied to consumption. It also shows that because of differ-
ences in growth expectations, nations may have different attitudes
towards reducing present consumption for the benefit of future gener-
ations. This is also a further source of international disagreement on
the strength of GHG mitigation efforts. The global discount rate for
evaluating global actions will therefore depend on how costs and ben-
efits are allocated across countries.
16
A prudent society should favour actions that generate more benefits
for the generations that face greater uncertainty, which justifies a
16
Table 3.3 is based on the assumption that the growth process is a random walk,
so that the average growth rate converges to its mean in the very long run. It
would be more realistic to recognize that economic growth has a much more
uncertain nature in the long run: shocks on growth rates are often persistent,
economies faces long-term cycles of uncertain length, and some parameters of
the growth process are uncertain. Because these phenomena generate a positive
correlation in future annual growth rates, they tend to magnify the uncertainty
affecting the wellbeing of distant generations, compared to the random walk
hypothesis of the extended Ramsey rule (Equation 3.6.5).
decreasing term structure for risk-free discount rates (Gollier, 2012;
Arrow etal., 2013; Weitzman, 2013). These results are related to the
literature on Gamma discounting (Weitzman, 1998, 2001, 2010b; New-
ell and Pizer, 2003; Gollier and Weitzman, 2010). A simple guideline
emerging from this literature is that the long-maturity discount rate is
equal to the smallest discount rate computed from
Equation 3.6.5
with
the different plausible levels of its parameters. For example, assuming
η =2, if the trend of growth g
t
is unknown but somewhere between
1 % and 3 %, a discount rate around 2 x mean (1 %, 3 %)=4 % is
socially desirable in the short term, although a discount rate of only 2 x
min (1 %, 3 %) =2 % is desirable for very long maturities.
Assuming a constant rate of pure preference for the present (actu-
ally δ =0), these recommendations yield a perfectly time-consistent
valuation strategy, although the resulting discount rates decrease with
maturity. A time inconsistency problem arises only if we assume that
the rate of pure preference for the present varies according to the time
horizon. Economists have tended to focus on hyperbolic discounting
and time inconsistency (Laibson, 1997) and the separation between
risk aversion and consumption aversion fluctuations over time (Epstein
and Zin, 1991). See Section 3.10.1 and Chapter 2.
The literature deals mainly with the rate at which safe projects should
be discounted. In most cases, however, actions with long-lasting
impacts are highly uncertain, something that must be taken into
account in their evaluation. Actions that reduce the aggregated risk
borne by individuals should be rewarded and those that increase risk
should be penalized. This has traditionally been done by raising the
discount rate of a project by a risk premium π=βπ
g
that is equal to
the project-specific risk measure β times a global risk premium π
g.
The
project-specific beta is defined as the expected increase in the ben-
efit of the project when the consumption per capita increases by 1 %.
It measures the additional risk that the action imposes on the com-
munity. On average, it should be around 1. As we see from Table 3.3,
Table 3�3 | Country-specific discount rate computed from the Ramsey rule (Equation 3.6.5) using the historical mean g and standard deviation σ of growth rates of real GDP / cap
1969 – 2010, together with δ = 0,and η = 2. Source: Gollier (2012).
Country g
σ
Discount rate
Ramsey rule Equation 3�6�4 Extended Ramsey rule
OECD countries
United States 1.74 % 2.11 % 3.48 % 3.35 %
United Kingdom 1.86 % 2.18 % 3.72 % 3.58 %
Japan 2.34 % 2.61 % 4.68 % 4.48 %
Economies in transition
China 7.60 % 3.53 % 15.20 % 14.83 %
India 3.34 % 3.03 % 6.68 % 6.40 %
Russia 1.54 % 5.59 % 3.08 % 2.14 %
Africa
Gabon 1.29 % 9.63 % 2.58 % – 0.20 %
Zaire (RDC) – 2.76 % 5.31 % – 5.52 % – 6.37 %
Zambia – 0.69 % 4.01 % – 1.38 % – 1.86 %
Zimbabwe – 0.26 % 6.50 % – 0.52 % – 1.79 %
232232
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
the risk premium as measured by the difference between the rate of
return on bonds and the rate of return on equity is between 3 % and
6 %. A more normative approach described by the consumption-based
capital asset pricing model (Cochrane, 2001) would lead to a much
smaller risk premium equalling π
gt
= η σ
t
2
if calibrated on the volatil-
ity of growth in western economies.
17
However, Barro (2006, 2009)
and Martin (2013) recently showed that the introduction of rare cata-
strophic events — similar to those observed in some developing coun-
tries during the last century — can justify using a low safe discount rate
of around 1 % and a large aggregate risk premium of around 4 % at
the same time. The true discount rate to be used in the context of cli-
mate change will then rely heavily on the climate beta. So far, almost
no research has been conducted on the value of the climate beta, that
is, the statistical relationship between the level of climate damage
and the level of consumption per capita in the future. The exception
is Sandsmark and Vennemo (2006), who suggest that it is almost zero.
But existing Integrated Assessment Models (IAMs) show that more cli-
mate damage is incurred in scenarios with higher economic growth,
suggesting that combating climate change does not provide a hedge
against the global risk borne by future generations. Nordhaus (2011b)
assumes that the actual damages borne by future generations are
increasing, so that the climate beta is positive, and the discount rate
for climate change should be larger than just applying the extended
Ramsey rule.
Several authors (Malinvaud, 1953; Guesnerie, 2004; Weikard and Zhu,
2005; Hoel and Sterner, 2007; Sterner and Persson, 2008; Gollier, 2010;
Traeger, 2011; Guéant etal., 2012) emphasize the need to take into
account the evolution of relative prices in CBAs involving the distant
future. In a growing economy, non-reproducible goods like environ-
mental assets will become relatively scarcer in the future, thereby
implying an increasing social value.
3�6�3 Co-benefits and adverse side-effects
This section defines the concept of co-benefits and provides a gen-
eral framework for analysis in other chapters (a negative co-benefit is
labelled an ‘adverse side effect’). A good example of a co-benefit in the
literature is the reduction of local pollutants resulting from a carbon
policy that reduces the use of fossil fuels and fossil-fuel-related local
pollutants (see Sections 5.7 and 6.6.2.1). It is also important to dis-
tinguish between co-benefits and the societal welfare consequences
of generated co-benefits. To use the same example, if local pollutants
are already heavily regulated, then the net welfare benefits of further
reductions in local pollutants may be small or even negative.
17
With a volatility in the growth rate of consumption per capita around σ
t
= 4 %
(see Table 3.3), and a degree of inequality aversion of, η = 2, we obtain a risk
premium of only π
gt
= 0.32 %.
3�6�3�1 A general framework for evaluation of
co-benefits and adverse side-effects
As a simple example, suppose social welfare V is a function of different
goods or objectives z
i
(i = 1,…,m), and that each of those objectives
might be influenced by some policy instrument, p
1
.
18
The policy may
have an impact on several objectives at the same time. Now consider a
marginal change d p
1
in the policy. The welfare effect is given by:
Equation 3�6�6 dV =
∑
i=1
m
∂V
_
∂ z
i
∂ z
i
_
∂ p
1
d p
1
For example, suppose d p
1
> 0 is additional GHG abatement (tightening
the cap on carbon dioxide (CO
2
) emissions). Then the ‘direct’ benefits
of that climate policy might include effects on climate objectives, such
as mean global temperature ( z
1
), sea level rise ( z
2
), agricultural pro-
ductivity ( z
3
), biodiversity ( z
4
), and health effects of global warming
( z
5
). The ‘co-benefits’ of that climate policy might include changes in a
set of objectives such as SO
2
emissions ( z
6
), energy security ( z
7
), labour
supply and employment ( z
8
), the distribution of income ( z
9
), the degree
of urban sprawl ( z
10
), and the sustainability of the growth of develop-
ing countries ( z
11
). See Table 15.1 for an overview of objectives dis-
cussed in the sector chapters in the context of co-benefits and adverse
side effects. The few studies that attempt a full evaluation of the global
welfare effects of mitigation co-benefits focus only on a few objectives
because of methodological challenges (as assessed in Section 6.6). For
discussion of income distribution objectives, see the ‘social welfare
functions’ in Section 3.4.6.
Because this problem inherently involves multiple objectives, it can be
analysed using Multi-Criteria Analysis (MCA) that “requires policymak-
ers to state explicit reasons for choosing policies, with reference to the
multiple objectives that each policy seeks to achieve” (Dubash etal.,
2013, p.47). See also Section 3.7.2.1, Section 6.6 and McCollum etal.
(2012).
Even external effects on public health could turn out to be either direct
benefits of climate policy or co-benefits. The social cost of carbon
includes the increased future incidence of heat stroke, heart attacks,
malaria, and other warm climate diseases. Any reduction in such
health-related costs of climate change is therefore a direct benefit of
climate policy. The definition of a co-benefit is limited to the effect of
reductions in health effects caused by non-climate impacts of mitiga-
tion efforts.
Use of the terminology should be clear and consistent. CBAs need
to include all gains and losses from the climate policy being anal-
ysed — as shown in Equation 3.6.6 — the sum of welfare effects from
direct benefits net of costs, plus the welfare effects of co-benefits and
adverse side effects.
18
This V is a loose interpretation of a social welfare function, such as defined in
Equation 3.6.2, insofar as welfare is not usually represented a function of policy
objectives or aggregate quantities of goods.
233233
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
Here, the co-benefit is defined as the effect on a non-climate objective
(∂ z
i
/ ∂ p
1
), leaving aside social welfare (not multiplied by ∂V / ∂ z
i
). In con-
trast, the ‘value’ of the co-benefit is the effect on social welfare (∂V / ∂
z
i
), which could be evaluated by economists using valuation methods
discussed elsewhere in this chapter.
19
It may require use of a ‘second-
best’ analysis that accounts for multiple market distortions (Lipsey and
Lancaster, 1956). This is not a minor issue. In particular, ∂V / ∂ z
i
may be
positive or negative.
The full evaluation of dV in the equation above involves four steps: first,
identify the various multiple objectives z
i
(i = 1,…,m) (see, e. g., Table
4.8.1 for a particular climate policy such as a CO
2
emissions cap); sec-
ond, identify all significant effects on all those objectives (direct effects
and co-effects ∂ z
i
/∂ p
1
, for i = 1,…,m) (see Chapters 7 – 12); third, eval-
uate each effect on social welfare (multiply each ∂ z
i
/ ∂ p
1
by ∂V / ∂ z
i
);
and fourth, aggregate them as in Equation 3.6.6. Of course, computing
social welfare also has normative dimensions (see Section 3.4.6).
3�6�3�2 The valuation of co-benefits and adverse side-
effects
The list of goods or objectives z
i
(i = 1,…,m) could include any com-
modity, but some formulations allow the omission of goods sold in
markets with no market failure or distortion, where the social marginal
benefit (all to the consumer) is equal to the social marginal cost (all on
the producer). With no distortion in a market for good i, a small change
in quantity has no net effect on welfare (∂V / ∂ z
i
=0). The effect on
welfare is not zero, however, if climate policy affects the quantity of a
good sold in a market with a ‘market failure’, such as non-competitive
market power, an externality, or any pre-existing tax. In general, either
monopoly power or a tax would raise the price paid by consumers
relative to the marginal cost faced by producers. In such cases, any
increase in the commodity would have a social marginal benefit higher
than social marginal cost (a net gain in welfare).
We now describe a set of studies that have evaluated some co-benefits
and adverse side-effects (many more studies are reviewed in Sections
5.7, 7.9, 8.7, 9.7, 10.8, 11.7, 12.8 and synthesized in Section 6.6). First,
oligopolies may exert market power and raise prices above marginal
cost in large industries such as natural resource extraction, iron and
steel, or cement. And climate policy may affect that market power.
Ryan (2012) finds that a prominent environmental policy in the United
States actually increased the market power of incumbent cement man-
ufactures, because it decreased competition from potential entrants
that faced higher sunk costs. That is, it created barriers to entry. That
effect led to a significant loss in consumer surplus that was not incor-
porated in the policy’s initial benefit-cost analysis.
19
We distinguish here between the welfare effect of the co-benefit (∂V / ∂ z
i
) and the
welfare effect of the policy operating through a particular co-benefit (
∂V
_
∂ z
i
∂ z
i
_
∂ p
1
d p
1
).
Second, Ren et al. (2011) point out that a climate policy to reduce
CO
2
emissions may increase the use of biofuels, but that “corn-based
ethanol production discharges nitrogen into the water environment …
[which] … can cause respiratory problems in infants and exacerbate
algae growth and hypoxia in water bodies” (p.498). In other words,
a change in climate policy (d p
1
) affects the use of nitrogen fertilizer
and its runoff (∂ z
i
/ ∂ p
1
). The effect is an ‘adverse side effect.’ If nitrogen
runoff regulation is less than optimal, the effect on social welfare is
negative (∂V / ∂ z
i
<0).
Third, arguably the most studied co-benefits of climate policy are the
effects on local air pollutant emissions, air quality, and health effects
of ground-level ozone (see Section 6.6 for a synthesis of findings from
scenario literature and sector-specific measures). Burtraw etal. (2003)
conclude that a USD 25 per tonne carbon tax in the United States
would reduce NO
X
emissions and thereby provide health improve-
ments. Further, the researchers valued these health co-benefits at
USD
1997
8 (USD
2010
10,50) per tonne of carbon reduction in the year
2010. More recently, Groosman et al. (2011) model a specific U. S.
climate policy proposal (Warner-Lieberman, S.2191). They calculate
effects on health from changes in local flow pollutants (a co-benefit).
These health co-benefits mainly come from reductions in particulates
and ozone, attributable to reductions in use of coal-fired power plants
(Burtraw etal., 2003; Groosman etal., 2011).
20
The authors also value
that co-benefit at USD
2006
103 billion to USD
2006
1.2 trillion (USD
2010
111 billion to USD
2010
1,3 billion) for the years 2010 – 2030. That total
amount corresponds to USD 1 to USD 77 per tonne of CO
2
(depend-
ing on model assumptions and year; see Section 5.7 for a review of a
broader set of studies with higher values particularly for developing
countries).
Researchers have calculated climate policy co-benefits in many other
countries; for instance, Sweden (Riekkola etal., 2011), China (Aunan
etal., 2004), and Chile (Dessus and O’Connor, 2003).
A complete analysis of climate policy would measure all such direct
or side-effects (∂ z
i
/ ∂ p
1
) while recognizing that other markets may be
functioning properly or be partially regulated (for optimal regulation,
∂V / ∂ z
i
= 0). If the externality from SO
2
is already partly corrected by a
tax or permit price that is less than the marginal environmental dam-
age (MED) of SO
2
, for example, then the welfare gain from a small
reduction in SO
2
may be less than its MED. Or, if the price per tonne of
SO
2
is equal to its MED, and climate policy causes a small reduction in
SO
2
, then the social value of that co-benefit is zero.
21
Similarly, if the
labour market is functioning properly with no involuntary unemploy-
20
Both of the cited studies estimate the dollar value of health improvements, but
these are ‘gross’ benefits that may or may not correctly account for the offsetting
effects of existing controls on these local pollution emissions, which is necessary
to determine the net welfare effects.
21
This ‘marginal’ analysis contemplates a small change in either CO
2
or SO
2
. If either
of those changes is large, however, then the analysis is somewhat different.
234234
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
ment, then climate policy may have direct costs from use of that labour
but no welfare gain from changes in employment. In other words, in
measuring the welfare effects of co-benefits, it is not generally appro-
priate simply to use the gross marginal value associated with a co-
benefit.
In the context of externalities and taxes, this point can be formalized
by the following extension of Fullerton and Metcalf (2001):
Equation 3�6�7 dV =
∑
i=1
m
( t
i
− μ
i
)
∂ z
i
_
∂ p
1
d p
1
On the right side of the equation, μ
i
is the MED from the i
th
commodity;
and t
i
is its tax rate (or permit price, or the effect of a mandate that
makes an input such as emissions more costly). The effect of each good
on welfare (∂V / ∂ z
i
in Equation 3.6.6 above) is reduced in this model
to just ( t
i
− μ
i
). The intuition is simple: t
i
is the buyer’s social marginal
benefit minus the seller’s cost; the externality μ
i
is the social marginal
cost minus the seller’s cost. Therefore, ( t
i
− μ
i
) is the social marginal
benefit minus social marginal cost. It is the net effect on welfare from
a change in that commodity. If every externality μ
i
is corrected by a
tax rate or price exactly equal to μ
i
, then the outcome is ‘first best’. In
that case, dV in
Equation 3.6.7
is equal to zero, which means welfare
cannot be improved by any change in any policy. If any t
i
is not equal
to μ
i
, however, then the outcome is not optimal, and a ‘second best’
policy might improve welfare if it has any direct or indirect effect on
the amount of that good.
Although the model underlying
Equation 3.6.7
is static and climate
change is inherently dynamic, the concepts represented in the static
model can be used to understand the application to climate. Climate
policy reduces carbon emissions, but
Equation 3.6.7
shows that this
‘direct’ effect does not add to social welfare unless the damage per
tonne of carbon ( μ
C
) exceeds the tax on carbon ( t
C
). The social cost of
carbon is discussed in Section 3.9.4. To see a co-benefit in this equa-
tion, suppose z
S
is the quantity of SO
2
emissions, t
S
is the tax per tonne,
and μ
S
is the MED of additional SO
2
. If the tax on SO
2
is too small
to correct for the externality ( t
S
− μ
S
< 0), then the market provides
‘too much’ of it, and any policy such as a carbon tax that reduces the
amount of SO
2
(∂ z
S
/ ∂ p
1
< 0) would increase economic welfare. The
equation sums over all such effects in all markets for all other inputs,
outputs, and pollutants.
If those local pollution externalities are already completely corrected
by a tax or other policy ( t
S
= μ
S
), however, then a reduction in SO
2
adds nothing to welfare. The existing policy raises the firm’s cost of
SO
2
emissions by exactly the MED. That firm’s consumers reap the full
social marginal benefit per tonne of SO
2
through consumption of the
output, but those consumers also pay the full social marginal cost per
tonne of SO
2
. In that case, one additional tonne of SO
2
has social costs
exactly equal to social benefits, so any small increase or decrease in
SO
2
emissions caused by climate policy provides no net social gain. In
fact, if t
S
> μ
S
, then those emissions are already over-corrected, and any
decrease in SO
2
would reduce welfare.
3�6�3�3 The double dividend hypothesis
Another good example of a co-benefit arises from the interaction
between carbon policies and other policies (Parry, 1997; Parry and
Williams, 1999). Though enacted to reduce GHG emissions, a climate
policy may also raise product prices and thus interact with other taxes
that also raise product prices. Since the excess burden of taxation rises
more than proportionately with the size of the overall effective mar-
ginal tax rate, the carbon policy’s addition to excess burden may be
much larger if it is added into a system with high taxes on output or
inputs.
This logic has given rise to the ‘double dividend hypothesis’ that an
emissions tax can both improve the environment and provide revenue
to reduce other distorting taxes and thus improve efficiency of the
tax system (e. g., Oates and Schwab, 1988; Pearce, 1991; Parry, 1995;
Stern, 2009).
22
Parry (1997) and Goulder etal. (1997) conclude that the
implementation of a carbon tax or emissions trading can increase the
deadweight loss of pre-existing labour tax distortions (the ‘tax inter-
action effect’), but revenue can be used to offset distortionary taxes
(the ‘revenue recycling effect’). Parry and Williams (1999) investigate
the impacts of existing tax distortions in the labour market for eight
climate policy instruments (including energy taxes and performance
standards) for the United States in 1995. They conclude that pre-exist-
ing tax distortions raise the costs of all abatement policies, so the co-
benefits of carbon taxes or emissions trading depend on whether gen-
erated revenues can be directed to reduce other distortionary taxes.
A lesson is that forgoing revenue-raising opportunities from a GHG
regulation can significantly increase inefficiencies. The European Union
is auctioning an increasing share of permits with revenue going to
Member States (see 14.4.2). Australia is using a large share of carbon
pricing revenue to reduce income tax (Jotzo, 2012).
To put this discussion into the context of co-benefits, note that Ful-
lerton and Metcalf (2001) use their version of
Equation 3.6.7
to con-
sider labour ( z
L
), taxed at a pre-existing rate t
L
(with marginal exter-
nal damages of zero, so μ
L
= 0). Suppose the only other distortion is
from carbon emissions ( z
C
), with MED of μ
C
. Thus the economy has ‘too
little’ labour supply, and ‘too much’ pollution. The combination ‘policy
change’ is a small carbon tax with revenue used to cut the tax rate t
L
.
Other taxes and damages are zero ( t
i
= μ
i
= 0) for all goods other than
z
L
and z
C
. Thus,
Equation 3.6.7
above simplifies further, to show that
the two key outcomes are just the net effect on pollution (d z
C
) and the
net effect on labour (d z
L
):
Equation 3�6�8 dV = t
L
d z
L
+ ( t
C
− μ
C
) d z
C
22
The literature contains two versions of the double dividend hypothesis. A ‘strong’
version says that efficiency gains from diminishing distortionary taxes can more
than compensate the costs of pollution taxes. Another ‘weak’ version says that
those gains compensate only part of the costs of pollution taxes (Goulder, 1995).
235235
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
Therefore, an increase in the carbon tax that reduces emissions (d
z
C
< 0) has a direct benefit of increased economic welfare through the
second term, but only to the extent that emissions damages exceed
the tax rate ( μ
C
> t
C
). If the labour tax cut increases labour supply, then
the first term also increases welfare (a double dividend). But the car-
bon tax also raises the cost of production and the equilibrium output
price, which itself reduces the real net wage (the tax interaction effect).
If that effect dominates the reduction in the labour tax rate (from the
revenue recycling effect), then labour supply may fall (d z
L
< 0). In that
case, the first term has a negative effect on wellbeing. In other words,
the double-dividend is possible under some circumstances and not
others. If the revenue is not used to cut the labour tax rate, then the
real net wage does fall, and the labour supply may fall.
3.7 Assessing methods
of policy choice
Specific climate policies are discussed in Section 3.8; in this section,
we discuss methods for evaluating the relative merits of different poli-
cies. See also Alkin (2004), Pawson and Tilley (1997), Bardach (2005),
Majchrzak (1984), Scriven (1991) Rossi etal. (2005), and Chen (1990).
The design and choice of a specific climate policy instrument (or mix of
instruments) depends on many economic, social, cultural, ethical, insti-
tutional, and political contexts. Different methods for ex-ante and ex-
post analysis are available and different types of analytical approaches
may be used in tandem to provide perspectives to policymakers.
3�7�1 Policy objectives and evaluation criteria
In addition to reducing GHG emissions, climate policy may have other
objectives. Following WGIII AR4 (Gupta etal., 2007), these objectives
are organized below in four broad categories: economic, distribu-
tional / fairness, environmental, and institutional / political feasibility.
23
The relative importance of these policy objectives differs among coun-
tries, especially between developed and developing countries.
In this section we discuss elements of these four categories and expand
on recent policy evaluation studies (e. g., Opschoor and Turner, 1994;
Ostrom, 1999; Faure and Skogh, 2003; Sterner, 2003; Mickwitz, 2003;
Blok, 2007), leaving details of applications and evidence to Chapters
8 – 11 and 13 – 15.
23
Political factors have often been more important than economic factors in explain-
ing instrument choice (Hepburn, 2006). Redistribution to low-income households
is an important feature in Australia’s emissions pricing policy (Jotzo and Hatfield-
Dodds, 2011).
The basic economic framework for policy analysis is depicted in Figure
3.3. This diagram illustrates both the impacts of policies and the crite-
ria for evaluating them in the context of the production of a polluting
good (i. e., emissions associated with producing a good). The focus is
stylized, but we note that many ‘non-economic’ values can still be
incorporated, to the extent that values can be placed on other consid-
erations, such as effects on nature, culture, biodiversity and ‘dignity’
(see Sections 3.4.1 and 3.4.2).
As shown in Figure 3.3, the quantity of GHG emissions from producing
a good, such as electricity, is shown on the horizontal axis, and the
price or cost per unit of that good is shown on the vertical axis. The
demand for the emissions is derived from the demand for electricity, as
shown by the curve called Private Marginal Benefit (PMB). The private
market supply curve is the Private Marginal Cost (PMC) of production,
and so the unfettered equilibrium quantity would be Q
0
at equilibrium
price P
0
. This polluting activity generates external costs, however, and
so each unit of output has a Social Marginal Cost (SMC) measured by
the vertical sum of PMC plus Marginal External Cost (MEC). With no
externalities on the demand side, PMB=SMB.
Under the stated simplifying assumptions, the social optimum is where
SMC=PMB, at Q’. The first point here, then, is that the optimal quan-
tity can be achieved by several different policies under these simple
conditions. A simple regulatory quota could restrict output from Q
0
to Q’, or a fixed number of tradeable permits could restrict pollution
to the quantity Q’. In that case, P
n
is the equilibrium price net of per-
mit cost (the price received by the firm), while P
g
is the price gross of
permit cost (paid by the consumer). The permit price is the difference,
Figure 3�3 | A partial equilibrium model of the costs and benefits of a market output,
assuming perfect competition, perfect information, perfect mobility, full employment,
and many identical consumers (so all individuals equally benefit from production and
they equally bear the external cost of pollution).
SMC = Social Marginal Cost
(PMC + MEC)
PMC = Private
Marginal Cost
Demand = Private/Social
Marginal Benefits (PMB, SMB)
Quantity of the
Polluting Good
Price
P
g
P
0
P
n
Q
’
Q
0
A
B E
D
C
F
236236
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
P
g
– P
n
. Alternatively, a tax of (P
g
– P
n
) per unit of pollution would raise
the firm’s cost to SMC and result in equilibrium quantity Q’.
The diagram in Figure 3.3 will be used below to show how the equiva-
lence of these instruments breaks down under more general circum-
stances, as well as gains and losses to various groups. In other words,
we use this diagram to discuss economic as well as distributional,
other environmental and cultural objectives, and institutional / political
feasibility.
3�7�1�1 Economic objectives
Economic efficiency� Consider an economy’s allocation of resources
(goods, services, inputs, and productive activities). An allocation is effi-
cient if it is not possible to reallocate resources so as to make at least
one person better off without making someone else worse off. This
is also known as the Pareto criterion for efficiency (discussed in Sec-
tion 3.6.1) (see e. g., Sterner, 2003; Harrington etal., 2004; Tietenberg,
2006). In Figure 3.3, any reduction in output from Q
0
improves effi-
ciency because it saves costs (height of SMC) that exceed the benefits
of that output (height of PMB).
24
This reduction can be achieved by a
tax levied on the externality (a carbon tax), or by tradeable emission
permits. Further reductions in output generate further net gains, by the
extent to which SMC exceeds SMB, until output is reduced to Q’ (where
SMC=SMB). Hence, the gain in economic efficiency is area C. Perfect
efficiency is difficult to achieve, for practical reasons, but initial steps
from Q
0
achieve a larger gain (SMC>SMB) than the last step to Q’
(because SMC≈SMB near the left point of triangle C).
An aspect of economic efficiency over time is the extent to which a
carbon policy encourages the right amount of investment in research,
innovation, and technological change, in order to reduce GHG emis-
sions more cheaply (Jung etal., 1996; Mundaca and Neij, 2009). See
Section 3.11.
Cost-effectiveness� Pollution per unit of output in Figure 3.3 is fixed,
but actual technologies provide different ways of reducing pollution
per unit of output. A policy is cost-effective if it reduces pollution
(given a climate target) at lowest cost. An important condition of cost-
effectiveness is that marginal compliance costs should be equal among
parties (ignoring other distortions such as regulations) (Babiker etal.,
2004).
Transaction costs� In addition to the price paid or received, market
actors face other costs in initiating and completing transactions. These
costs alter the performance and relative effectiveness of different poli-
cies and need to be considered in their design, implementation, and
assessment (Mundaca etal., 2013; see also Matthews, 1986, p.906).
24
Other approaches are discussed in Section 3.6.
3�7�1�2 Distributional objectives
Six distributional effects� A policy may generate gains to some and
losses to others. The fairness or overall welfare consequences of these
distributional effects is important to many people and can be evalu-
ated using a SWF, as discussed in Section 3.4.6. These effects fall into
six categories (Fullerton, 2011), and are illustrated in Box 3.6 below. In
Figure 3.3, any policy instrument might reduce the quantity of pollut-
ing output, such as from Q
0
to Q’, which reduces emissions, raises the
equilibrium price paid by consumers (from P
0
to P
g
), and reduces the
price received by firms (from P
0
to P
n
). The six effects are illustrated in
Box 3.6. The framework can be applied to any environmental problem
and any policy to correct it.
With reference to Box 3.6, the first effect of a carbon policy on con-
sumers is generally regressive (though most analyses are for developed
countries), because the higher price of electricity imposes a heavier
burden on lower income groups who spend more of their income on
electricity (Metcalf, 1999; Grainger and Kolstad, 2010). However, fuel
taxes tend to be progressive in developing countries (Sterner, 2011).
The sign of the second effect, on factors of production, is generally
ambiguous. The third effect is regressive if permits are given to firms,
because then profits accrue to shareholders who tend to be in high-
income brackets (Parry, 2004). But if government captures the scar-
city rents by selling permits or through a carbon tax, the funds can be
used to offset burdens on low-income consumers and make the overall
effect progressive instead of regressive. Other effects are quite difficult
to measure.
Much of the literature on ‘environmental justice’ discusses the poten-
tial effects of a pollution policy on neighbourhoods with residents from
different income or ethnic groups (Sieg etal., 2004). Climate policies
affect both GHG emissions and other local pollutants such as SO
2
or
NO
X
, whose concentrations vary widely. Furthermore, the cost of miti-
gation may not be shared equally among all income or ethnic groups.
And even ‘global’ climate change can have different temperature
impacts on different areas, or other differential effects (e. g., on coastal
areas via rise in sea level).
The distributional impacts of policies include aspects such as fairness /
equity (Gupta etal., 2007). A perceived unfair distribution of costs and
benefits could prove politically challenging (see below), since efficiency
may be gained at the expense of equity objectives.
3�7�1�3 Environmental objectives
Environmental effectiveness� A policy is environmentally effective
if it achieves its expected environmental target (e. g., GHG emission
reduction). The simple policies mentioned above might be equally
effective in reducing pollution (from Q
0
to Q’ in Figure 3.3), but actual
policies differ in terms of ambition levels, enforcement and compli-
ance.
Box 3�6 | Six distributional effects of climate policy, illustrated for a permit obligation or emissions
tax on coal-fired electricity, under the assumption of perfectly competitive electricity markets
First, the policy raises the cost of generating electricity and if cost
increases are passed through to consumers, for example through
competitive markets or changes in regulated prices, the consum-
er’s price increases (from P
0
to P
g
), so it reduces consumer surplus.
In Figure 3.3, the loss to consumers is the sum of areas A + D.
Losses are greater for those who spend more on electricity.
Second, the policy reduces the net price received by the firm (from
P
0
to P
n
), so it reduces producer surplus by the sum of areas B + E.
The effect is reduced payments to factors of production, such as
labour and capital. Losses are greater for those who receive more
income from the displaced factor.
Third, pollution and output are restricted, so the policy generates
‘scarcity rents’ such as the value of a restricted number of permits
(areas A + B). If the permits are given to firms, these rents accrue
to shareholders. The government could partly or fully capture the
rents by selling the permits or by a tax per unit of emissions (Ful-
lerton and Metcalf, 2001).
Fourth, because the policy restricts GHG emissions, it confers ben-
efits on those who would otherwise suffer from climate change.
The value of those benefits is areas C + D + E.
Fifth, the electricity sector uses less labour, capital and other
resources. It no longer pays them (areas E + F). With perfect
mobility, these factors are immediately redeployed elsewhere,
with no loss. In practice however, social costs may be substan-
tial, including transaction costs of shifting to other industries or
regions, transitional or permanent unemployment, and social and
psychological displacement.
Sixth, any gain or loss described above can be capitalized into
asset prices, with substantial immediate effects for current own-
ers. For example, the value of a corporation that owns coal-fired
generation assets may fall, in line with the expected present value
of the policy change, while the value of corporations that own
low-emissions generation technologies may rise.
The connection between these distributional effects and
‘economic efficiency’ is revealed by adding up all the gains
and losses just described: the consumer surplus loss is A + D;
producer surplus loss is B + E; the gain in scarcity rents is A + B;
and the environmental gain is C + D + E, assuming the gainers
and losers receive equal weights. The net sum of the gains and
losses is area C, described above as the net gain in economic
efficiency.
In many cases, a distributional implication of imposing effi-
cient externality pricing (e. g., area A + B) is much larger than
the efficiency gains (area C). This illustrates the importance of
distributional considerations in discussions on emissions-reducing
policies, and it indicates why distributional considerations often
loom large in debates about climate policy.
237237
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
Co-benefits� Climate policy may reduce both GHG emissions and
local pollutants, such as SO
2
emissions that cause acid rain, or NO
X
emissions that contribute to ground level ozone. As described in Sec-
tion 3.6.3, reductions in other pollutants may not yield any net gain to
society if they are already optimally regulated (where their marginal
abatement costs and their marginal damages are equal). If pollutants
are inefficiently regulated, however, climate regulations can yield posi-
tive or negative net social gains by reducing them.
Climate policy is also likely to affect other national objectives, such as
energy security. For countries that want to reduce their dependence on
imported fossil fuels, climate policy can bolster energy efficiency and
the domestic renewable energy supply, while cutting GHG emissions.
See Section 3.6.3 on co-benefits.
Carbon leakage� The effectiveness of a national policy to reduce emis-
sions can be undermined if it results in increased emissions in other
countries, for example, because of trading advantages in countries
with more relaxed policies (see Section 3.9.5). Another type of leakage
occurs within emission trading systems. Unilateral emission reductions
by one party will release emission permits and be outweighed by new
emissions within the trading regime.
3�7�1�4 Institutional and political feasibility
Administrative burden� This depends on how a policy is imple-
mented, monitored, and enforced (Nordhaus and Danish, 2003). The
size of the burden reflects, inter alia, the institutional framework,
human and financial costs and policy objectives (Nordhaus and Dan-
ish, 2003; Mundaca etal., 2010). Administrative costs in public policy
are often overlooked (Tietenberg, 2006)
Political feasibility is the likelihood of a policy gaining acceptance
and being adopted and implemented (Gupta etal., 2007, p.785). It
covers the obstacles faced and key design features that can generate
or reduce resistance among political parties (Nordhaus and Danish,
2003). Political feasibility may also depend on environmental effective-
3�7�1�2 Distributional objectives
Six distributional effects� A policy may generate gains to some and
losses to others. The fairness or overall welfare consequences of these
distributional effects is important to many people and can be evalu-
ated using a SWF, as discussed in Section 3.4.6. These effects fall into
six categories (Fullerton, 2011), and are illustrated in Box 3.6 below. In
Figure 3.3, any policy instrument might reduce the quantity of pollut-
ing output, such as from Q
0
to Q’, which reduces emissions, raises the
equilibrium price paid by consumers (from P
0
to P
g
), and reduces the
price received by firms (from P
0
to P
n
). The six effects are illustrated in
Box 3.6. The framework can be applied to any environmental problem
and any policy to correct it.
With reference to Box 3.6, the first effect of a carbon policy on con-
sumers is generally regressive (though most analyses are for developed
countries), because the higher price of electricity imposes a heavier
burden on lower income groups who spend more of their income on
electricity (Metcalf, 1999; Grainger and Kolstad, 2010). However, fuel
taxes tend to be progressive in developing countries (Sterner, 2011).
The sign of the second effect, on factors of production, is generally
ambiguous. The third effect is regressive if permits are given to firms,
because then profits accrue to shareholders who tend to be in high-
income brackets (Parry, 2004). But if government captures the scar-
city rents by selling permits or through a carbon tax, the funds can be
used to offset burdens on low-income consumers and make the overall
effect progressive instead of regressive. Other effects are quite difficult
to measure.
Much of the literature on ‘environmental justice’ discusses the poten-
tial effects of a pollution policy on neighbourhoods with residents from
different income or ethnic groups (Sieg etal., 2004). Climate policies
affect both GHG emissions and other local pollutants such as SO
2
or
NO
X
, whose concentrations vary widely. Furthermore, the cost of miti-
gation may not be shared equally among all income or ethnic groups.
And even ‘global’ climate change can have different temperature
impacts on different areas, or other differential effects (e. g., on coastal
areas via rise in sea level).
The distributional impacts of policies include aspects such as fairness /
equity (Gupta etal., 2007). A perceived unfair distribution of costs and
benefits could prove politically challenging (see below), since efficiency
may be gained at the expense of equity objectives.
3�7�1�3 Environmental objectives
Environmental effectiveness� A policy is environmentally effective
if it achieves its expected environmental target (e. g., GHG emission
reduction). The simple policies mentioned above might be equally
effective in reducing pollution (from Q
0
to Q’ in Figure 3.3), but actual
policies differ in terms of ambition levels, enforcement and compli-
ance.
Box 3�6 | Six distributional effects of climate policy, illustrated for a permit obligation or emissions
tax on coal-fired electricity, under the assumption of perfectly competitive electricity markets
First, the policy raises the cost of generating electricity and if cost
increases are passed through to consumers, for example through
competitive markets or changes in regulated prices, the consum-
er’s price increases (from P
0
to P
g
), so it reduces consumer surplus.
In Figure 3.3, the loss to consumers is the sum of areas A + D.
Losses are greater for those who spend more on electricity.
Second, the policy reduces the net price received by the firm (from
P
0
to P
n
), so it reduces producer surplus by the sum of areas B + E.
The effect is reduced payments to factors of production, such as
labour and capital. Losses are greater for those who receive more
income from the displaced factor.
Third, pollution and output are restricted, so the policy generates
‘scarcity rents’ such as the value of a restricted number of permits
(areas A + B). If the permits are given to firms, these rents accrue
to shareholders. The government could partly or fully capture the
rents by selling the permits or by a tax per unit of emissions (Ful-
lerton and Metcalf, 2001).
Fourth, because the policy restricts GHG emissions, it confers ben-
efits on those who would otherwise suffer from climate change.
The value of those benefits is areas C + D + E.
Fifth, the electricity sector uses less labour, capital and other
resources. It no longer pays them (areas E + F). With perfect
mobility, these factors are immediately redeployed elsewhere,
with no loss. In practice however, social costs may be substan-
tial, including transaction costs of shifting to other industries or
regions, transitional or permanent unemployment, and social and
psychological displacement.
Sixth, any gain or loss described above can be capitalized into
asset prices, with substantial immediate effects for current own-
ers. For example, the value of a corporation that owns coal-fired
generation assets may fall, in line with the expected present value
of the policy change, while the value of corporations that own
low-emissions generation technologies may rise.
The connection between these distributional effects and
‘economic efficiency’ is revealed by adding up all the gains
and losses just described: the consumer surplus loss is A + D;
producer surplus loss is B + E; the gain in scarcity rents is A + B;
and the environmental gain is C + D + E, assuming the gainers
and losers receive equal weights. The net sum of the gains and
losses is area C, described above as the net gain in economic
efficiency.
In many cases, a distributional implication of imposing effi-
cient externality pricing (e. g., area A + B) is much larger than
the efficiency gains (area C). This illustrates the importance of
distributional considerations in discussions on emissions-reducing
policies, and it indicates why distributional considerations often
loom large in debates about climate policy.
238238
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
ness and whether regulatory and other costs are equitably distributed
across society (Rist, 1998). The ability of governments to implement
political decisions may be hampered by interest groups; policies will
be more feasible if the benefits can be used to buy the support of a
winning coalition (Compston, 2010). Ex ante, these criteria can be used
in assessing and improving policies. Ex post, they can be used to verify
results, withdraw inefficient policies and correct policy performance.
For specific applications, see Chapters 7 – 15.
3�7�2 Analytical methods for decision support
Previous IPCC Assessment Reports have addressed analytical methods
to support decision making, including both numerical and case-based
methods. Bruce etal. (1996, chap. 2 and 10) focus heavily on quantita-
tive methods and IAMs. Metz etal. (2001) provide a wider review of
approaches, including emerging participatory forms of decision mak-
ing. Metz etal. (2007) briefly elaborate on quantitative methods and
list sociological analytical frameworks. In this section, we summarize
the core information on methodologies separated into quantitative-
and qualitative-oriented approaches.
3�7�2�1 Quantitative-oriented approaches
In decision making, quantitative methods can be used to organize and
manage numerical information, provide structured analytical frame-
works, and generate alternative scenarios — with different levels of
uncertainty (Majchrzak, 1984). An approach that attempts to estimate
and aggregate monetized values of all costs and benefits that could
result from a policy is CBA. It may require estimating non-market val-
ues, and choosing a discount rate to express all costs and benefits
in present value. When benefits are difficult to estimate in monetary
terms, a Cost-Effectiveness Analysis (CEA) may be preferable. A CEA
can be used to compare the costs of different policy options (Tieten-
berg, 2006) for achieving a well-defined goal. It can also estimate and
identify the lowest possible compliance costs, thereby generating a
ranking of policy alternatives (Levin and McEwan, 2001). Both CEA
and CBA are similarly limited in their ability to generate data, measure
and value future intangible costs.
Various types of model can provide information for CBA, including
energy-economy-environment models that study energy systems and
transitions towards more sustainable technology. A common classifi-
cation of model methodologies includes ‘bottom-up’ and ‘top-down’
approaches. Hybrids of the two can compensate for some known limi-
tations and inherent uncertainties (Rivers and Jaccard, 2006):
25
25
The literature acknowledges that it is difficult to make a clear classification among
modelling approaches, as variations among categories and also alternative
simulation methodologies do exist (e. g., macroeconometric Keynesian models,
agent-based approaches) (Hourcade etal., 2006; Mundaca etal., 2010; Scrieciu
etal., 2013).
• Given exogenously defined macroeconomic and demographic sce-
narios, bottom-up models can provide detailed representations of
supply- and demand-side technology paths that combine both cost
and performance data. Conventional bottom-up models may lack a
realistic representation of behaviour (e. g., heterogeneity) and may
overlook critical market imperfections, such as transaction costs
and information asymmetries (e. g., Craig et al., 2002; DeCanio,
2003; Greening and Bernow, 2004).
• By contrast, top-down models, such as computable general equi-
librium (CGE), represent technology and behaviour using an aggre-
gate production function for each sector to analyze effects of poli-
cies on economic growth, trade, employment, and public revenues
(see, e. g., DeCanio, 2003). They are often calibrated on real data
from the economy. However, such models may not represent all
markets, all separate policies, all technological flexibility, and all
market imperfections (Laitner et al., 2003). Parameters are esti-
mated from historical data, so forecasts may not predict a future
that is fundamentally different from past experience (i. e., path
dependency) (Scheraga, 1994; Hourcade etal., 2006). For potential
technology change, many models use sub-models of specific sup-
ply or end-use devices based on engineering data (Jacoby etal.,
2006; Richels and Blanford, 2008; Lüken etal., 2011; Karplus etal.,
2013).
With CBA, it is difficult to reduce all social objectives to a single met-
ric. One approach to dealing with the multiple evaluation criteria is
Multi-Criteria Analysis, or MCA (Keeney and Raiffa, 1993; Greening
and Bernow, 2004). Some argue that analyzing environmental and
energy policies is a multi-criteria problem, involving numerous deci-
sion makers with diverse objectives and levels of understanding of the
science and complexity of analytical tools (Sterner, 2003; Greening and
Bernow, 2004). The advantage of MCA is that the analyst does not
have to determine how outcomes are traded-off by the policymaker.
For instance, costs can be separated from ecosystem losses. But even
with MCA, one must ultimately determine the appropriate trade-off
rates among the different objectives. Nevertheless, it can be a use-
ful way of analyzing problems where being restricted to one metric
is problematic, either politically or practically. CGE models can specify
consumer and producer behaviour and ‘simulate’ effects of climate
policy on various outcomes, including real gains and losses to different
groups (e. g., households that differ in income, region or demographic
characteristics). With behavioural reactions, direct burdens are shifted
from one taxpayer to another through changes in prices paid for vari-
ous outputs and received for various inputs. A significant challenge is
the definition of a ‘welfare baseline’ (i. e., identifying each welfare level
without a specific policy).
Integrated Assessment Models (IAMs) or simply Integrated Models
(IAs) combine some or all of the relevant components necessary to
evaluate the consequences of mitigation policies on economic activity,
the global climate, the impacts of associated climate change, and the
relevance of that change to people, societies, and economies. Some
239239
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
models may only be able to represent how the economy responds to
mitigation policy and no more; some models may include a physical
model of the climate and be able to translate changes in emissions
into changes in global temperature; some models may also include
a representation of the impacts of climate change; and some models
may translate those impacts into damage to society and economies.
Models can be highly aggregate (top-down) or detailed process analy-
sis models (bottom-up), or a combination of both (see also Chapter
6). Some IAMs relate climate change variables with other physical
and biological variables like crop yield, food prices, premature death,
flooding or drought events, or land use change (Reilly et al., 2013).
Computational limits may preclude the scales required for some cli-
mate processes (Donner and Large, 2008),
26
but recent attempts are
directed towards integrating human activities with full Earth System
models (Jones etal., 2013). All of the models used in WGIII (primarily
Chapter 6) focus on how mitigation policies translate into emissions;
none of those models have a representation of climate damages. IAMs
have been criticized in recent years (e. g., Ackerman etal., 2009; Pin-
dyck, 2013). Much of the most recent criticism is directed at models
that include a representation of climate damage; none of the models
used in Chapter 6 fall into this category. Refer to Chapter 6 for more
detail in this regard.
Other quantitative-oriented approaches to support policy evaluation
include tolerable windows (Bruckner etal., 1999), safe-landing / guard
rail (Alcamo and Kreileman, 1996), and portfolio theory (Howarth,
1996). Outside economics, those who study decision sciences empha-
size the importance of facing difficult value-based trade-offs across
objectives, and the relevance of various techniques to help stakehold-
ers address trade-offs (see, e. g., Keeney and Raiffa, 1993).
3�7�2�2 Qualitative approaches
Various qualitative policy evaluation approaches focus on the social,
ethical, and cultural dimensions of climate policy. They sometimes
complement quantitative approaches by considering contextual dif-
ferences, multiple decision makers, bounded rationality, information
asymmetries, and political and negotiation processes (Toth etal., 2001;
Halsnæs et al., 2007). Sociological analytical approaches examine
human behaviour and climate change (Blumer, 1956), including beliefs,
attitudes, values, norms, and social structures (Rosa and Dietz, 1998).
Focus groups can capture the fact that “people often need to listen to
others’ opinions and understandings to form their own” (Marshall and
Rossman, 2006, p. 114). Participatory approaches focus on process,
involving the active participation of various actors in a given decision-
making process (van den Hove, 2000). Participatory approaches in sup-
port of decision making include appreciation-influence-control, goal
26
Stanton et al. (2009) also place climate change models into categories (welfare
maximization, general equilibrium, partial equilibrium, cost minimization, and
simulation models).
oriented project planning, participatory rural appraisal, and beneficiary
assessment. MCA can also take a purely qualitative form. For the pros
and cons of participatory approaches, see Toth etal. (2001, p.652).
Other qualitative-oriented approaches include systematic client con-
sultation, social assessment and team up (Toth etal., 2001; Halsnæs
etal., 2007).
3.8 Policy instruments
and regulations
A broad range of policy instruments for climate change mitiga-
tion is available to policymakers. These include economic incentives,
such as taxes, tradeable allowances, and subsidies; direct regulatory
approaches, such as technology or performance standards; information
programs; government provision, of technologies or products; and vol-
untary actions.
Chapter 13 of WGIII AR4 provided a typology and definition of mitiga-
tion policy instruments. Here we present an update on the basis of new
research on the design, applicability, interaction, and political economy
of policy instruments, as well as on applicability of policy instruments
in developed and developing countries (see Box 3.8). For details about
applications and empirical assessments of mitigation policy instru-
ments, see Chapters 7 – 12 (sectoral level), Chapter 13 (international
cooperation), Chapter 14 (regional cooperation), and Chapter 15
(national and sub-national policies).
3�8�1 Economic incentives
Economic (or market) instruments include incentives that alter the con-
ditions or behaviour of target participants and lead to a reduction in
aggregate emissions. In economic policy instruments, a distinction is
made between ‘price’ and ‘quantity’. A tradeable allowance or permit
system represents a quantity policy whereby the total quantity of pol-
lution (a cap) is defined, and trading in emission rights under that cap
is allowed. A price instrument requires polluters to pay a fixed price per
unit of emissions (tax or charge), regardless of the quantity of emis-
sions.
3�8�1�1 Emissions taxes and permit trading
Both the approaches described above create a price signal as an incen-
tive to reducing emissions (see Box 3.7), which can extend throughout
the economy. Economic instruments will tend to be more cost-effective
than regulatory interventions and may be less susceptible to rent-seek-
ing by interest groups. The empirical evidence is that economic instru-
ments have, on the whole, performed better than regulatory instru-
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Social, Economic, and Ethical Concepts and Methods
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ments, but that in many cases improvements could have been made
through better policy design (Hahn, 1989; Anthoff and Hahn, 2010).
3�8�1�2 Subsidies
Subsidies can be used as an instrument of mitigation policy by correct-
ing market failures in the provision of low-carbon technologies and
products. They have a particular role in supporting new technologies.
Empirical research has shown that social rates of return on R&D can be
higher than private rates of return, since spillovers are not fully inter-
nalized by the firms (see 3.11).
Subsidies are also used to stimulate energy efficiency and renewable
energy production. Such subsidies do generally not fully correct nega-
tive externalities but rather support the alternatives, and are less effi-
cient alternatives to carbon taxes and emission trading for inducing
mitigation. Energy subsidies are often provided for fossil fuel produc-
tion or consumption, and prove to increase emissions and put heavy
burdens on public budgets (Lin and Jiang, 2011; Arze del Granado
etal., 2012; Gunningham, 2013). Lowering or removing such subsidies
would contribute to global mitigation, but this has proved difficult (IEA
etal., 2011).
Subsidies to renewable energy and other forms of government expen-
diture on mitigation also have other drawbacks. First, public funds
need to be raised to finance the expenditures, with well-known eco-
nomic inefficiencies arising from taxation (Ballard and Fullerton, 1992).
Second, subsidies, if not correcting market failures, can lead to exces-
sive entry into, or insufficient exit from, an industry (Stigler, 1971).
Third, subsidies can become politically entrenched, with the beneficia-
ries lobbying governments for their retention at the expense of society
overall (Tullock, 1975).
Hybrids of fees and subsidies are also in use. A renewable energy cer-
tificate system can be viewed as a hybrid with a fee on energy con-
sumption and a subsidy to renewable production (e. g., Amundsen and
Mortensen, 2001). Feebates (Greene et al., 2005) involve setting an
objective, such as average vehicle fuel economy; then firms or individu-
als that under-perform pay a fee per unit of under-performance and
over-performers receive a subsidy. The incentives may be structured to
generate no net revenue — the fees collected finance the subsidy.
3�8�2 Direct regulatory approaches
Prescriptive regulation involves rules that must be fulfilled by polluters
who face a penalty in case of non-compliance. Examples are perfor-
mance standards that specify the maximum allowable GHG emissions
from particular processes or activities; technology standards that man-
date specific pollution abatement technologies or production methods;
and product standards that define the characteristics of potentially
polluting products, including labelling of appliances in buildings, indus-
try, and the transport sector (Freeman and Kolstad, 2006).
These regulatory approaches will tend to be more suitable in circum-
stances where the reach or effectiveness of market-based instruments
is constrained because of institutional factors, including lack of mar-
kets in emissions intensive sectors such as energy. In ‘mixed econo-
mies’, where parts of the economy are based on command-and-control
Box 3�7 | Equivalence of emissions taxes and permit trading schemes
Price-based and quantity-based instruments are equivalent
under certainty, but differ in the extent of mitigation and costs
if emissions and abatement costs are uncertain to the regulator
(Weitzman, 1974). Hybrid instruments, where a quantity constraint
can be overridden if the price is higher or lower than a thresh-
old, have been shown to be more efficient under uncertainty
(Roberts and Spence, 1976; McKibbin and Wilcoxen, 2002; Pizer,
2002). Variants of hybrid approaches featuring price ceilings and
price floors have been implemented in recent emissions trading
schemes (Chapters 14 and 15). The possibility of periodic adjust-
ments to tax rates and caps and their implementation under
permit schemes further breaks down the distinction between
price-based and quantity-based market-based instruments.
Equivalence also exists for fiscal effects and the costs imposed on
emitters. Until recently, most of the literature has assumed that
emissions taxes and permit trading differ in the revenue they yield
for governments and the costs imposed on emitters, assuming
that emissions tax revenue fully accrues to governments while
under emissions trading schemes permits are given freely to
emitters. This was also the case in early policy practice (Chapters
14 and 15). It has been widely assumed that permit schemes are
easier to implement politically because permits are allocated free
to emitters. However, recognition has grown that permits can be
wholly or partly auctioned, and that an emissions tax need not
apply to the total amount of emissions covered (e. g., Aldy J.E.
etal., 2010; Goulder, 2013). Tax thresholds could exempt part of
the overall amount of an emitter’s liabilities, while charging the
full tax rate on any extra emissions, analogous to free permits
(Pezzey, 2003; Pezzey and Jotzo, 2012). Conversely, governments
could auction some or all permits in an emissions trading scheme,
and use the revenue to reduce other more distorting taxes and
charges (Section 3.6.3.3), assist consumers, or pay for complemen-
tary policies.
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Social, Economic, and Ethical Concepts and Methods
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approaches while others rely on markets, effective climate change mit-
igation policy will generally require a mix of market and non-market
instruments.
3�8�3 Information programmes
Reductions in GHG emissions can also be achieved by providing accu-
rate and comprehensive information to producers and consumers on
the costs and benefits of alternative options. Information instruments
include governmental financing of research and public statistics, and
awareness-raising campaigns on consumption and production choices
(Mont and Dalhammar, 2005).
3�8�4 Government provision of public goods
and services, and procurement
Government funding of public goods and services may be aimed
directly at reducing GHG emissions, for example, by providing infra-
structures and public transport services that use energy more effi-
ciently; promoting R&D on innovative approaches to mitigation; and
removing legal barriers (Creutzig etal., 2011).
3�8�5 Voluntary actions
Voluntary agreements can be made between governments and pri-
vate parties in order to achieve environmental objectives or improve
environmental performance beyond compliance with regulatory obli-
gations. They include industry agreements, self-certification, environ-
mental management systems, and self-imposed targets. The literature
is ambiguous about whether any additional environmental gains are
obtained through voluntary agreements (Koehler, 2007; Lyon and Max-
well, 2007; Borck and Coglianese, 2009).
3�8�6 Policy interactions and complementarity
Most of the literature deals with the use and assessment of one instru-
ment, or compares alternative options, whereas, in reality, numerous,
often overlapping instruments are in operation (see Chapters 7 – 16).
Multiple objectives in addition to climate change mitigation, such
as energy security and affordability and technological and industrial
development, may call for multiple policy instruments. Another ques-
tion is whether and to what extent emissions pricing policies need to
be complemented by regulatory and other instruments to achieve cost-
effective mitigation, for example, because of additional market failures,
as in the case of energy efficiency (Box 3.10) and technological devel-
opment (3.11.1).
However, the coexistence of different instruments creates synergies,
overlaps and interactions that may influence the effectiveness and
costs of policies relative to a theoretical optimum (Kolstad etal., 1990;
see also Section 3.6 above). Recent studies have analyzed interactions
between tradeable quotas or certificates for renewable energy and
emission trading (e. g., Möst and Fichtner, 2010; Böhringer and Rosen-
dahl, 2010) and emissions trading and tradeable certificates for energy
efficiency improvements (e. g., Mundaca, 2008; Sorrell etal., 2009) (see
also Chapters 9 and 15). Similar effects occur in the overlay of other
selective policy instruments with comprehensive pricing instruments.
Policy interactions can also create implementation and enforcement
challenges when policies are concurrently pursued by different legal
or administrative jurisdictions (Goulder and Parry, 2008; Goulder and
Stavins, 2011).
3�8�7 Government failure and policy failure
To achieve large emissions reductions, policy interventions will be
needed. But failure is always a possibility, as shown by recent experi-
ences involving mitigation policies (Chapters 13 – 16). The literature is
beginning to reflect this. The failure of such policies tends to be asso-
ciated with the translation of individual preferences into government
action.
3�8�7�1 Rent-seeking
Policy interventions create rents, including subsidies, price changes
arising from taxation or regulation, and emissions permits. Private
interests lobby governments for policies that maximize the value of
their assets and profits. The sums involved in mitigating climate change
provide incentives to the owners of assets in GHG intensive industries
or technologies for low-carbon production to engage in rent-seeking.
27
The political economy of interest group lobbying (Olson, 1971) is
apparent in the implementation of climate change mitigation policies.
Examples include lobbying for allocations of free permits under the
emissions trading schemes in Europe (Hepburn etal., 2006; Sijm etal.,
2006; Ellerman, 2010) and Australia (Pezzey et al., 2010) as well as
renewable energy support policies in several countries (Helm, 2010).
To minimize the influence of rent-seeking and the risk of regulatory
capture, two basic approaches have been identified (Helm, 2010).
One is to give independent institutions a strong role, for example, the
United Kingdom’s Committee on Climate Change (McGregor et al.,
2012) and Australia’s Climate Change Authority (Keenan R.J et al.,
2012) (see also Chapter 15).
Another approach to reducing rent-seeking is to rely less on regulatory
approaches and more on market mechanisms, which are less prone to
capture by special interests because the value and distribution of rents
27
CBA takes into account that governments are social-profit maximizers, which may
not necessarily be the case.
242242
Social, Economic, and Ethical Concepts and Methods
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Chapter 3
is more transparent. This may of course lead to other problems associ-
ated with regulatory design.
3�8�7�2 Policy uncertainty
One aim of climate change mitigation policy is to promote emissions-
reducing investments in sectors where assets have a long economic
lifespan, such as energy (Chapter 7), buildings (Chapter 9) and transport
(Chapter 8). Investment decisions are mainly based on expectations
about future costs and revenues. Therefore, expectations about future
policy settings can be more important than current policies in determin-
ing the nature and extent of investment for mitigation (Ulph, 2013).
Uncertainty over future policy directions, including changes in existing
policies arising from, say, political change, can affect investment deci-
sions and inhibit mitigation, as well as create economic costs
(Weitzman, 1980; see also Chapter 2). To achieve cost-effective mitiga-
tion actions, a stable and predictable policy framework is required.
3.9 Metrics of costs
and benefits
This section focuses on conceptual issues that arise in the quantifica-
tion and measurement, using a common metric, of the pros and cons
associated with mitigation and adaptation (i. e., benefits and costs).
How costs are balanced against benefits in evaluating a climate policy
is a matter for ethics, as has repeatedly been emphasized in this chap-
ter. The discussion is largely based on the economic paradigm of bal-
ancing costs against benefits, with both measured in monetary units.
But leaving aside how benefits and costs are monetized or balanced
to develop policy, the underlying information can be helpful for policy
makers who adopt other ethical perspectives. This section is also rel-
evant for methods that reduce performance to a small number of met-
rics rather than a single one (such as MCA).
We begin with the chain of cause and effect. The chain starts with
human activity that generates emissions that may be reduced with
mitigation (recognizing that nature also contributes to emissions of
GHGs). The global emissions of GHGs lead to changes in atmospheric
concentrations, then to changes in radiative forcing, and finally to
changes in climate. The latter affect biological and physical systems in
good as well as bad ways (including through impacts on agriculture,
forests, ecosystems, energy generation, fire, and floods). These changes
in turn affect human wellbeing, negatively or positively, with both
monetary and other consequences.
28
Each link in the chain has a time
dimension, since emissions at a particular point in time lead to radia-
tive forcing at future points in time, which later lead to more impacts
and damages. The links also have spatial dimensions. Models play a key
role in defining the relationships between the links in the chain. Global
Climate Models (GCMs) translate emissions through atmospheric con-
centrations and radiative forcing into changes in climate. Other mod-
els — including crop, forest growth and hydrology models — translate
28
We refer to effects on biological and physical systems as ‘impacts’, and effects of
those impacts on human wellbeing as ‘damages’, whether positive or negative.
These effects may include non-human impacts that are of concern to humans (see
also Sections 3.4.1 and 3.4.3).
Box 3�8 | Different conditions in developed and developing countries and implications for suit-
ability of policy instruments
Differences in economic structure, institutions, and policy objec-
tives between low-income and high-income countries can mean
differences in the suitability and performance of policy instru-
ments. Overriding policy objectives in most developing countries
tend to be strongly oriented towards facilitating development (Kok
etal., 2008), increasing access to energy and alleviating poverty
(see Chapters 4 and 14). In general, they have fewer human and
financial resources, less advanced technology, and poorer institu-
tional and administrative capacity than developed countries. This
may constrain their ability to evaluate, implement, and enforce
policies. Further, the prerequisites for effectiveness, such as liberal-
ized energy markets to underpin price-based emissions reduc-
tion instruments, are often lacking. Thus, the use of some policy
instruments, including carbon trading schemes, can pose greater
institutional hurdles and implementation costs, or not be feasible.
Capacity building is therefore critical in creating mechanisms to
support policy choices and implementation. Economic reform may
also be needed in order to remove distortions in regulatory and
pricing mechanisms and enable effective mitigation policies to be
devised and implemented.
The opportunity cost of capital, and of government resources in
particular, may be higher in developing countries than in devel-
oped countries. Consequently, the payoff from mitigation policies
needs to be higher than in developed countries in order for
mitigation investment to be judged worthwhile. Thus, developing
countries may require international financial assistance in order
to support their mitigation activities or make them economically
viable.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
changes in climate into physical impacts. Economic models translate
those impacts into measures that reflect a human perspective, typically
monetary measures of welfare loss or gain. GCMs aggregate emissions
of various gases into an overall level of radiative forcing; hydrology
models aggregate precipitation at multiple locations within a water-
shed into stream flow at a given location; economic models aggregate
impacts into an overall measure of welfare loss.
Much of the literature on impacts focuses on particular types of
impacts at particular locations. Another aspect involves metrics that
allow differential regulation of different GHGs, for instance, the rela-
tive weight that regulators should place on CH
4
and CO
2
in mitigation
strategies. Because impacts and damages are so poorly known it has
proved surprisingly difficult to provide a rigorous answer to that ques-
tion.
3�9�1 The damages from climate change
The impacts of climate change may benefit some people and harm
others. It can affect their livelihood, health, access to food, water and
other amenities, and natural environment. While many non-monetary
metrics can be used to characterize components of impacts, they pro-
vide no unambiguous aggregation methods for characterizing over-
all changes in welfare. In principle, the economic theory of monetary
valuation provides a way, albeit an imperfect one, of performing this
aggregation and supporting associated policy-making processes.
Changes that affect human wellbeing can be ‘market’ or ‘non-market’
changes. Market effects involve changes in prices, revenue and net
income, as well as in the quantity, quality, or availability of market
commodities. Key is the ability to observe both prices and how people
respond to them when choosing quantities to consume. Non-market
changes involve the quantity, quality, or availability of things that mat-
ter to people and which are not obtained through the market (e. g.,
quality of life, culture, and environmental quality). A change in a physi-
cal or biological system can generate both market and non-market
damage to human wellbeing. For example, an episode of extreme heat
in a rural area may generate heat stress in farm labourers and may
dry up a wetland that serves as a refuge for migratory birds, while kill-
ing some crops and impairing the quality of others. From an economic
perspective, damages would be conceptualized as a loss of income for
farmers and farm workers, an increase in crop prices for consumers
and a reduction in their quality; and non-market impacts might include
the impairment of the ecosystem and human health (though some
health effects may be captured in the wages of farm workers).
Economists define value in terms of a ‘trade-off’. As discussed in Sec-
tion 3.6.1, the economic value of an item, measured in money terms,
is defined as the amount of income that would make a person whole,
either in lieu of the environmental change or in conjunction with the
environmental change; that is, its ‘income equivalent’. This equivalence
is evaluated through the Willingness To Pay (WTP) and Willingness To
Accept (WTA) compensation measures (see also Willig, 1976; Hane-
mann, 1991). The item in question may or may not be a marketed com-
modity: it can be anything that the person values. Thus, the economic
value of an item is not in general the same as its price or the total
expenditure on it. The economic concept of value based on a trade-off
has some critics. The item being valued may be seen as incommensu-
rable with money, such that no trade-off is possible. Or, the trade-off
may be deemed inappropriate or unethical (e. g., Kelman, 1981; see
also Jamieson, 1992; Sagoff, 2008). In addition, while the economic
concept of value is defined for an individual, it is typically measured for
aggregates of individuals, and the issue of equity-weighting is often
disregarded (Nyborg, 2012; see also Subsection 3.5.1.3).
29
The methods used to measure WTP and WTA fall into two categories,
known as ‘revealed preference’ and ‘stated preference’ methods. For a
marketed item, an individual’s purchase behaviour reveals information
about their value of it. Observation of purchase behaviour in the mar-
ketplace is the basis of the revealed preference approaches. One can
estimate a demand function from data on observed choice behaviour.
Then, from the estimated demand function, one can infer the purchas-
er’s WTP or WTA values for changes in the price, quantity, quality, or
availability of the commodity. Another revealed preference approach,
known as the hedonic pricing method, is based on finding an observed
relationship between the quality characteristics of marketed items and
the price at which they are sold (e. g., between the price of farmland
and the condition and location of the farmland). From this approach,
one can infer the ’marginal’ value of a change in characteristics.
30
For
instance, some have attempted to measure climate damages using an
hedonic approach based on the correlation of residential house prices
and climate in different areas (Cragg and Kahn, 1997; Maddison, 2001,
2003; Maddison and Bigano, 2003; Rehdanz and Maddison, 2009). The
primary limitation of revealed preference methods is the frequent lack
of a market associated with the environmental good being valued.
With stated preference, the analyst employs a survey or experiment
through which subjects are confronted with a trade-off. With contin-
gent valuation, for example, they are asked to choose whether or not
to make a payment, such as a tax increase that allows the govern-
ment to undertake an action that accomplishes a specific outcome
(e. g., protecting a particular ecosystem). By varying the cost across
subjects and then correlating the cost offered with the percentage of
‘yes’ responses, the analyst traces out a form of demand function from
which the WTP (or WTA) measure can be derived. With choice experi-
ments, subjects are asked to make repeated choices among alternative
29
The use of the term ‘willingness’ in WTP and WTA should not be taken literally. For
instance, individuals may have a willingness to pay for cleaner air (the reduction
in income that would be equivalent in welfare terms to an increase in air quality)
but they may be very unwilling to make that payment, believing that clean air is a
right that should not have to be purchased.
30
Details of these methods can be found in Becht (1995), chapters by McConnell
and Bockstael (2006), Palmquist (2006), Phaneuf and Smith (2006), Mäler and
Vincent (2005), or in textbooks such as Kolstad (2010), Champ, Boyle and Brown
(2003), Haab and McConnell (2002) or Bockstael and McConnell (2007).
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
options that combine different outcomes with different levels of cost.
31
Although a growing number of researchers use stated preference stud-
ies to measure the public’s WTP for climate change mitigation, one
prominent criticism is the hypothetical nature of the choices involved.
32
All these methods have been applied to valuing the damages from cli-
mate change.
33
AR2 contained a review of the literature on the eco-
nomic valuation of climate change impacts. Since then, the literature
has grown exponentially. The economic methodology has changed
little (except for more coverage of non-market impacts and more use
of stated preference). The main change is in the spatial representa-
tion of climate change impacts; whereas the older literature tended
to measure the economic consequences of a uniform increase of, say
2.5 °C across the United States, the recent literature uses downscaling
to measure impacts on a fine spatial scale. Most of the recent literature
on the economic valuations of climate change has focused on market
impacts, especially impacts on agriculture, forestry, sea level, energy,
water, and tourism.
34
The most extensive economic literature pertains to agriculture. The
demand for many such commodities is often inelastic, so the short-run
consequence of a negative supply shock is a price increase; while a
benefit to producers, it is harmful for consumers (Roberts and Schlenker,
2010; Lobell etal., 2011). Some studies measure the effect of weather
on current profits, rather than that of climate on long-term profitability
(e. g., Deschênes and Greenstone, 2007), and some explore the effect
of both weather and climate on current profits (Kelly et al., 2005).
Examining weather and climate simultaneously leads to difficulties
in identifying the separate effects of weather and climate (Deschênes
and Kolstad, 2011), as well as in dealing with the confounding effects
of price changes (Fisher etal., 2012). While some recent studies have
found that extreme climate events have a disproportionate impact on
agricultural systems (Schlenker and Roberts, 2009; Lobell etal., 2011;
Deschênes and Kolstad, 2011; see also WGII, Section 7.3.2.1), the
relatively high degree of spatial or temporal aggregation means that
31
Details can be found in Carson and Hanemann (2005), or in textbooks such as
Champ, Boyle and Brown (2003), Haab and McConnell (2002), and Bennett and
Blamey (2001).
32
Examples include Berrens et al. (2004), Lee and Cameron (2008), Solomon and
Johnson (2009), and Aldy et al. (2012) for the U. S.; Akter and Bennett (2011) for
Australia; Longo et al. (2012) for Spain; Lee et al. (2010) for Korea; Adaman et al.
(2011) for Turkey; and Carlsson et al. (2012) for a comparative study of WTP in
China, Sweden and the US.
33
Other economic measures of damage are sometimes used that may not be
appropriate. The economic damage is, in principle, the lesser of the value of what
was lost or the cost of replacing it (assuming a suitable and appropriate replace-
ment exists). Therefore, the replacement cost itself may or may not be a relevant
measure. Similarly, if the cost of mitigation is actually incurred, it is a lower bound
on the value placed on the damage avoided. Otherwise, the mitigation cost is
irrelevant if nobody is willing to incur it.
34
While there is a large literature covering physical and biological impacts, except
for agriculture and forestry only a tiny portion of the literature carries the analysis
to the point of measuring an economic value. However, the literature is expanding.
A Web of Knowledge search on the terms (“climate change” or “global warm-
ing”) and “damage” and “economic impacts” returns 39 papers for pre-2000,
136 papers for 2000 – 2009 and 209 papers for 2010 through September 2013.
those events are not well captured in many existing economic analy-
ses. Another difficulty is the welfare significance of shifts in location
of agricultural production caused by climate. Markets for agricultural
commodities are national or international in scope, so some economic
analyses focus on aggregate international producer and consumer
welfare. Under the potential Pareto criterion, transfers of income from
one region to another are of no welfare significance, though of real
policy significance.
35
With other market sectors, the literature is both sparse and highly frag-
mented, but includes some estimates of economic impacts of climate
change on energy, water, sea level rise, tourism, and health in partic-
ular locations. With regard to energy, climate change is expected to
reduce demand for heating and increase demand for cooling (see WGII
AR5, Chapter 10). Even if those two effects offset one another, the eco-
nomic cost need not be negligible. With water supply, what matters in
many cases is not total annual precipitation but the match between
the timing of precipitation and the timing of water use (Strzepek and
Boehlert, 2010). Those questions require analysis on a finer temporal
or spatial scale than has typically been employed in the economic
damage literature.
Estimates of the economic costs of a rise in sea level generally focus on
either the property damage from flooding or on the economic costs of
prevention, for example, sea wall construction (Hallegatte etal., 2007;
Hallegatte, 2008; 2012). They sometimes include costs associated with
the temporary disruption of economic activity. Estimates typically do
not measure the loss of wellbeing for people harmed or displaced by
flooding.
36
Similarly, the economic analyses of climate change impacts
on tourism have focused on changes, for example, in the choice of
destination and the income from tourism activities attributable to an
increase in temperature, but not on the impacts on participants’ well-
being.
37
The economic metrics conventionally used in the assessment of non-
climate health outcomes have also been used to measure the impact
of climate on health (e. g., Deschênes and Greenstone, 2011; Watkiss
and Hunt, 2012). Measures to reduce GHGs may also reduce other pol-
lutants associated with fossil fuel combustion, such as NO
x
and par-
ticulates, which lead to time lost from work and reduced productivity
(Östblom and Samakovlis, 2007). Exposure to high ambient tempera-
35
The same issue arises with the effects on timber production in a global timber
market; see for example, Sohngen et al. (2001).
36
Exceptions include Daniel et al. (2009) and Botzen and van den Bergh (2012).
Cardoso and Benhin (2011) provide a stated preference valuation of protecting
the Columbian Caribbean coast from sea level rise.
37
Exceptions include Pendleton and Mendelsohn (1998); Loomis and Richardson
(2006); Richardson and Loomis (2004); Pendleton et al. (2011); Tseng and Chen
(2008); and for commercial fishing, Narita et al. (2012).
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
tures is known to diminish work capacity and reduce labour produc-
tivity.
38
3�9�2 Aggregate climate damages
This section focuses on the aggregate regional and global economic
damages from climate change as used in IAMs to balance the benefits
and costs of mitigation on a global scale.
The first estimates of the economic damage associated with a specific
degree of climate change were made for the United States (Smith and
Tirpak, 1989; Nordhaus, 1991; Cline, 1992; Titus, 1992; Fankhauser,
1994). These studies involved static analyses estimating the damage
associated with a particular climate end-point, variously taken to be a
1 °C, 2.5 °C, or 3 °C increase in global average annual temperature. This
approach gave way to dynamic analyses in IAMs that track economic
output, emissions, atmospheric CO
2
concentration, and damages.
Because some IAMs examine costs and benefits for different levels of
emissions, they need damage ‘functions’ rather than point estimates.
Three IAMs have received most attention in the literature, all initially
developed in the 1990s. The DICE model was first published in Nord-
haus (1993a; b) but had its genesis in Nordhaus (1977); its regionally
disaggregated sibling RICE was first published by Nordhaus and Yang
(1996).
39
The FUND model was first published in Tol (1995). And the
PAGE model, developed for European decision makers, was first pub-
lished in Hope etal. (1993) and was used in the Stern (2007) review.
40
The models have undergone various refinements and updates.
41
While
details have changed, their general structure has stayed the same, and
questions remain about the validity of their damage functions (see Pin-
dyck, 2013).
The IAMs use a highly aggregated representation of damages. The spa-
tial unit of analysis in DICE is the entire world, whereas the worldis
divided into 12 broad regions in RICE, 16 regions in FUND, and eight
in PAGE. DICE and RICE have a single aggregate damage function for
the change in global or regional GDP as a function of the increase
in global average temperature, here denoted ΔT
t
, and sea-level rise
38
See Kjellstrom et al. (2009), Zivin and Neidell (2010), or Dunne et al. (2013). Some
recent studies have focused on the correlation between high temperatures and
poverty (Nordhaus, 2006), the link between fluctuations in temperature, cyclones
and fluctuations in economic activity (Dell et al., 2009, 2012; Hsiang, 2010), and
the connection between climate change and human conflict (Hsiang et al., 2013).
39
There are many extensions of DICE, including AD-DICE (de Bruin et al., 2009), with
a more explicit treatment of adaptation.
40
Some other IAMs have damage functions, including the MERGE Model (Manne
and Richels, 1992, 1995, 2004a); the CETA model (Peck and Teisberg, 1992,
1994); and, more recently, several IAMs developed by European researchers
including the WITCH model (Bosetti et al., 2006), its extension the AD-WITCH
model (Bosello et al., 2010), the ENVISAGE model (Roson and Mensbrugghe,
2012), and a model developed by Eboli et al. (2010) and Bosello et al. (2012).
41
The most recent versions are: DICE2013 (Nordhaus and Sztorc, 2013); RICE2010
(Nordhaus, 2010); PAGE 2009 (Hope, 2011, 2013); FUND 3.7 (Anthoff and Tol,
2013).
(which in turn is modelled as a function of ΔT
t
). PAGE has four sepa-
rate damage functions for different types of damages in each region:
economic, non-economic, sea-level rise, and climate discontinuity (as
a function of ΔT
t
and the derivative rise in sea level). FUND has eight
sectoral damage functions for each region, with each damage depen-
dent on the regional ΔT
t
and, in some cases, the rate of change in ΔT
t
.
Adaptation and catastrophic damage are included in a very simple way
in some models (Greenstone etal., 2013).
Let D
jkt
denote damages of type j in year t and region k, expressed as a
proportion of per capita GDP in that year and region, Y
kt
. The damage
functions, say D
jkt
= D
jkt
(ΔT
t
) are calibrated based on: (1) the modeller’s
choice of a particular algebraic formula for D
jkt
(ΔT
t
): (2) the common
assumption of zero damage at the origin [D
jkt
(0)=0]; and (3) the mod-
eller’s estimate of damages at a benchmark change in global average
temperature, ΔT* (typically associated with a doubling of atmospheric
CO
2
). For example, in the original versions of PAGE and DICE the dam-
age function resolves into a power function:
Equation 3�9�1 D
jt
= a
j
[ΔT
t
/ ΔT*]
b
Y
t
where b is a coefficient estimated or specified by the modeller, and
a
j
is the modeller’s estimate of the economic damage for the bench-
mark temperature change.
42
In DICE, b = 2 is chosen.
43
In PAGE, b is
a random variable between 1.5 and 3. In FUND, the damage functions
are deterministic but have a slightly more complicated structure and
calibration than in Equation 3.9.1.
Because each damage function is convex (with increasing marginal
damage), the high degree of spatial and temporal aggregation causes
the model to understate aggregate damages. This can be seen by rep-
resenting the spatial or temporal distribution of warming by a mean
and variance, and writing expected damages in a second order expan-
sion around the mean.
A concern may be whether the curvature reflected in Equation 3.9.1
is adequate. The functions are calibrated to the typical warming asso-
ciated with a doubling of CO
2
concentration, along with associated
damage. The aggregate damage is based on heroic extrapolations to
a regional or global scale from a sparse set of studies (some from the
1990s) done at particular geographic locations. The impacts literature
is now paying somewhat more attention to higher levels of warm-
ing (New etal. (2011), World Bank (2012), and WGII Section 19.5.1),
though estimates of monetary damage remain scarce (however, the
literature is expanding rapidly). Another concern is the possibility of
tipping points and extreme events (Lenton etal., 2008) (see also Box
3.9), possibly including increases in global temperature as large as
10 – 12 °C that are not always reflected in the calibration (Sherwood
and Huber, 2010).
42
Typically, ΔT* is 2.5 or 3
°C. When ΔT
t
= ΔT* in this equation, then D
jt
= a
j
Y
t
.
43
This formulation is also used by Kandlikar (1996) and Hammitt et al. (1996a) with
b = 1, 2 or 3.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
The economic loss or gain from warming in a given year typically
depends on the level of warming in that same year, with no lagged
effects (at least for damages other than sea-level rise in DICE, the
non-catastrophe component of damages in PAGE, and some sectors
of FUND). Thus, impacts are (a) reversible, and (b) independent of the
prior trajectory of temperatures. This assumption simplifies the com-
putations, but some impacts and damages may actually depend on
the rate of increase in temperature.
44
The optimal trajectory of mitiga-
44
This rate of change was considered by Manne and Richels (2004a) in MERGE and
by Peck and Teisberg (1994) in CETA. The latter found that it can have quite a
large effect on the size of the optimal carbon tax.
tion and the level of damages could also depend on the cumulative
amount of warming in previous years (measured, say, in degree
years).
DICE, FUND and PAGE represent damage as equivalent to a change in
production of market commodities that is proportional to output (a ‘mul-
tiplicative’ formulation). Weitzman (2010a) finds that this specification
matters with high levels of warming because an additive formulation
leads to more drastic emission reduction. Besides affecting current mar-
ket production, climate change could damage natural, human, or physi-
cal capital (e. g., through wildfires or floods). Damage to capital stocks
may last beyond a year and have lingering impacts that are not cap-
tured in current formulations (Wu etal., 2011). Economic consequences
Box 3�9 | Uncertainty and damages: the fat tails problem
Weitzman (2009, 2011) has drawn attention to what has become
known as the fat-tails problem. He emphasized the existence of a
chain of structural uncertainties affecting both the climate system
response to radiative forcing and the possibility of some resulting
impacts on human wellbeing that could be catastrophic. Uncer-
tainties relate to both means of distributions and higher moments.
The resulting compounded probability distribution of possible
economic damage could have a fat bad tail: i. e., the likelihood of
an extremely large reduction in wellbeing does not go quickly to
zero.
1
With or without risk aversion, the expected marginal reduc-
tion in wellbeing associated with an increment in emissions today
could be very large, even infinite
2
See also Section 2.5.3.3.
A policy implication of the conditions described in the previous
paragraph is that tail events can become much more important
in determining expected damage than would be the case with
probability distributions with thinner tails. Weitzman (2011) illus-
trates this for the distribution of temperature consequences of a
doubling of atmospheric CO
2
(climate sensitivity), using WGI AR4
estimates to calibrate two distributions, one fat-tailed and one
thin-tailed, to have a median temperature change of 3 °C and a
15 % probability of a temperature change in excess of 4.5 °C. With
this calibration, the probability of temperatures in excess of 8 °C
is nearly ten times greater with the fat-tailed distribution than
1
Weitzman (2009) defines a fat-tailed distribution as one with an infinite
moment generating function (a thin-tailed distribution has a finite moment
generating function); more intuitively, for a fat-tailed distribution, the tail
probability approaches zero more slowly than exponentially. For example,
the normal (and any distribution with finite support) would be thin-tailed
whereas the Pareto distribution (a power law distribution) would be fat-
tailed.
2
Weitzman (2007b, 2009) argued that the expected marginal reduction in
wellbeing could be infinite. His results have been challenged by some as
too pessimistic, e. g., Nordhaus (2011a), Pindyck (2011) and Costello et al.
(2010).
the thin-tailed distribution. If high consequence, low probability
events become more likely at higher temperatures, then tail events
can dominate the computation of expected damages from climate
change, depending on the nature of the probability distribution
and other features of the problem (including timing and discount-
ing).
At a more technical level, with some fat-tailed distributions and
certain types of utility functions (constant relative risk aversion),
the expectation of a marginal reduction in wellbeing associated
with an increment in emissions is infinite. This is because in these
cases, marginal utility becomes infinite as consumption goes to
zero. This is a troubling result since infinite marginal damage
implies all available resources should be dedicated to reducing
the effects of climate change. But as Weitzman himself and other
authors have pointed out, this extreme result is primarily a techni-
cal problem that can be solved by bounding the utility function or
using a different functional form.
The primary conclusion from this debate is the importance of
understanding the impacts associated with low probability,
high climate change scenarios. These may in fact dominate the
expected benefits of mitigation.
The policy implication of this conclusion is that the nature of
uncertainty can profoundly change how climate policy is framed
and analyzed with respect to the benefits of mitigation. Specifi-
cally, fatter tails on probability distributions of climate outcomes
increase the importance in understanding and quantifying the
impacts and economic value associated with tail events (such as
8 °C warming). It is natural to focus research attention on most
likely outcomes (such as a 3 °C warming from a CO
2
doubling),
but it may be that less likely outcomes will dominate the expected
value of mitigation.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
⇒
depend on what is assumed about the elasticity of substitution in the
utility function between market commodities and non-market climate
impacts. An elasticity of substitution of unity is equivalent to the conven-
tional multiplicative formulation, but a value less than unity, generates
a more drastic trajectory of emission reductions (Krutilla, 1967; Sterner
and Persson, 2008).
The utility function in these three IAMs does not distinguish between
the welfare gains deriving from risk reduction when people are risk
averse versus the gains from smoothing consumption over time
when people have declining marginal utility of income: both prefer-
ences are captured by the curvature of the utility function as mea-
sured by η, in
Equation 3.6.4
. However, Kreps and Porteus (1978) and
Epstein and Zin (1991) show that two separate functions can have
separate parameters for risk aversion and inter-temporal substitu-
tion. This formulation is used successfully in the finance literature to
explain anomalies in the market pricing of financial assets, including
the equity premium (Campbell, 1996; Bansal and Yaron, 2004). The
insight from this literature is that the standard model of discounted
expected utility, used in DICE, FUND and PAGE, sets the risk premium
too low and the discount rate too high, a result confirmed by Acker-
man etal. (2013) and Crost and Traeger (2013).
Our general conclusion is that the reliability of damage functions
in current IAMs is low. Users should be cautious in relying on them
for policy analysis: some damages are omitted, and some estimates
may not reflect the most recent information on physical impacts; the
empirical basis of estimates is sparse and not necessarily up-to-date;
and adaptation is difficult to properly represent. Furthermore, the lit-
erature on economic impacts has been growing rapidly and is often
not fullyrepresented in damage functions used in IAMs. Some authors
(e. g., WGII Chapter 19) conclude these damage functions are biased
downwards. It should be underscored that most IAMs used in Chapter
6 of this volume do not consider damage functions so this particular
criticism does not apply to Chapter 6 analyses.
3�9�3 The aggregate costs of mitigation
Reductions in GHG emission often impose costs on firms, households
(see also Box 3.10), and governments as a result of changes in prices,
revenues and net income, and in the availability or quality of com-
modities. GHG reduction requires not only technological but also
behavioural and institutional changes, which may affect wellbeing.
The changes in wellbeing are measured in monetary terms through
a change in income that is equivalent to the impact on wellbeing.
Changes in prices and incomes are often projected through economic
models (see Chapter 6). In many cases, mitigation primarily involves
improvements in energy efficiency or changes in the generation and
use of energy from fossil fuels in order to reduce GHG emissions.
The models assessed in Chapter 6 are called IAMs (or Integrated
Models — IMs) because they couple several systems together (such
as the economy and the climate) in an integrated fashion, track-
ing the impact of changes in economic production on GHG emis-
sions, as well as of emissions on global temperatures and the effect
of mitigation policies on emissions. As discussed in Section 6.2, the
IAMs used in Chapter 6 are heterogeneous. However, for most of the
Chapter 6 IAMs, climate change has no feedback effects on market
supply and demand, and most do not include damage functions.
45
45
Climate is assumed to be separable from market goods in the models’ utility
functions. If that assumption is incorrect, Carbone and Smith (2013) show that the
welfare calculation may have significant error.
Box 3�10 | Could mitigation have a negative private cost?
A persistent issue in the analysis of mitigation options and costs
is whether available mitigation opportunities can be privately
profitable — that is, generate benefits to the consumer or firm that
are in excess of their own cost of implementation — but which
are not voluntarily undertaken. Absent another explanation, a
negative private cost implies that a person is not fully pursuing his
own interest. (By contrast, a negative social cost arises when the
total of everybody’s benefits exceeds costs, suggesting that some
private decision-maker is not maximizing the interests of others.)
The notion that available mitigation opportunities may have
negative costs recently received attention because of analyses
by McKinsey & Company (2009), Enkvist etal. (2007) and others
that focused especially on energy use for lighting and heating in
residential and commercial buildings, and on some agricultural
and industrial processes. Much of this literature is in the context
of the “energy efficiency gap,”
1
which dates to the 1970s, and the
“Porter hypothesis”.
2
The literature suggesting that available opportunities may have
negative cost often points to institutional, political, or social
barriers as the cause. But other literature suggests economic
1
The efficiency gap is defined as the difference between the socially desirable
amount of energy efficiency (however defined) and what firms and consum-
ers are willing to undertake voluntarily (see Meier and Whittier, 1983; Joskow
and Marron, 1992, 1993; Jaffe and Stavins, 1994).
2
Porter (1991) and Porter and van der Linde (1995) argued that unilateral
reductions in pollution could stimulate innovation and improve firms’ com-
petitiveness as a by-product; see also Lanoie et al. (2008); Jaffe and Palmer
(1997). The subsequent literature has obtained mixed finding (Ambec and
Barla, 2006; Ambec et al., 2013).
248248
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
explanations. In addition, however, evidence indicates that the
extent of such negative cost opportunities can be overstated,
particularly in purely engineering studies.
Engineering studies may overestimate the energy savings, for
example because they assume perfect installation and mainte-
nance of the equipment (Dubin etal., 1986; Nadel and Keating,
1991) or they fail to account for interactions among different
investments such as efficient lighting and cooling (Hunting-
ton, 2011). Engineering studies also may fail to account for all
costs actually incurred, including time costs, scarce manage-
rial attention and the opportunity cost of the money, time, or
attention devoted to energy efficiency.
3
In some cases, the
engineering analysis may not account for reductions in qual-
ity (e. g., CFL lighting is perceived as providing less attractive
lighting services). Choices may also be influenced by uncertainty
(e. g., this is an unfamiliar product, one doesn’t know how
well it will work, or what future energy prices will be). Another
consideration sometimes overlooked in engineering analyses is
the rebound effect — the cost saving induces a higher rate of
equipment usage (see Section 3.9.5). The analyses may overlook
heterogeneity among consumers: what appears attractive for
the average consumer may not be attractive for all (or many)
consumers, based on differences in their circumstances and
preferences. One approach to validation is to examine energy
efficiency programs and compare ex ante estimates of efficiency
opportunities with ex post accomplishment; the evidence from
such comparisons appears to be inconclusive, though more
analysis may be fruitful.
4
Economic explanations for the apparent failure to pursue
profitable mitigation / energy saving opportunities include the
following.
5
Given uncertainty and risk aversion, consumers
may rationally desire a higher return as compensation. Price
uncertainty and the irreversibility of investment may also pose
additional economic barriers to the timing of adoption — it may
pay to wait before making the investment (Hassett and Metcalf,
3
For example, Anderson and Newell (2004) examined energy audits for manu-
facturing plants and found that roughly half of the projects recommended by
auditors were not adopted despite extremely short payback periods. When
asked, plant managers responded that as much as 93 % of the projects were
rejected for economic reasons, many of which related to high opportunity
costs. Joskow and Marron (1992, 1993) show some engineering estimates
understated actual costs.
4
Arimura et al. (2012) review US electricity industry conservation programmes
(demand side management — DSM) and conclude that programmes saved
energy at a mean cost of USD 0.05 per kWh, with a 90 % confidence interval
of USD 0.003 to USD 0.010. Allcott and Greenstone (2012) conclude that
this average cost is barely profitable. Although this may be true, one cannot
conclude that on this evidence alone that ex ante engineering estimates of
costs were too optimistic.
5
Allcott and Greenstone (2012) and Gillingham and Palmer (2014) provide
excellent reviews.
1993; Metcalf, 1994). Mitigation investments take time to pay
off, and consumers act as if they are employing high discount
rates when evaluating such investments (Hausman, 1979). These
consumer discount rates might be much higher than those of
commercial businesses, reflecting liquidity and credit constraints.
The durability of the existing capital stock can be a barrier to
rapid deployment of otherwise profitable new technologies. Also,
a principal-agent problem arises when the party that pays for an
energy-efficiency investment doesn’t capture all the benefits, or
vice versa. For example a tenant installs an efficient refrigerator,
but the landlord retains ownership when the tenant leaves (split
incentives). Or the landlord buys a refrigerator but doesn’t care
about its energy efficiency. Such problems can also arise in orga-
nizations where different actors are responsible, say, for energy
bills and investment accounts.
6
Finally, energy users, especially
residential users, may be uninformed, or poorly informed, about
the energy savings they are forgoing. In some cases, the seller
of the product has better information than the potential buyer
(asymmetric information) and may fail to convey that informa-
tion credibly (Bardhan etal., 2013).
Recently, some economists have suggested that systematic
behavioral biases in decision-making can cause a failure to
make otherwise profitable investment. These have been classi-
fied as non-standard beliefs (e. g., incorrect assessments of fuel
savings — Allcott, 2013), non-standard preferences (e. g., loss
aversion — Greene etal., 2009), and non-standard decision mak-
ing (e. g., tax salience — Chetty etal., 2009). Such phenomena
can give rise to what might be considered ‘misoptimization’ by
decision makers, which in turn could create a role for efficiency-
improving policy not motivated by conventional market failures
(Allcott etal., forthcoming); see Section 3.10.1 for a fuller
account.
In summary, whether opportunities for mitigation at negative
private cost exist is ultimately an empirical question. Both eco-
nomic and non-economic reasons can explain why they might
exist, as noted in recent reviews (Huntington, 2011; Murphy and
Jaccard, 2011; Allcott and Greenstone, 2012; Gillingham and
Palmer, 2014). But, evidence also suggests that the occurrence
of negative private costs is sometimes overstated, for reasons
identified above. This remains an active area of research and
debate.
6
Davis (2011) and Gillingham et al. (2012) provide evidence of principal-agent
problems in residential energy, although amount of energy lost as a result
was not large in the cases examined.
⇐
249249
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
The calculation of cost depends on assumptions made (1) in specify-
ing the model’s structure and (2) in calibrating its parameters. The
models are calibrated to actual economic data. While more valida-
tion is required, some models are validated by making and testing
predictions of the response to observed changes (Valenzuela etal.,
2007; Beckman etal., 2011; Baldos and Hertel, 2013). While some
models do not address either the speed or cost of adjustment, many
models incorporate adjustment costs and additional constraints to
reflect deviations from full optimization (see Jacoby et al., 2006;
Babiker et al., 2009; van Vuuren etal., 2009). Most models allow
little scope for endogenous (price-induced) technical change (3.11.4)
or endogenous non-price behavioural factors (3.10.1). It is a mat-
ter of debate how well the models accurately represent underlying
economic processes (see Burtraw, 1996; Burtraw etal., 2005; Hane-
mann, 2010).
Besides estimating total cost, the models can be used to estimate
Marginal Abatement Cost (MAC), the private cost of abating one
additional unit of emissions. With a cap-and-trade system, emissions
would theoretically be abated up to the point where MAC equals
the permit price; with an emissions tax, they would be abated to the
point where MAC equals the tax rate. It is common to graph the MAC
associated with different levels of abatement. Under simplified con-
ditions, the area under the MAC curve measures the total economic
cost of emissions reduction, but not if it fails to capture some of the
economy-wide effects associated with large existing distortions (Klep-
per and Peterson, 2006; Paltsev etal., 2007; Kesicki and Ekins, 2012;
Morris etal., 2012). However, a MAC is a static approximation to the
dynamic process involved in pollution abatement; it thus has its limi-
tations.
3�9�4 Social cost of carbon
Although estimates of aggregate damages from climate change are
useful in formulating GHG mitigation policies (despite the caveats
listed in Section 3.9.2), they are often needed for more mundane
policy reasons. Governments have to make decisions about regulation
when implementing energy policies, such as on fuel or EE standards
for vehicles and appliances. The social cost of carbon emissions can be
factored into such decisions.
To calculate the social cost, consider a baseline trajectory of emissions
(E
0
,…,E
t
) that results in a trajectory of temperature changes, ΔT
t
. Sup-
pose a damage function for year t is discounted to the present and
called D(ΔT
t
), as discussed in Equation 3.9.2. These trajectories result
in a discounted present value of damages:
Equation 3�9�2 PVD≡
∫
0
∞
D(Δ T
t
)dt
Then take the derivative with respect to a small change in emissions
at t=0, E
0
, to measure the extra cost associated with a one tonne
increase in emissions at time 0 (that is, the increment in PVD):
Equation 3�9�3 MDCC =
∂PVD
__
∂ E
0
When applied to CO
2
this equation gives the marginal damage from
the change in climate that results from an extra tonne of carbon. It
is also called the social cost of carbon (SCC). It should be empha-
sized that the calculation of SCC is highly sensitive to the projected
future trajectory of emissions and also any current or future regulatory
regime.
46
Because of its potential use in formulating climate or energy regula-
tory policy, governments have commissioned estimates of SCC. Since
2002, an SCC value has been used in policy analysis and regulatory
impact assessment in the United Kingdom (Clarkson and Deyes, 2002).
It was revised in 2007 and 2010. In 2010, a standardized range of SCC
values based on simulations with DICE, FUND, and PAGE using alterna-
tive projections of emissions and alternative discount rates, was made
available to all U. S. Government agencies.
47
It was updated in 2013
(US Interagency Working Group, 2013).
3�9�5 The rebound effect
Technological improvements in energy efficiency (EE) have direct
effects on energy consumption and thus GHG emissions, but can
cause other changes in consumption, production, and prices that
will, in turn, affect GHG emissions. These changes are generally
called ‘rebound’ or ‘takeback’ because in most cases they reduce
the net energy or emissions reduction associated with the effi-
ciency improvement. The size of rebound is controversial, with some
research papers suggesting little or no rebound and others conclud-
ing that it offsets most or all reductions from EE policies (Greening
etal., 2000; Binswanger, 2001; Gillingham etal., 2013, summarize
the empirical research). Total EE rebound can be broken down into
three distinct parts: substitution-effect, income-effect, and economy-
wide.
In end-use consumption, substitution-effect rebound, or ‘direct
rebound’ assumes that a consumer will make more use of a device
if it becomes more energy efficient because it will be cheaper to use.
Substitution-effect rebound extends to innovations triggered by the
improved EE that results in new ways of using the device. To pay for
that extra use, the individual must still consume less of something
else, so net substitution-effect rebound is the difference between the
energy expended in using more of the device and the energy saved
from using whatever was previously used less (see Thomas and Aze-
vedo, 2013).
46
Some ambiguity regards the definition of the SCC and the correct way to calculate
it in the context of an equilibrium IAM (in terms of distinguishing between a mar-
ginal change in welfare vs. a marginal change in damage only). See, for instance,
an account of the initial U. S. Government effort (Greenstone et al., 2013).
47
Obviously, estimates of the SCC are sensitive to the structural and data assump-
tions in the models used to compute the SCC. Weitzman (2013), for instance,
demonstrates the significance of the discount rate in the calculation.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
Income-effect rebound or ‘indirect rebound’, arises if the improvement
in EE makes the consumer wealthier and leads them to consume addi-
tional products that require energy. Even if energy efficient light bulbs
lead to no substitution-effect rebound (more lighting), income-effect
rebound would result if the consumer spends the net savings from
installing the bulbs on new consumption that uses energy. The income-
effect rebound will reflect the size of the income savings from the EE
improvement and the energy intensity of marginal income expendi-
tures.
Analogous rebound effects for EE improvements in production are
substitution towards an input with improved energy efficiency, and
substitution among products by consumers when an EE improve-
ment changes the relative prices of goods, as well as an income effect
when an EE improvement lowers production costs and creates greater
wealth.
Economy-wide rebound refers to impacts beyond the behaviour of
the entity benefiting directly from the EE improvement, such as the
impact of EE on the price of energy. For example, improved fuel econ-
omy lowers vehicle oil demand and prices leading some consumers
to raise their consumption of oil products. The size of this energy
price effect will be greater with less elastic supply and more elas-
tic demand. Some argue that the macroeconomic multiplier effects
of a wealth shock from EE improvement also create economy-wide
rebound.
Rebound is sometimes confused with the concept of economic leak-
age, which describes the incentive for emissions-intensive economic
activity to migrate away from a region that restricts GHGs (or other
pollutants) towards areas with fewer or no restrictions on such emis-
sions. Energy efficiency rebound will occur regardless of how broadly
or narrowly the policy change is adopted. As with leakage, however,
the potential for significant rebound illustrates the importance of con-
sidering the full equilibrium effects of a policy designed to address
climate change.
3�9�6 Greenhouse gas emissions metrics
The purpose of emissions metrics is to establish an exchange rate, that
is, to assign relative values between physically and chemically different
GHGs and radiative forcing agents (Fuglestvedt etal., 2003; Plattner
etal., 2009). For instance, per unit mass, CH
4
is a more potent GHG
than CO
2
in terms of instantaneous radiative forcing, yet it operates
on a shorter time scale. In a purely temporal sense, the impacts are
different. Therefore, how should mitigation efforts be apportioned for
emissions of different GHGs?
48
48
This issue is discussed in Chapter 8 of WGI.
GHG emissions metrics are required for generating aggregate GHG
emissions inventories; to determine the relative prices of different
GHGs in a multi-gas emissions trading system; for designing multi-gas
mitigation strategies; or for undertaking life-cycle assessment (e. g.,
Peters et al., 2011b). Since metrics quantify the trade-offs between
different GHGs, any metric used for mitigation strategies explicitly or
implicitly evaluates the climate impact of different gases relative to
each other.
The most prominent GHG emissions metric is the Global Warming
Potential (GWP), which calculates the integrated radiative forcing from
the emission of one kilogram of a component j out to a time horizon T:
Equation 3�9�4 AGW P
j
(
T
)
= ∫
0
T
R F
j
(
t
)
dt
The AGWP is an absolute metric. The corresponding relative metric is
then defined as GWP
j
= AGWP
j
/ AGWP
CO2
.
The GWP with a finite time horizon T was introduced by the IPCC
(1990). With a 100-year time horizon, the GWP is used in the Kyoto
Protocol and many other scientific and policy applications for convert-
ing emissions of various GHGs into ‘CO
2
equivalents’. As pointed out
in WGI, no scientific argument favours selecting 100 years compared
with other choices. Conceptual shortcomings of the GWP include: (a)
the choice of a finite time horizon is arbitrary, yet has strong effects on
metric value (IPCC, 1990); (b) the same CO
2
-equivalent amount of dif-
ferent gases may have different physical climate implications (Fuglest-
vedt etal., 2000; O’Neill, 2000; Smith and Wigley, 2000); (c) physical
impacts and impacts to humans (well-being) are missing; and (d) tem-
poral aggregation of forcing does not capture important differences in
temporal behaviour. Limitations and inconsistencies also relate to the
treatment of indirect effects and feedbacks (see WGI, Chapter 8).
Many alternative metrics have been proposed in the scientific lit-
erature. It can be argued that the net impacts from different gases
should be compared (when measured in the same units) and the rela-
tive impact used for the exchange rate. The Global Damage Potential
(GDamP) follows this approach by using climate damages as an impact
proxy, and exponential discounting for inter-temporal aggregation of
impacts (Hammitt etal., 1996b; Kandlikar, 1996). Since marginal dam-
ages depend on the time at which GHGs are emitted, the GDamP is
a time-variant metric. The GDamP accounts for the full causal chain
from emissions to impacts. One advantage of the framework is that
relevant normative judgements, such as the choice of inter-temporal
discounting and the valuation of impacts, are explicit (Deuber etal.,
2013). In practice, however, the GDamP is difficult to operationalize.
The difficulties in calculating the GDamP and SCC are closely related
(see Section 3.9.4).
The Global Cost Potential (GCP) calculates the time-varying ratio of
marginal abatement costs of alternative gases arising in a cost-effec-
tive multi-gas mitigation strategy given a prescribed climate target
(Manne and Richels, 2001), such as a cap on temperature change or
251251
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
on GHG concentrations. While the GCP avoids the problems associated
with damage functions, it still requires complex integrated energy-
economy-climate models to calculate GHG price ratios, and is therefore
less transparent to stakeholders than physical metrics.
49
The time-dependant Global Temperature Change Potential (GTP) is a
physical metric that does not involve integration of the chosen impact
parameter over time (Shine etal., 2007). It is defined as the relative
effect of different gases on temperature at a predefined future date
from a unit impulse of those gases. Typically these are normalized to
a base, such as same mass of CO
2
emitted. While the GWP and GTP
were not constructed with a specific policy target in mind, the GCP is
conceptually more consistent with a policy approach aiming at achiev-
ing climate objectives in a cost-effective way (Fuglestvedt etal., 2003;
Manning and Reisinger, 2011; Tol etal., 2012).
Virtually all absolute metrics (AM
j
) can be expressed in terms of a gen-
eralization of Equation 3.9.4 (Kandlikar, 1996; Forster etal., 2007):
Equation 3�9�5 A M
j
= ∫
0
∞
I
j
(
ΔT(t), RF(t), …
)
W
(
t
)
dt
where the impact function I
j
links the metric to the change in a physi-
cal climate parameter, typically the global mean radiative forcing RF
(e. g., in the case of the GWP) or the change in global mean tempera-
ture ∆T (e. g., GTP and most formulations of the GDamP). In some
cases, the impact function also considers the rate of change of a phys-
ical climate parameter (Manne and Richels, 2001; Johansson et al.,
2006).
49
In the context of a multi-gas integrated assessment model which seeks to mini-
mize the cost of meeting a climate target.
The temporal ‘weighting function, W(t)’, determines how the met-
ric aggregates impacts over time. It can prescribe a finite time hori-
zon (GWP), evaluation at a discrete point in time (GTP), or expo-
nential discounting over an infinite time horizon (GDamP), which is
consistent with the standard approach to inter-temporal aggrega-
tion used in economics (see Section 3.6.2). The weighting used in
the GWP is a weight equal to one up to the time horizon and zero
thereafter.
The categorization according to their choice of impact and temporal
weighting function (Table 3.4) serves to expose underlying explicit and
implicit assumptions, which, in turn, may reflect normative judgements.
It also helps to identify relationships between different metric concepts
(Tol et al., 2012; Deuber et al., 2013). In essence, the choice of an
appropriate metric for policy applications involves a trade-off between
completeness, simplicity, measurability, and transparency (Fuglestvedt
etal., 2003; Plattner etal., 2009; Deuber etal., 2013). The GDP and
GCP are cost effective in implementing multi-gas mitigation policies,
but are subject to large measurability, value-based, and scientific
uncertainties. Simple physical metrics, such as the GWP, are easier to
calculate and produce a more transparent result, but are inaccurate in
representing the relevant impact trade-offs between different GHGs
(Fuglestvedt etal., 2003; Deuber etal., 2013).
The choice of metric can have a strong effect on the numerical value of
GHG exchange rates. This is particularly relevant for CH
4
, which oper-
ates on a much shorter timescale than CO
2
. In WGI, Section 8.7, an
exchange ratio of CH
4
to CO
2
of 28 is given for GWP and of 4 for a time
horizon of 100 years for GTP.
50
For a quadratic damage function and a
50
See WGI Chapter 8, Appendix 8A for GWP and GTP values for an extensive list of
components.
Table 3�4 | Overview and classification of different metrics from the scientific literature.
Name of metric Impact function Atmospheric background Time dimension Reference
GWP Global Warming Potential RF Constant
Constant temporal weighting
over fixed time horizon
IPCC (1990)
GWP-LA
Global Warming Potential
(discounting)
RF
Constant, average of
future conditions
Exponential discounting Lashof and Ahuja (1990)
GTP-H
Global Temperature Change
Potential (fixed time horizon)
ΔT Constant
Evaluation at a fixed time
T after emission
Fuglestvedt etal., (2010),
Shine etal. (2005)
GTP(t)
Time-dependent global
temperature change potential
ΔT Time-varying
Evaluation at a fixed end
point time in the future
Shine etal. (2007)
CETP
Cost Effective Temperature
Potential
ΔT Exogenous scenario
Complex function of time when
climate threshold is reached
Johannson (2012)
MGTP
Mean Global Temperature
Change Potential
ΔT Time-varying
Constant temporal weighting
over fixed time horizon
Gillet and Mathews (2010),
Peters et al. (2011a)
GCP Global Cost Potential
Infinite damage above
climate target
Time-varying Exponential discounting Manne and Richels (2001)
GDamP Global Damage Potential D(ΔT) Time-varying Exponential discounting
Kandlikar (1996), Hammit
etal. (1996a)
252252
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
discount rate of 2 %, Boucher (2012) obtained a median estimate of
the GDamP exchange ratios of 24.3. This exchange rate obviously has
very significant implications for relative emphasis a country may place
on methane mitigation vs. carbon dioxide mitigation.
A small but increasing body of literature relates to the economic
implications of metric choice. A limited number of model-based
examinations find that, despite its conceptual short-comings, the
GWP-100 performs roughly similarly to GTP or a cost-optimizing
metric (such as the GCP) in terms of aggregate costs of reaching a
prescribed climate target, although regional and sectoral differences
may be significant (Godal and Fuglestvedt, 2002; Johansson etal.,
2006; Reisinger etal., 2013; Smith etal., 2013; Ekholm etal., 2013).
In other words, based on these few studies, the scope for reducing
aggregate mitigation costs of reaching a particular climate target by
switching to a metric other than the currently used GWP-100 may
be limited, although there may be significant differences in terms of
regional costs.
In the Kyoto Protocol, emission reductions of one GHG can be traded
with reductions in all other GHGs. Such ‘single-basket’ approaches
implicitly assume that the GHGs can linearly substitute each other in
the mitigation effort. However, the same CO
2
-equivalent amount of dif-
ferent GHGs can result in climate responses that are very different for
transitional and long-term temperature change, chiefly due to differ-
ent life-times of the substances (Fuglestvedt etal., 2000; Smith and
Wigley, 2000). As an alternative, multi-basket approaches have been
proposed, which only allow trading within groups of forcing agents
with similar physical and chemical properties (Rypdal etal., 2005; Jack-
son, 2009; Daniel etal., 2012; Smith etal., 2013). Smith etal. (2013)
propose a methodology for categorizing GHGs into two baskets of
(a) long-lived species, for which the cumulative emissions determine
the long-term temperature response, and (b) shorter-lived species
for which sustained emissions matter. Applying separate emission
equivalence metrics and regulations to each of the two baskets can
effectively control the maximum peak temperature reached under a
global climate policy regime. However, further research on the insti-
tutional requirements and economic implications of such an approach
is needed, as it requires regulators to agree on separate caps for each
basket and reduces the flexibility of emission trading systems to har-
vest the cheapest mitigation options.
3.10 Behavioural economics
and culture
This section summarizes behavioural economics related to climate
change mitigation. We focus on systematic deviations from the tra-
ditional neoclassical economic model, which assumes that prefer-
ences are complete, consistent, transitive, and non-altruistic, and that
humans have unbounded computational capacity and rational expec-
tations. In this context, social and cultural issues and conditions that
frame our attitudes, as well as living conditions, are also addressed.
Chapter 2 also considers behavioural questions, though primarily in
the context of risk and uncertainty.
Although the focus is on the behaviour of individuals, some firms and
organizations also take actions that appear to be inconsistent with the
standard neoclassical model of the profit-maximizing firm (Lyon and
Maxwell, 2007).
3�10�1 Behavioural economics and the cost of
emissions reduction
Behavioural economics deals with cognitive limitations (and abilities)
that affect people’s economic decision-making processes. Choices can
be affected and / or framed by perceived fairness, social norms, cooper-
ation, selfishness, and so on.
51
Behavioural economics emphasizes the
cognitive, social, and emotional factors that lead to apparently irratio-
nal choices. A growing number of documented systematic deviations
from the neoclassical model help explain people’s behaviour, but here
we focus on several that we see as most relevant to climate change
mitigation.
52
3�10�1�1 Consumer undervaluation of energy costs
Consumers may undervalue energy costs when they purchase energy-
using durables, such as vehicles, or make other investment decisions
related to energy use.
53
By ‘undervalue’, we mean that consumers’
choices systematically fail to maximize the utility they experience when
the choices are implemented (‘experienced’ utility) (Kahneman and
Sugden, 2005; see also, e. g., Fleurbaey, 2009). This misoptimization
reduces demand for EE. Three potential mechanisms of undervaluation
may be most influential (see also Box 3.10). First, when considering
a choice with multiple attributes, evidence suggests that consumers
are inattentive to add-on costs and ancillary attributes, such as ship-
ping and handling charges or sales taxes (Hossain and Morgan, 2006;
Chetty etal., 2009). It could be that EE is a similar type of ancillary
product attribute and is thus less salient at the time of purchase. Sec-
ond, significant evidence across many contexts also suggests that
humans are ‘present biased’ (DellaVigna, 2009). If energy costs affect
consumption in the future while purchase prices affect consumption
in the present, this would lead consumers to be less energy efficient.
Third, people’s beliefs about the implications of different choices may
51
See, e. g., Babcock and Loewenstein (1997), Shiv and Fedorikhin (1999), Asheim
et al. (2006), Barrett (2007), Levati et al. (2007), Potters et al. (2007), Shogren and
Taylor (2008) and Dannenberg et al. (2010).
52
See Rachlinksi (2000), Brekke and Johansson-Stenmann (2008), Gowdy (2008)
and the American Psychological Association (2010).
53
This can even apply to cases that use sophisticated methods to support decisions
(e. g., Korpi and Ala-Risku, 2008).
253253
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
be systematically biased (Jensen, 2010; Bollinger etal., 2011; Kling
et al., 2012; McKenzie et al., 2013). Attari et al. (2010) show that
people systematically underestimate the energy savings from a set
of household energy conserving activities, and Allcott (2013) shows
that the average consumer either correctly estimates or systematically
slightly underestimates the financial savings from more fuel-efficient
vehicles. Each of these three mechanisms of undervaluation appears
plausible based on results from other contexts. However, rigorous evi-
dence of misoptimization is limited in the specific context of energy
demand (Allcott and Greenstone, 2012).
Three implications arise for climate and energy policy if the aver-
age consumer who is marginal to a policy does, in fact, undervalue
energy costs. The first is an ‘internality dividend’ from carbon taxes
(or other policies that internalize the carbon externality into energy
prices): a carbon tax can actually increase consumer welfare when
consumers undervalue energy costs (Allcott etal., forthcoming). This
occurs because undervaluation would be a pre-existing distortion that
reduces demand for EE below consumers’ private optima, and one that
increasing carbon taxes helps to correct. Second, in addition to car-
bon taxes, other tax or subsidy policies that raise the relative purchase
price of energy-inefficient durable goods can improve welfare (Crop-
per and Laibson, 1999; O’Donoghue and Rabin, 2008; Fullerton etal.,
2011). Third, welfare gains are largest from policies that preferentially
target consumers who undervalue energy costs the most. This effect is
related to the broader philosophies of libertarian paternalism (Sunstein
and Thaler, 2003) and asymmetric paternalism (Camerer etal., 2003),
which advocate policies that do not infringe on freedom of choice but
could improve choices by the subset of people who misoptimize. In
the context of energy demand, such policies might include labels or
programmes that provide information about, and attract attention to,
energy use by durable goods.
3�10�1�2 Firm behaviour
Some of the phenomena described above may also apply to firms. Lyon
and Maxwell (2004, 2008) examine in detail the tendency of firms to
undertake pro-environment actions, such as mitigation, without being
prompted by regulation. Taking a neoclassical approach to the prob-
lem, they find that firms view a variety of pro-environment actions as
being to their advantage. However, evidence of a compliance norm
has been found in other contexts where firms’ responses to regulation
have been studied (Ayres and Braithwaite, 1992; Gunningham etal.,
2003).
The conventional economic model represents the firm as a single,
unitary decision-maker, with a single objective, namely, profit maxi-
mization. As an alternative to this ‘black-box’ model of the firm (Mal-
loy, 2002), the firm may be seen as an organization with a multiplic-
ity of actors, perhaps with different goals, and with certain distinctive
internal features (Coase, 1937; Cyert and March, 1963; Williamson,
1975).
3�10�1�3 Non-price interventions to induce behavioural
change
Besides carbon taxes and other policies that affect relative prices,
other non-price policy instruments can reduce energy demand, and,
therefore, carbon emissions. Such interventions include supplying
information on potential savings from energy-efficient investment,
drawing attention to energy use, and providing concrete examples of
energy-saving measures and activities (e. g., Stern, 1992; Abrahamse
etal., 2005). They also include providing feedback on historical energy
consumption (Fischer, 2008) and information on how personal energy
use compares to a social norm (Allcott, 2011).
54
In some cases, non-price energy conservation and efficiency pro-
grammes may have low costs to the programme operator, and it is
therefore argued that they are potential substitutes if carbon taxes
are not politically feasible (Gupta etal., 2007). However, it is question-
able whether such interventions are appropriate substitutes for carbon
taxes, for example, in terms of environmental and cost effectiveness,
because their impact may be small (Gillingham etal., 2006) and unac-
counted costs may reduce the true welfare gains. For example, con-
sumers’ expenditures on energy-efficient technologies and time spent
turning lights off may not be observed.
Research in other domains (e. g., Bertrand etal., 2010) has shown that
a person’s choices are sometimes not consistent. They may be mal-
leable by ‘ancillary conditions’ — non-informational factors that do
not affect experienced utility. In the context of EE, this could imply
that energy demand may be reduced with relatively low welfare costs
through publicity aimed at changing consumer preferences. However,
publicly-funded persuasion campaigns bring up important ethical and
political concerns, and the effectiveness of awareness-raising pro-
grammes on energy and carbon will depend on how consumers actu-
ally use the information and the mix of policy instruments (Gillingham
et al., 2006; Gupta et al., 2007; also Worrell etal., 2004; Mundaca
etal., 2010).
3�10�1�4 Altruistic reductions of carbon emissions
In many contexts, people are altruistic, being willing to reduce their
own welfare to increase that of others. For example, in laboratory ‘dic-
tator games’, people voluntarily give money to others (Forsythe etal.,
1994), and participants in public goods games regularly contribute
more than the privately-optimal amount (Dawes and Thaler, 1988; Led-
yard, 1993). Charitable donations in the United States amount to more
than 2 % of GDP (List, 2011). Similarly, many individuals voluntarily
contribute to environmental public goods, such as reduced carbon
54
The efficacy of these interventions can often be explained within neoclassical eco-
nomic models. From an expositional perspective, it is still relevant to cover them in
this section.
254254
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
emissions. For example, USD 387 million were spent in the U. S. on vol-
untary carbon offset purchases in 2009 (Bloomberg, 2010).
Pre-existing altruistic voluntary carbon emission reductions could mod-
erate the effects of a new carbon tax on energy demand because the
introduction of monetary incentives can ‘crowd out’ altruistic motiva-
tions (Titmuss, 1970; Frey and Oberholzer-Gee, 1997; Gneezy and Rus-
tichini, 2000). Thus, a carbon tax could reduce voluntary carbon emis-
sion reductions even as it increases financially-motivated reductions.
While this effect might not weaken the welfare argument for a carbon
tax, it does reduce the elasticity of carbon emissions with respect to a
carbon tax.
Reciprocity, understood as the practice of people rewarding generos-
ity and castigating cruelty towards them, has been found to be a key
driver of voluntary contributions to public goods. Positive reciprocity
comes in the form of conditional cooperation, which is a tendency to
cooperate when others do so too (Axelrod, 1984; Fischbacher etal.,
2001; Frey and Meier, 2004). However, cooperation based on positive
reciprocity is often fragile and is declining over time (Bolton et al.,
2004; Fischbacher and Gächter, 2010). Incentives and penalties are
fundamental to maintaining cooperation in environmental treaties
(Barrett, 2003). Adding a strategic option to punish defectors often
stabilizes cooperation, even when punishment comes at a cost to pun-
ishers (Ostrom etal., 1992; Fehr and Gächter, 2002). Yet, if agents are
allowed to counter-punish, the effectiveness of reciprocity to promote
cooperation might be mitigated (Nikiforakis, 2008). However, most
laboratory studies have been conducted under symmetric conditions
and little is known about human cooperation in asymmetric settings,
which tend to impose more serious normative conflicts (Nikiforakis
etal., 2012).
Experiments also reveal a paradox: actors can agree to a combined
negotiated climate goal for reducing the risk of catastrophe, but
behave as if they were blind to the risks (Barrett and Dannenberg,
2012). People are also often motivated by concerns about the fairness
of outcomes and procedures; in particular, many do not like falling
behind others (Fehr and Schmidt, 1999; Bolton and Ockenfels, 2000;
Charness and Rabin, 2002; Bolton et al., 2005). Such concerns can
both promote and hamper the effectiveness of negotiations, includ-
ing climate negotiations, in overcoming cooperation and distributional
problems (Güth etal., 1982; Lange and Vogt, 2003; Lange etal., 2007;
Dannenberg etal., 2010).
Uncertainty about outcomes and behaviours also tends to hamper
cooperation (Gangadharan and Nemes, 2009; Ambrus and Greiner,
2012). As a result, the information given to, and exchanged by, deci-
sion makers may affect social comparison processes and reciprocal
interaction, and thus the effectiveness of mechanisms to resolve con-
flicts (Goldstein etal., 2008; Chen etal., 2010; Bolton etal., 2013). In
particular, face-to-face communication has been proved to significantly
promote cooperation (Ostrom, 1990; Brosig et al., 2003). Concerns
about free-riding are perceived as a barrier to engaging in mitigation
actions (Lorenzoni etal., 2007). The importance of fairness in promot-
ing international cooperation (see also Chapter 4) is one of the few
non-normative justifications for fairness in climate policy.
3�10�1�5 Human ability to understand climate change
So far, we have covered deviations from the neoclassical model that
affect energy demand. Such deviations can also affect the policy-mak-
ing process. The understanding of climate change as a physical phe-
nomenon with links to societal causes and impacts is highly complex
(Weber and Stern, 2011). Some deviations are behavioural and affect
perceptions and decision making in various settings besides climate
change. (See Section 2.4 for a fuller discussion). For example, percep-
tions of, and reactions to, uncertainty and risk can depend not only
on external reality, as assumed in the neoclassical model, but also on
cognitive and emotional processes (Section 2.4.2). When making deci-
sions, people tend to overweight outcomes that are especially ‘avail-
able’ or salient (Kahneman and Tversky, 1974, 1979). They are more
averse to losses than they are interested in gains relative to a refer-
ence point (Kahneman and Tversky, 1979). Because climate change
involves a loss of existing environmental amenities, this can increase
its perceived costs. However, if the costs of abatement are seen as a
reduction relative to a reference rate of future economic growth, this
can increase the perceived costs of climate change mitigation.
Some factors make it hard for people to think about climate change
and lead them to underweight it: change happens gradually; the major
effects are likely to occur in the distant future; the effects will be felt
elsewhere; and their nature is uncertain. Furthermore, weather is natu-
rally variable, and the distinction between weather and climate is often
misunderstood (Reynolds etal., 2010). People’s perceptions and under-
standing of climate change do not necessarily correspond to scientific
knowledge (Section 2.4.3) because they are more vulnerable to emo-
tions, values, views, and (unreliable) sources (Weber and Stern, 2011).
People are likely to be misled if they apply their conventional modes of
understanding to climate change (Bostrom etal., 1994).
3�10�2 Social and cultural issues
In recent years, the orientation of social processes and norms towards
mitigation efforts has been seen as an alternative or complement to
traditional mitigation actions, such as incentives and regulation. We
address some of the concepts discussed in the literature, which, from
a social and cultural perspective, contribute to strengthening climate
change actions and policies.
3�10�2�1 Customs
In both developed and developing countries, governments, social orga-
nizations, and individuals have tried to change cultural attitudes
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
towards emissions, energy use, and lifestyles (European Commission,
2009). For example, household energy-use patterns for space and
water heating differ significantly between Japan and Norway because
of lifestyle differences (Wilhite et al., 1996; Gram-Hanssen, 2010).
Some have argued that the bio-cultural heritage of indigenous peoples
is a resource that should be valued and preserved as it constitutes an
irreplaceable bundle of teachings on the practices of mitigation and
sustainability (Sheridan and Longboat, 2006; Russell-Smith et al.,
2009; Kronik and Verner, 2010). Sometimes local strategies and indices
have metamorphosed into national policies, as in the case of ‘Buen
Vivir’ in Ecuador (Choquehuanca, 2010; Gudynas, 2011) and ‘Gross
National Happiness’ (GNH), described in Box 3.11. In rich countries,
and among social groups with high levels of environmental awareness,
interest in sustainability has given rise to cultural movements promot-
ing change in modes of thought, production, and consumption. Includ-
ing the cultural dimension in mitigation policies facilitates social
acceptability.
3�10�2�2 Indigenous peoples
Indigenous peoples number millions across the globe (Daes, 1996).
Land and the natural environment are integral to their sense of iden-
tity and belonging and to their culture, and are essential for their
survival (Gilbert, 2006; Xanthaki, 2007). The ancestral lands of indig-
enous peoples contain 80 % of the earth’s remaining healthy eco-
systems and global biodiversity priority areas, including the largest
tropical forests (Sobrevila, 2008). Because they depend on natural
resources and inhabit biodiversity-rich but fragile ecosystems, indig-
enous peoples are particularly vulnerable to climate change and have
only limited means of coping with such change (Henriksen, 2007; Per-
manent Forum on Indigenous Issues, 2008). They are often marginal-
ized in decision making and unable to participate adequately in local,
national, regional, and international climate-change mechanisms. Yet,
it is increasingly being recognized that indigenous peoples can impart
valuable insights into ways of managing mitigation and adaptation
(Nakashima etal., 2012), including forest governance and conserving
ecosystems (Nepstad etal., 2006; Hayes and Murtinho, 2008; Persha
etal., 2011).
3�10�2�3 Women and climate change
Women often have more restricted access to, and control of, the
resources on which they depend than men. In many developing coun-
tries, most small-scale food producers are women. They are usually the
ones responsible for collecting water and fuel and for looking after
the sick. If climate change adversely affects crop production and the
availability of fuel and water, or increases ill health, women may bear
a disproportionate burden of those consequences (Dankelman, 2002;
UNEP, 2011).
55
On the other hand, they may be better at adapting to
climate change, both at home and in the community. But given their
traditional vulnerability, the role of women across society will need
to be re-examined in a gender-sensitive manner to ensure they have
equal access to all types of resources (Agostino and Lizarde, 2012).
3�10�2�4 Social institutions for collective action
Social institutions shape individual actions in ways that can help in
both mitigation and adaptation. They promote trust and reciprocity,
establish networks, and contribute to the evolution of common rules.
They also provide structures through which individuals can share
information and knowledge, motivate and coordinate behaviour, and
act collectively to deal with common challenges. Collective action is
reinforced when social actors understand they can participate in local
solutions to a global problem that directly concerns them.
As noted in Sections 3.10.1.5 and 2.4, public perceptions of the cause
and effect of climate change vary, in both developed and developing
countries, with some erroneous ideas persisting even among well-
educated people. Studies of perceptions (O’Connor etal., 1999; Corner
etal., 2012) demonstrate that the public is often unaware of the roles
that individuals and society can play in both mitigation and adapta-
tion. The concepts of social and policy learning can be used in stimu-
55
Natural disasters over the period 1981 – 2002 revealed evidence of a gender gap:
natural disasters lowered women’s life expectancy more than men’s: the worse the
disaster and the lower the woman’s socio-economic status the bigger the disparity
(Neumayer and Plümper, 2007).
Box 3�11 | Gross National Happiness (GNH)
The Kingdom of Bhutan has adopted an index of GNH as a tool for
assessing national welfare and planning development (Kingdom
of Bhutan, 2008). According to this concept, happiness does not
derive from consumption, but rather from factors such as the
ability to live in harmony with nature (Taplin etal., 2013). Thus,
GNH is both a critique of, and an alternative to, the conventional
global development model (Taplin etal., 2013). The GNH Index
measures wellbeing and progress according to nine key domains
(and 72 core indicators) (Uddin etal., 2007). The intention is to
increase access to health, education, clean water, and electrical
power (Pennock and Ura, 2011) while maintaining a balance
between economic growth, environmental protection, and the
preservation of local culture and traditions. This is seen as a
‘Middle Way’ aimed at tempering the environmental and social
costs of unchecked economic development (Frame, 2005; Taplin
etal., 2013).
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
lating and organizing collective action. Social learning involves par-
ticipation by members of a group in discourse, imitation, and shared
collective or individual actions. The concept of policy learning describes
the process of adaptation by organizations to external change while
retaining or strengthening their own objectives and domination over
existing socio-economic structures (Adger and Kelly, 1999). The task
of an educational programme in mitigating and adapting to climate
change is to represent a collective global problem in individual and
social terms. This will require the strategies for disseminating scientific
information to be reinforced and the practical implications advertised
in ways that are understandable to diverse populations (González
Gaudiano and Meira Cartea, 2009).
3.11 Technological change
Mitigation scenarios aim at significant reductions in current emission
levels that will be both difficult and costly to achieve with existing tech-
nological options. However, cost-reducing technological innovations are
plausible. The global externality caused by climate change compounds
market failures common to private sector innovations. Appropriate
policy interventions are accordingly needed to encourage the type and
amount of climate-friendly technological change (TC) that would lead
to sizable reductions in the costs of reducing carbon emissions. This
section reviews theories, concepts, and principles used in the study of
environmentally oriented TC, and highlights key lessons from the lit-
erature, in particular, the potential of policy to encourage TC. Examples
of success and failure in promoting low carbon energy production and
consumption technologies are further evaluated in Chapters 6 – 16.
3�11�1 Market provision of TC
As pollution is not fully priced by the market, private individuals lack
incentives to invest in the development and use of emissions-reducing
technologies in the absence of appropriate policy interventions. Mar-
ket failures other than environmental pollution include what is known
as the ‘appropriability problem’. This occurs when inventors copy and
build on existing innovations, and reap part of the social returns on
them. While the negative climate change externality leads to over
use of the environment, the positive ‘appropriability’ externality leads
to an under-supply of technological innovation.
56
Indeed, empirical
research provides ample evidence that social rates of return on R&D
are higher than private rates of return (Griliches, 1992). Thus, the ben-
56
For incremental innovations, the net technology externality can be negative.
Depending on market structure and intellectual property rules, the inventor of an
incremental improvement on an existing technology may be able to appropriate
the entire market, thereby earning profits that exceed the incremental value of the
improvement.
efits of new knowledge may be considered as a public good (see, e. g.,
Geroski, 1995).
Imperfections in capital markets often distort the structure of incen-
tives for financing technological development. Information about the
potential of a new technology may be asymmetrically held, creating
adverse selection (Hall and Lerner, 2010). This may be particularly
acute in developing countries. The issue of path dependence, acknowl-
edged in evolutionary models of TC, points to the importance of trans-
formative events in generating or diverting technological trajectories
(see Chapters 4 and 5). Even endogenously induced transformative
events may not follow a smooth or predictable path in responding
to changing economic incentives, suggesting that carbon-price policy
alone may not promote the desired transformative events.
3�11�2 Induced innovation
The concept of ‘induced innovation’ postulates that investment in
R&D is profit-motivated and responds positively to changes in relative
prices
57
(Hicks, 1932; Binswanger and Ruttan, 1978; Acemoglu, 2002).
58
Initial evidence of induced TC focused on the links between energy
prices and innovation and revealed the lag between induced responses
and the time when price changes came into effect, which is estimated
at five years by Newell etal. (1999) and Popp (2002) (see Chapter 5).
Policy also plays an important role in inducing innovation, as demon-
strated by the increase in applications for renewable energy patents
within the European Union in response to incentives for innovation
provided by both national policies and international efforts to combat
climate change (Johnstone etal., 2010). Recent evidence also suggests
that international environmental agreements provide policy signals that
encourage both innovation (Dekker et al., 2012) and diffusion (Popp
etal., 2011). With the exception of China, most climate-friendly inno-
vation occurred in developed countries (Dechezlepretre etal., 2011).
59
3�11�3 Learning-by-doing and other structural
models of TC
An extensive literature relates to rates of energy cost reduction based
on the concept of ‘experience’ curves (see Chapter 6). In econom-
ics, this concept is often described as learning-by-doing (LBD) — to
describe the decrease in costs to manufacturers as a function of cumu-
lative output — or ‘learning-by-using’, reflecting the reduction in costs
57
It should be pointed out that in economics, ‘induced innovation’ typically means
innovation induced by relative price differences. The IPCC uses a different defini-
tion: innovation induced by policy.
58
In economics, ‘induced innovation’ typically means innovation induced by relative
price differences. The IPCC uses a different definition: innovation induced by
policy.
59
Global R&D expenditures amounted to USD 1.107 trillion in 2007, with OECD
nations accounting for 80 %, and the U. S. and Japan together accounting for
46 % (National Science Board, 2010).
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
(and / or increase in benefits) to consumers as a function using a tech-
nology. While learning curves are relatively easy to incorporate into
most climate integrated assessment models (IAMs), the application of
LBD has limitations as a model of TC (Ferioli etal., 2009). Learning
curves ignore potential physical constraints. For example, while costs
may initially fall as cumulative output expands, if renewable energy
is scaled up, the use of suboptimal locations for production would
increase costs. Ferioli et al. (2009) also provide evidence that learn-
ing can be specific to individual components, so that the savings from
learning may not fully transfer from one generation of equipment to
the next. They therefore suggest caution when extrapolating cost sav-
ings from learning curves to long-term frames or large-scale expan-
sions. Similarly, in a study on cost reductions associated with photo-
voltaic cells, Nemet (2006) finds that most efficiency gains come from
universities, which have little traditional LBD through production expe-
rience. Hendry and Harborne (2011) provide examples of the interac-
tion of experience and R&D in the development of wind technology.
3�11�4 Endogenous and exogenous TC and
growth
Within climate policy models, TC is either treated as exogenous or
endogenous. Köhler et al. (2006), Gillingham et al. (2008) and Popp
etal. (2010) provide reviews of the literature on TC in climate models.
Exogenous TC (most common in models) progresses at a steady rate
over time, independently of changes in market incentives. One draw-
back of exogenous TC is that it ignores potential feedback between
climate policy and the development of new technologies. Models
with endogenous TC address this limitation by relating technological
improvements in the energy sector to changes in energy prices and
policy. These models demonstrate that ignoring induced innovation
overstates the costs of climate control.
The Nordhaus (1977, 1994) DICE model is the pioneering example
of a climate policy model incorporating TC into IAMs. In most imple-
mentations of DICE, TC is exogenous. Efforts to endogenize TC have
been difficult, mainly because market-based spillovers from R&D are
not taken into account when deciding how much R&D to undertake.
Recent attempts to endogenize TC include WITCH model (Bosetti etal.,
2006) and Popp’s (2004) ENTICE model. Popp (2004) shows that mod-
els that ignore directed TC do indeed significantly overstate the costs
of environmental regulation (more detailed discussion on TC in these
and more recent models is provided in Chapter 6).
An alternative approach builds on new growth theories, where TC is
by its nature endogenous, in order to look at the interactions between
growth and the environment. Policies like R&D subsidies or carbon
taxes affect aggregate growth by affecting entrepreneurs’ incentives
to innovate. Factoring in firms’ innovations dramatically changes our
view of the relationship between growth and the environment. More
recent work by Acemoglu etal. (2012) extends the endogenous growth
literature to the case where firms can choose the direction of innova-
tion (i. e., they can decide whether to innovate in more or less carbon-
intensive technologies or sectors).
60
In contrast, LBD models use learning curve estimates to simulate fall-
ing costs for alternative energy technologies as cumulative experi-
ence with the technology increases. One criticism of these models is
that learning curve estimates provide evidence of correlation, but not
causation. While LBD is easy to implement, it is difficult to identify
the mechanisms through which learning occurs. Goulder and Mathai
(2000) provide a theoretical model that explores the implications of
modelling technological change through R&D or LBD (several empirical
studies on this are reviewed in more detail in Chapter 6).
3�11�5 Policy measures for inducing R&D
Correcting the environmental externality or correcting knowledge mar-
ket failures present two key options for policy intervention to encour-
age development of climate-friendly technologies. Patent protection,
R&D tax credits, and rewarding innovation are good examples of
correcting failures in knowledge markets and promoting higher rates
of innovation. On the other hand, policies regulating environmental
externalities, such as a carbon tax or a cap-and-trade system, influence
the direction of innovation.
Chapter 15 discusses in more detail how environmental and tech-
nology policies work best in tandem (e. g., Popp, 2006; Fischer, 2008;
Acemoglu etal., 2012). For instance, in evaluating a broad set of poli-
cies to reduce CO
2
emissions and promote innovation and diffusion
of renewable energy in the United States electricity sector, Fischer &
Newell (2008) find that a portfolio of policies (including emission pric-
ing and R&D) achieves emission reductions at significantly lower cost
than any single policy (see Chapters 7 to 13). However, Gerlagh and
van der Zwaan (2006) note the importance of evaluating the trade-off
between cost savings from innovation and Fischer and Newell (2008)
assumptions of decreasing returns to scale due to space limitations for
new solar and wind installations.
3�11�6 Technology transfer (TT)
Technology transfer (TT) has been at the centre of the scholarly debate
on climate change and equity in economic development as a way for
developed countries to assist developing countries access new low car-
bon technologies. Modes of TT include, trade in products, knowledge
and technology, direct foreign investment, and international move-
60
Other works investigating the response of technology to environment regulations
include Grübler and Messner (1998), Manne and Richels (2004b), Messner (1997),
Buonanno et al. (2003), Nordhaus (2002), Di Maria and Valente (2008), Bosetti
et al. (2008), Massetti et al. (2009), Grimaud and Rouge (2008), and Aghion et al.
(2009).
258258
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
ment of people (Hoekman etal., 2005). Phases and steps for TT involve
absorption and learning, adaptation to the local environment and
needs, assimilation of subsequent improvements, and generalization.
Technological learning or catch-up thus proceeds in stages: importing
foreign technologies; local diffusion and incremental improvements in
process and product design; and marketing, with different policy mea-
sures suited to different stages of the catch-up process.
‘Leapfrogging’, or the skipping of some generations of technology or
stages of development, is a useful concept in the climate change miti-
gation literature for enabling developing countries to avoid the more
emissions-intensive stages of development (Watson and Sauter, 2011).
Examples of successful low-carbon leapfrogging are discussed in more
detail in Chapter 14.
Whether proprietary rights affect transfers of climate technologies has
become a subject of significant debate. Some technologies are in the
public domain; they are not patented or their patents have expired.
Much of the debate on patented technologies centres on whether
the temporary monopoly conferred by patents has hampered access
to technology. Proponents of strong intellectual property (IP) rights
believe that patents enhance TT as applicants have to disclose informa-
tion on their inventions. Some climate technology sectors, for example,
those producing renewable energy, have easily available substitutes
and sufficient competition, so that patents on these technologies do
not make them costly or prevent their spread (Barton, 2007). In other
climate-related technology sectors, IP protection could be a barrier to
TT (Lewis, 2007). (The subject is further discussed in Chapters 13 and
15.)
Various international agreements on climate change, trade, and intel-
lectual property include provisions for facilitating the transfer of tech-
nology to developing countries. Climate change agreements encour-
age participation by developing countries and address barriers to the
adoption of technologies, including financing. However, some scholars
have found these agreements to be ineffective because they do not
incorporate mechanisms for ensuring technology transfers to develop-
ing countries (Moon, 2008). (The literature on international coopera-
tion on TT is further discussed in Chapters 13, 14 and 16.)
3.12 Gaps in knowledge
and data
As this chapter makes clear, many questions are not completely
answered by the literature. So it is prudent to end our assessment with
our findings on where research might be directed over the coming
decade so that the AR6 (should there be one) may be able to say more
about the ethics and economics of climate change.
• To plan an appropriate response to climate change, it is important
to evaluate each of the alternative responses that are available.
How can we take into account changes in the world’s population?
Should society aim to promote the total of people’s wellbeing
in the world, or their average wellbeing, or something else? The
answer to this question will make a great difference to the conclu-
sions we reach.
• The economics and ethics of geoengineering is an emerging
field that could become of the utmost importance to policymak-
ers. Deeper analysis of the ethics of this topic is needed, as well
as more research on the economic aspects of different possible
geoengineering approaches and their potential effects and side-
effects.
• To develop better estimates of the social cost of carbon and to bet-
ter evaluate mitigation options, it would be helpful to have more
realistic estimates of the components of the damage function,
more closely connected to WGII assessments of physical impacts.
Quantifying non-market values, that is, measuring valuations
placed by humans on nature and culture, is highly uncertain and
could be improved through more and better methods and empiri-
cal studies. As discussed in Section 3.9, the aggregate damage
functions used in many IAMs are generated from a remarkable
paucity of data and are thus of low reliability.
• The development of regulatory mechanisms for mitigation would
be helped by more ex-post evaluation of existing regulations,
addressing the effectiveness of different regulatory approaches,
both singly and jointly. For instance, understanding, retrospec-
tively, the effectiveness of the European Union Emissions Trad-
ing Scheme (EU ETS), the California cap-and-trade system, or the
interplay between renewable standards and carbon regulations in
a variety of countries.
• Energy models need to provide a more realistic portrait of micro-
economic decision-making frameworks for technology-choice
(energy-economy models).
• A literature is emerging in economics and ethics on the risk of cat-
astrophic climate change impacts, but much more probing into the
ethical dimensions is needed to inform future economic analysis.
• More research that incorporates behavioural economics into
climate change mitigation is needed. For instance, more work
on understanding how individuals and their social preferences
respond to (ambitious) policy instruments and make decisions rel-
evant to climate change is critical.
• Despite the importance of the cost of mitigation, the aggregate
cost of mitigating x tonnes of carbon globally is poorly understood.
To put it differently, a global carbon tax of x dollars per tonne
259259
Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
would yield y(t) tonnes of carbon abatement at time, t. We do not
understand the relationship between x and y(t).
• The choice of the rate at which future uncertain climate damages
are discounted depends on their risk profile in relation to other
risks in the economy. By how much does mitigating climate change
reduce the aggregate uncertainty faced by future generations?
• As has been recently underscored by several authors (Pindyck,
2013; Stern, 2013) as well as this review, integrated assessment
models have very significant shortcomings for CBA, as they do
not fully represent climate damages, yet remain important tools
for investigating climate policy. They have been widely and suc-
cessfully applied for CEA analysis (Paltsev etal., 2008; Clarke etal.,
2009; Krey and Clarke, 2011; Fawcett etal., 2013). Research into
improving the state-of-the-art of such models (beyond just updat-
ing) can have high payoff.
3.13 Frequently Asked
Questions
FAQ 3�1 The IPCC is charged with providing the
world with a clear scientific view of the
current state of knowledge on climate
change� Why does it need to consider
ethics?
The IPCC aims to provide information that can be used by govern-
ments and other agents when they are considering what they should
do about climate change. The question of what they should do is a
normative one and thus has ethical dimensions because it generally
involves the conflicting interests of different people. The answer rests
implicitly or explicitly on ethical judgements. For instance, an answer
may depend on a judgement about the responsibility of the present
generation towards people who will live in the future or on a judge-
ment about how this responsibility should be distributed among dif-
ferent groups in the present generation. The methods of ethical theory
investigate the basis and logic of judgements such as these.
FAQ 3�2 Do the terms justice, fairness and equity
mean the same thing?
The terms ‘justice’, ‘fairness’ and ‘equity’ are used with subtly different
meanings in different disciplines and by different authors. ‘Justice’ and
‘equity’ commonly have much the same meaning: ‘justice’ is used more
frequently in philosophy; ‘equity’ in social science. Many authors use
‘fairness’ as also synonymous with these two. In reporting on the lit-
erature, the IPCC assessment does not impose a strictly uniform usage
on these terms. All three are often used synonymously. Section 3.3
describes what they refer to, generally using the term ‘justice’.
Whereas justice is broadly concerned with a person receiving their due,
‘fairness’ is sometimes used in the narrower sense of receiving one’s
due (or ‘fair share’) in comparison with what others receive. So it is
unfair if people do not all accept an appropriate share of the burden
of reducing emissions, whereas on this narrow interpretation it is not
unfair — though it may be unjust — for one person’s emissions to harm
another person. Fairness is concerned with the distribution of goods
and harms among people. ‘Distributive justice’ — described in Section
3.3 — falls under fairness on the narrow interpretation.
FAQ 3�3 What factors are relevant in considering
responsibility for future measures that
would mitigate climate change?
It is difficult to indicate unambiguously how much responsibility dif-
ferent parties should take for mitigating future emissions. Income and
capacity are relevant, as are ethical perceptions of rights and justice.
One might also investigate how similar issues have been dealt with
in the past in non-climate contexts. Under both common law and civil
law systems, those responsible for harmful actions can only be held
liable if their actions infringe a legal standard, such as negligence or
nuisance. Negligence is based on the standard of the reasonable per-
son. On the other hand, liability for causing a nuisance does not exist
if the actor did not know or have reason to know the effects of its
conduct. If it were established that the emission of GHGs constituted
wrongful conduct within the terms of the law, the nature of the causal
link to the resulting harm would then have to be demonstrated.
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Social, Economic, and Ethical Concepts and Methods
3
Chapter 3
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