Designing an optimal 'tech fix' path to global climate stability: R&D in a multi-phase climate policy framework
AbstractThe research reported here gives priority to understanding the inter-temporal resource allocation requirements of a program of technological changes that could halt global warming by completing the transition to a "green" (zero net CO2- emission) production regime within the possibly brief finite interval that remains before Earth's climate is driven beyond a catastrophic tipping point. This paper formulates a multi-phase, just-in-time transition model incorporating carbon-based and carbon-free technical options requiring physical embodiment in durable production facilities, and having performance attributes that are amenable to enhancement by directed R&D expenditures. Transition paths that indicate the best ordering and durations of the phases in which intangible and tangible capital formation is taking place, and capital stocks of different types are being utilized in production, or scrapped when replaced types embodying socially more efficient technologies, are obtained from optimizing solutions for each of a trio of related models that couple the global macro-economy's dynamics with the dynamics of the climate system. They describe the flows of consumption, CO2 emissions and the changing atmospheric concentration of green-house gas (which drives global warming), along with the investment dynamics required for the timely transformation of the production regime. These paths are found as the welfare-optimizing solutions of three different "stacked Hamiltonians", each corresponding to one of our trio of integrated endogenous growth models that have been calibrated comparably to emulate the basic global setting for the "transition planning" framework of dynamic integrated requirements analysis modelling (DIRAM). As the paper's introductory section explains, this framework is proposed in preference to the (IAM) approach that environmental and energy economists have made familiar in integrated assessment models of climate policies that would rely on fiscal and regulatory instruments -- but eschew any analysis of the essential technological transformations that would be required for those policies to have the intended effect. Simulation exercises with our models explore the optimized transition paths' sensitivity to parameter variations, including alternative exogenous specifications of the location of a pair of successive climate "tipping points": the first of these initiates higher expected rates of damage to productive capacity by extreme weather events driven by the rising temperature of the Earth's surface; whereas the second, far more serious "climate catastrophe" tipping point occurs at a still higher temperature (corresponding to a higher atmospheric concentration of CO2). In effect, that sets the point before which the transition to a carbon-free global production regime must have been completed in order to secure the possibility of future sustainable development and continued global economic growth.
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Bibliographic InfoPaper provided by United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) in its series MERIT Working Papers with number 009.
Date of creation: 2013
Date of revision:
global warming; tipping point; catastrophic climate instability; extreme weather-related damages; R&D based technical change; embodied technical change; optimal sequencing; multi-phase optimal control; sustainable endogenous growth;
Other versions of this item:
- Paul A. David & Adriaan van Zon, 2013. "Designing an Optimal 'Tech Fix' Path to Global Climate Stability: R&D in a Multi-Phase Climate Policy Framework," Discussion Papers 12-013, Stanford Institute for Economic Policy Research.
- Zon, Adriaan van & David, Paul, 2013. "Designing an optimal 'tech fix' path to global climate stability: R&D in a multi-phase climate policy framework," MERIT Working Papers 009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
- Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
- O32 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Management of Technological Innovation and R&D
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
- O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
- O44 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-11-29 (All new papers)
- NEP-ENE-2013-11-29 (Energy Economics)
- NEP-ENV-2013-11-29 (Environmental Economics)
- NEP-INO-2013-11-29 (Innovation)
- NEP-RES-2013-11-29 (Resource Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kelly C. de Bruin & Rob B. Dellink & Richard S.J. Tol, 2007.
"AD-DICE: an implementation of adaptation in the DICE model,"
FNU-126, Research unit Sustainability and Global Change, Hamburg University, revised Feb 2007.
- Kelly C. de Bruin & Rob B. Dellink & Richard S.J. Tol, 2007. "AD-DICE: An Implementation of Adaptation in the DICE Mode," Working Papers 2007.51, Fondazione Eni Enrico Mattei.
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