sectoral economic costs and benefits of ghg mitigation - IPCC

Patrick Criqui, Nikos Kouvaritakis and Leo Schrattenholzer
3 Integrating the impacts of R&D and of learning by doing in a world energy
modelling framework
The abundant literature on the sources and dynamics of technological change suggest that the
process is always uncertain and shows important stochastic features. However, inducement
factors such as price signals and technological imbalances in the “demand-pull” perspective
(Schmookler, 1966), R&D programmes and factor availability in the “supply-push” approach
(Rosenberg, 1976) can be identified as playing an important role in technology development.
Last but not least, endogenous mechanisms based on the development of technological
“trajectories” (Dosi, 1982), with the accumulation of experience through “learning by doing”
processes described above also explain the improvements in the costs and performances of
technologies (Arrow, 1962), as they progressively diffuse from “niche markets” to large scale
applications.
3.1. A modelling scheme for a partial endogenisation of technology in energy models
The POLES model is a global sectoral model of the world energy system. It has been developed
in the framework of a hierarchical structure of interconnected sub-models at the international,
regional and national levels (for a detailed description of the model see Criqui et al., 1996). The
dynamics of the model is based on a recursive (year-by-year) simulation process of energy
demand and supply, with lagged adjustments to prices and a feedback loop through endogenous
international energy prices. The price mechanisms, which are pervasive in the model, allow to
consistently study the impacts of environmental policies based on the principle of internalisation
of environmental costs, while the level of detail in the description of energy technologies allows
to identify the impact of changes in the technologies’ performances and costs.
As an attempt to provide more detail in the description of these mechanisms, modelling efforts
have recently been performed in order to develop a module for the endogenisation of technical
change in energy models. The basic structure of this module is described in Diagram 2, showing
the integration of four main sets of variables / modelling mechanisms: i. the exogenous public
policy variables which give the impulse / constraints to the whole system, ii. the endogenous
industry R&D investment module, iii. the “two factor learning curve”, which provides the
dynamics for technology improvement, and iv. the main POLES model, as a technology
diffusion model. Each of these components is described below.
3.2. The exogenous policy variables: public energy R&D and price signals
This first component in the system remains exogenous as it represents the key elements of public
policies, the endogenisation of which would make no sense as the proper goal of all the
modelling exercises is precisely to investigate and assess the consequences of the different policy
options. Two sets of variables or constraints are to be taken into account: on one hand the volume
and structure of public energy R&D and on the other hand the constraints concerning the
environment and expressed either in terms of environmental taxes or emission targets and
corresponding “carbon value”.
The first set of variables clearly corresponds to the “technology-push” approach, through public
R&D programmes. They will have an impact on a more or less important part of the accumulated
knowledge, according to the technology considered. This variable will have in turn an impact on
the current and expected cost and performances of each technology.
The second set of variable represents “demand-pull” inducement factors, as they allow to
introduce in the model social and environmental targets, through the system of “shadow
environmental taxes” or “emission trading systems”. In that way, they will be a powerful means
in order to stimulate technological change towards more environmentally compatible solutions.
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