sectoral economic costs and benefits of ghg mitigation - IPCC

Patrick Criqui, Nikos Kouvaritakis and Leo Schrattenholzer
- the path-dependency associated to the phenomenon of “increasing returns to adoption” and
the consequent possibility of “lock-in”;
- the relative weight of path-dependency and of the “inducement factors” of TC;
- in the inducement factors, the relative weight of “demand pull” (Schmookler, 1966) and of
“supply push” factors;
- subsequently in the “supply push” the relative weight, of exogenous science-driven
innovations (Rosenberg, 1976) and of the endowments or scarcity in the relevant factors of
production in a Hicksian perspective.
While the inherently stochastic and uncertain nature of any TC process, particularly as concerns
radical innovation, cannot be ignored, the effort towards an endogenisation of TC in economic
analysis and models may provide useful insights on the pre-determined components of the
technological trajectories, as well as on the inter-industry, intra-industry and intra-firm processes
of TC.
The sources of TC: exogenous, stochastic and irreversible events
Of course, no innovation can be considered completely independently of the existing knowledge
base and of the prevailing socio-economic conditions, radical innovations, i.e. innovations, which
imply an important new product or a new factory, always incorporate a dimension of “surprise”.
They are in that case associated with breakthroughs in the scientific and technological
knowledge-base. But inventions can also occur, in a non-deterministic way, due to opportunities
arising from the regular development of the knowledge base and from the corresponding interrelatedness
effects.
The dynamics of TC: endogenous, deterministic and irreversible aspects of TC
Technical Change is often treated as a deterministic process when it concerns incremental
innovations. For some authors, the concept of technological paradigm incorporates key
parameters which are pre-determined and will develop over time along a given trajectory (Dosi,
1982). The cumulative experience in the making or in the use of a product will allow for the
successive solution of the technological bottlenecks or of the difficulties not foreseen at the R&D
stage. This process is usually captured by learning curves, in which the progress in costs or
performance is empirically described as a function of cumulative production, taken as a proxy for
the accumulated experience (see below Section 1.3).
This deterministic feature of the TC process is reinforced when increasing returns to adoption
(i.e. the probability of adoption increases with the level of adoption) are taken into account. They
result in a positive feedback loop between the learning or experience phenomenon and imitative
diffusion profiles. This positive feedback loop in turn explains the possibility of a lock in, i.e. a
situation in which a new technology, even if it is not intrinsically superior, may completely
dominate a given market (Arthur, 1983; David, 1985).
It has however to be noted that such situations of path-dependency with strong irreversibilities
may still be strongly dependent of two types of factors of a very different nature:
- the initial conditions of the system and the so-called “tyranny of small events”, which
reintroduces some elements of uncertainty, at least at the very beginning of a trajectory; and
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