Induced Technological Change in a Limited Foresight Optimization Model

dc.creatorHedenus, Fredrik
dc.creatorAzar, Christian
dc.creatorLindgren, Kristian
dc.date2017-04-01T14:07:39Z
dc.date.accessioned2026-07-09T03:03:13Z
dc.descriptionThe threat of global warming calls for a major transformation of the energy system the coming century. Modeling technological change is an important factor in energy systems modeling. Technological change may be treated as induced by climate policy or as exogenous. We investigate the importance of induced technological change (ITC) in GET-LFL, an iterative optimization model with limited foresight that includes learning-by-doing. Scenarios for stabilization of atmospheric CO2 concentrations at 400, 450, 500 and 550 ppm are studied. We find that the introduction of ITC reduces the total net present value of the abatement cost over this century by 3-9% compared to a case where technological learning is exogenous. Technology specific polices which force the introduction of fuel cell cars and solar PV in combination with ITC reduce the costs further by 4-7% and lead to significantly different technological solutions in different sectors, primarily in the transport sector.
dc.identifierdoi:10.22004/ag.econ.12036
dc.identifierhttps://ageconsearch.umn.edu/record/12036/files/wp050125.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/12036
dc.identifier.urihttp://hdl.handle.net/123456789/525593
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/12036
dc.titleInduced Technological Change in a Limited Foresight Optimization Model
dc.typeText

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