Technological Change and Learning Curves in the Context of the TranSust.Scan Modelling Network. TranSust.Scan Working Paper
The paper deals with the concept of learning curves against a broader background of modelling technological change. Based on a literature survey the paper addresses four approaches (endogenous growth theory, learning curves, innovation theory and diffusion theory) and attempts to highlight the links...| Link(s) zu Dokument(en): | WIFO Publikation |
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| Veröffentlicht in: | WIFO Studies |
| Hauptverfasser: | , , |
| Format: | book |
| Sprache: | Englisch |
| Veröffentlicht: |
2008
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| Zusammenfassung: | The paper deals with the concept of learning curves against a broader background of modelling technological change. Based on a literature survey the paper addresses four approaches (endogenous growth theory, learning curves, innovation theory and diffusion theory) and attempts to highlight the links between them. The second part of the paper tackles the empirical implementation of technological change in TranSust.Scan models. Learning curves are the predominantly used approach in empirical modelling as they show two main benefits: they allow inclusion of different technologies for which specific learning rates are estimated. Furthermore, evidence from ex-post observations and ex-ante estimation match closely. |
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