• Media type: E-Book
  • Title: Long-Term Growth Driven by a Sequence of General Purpose Technologies
  • Contributor: Schiess, Daniel [Author]; Wehrli, Roger [Other]
  • imprint: [S.l.]: SSRN, [2011]
  • Published in: CER-ETH Working Paper ; No. 11/148
  • Extent: 1 Online-Ressource (25 p)
  • Language: English
  • DOI: 10.2139/ssrn.1894588
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 25, 2011 erstellt
  • Description: We present a Schumpterian model of endogenous growth with General Purpose Technologies (GPTs) that captures two important historical stylized facts: First, from the beginning of mankind until today GPTs are arriving at an increasing frequency and, second, all GPTs heavily depended on previous technologies. In our model, the arrival of GPTs is endogenous and arises stochastically depending on the currently available applied knowledge stock. This way of endogenizing the arrival of new GPTs allows for a model which is more in tune with the historical reality than the existing GPT models
  • Access State: Open Access