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Supermultiplier, innovation and the ecosystem: A stock-flow dynamic model

Deleidi, Matteo; Pariboni, Riccardo; Passarella Veronese, Marco; (2019) Supermultiplier, innovation and the ecosystem: A stock-flow dynamic model. (Working Paper Series: IIPP WP 2019-01). UCL Institute for Innovation and Public Purpose: London, UK. Green open access

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Abstract

This work builds upon four different theoretical approaches: i. the Sraffian supermultiplier model; ii. the Schumpeterian framework of evolutionary economics that emphasises the entrepreneurial role of the state; iii. the ‘stock-flow consistent’ approach to macroeconomic modelling; and iv. recent developments in ecological economics literature aiming at cross-breeding post-Keynesian theories and models with more traditional ‘green’ topics. Our main purpose is to develop a simple analytical tool that can help examine: a) the impact of government spending on private innovation; b) the impact of innovation on economic growth and the ecosystem; and c) the impact of ecological feedbacks on economic growth and government spending effectiveness. We find that, in principle, government can be successful in supporting innovation and growth while slowing down matter and energy reserves’ depletion rates, and tackling climate change. However, the latter may well affect government policy effectiveness.

Type: Working / discussion paper
Title: Supermultiplier, innovation and the ecosystem: A stock-flow dynamic model
Open access status: An open access version is available from UCL Discovery
Publisher version: https://www.ucl.ac.uk/bartlett/public-purpose/publ...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Supermultiplier, mission-oriented policy, stock-flow consistent modelling, ecological economics
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10195883
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